Low digit ratio 2D:4D in alcohol dependent patients

The ratio of the lengths of the second and fourth finger (2D∶4D) has been described as reflecting the degree of prenatal androgen exposure in humans. 2D∶4D is smaller for males than females and is associated with traits such as left-handedness, physical aggression, attention-deficit-hyperactivity disorder and a genetic polymorphism of the androgen receptor. All of these traits are known to be correlated to the vulnerability for alcohol dependency. We therefore hypothesized low 2D∶4D in patients with alcohol dependency. In the present study on 131 patients suffering from alcohol dependency and 185 healthy volunteers, we found that alcohol dependent patients had smaller 2D∶4D ratios compared to controls with preserved sexual dimorphism but with reduced right-left differences. The detection of alcohol dependency based on 2D∶4D ratios was most accurate using the right hand of males (ROC-analysis: AUC 0.725, sensitivity 0.667, specificity 0.723). These findings provide novel insights into the role of prenatal androgen exposure in the development of alcohol dependency and for the use of 2D∶4D as a possible trait marker in identifying patients with alcohol dependency.     

The influence of training on chemosensory event-related potentials and interactions between the olfactory and trigeminal systems

It is not possible to accurately predict the perceptual response to odorants and odorant mixtures without understanding patterns of suppression and facilitation that result from interactions between the olfactory and trigeminal systems. The current study extends previous findings by exploring the effect of intensive training on the interaction between these systems and also by using a different mixed chemosensory stimulus to examine whether the principles established in earlier studies generalize to different odorants. Stimuli were chosen so as to selectively activate the olfactory (H2S) and trigeminal (CO2) nerves. In addition, linalool was included as a stimulus that activated both systems. Thirty-five participants (19 men, 16 women) rated the intensity of each stimulus when presented both alone and in binary mixtures (linalool + H2S, and linalool + CO2). Chemosensory event-related potentials were obtained from three recording positions. Analysis of intensity ratings showed that linalool was significantly less intense than the other stimuli when presented alone. In binary mixtures, H2S was strongly suppressed by linalool. One week of intensive odor training produced significant and specific reductions in the intensity of linalool and H2S, both alone and in their mixture. Training with a different odor (champignol) had no effect. Chemosensory event-related potential data confirmed previous findings showing changes in topographical distribution that reflected the degree of trigeminal activity. Binary mixtures generally produced larger amplitudes than single stimuli. Latencies clearly differentiated between the three single stimuli and the binary mixtures. Changes were observed in event-related potentials that reflected those obtained for intensity ratings in that they were observed for linalool and H2S in the linalool trained group only. The amplitude of the late 'endogenous' component (P3) was significantly decreased for these odors at frontal recording sites. In summary, strong and specific training effects were observed in intensity ratings for participants trained with the test odor (linalool), but not for those trained with a different odor. This was supported by a significant decrease of amplitudes of the event-related potentials at frontal recording sites following training with the test odor only     

Brain activation during processing of angry facial expressions in patients with alcohol dependency

Background

Alcoholism is associated with abnormal anger processing. The purpose of this study was to investigate brain regions involved in the evaluation of angry facial expressions in patients with alcohol dependency.

Methods

Brain blood-oxygenation-level-dependent (BOLD) responses to angry faces were measured and compared between patients with alcohol dependency and controls.

Results

During intensity ratings of angry faces, significant differences in BOLD were observed between patients with alcohol dependency and controls. That is, patients who were alcohol-dependent showed significantly greater activation in several brain regions, including the dorsal anterior cingulate cortex (dACC) and medial prefrontal cortex (MPFC).

Conclusions

Following exposure to angry faces, abnormalities in dACC and MPFC activation in patients with alcohol dependency indicated possible inefficiencies or hypersensitivities in social cognitive processing.     

Genetic studies of rice (Oryza sativa L.) anther culture response

Anthers of two rice (Oryza sativa L.) varieties, Lunhui 422 (P₁) and Jinzao 5 (P₂), their F₁, F₂ and first backcross generation-F₁ x Lunhui 422 (B₁), and F₁ x Jinzao 5 (B₂)-were cultured in L8 medium to study the inheritance of rice anther culturability using generation mean analysis. Significant effects of generation were observed for the four traits measured: anther response (%), frequency of callus induction (%), frequency of callus differentiation (%) and culture efficiency (%). Variation among the generations was similar for all traits: significant differences were found among six generations and the means of the P₂ and B₂ were significantly lower than those of the other generations. The frequency of callus differentiation showed a nonsignificant difference among the P₁, F₁, F₂ and B₁ generations which had slightly high values than the P₂ and B₂. Additive genetic variance (V_A) was higher than non-additive genetic variance (V_D) for anther response and frequency of callus induction. However, A_V was lower than V_D for frequence of callus differentiation and culture efficiency, V_A was significant for all traits except for the culture efficiency, and V_D was nonsignificant for all traits except for the frequency of callus differentiation. On the other hand, environmental variation (V_E) was significant for the 4 traits. Narrow-sense heritability estimates were 95.52%, 82.19% and 13.54% for anther response, frequency of callus induction and culture efficiency, respectively.Abbreviations 2,4-d 2,4-dichlorophenoxyacetic acid - IAA indole-3-acetic acid     

Joint Multipoint Linkage Analysis of Multivariate Qualitative and Quantitative Traits. II. Alcoholism and Event-Related Potentials

The availability of robust quantitative biological markers that are correlated with qualitative psychiatric phenotypes can potentially improve the power of linkage methods to detect quantitative-trait loci influencing psychiatric disorders. We apply a variance-component method for joint multipoint linkage analysis of multivariate discrete and continuous traits to the extended pedigree data from the Collaborative Study on the Genetics of Alcoholism, in a bivariate analysis of qualitative alcoholism phenotypes and quantitative event-related potentials. Joint consideration of the DSM-IV diagnosis of alcoholism and the amplitude of the P300 component of the Cz event-related potential significantly increases the evidence for linkage of these traits to a chromosome 4 region near the class I alcohol dehydrogenase locus ADH3. A likelihood-ratio test for complete pleiotropy is significant, suggesting that the same quantitative-trait locus influences both risk of alcoholism and the amplitude of the P300 component.     

Leaf decomposition depends on nutritional trait values but increasing trait variability does not always increase decomposition efficiency

The mass ratio (MRH) and niche complementarity (NCH) hypotheses can explain how leaf trait composition drives decomposition, an ecosystem process linked to nutrient cycling and carbon sequestration. However, few studies have used an experiment designed to disentangle the role of the mechanisms proposed by these hypotheses. This is especially true regarding the role of leaf functional traits for decomposition rates in tropical ecosystems. Here, we quantified the biomass loss of 120 leaf mixtures assembled according to four quasi-orthogonal combinations of different mean trait values (community-weighted mean; CWM) and trait variability (functional diversity; FD) of three leaf functional traits (leaf nitrogen and leaf magnesium concentrations and specific leaf area). We found that CWM values of leaf nutritional traits were positively related to greater biomass loss. This supports the hypothesis that the mean trait values of leaf mixtures can drive biomass loss (MRH). However, contrary to NCH expectations, in some circumstances, increasing trait variability of leaf nutritional traits decreased biomass loss. Our results reinforce some previous evidence that, together, CWM and FD can explain leaf decomposition and highlight that the mean resource quality of leaf mixtures is a driver of biomass loss. Also, as previously reported for temperate ecosystems, trait variability does not always increase leaf decomposition in tropical ecosystems. Therefore, there is a need to consider simultaneously both MRH and NCH in future studies, using an appropriate design, keeping in mind that both mechanisms will always be present in any species mixture or combination.     

The genetic variance but not the genetic covariance of life‐history traits changes towards the north in a time‐constrained insect

Seasonal time constraints are usually stronger at higher than lower latitudes and can exert strong selection on life‐history traits and the correlations among these traits. To predict the response of life‐history traits to environmental change along a latitudinal gradient, information must be obtained about genetic variance in traits and also genetic correlation between traits, that is the genetic variance‐covariance matrix, G . Here, we estimated G for key life‐history traits in an obligate univoltine damselfly that faces seasonal time constraints. We exposed populations to simulated native temperatures and photoperiods and common garden environmental conditions in a laboratory set‐up. Despite differences in genetic variance in these traits between populations (lower variance at northern latitudes), there was no evidence for latitude‐specific covariance of the life‐history traits. At simulated native conditions, all populations showed strong genetic and phenotypic correlations between traits that shaped growth and development. The variance–covariance matrix changed considerably when populations were exposed to common garden conditions compared with the simulated natural conditions, showing the importance of environmentally induced changes in multivariate genetic structure. Our results highlight the importance of estimating variance–covariance matrixes in environments that mimic selection pressures and not only trait variances or mean trait values in common garden conditions for understanding the trait evolution across populations and environments.     

Using mixtures of biological samples as process controls for RNA-sequencing experiments

Background

Genome-scale “-omics” measurements are challenging to benchmark due to the enormous variety of unique biological molecules involved. Mixtures of previously-characterized samples can be used to benchmark repeatability and reproducibility using component proportions as truth for the measurement. We describe and evaluate experiments characterizing the performance of RNA-sequencing (RNA-Seq) measurements, and discuss cases where mixtures can serve as effective process controls.

Results

We apply a linear model to total RNA mixture samples in RNA-seq experiments. This model provides a context for performance benchmarking. The parameters of the model fit to experimental results can be evaluated to assess bias and variability of the measurement of a mixture. A linear model describes the behavior of mixture expression measures and provides a context for performance benchmarking. Residuals from fitting the model to experimental data can be used as a metric for evaluating the effect that an individual step in an experimental process has on the linear response function and precision of the underlying measurement while identifying signals affected by interference from other sources. Effective benchmarking requires well-defined mixtures, which for RNA-Seq requires knowledge of the post-enrichment ‘target RNA’ content of the individual total RNA components. We demonstrate and evaluate an experimental method suitable for use in genome-scale process control and lay out a method utilizing spike-in controls to determine enriched RNA content of total RNA in samples.

Conclusions

Genome-scale process controls can be derived from mixtures. These controls relate prior knowledge of individual components to a complex mixture, allowing assessment of measurement performance. The target RNA fraction accounts for differential selection of RNA out of variable total RNA samples. Spike-in controls can be utilized to measure this relationship between target RNA content and input total RNA. Our mixture analysis method also enables estimation of the proportions of an unknown mixture, even when component-specific markers are not previously known, whenever pure components are measured alongside the mixture.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1912-7) contains supplementary material, which is available to authorized users.     

Mapping binary trait loci in the F(2:3) design

In the inheritance analysis of quantitative trait with low heritability, the precision is relatively low. In this situation, an F(2:3) design, which is genotyped in F(2) plants and phenotyped in the F(2:3) progeny, is applied to increase the precision in the detection of quantitative trait loci (QTL). This is because that residual variance on the basis of family-mean-based observations has been significantly decreased by increasing the number of F(2:3) progeny. Our previous results showed that the mixture distribution for the F(2:3) family of heterozygous F(2) plant can significantly increase the power of QTL detection relative to the classical F(2) design. In this article, we extended our previous method from continuous traits to binary traits in the F(2:3) design. The method here also takes full advantage of the mixture distribution. However, the method presented here differs from our previous method in 2 aspects. One is that the penetrance model is integrated with the liability model for mapping binary trait loci (BTL), and another is that the phenotypic data used in the analysis are the sum of phenotypic values of F(2:3) progeny derived from each F(2) plant rather than the average of F(2:3) progeny due to the fact that the distribution of the sum follows binomial distribution. In addition, the threshold in the liability model could also be estimated. Therefore, a new framework of mapping BTL on the basis of a single BTL model was set up and implemented via the Expectation-Maximization algorithm. Results of simulated studies showed that the proposed method provides accurate estimates for both the effects and the locations of BTL, with high statistical power even under the low heritability. With the new method, we are ready to map BTL, as we can do for quantitative traits under the F(2:3) design. The computer program performing the analysis of the simulated data is available to users for real data analysis.     

Honeybees Learn Odour Mixtures via a Selection of Key Odorants

Background

The honeybee has to detect, process and learn numerous complex odours from her natural environment on a daily basis. Most of these odours are floral scents, which are mixtures of dozens of different odorants. To date, it is still unclear how the bee brain unravels the complex information contained in scent mixtures.

Methodology/Principal Findings

This study investigates learning of complex odour mixtures in honeybees using a simple olfactory conditioning procedure, the Proboscis-Extension-Reflex (PER) paradigm. Restrained honeybees were trained to three scent mixtures composed of 14 floral odorants each, and then tested with the individual odorants of each mixture. Bees did not respond to all odorants of a mixture equally: They responded well to a selection of key odorants, which were unique for each of the three scent mixtures. Bees showed less or very little response to the other odorants of the mixtures. The bees'' response to mixtures composed of only the key odorants was as good as to the original mixtures of 14 odorants. A mixture composed of the other, non-key-odorants elicited a significantly lower response. Neither an odorant''s volatility or molecular structure, nor learning efficiencies for individual odorants affected whether an odorant became a key odorant for a particular mixture. Odorant concentration had a positive effect, with odorants at high concentration likely to become key odorants.

Conclusions/Significance

Our study suggests that the brain processes complex scent mixtures by predominantly learning information from selected key odorants. Our observations on key odorant learning lend significant support to previous work on olfactory learning and mixture processing in honeybees.     

Sampling intraspecific variability in leaf functional traits: Practical suggestions to maximize collected information

The choice of the best sampling strategy to capture mean values of functional traits for a species/population, while maintaining information about traits’ variability and minimizing the sampling size and effort, is an open issue in functional trait ecology. Intraspecific variability (ITV) of functional traits strongly influences sampling size and effort. However, while adequate information is available about intraspecific variability between individuals (ITV_BI) and among populations (ITV_POP), relatively few studies have analyzed intraspecific variability within individuals (ITV_WI). Here, we provide an analysis of ITV_WI of two foliar traits, namely specific leaf area (SLA) and osmotic potential (π), in a population of Quercus ilex L. We assessed the baseline ITV_WI level of variation between the two traits and provided the minimum and optimal sampling size in order to take into account ITV_WI, comparing sampling optimization outputs with those previously proposed in the literature. Different factors accounted for different amount of variance of the two traits. SLA variance was mostly spread within individuals (43.4% of the total variance), while π variance was mainly spread between individuals (43.2%). Strategies that did not account for all the canopy strata produced mean values not representative of the sampled population. The minimum size to adequately capture the studied functional traits corresponded to 5 leaves taken randomly from 5 individuals, while the most accurate and feasible sampling size was 4 leaves taken randomly from 10 individuals. We demonstrate that the spatial structure of the canopy could significantly affect traits variability. Moreover, different strategies for different traits could be implemented during sampling surveys. We partially confirm sampling sizes previously proposed in the recent literature and encourage future analysis involving different traits.     

水蚤滞育的数量遗传学研究:遗传与环境控制及遗传作用

在单性生殖循环水蚤群体中,滞育卵由有性生殖产生．在一系列实验中用到了不同种群和种类的水蚤,通过这些实验来观察：1)有性生殖和滞育卵复苏的遗传和环境控制;2)生活在相同区域中,但有不同生存微环境的近缘种类的有性生殖的光周期反应;3)在群体遗传结构上有性生殖的遗传效应(基因型均值和生活史性状遗传方差)．结果发现：1)遗传作用和环境作用,以及两者的相互作用都对有性生殖和滞育卵的孵化有显著的影响．GE显著的相互作用对环境中观察到的有性生殖来说,有助于维持其较高的遗传方差;2)在相同区域中,不同生存微环境的近缘种类的有性生殖的光周期反应有所不同．这有助于进一步区别近缘的水蚤种类,这也可能是一个水环境中同素异形的物种形成的例子;3)在有性生殖上,生活史性状平均值和遗传方差变化与前代选择造成的均值和遗传方差相反(遗传滑阻),这会造成暂时的适应不良(遗传滑阻和隐藏的遗传变异的表达),应对它补偿滞育的进化优势．     

Genetic parameters related to environmental variability of weight traits in a selection experiment for weight gain in mice; signs of correlated canalised response

Data from an experimental mice population selected from 18 generations to increase weight gain were used to estimate the genetic parameters associated with environmental variability. The analysis involved three traits: weight at 21 days, weight at 42 days and weight gain between 21 and 42 days. A dataset of 5273 records for males was studied. Data were analysed using Bayesian procedures by comparing the Deviance Information Criterion (DIC) value of two different models: one assuming homogeneous environmental variances and another assuming them as heterogeneous. The model assuming heterogeneity was better in all cases and also showed higher additive genetic variances and lower common environmental variances. The heterogeneity of residual variance was associated with systematic and additive genetic effects thus making reduction by selection possible. Genetic correlations between the additive genetic effects on mean and environmental variance of the traits analysed were always negative, ranging from -0.19 to -0.38. An increase in the heritability of the traits was found when considering the genetic determination of the environmental variability. A suggested correlated canalised response was found in terms of coefficient of variation but it could be insufficient to compensate for the scale effect associated with an increase of the mean.     

Plant domestication disrupts biodiversity effects across major crop types

Plant diversity fosters productivity in natural ecosystems. Biodiversity effects might increase agricultural yields at no cost in additional inputs. However, the effects of diversity on crop assemblages are inconsistent, probably because crops and wild plants differ in a range of traits relevant to plant–plant interactions. We tested whether domestication has changed the potential of crop mixtures to over‐yield by comparing the performance and traits of major crop species and those of their wild progenitors under varying levels of diversity. We found stronger biodiversity effects in mixtures of wild progenitors, due to larger selection effects. Variation in selection effects was partly explained by within‐mixture differences in leaf size. Our results indicate that domestication might disrupt the ability of crops to benefit from diverse neighbourhoods via reduced trait variance. These results highlight potential limitations of current crop mixtures to over‐yield and the potential of breeding to re‐establish variance and increase mixture performance.     

Haemoglobin synthesis in 28 obligatory cases for alpha-thalassemia traits.

In the Far East two types of alpha-thalassemia genes, namely alpha-thalassemia, (alpha-thal1), and alpha-thalassemia2 (alpha-thal2) exist. Definite diagnosis of the alpha-thal1 and alpha-thal2 traits is very difficult because their hematological findings are minimally abnormal or normal. This study attempts to characterize the heterozygotes by hemoglobin chain synthesis in reticulocytes from obligatory cases of the alpha-thal1 and alpha-thal2 traits. Twelve parents of babies with hemoglobin Bart's hydrops fetalis (obligatory alpha-thal1 trait) had the mean total radioactivity alpha/beta ratio of 0.76 +/- SD 0.04, while that of 7 normal controls was 1.06 +/- SD 0.04. The alpha/beta globin chain ratios of 16 cases, who were either parents or offspring of patients with hemoglobin H disease, were found to segregate into 2 groups, i.e. 0.78 +/- SD 0.03 (10 cases) and 0.9l1 and alpha-thal2 traits respectively. The hematological data of the first group showed definite hypochromic microcytic red cells, similar to those of the parents of the hydrops. The second group had significantly higher mean corpuscular hemoglobin than the first group, compatible with alpha-thal2 trait. Our globin chain synthesis study thus appears to be capable of discriminating normal, alpha-thal1 and alpha-thal2 traits.     

Leaf dry matter content as a predictor of grassland litter decomposition: a test of the ��mass ratio hypothesis��

The mass ratio hypothesis provides the key link between plant functional traits (PFTs) and ecosystem processes. Despite its centrality to the field it has had few direct tests. A litter decomposition study using grassland species, singly and in mixtures, was set up to see whether simple leaf traits could be used to predict the decomposition of leaf mixtures. Leaf Dry Matter Content (LDMC) was the trait that performed best. Mass loss in single species bags was best predicted using an exponential model. LDMC explained 48% of the variance in mixture mass loss. There was no significant impact of mixture species richness on mass loss. This study generally confirmed the predictions of the mass ratio hypothesis, but adds some support to other studies that indicate it needs broadening to take into account non-linear and threshold relationships between PFTs and ecosystem processes.     

Variability in patterns of growth and morphology of Posidonia oceanica exposed to urban and industrial wastes: contrasts with two reference locations

Urban and industrial wastes have been claimed to negatively affect Posidonia oceanica meadows, but few studies have addressed this issue by comparing disturbed locations with replicated reference locations. Here, we examined the general proposition that patterns of growth and morphology of P. oceanica exposed to urban and industrial effluents were different from those observed in reference meadows. Hypotheses were both on differences in mean values of response variables and on variation of these measures at a hierarchy of spatial scales (from centimetres to hundreds of metres). Results indicated a significant reduction in mean number of intermediate leaves at the outfall compared to reference locations, whereas the opposite pattern occurred for juvenile leaves. There were significant, though temporally variable differences in growth of rhizomes between disturbed and reference locations, with reduced growth at the outfall in 2 out of 3 years analysed. Measures of spatial variance in number of juvenile leaves and length of adult leaves at the scale of shoots were significantly larger at the outfall compared to reference locations. At the same scale, measures of spatial variance in length of juvenile and intermediate leaves were significantly lower at the putatively impacted location. Spatial variance in number of intermediate leaves was reduced at the outfall compared to reference locations at the scale of quadrats. Past values of spatial variance in number of leaves per shoot were lower at the outfall than at the two reference locations at the scale of shoots, whereas the opposite occurred at the scale of areas. None of the structural variables examined showed any difference between the putatively impacted location and the two reference locations, either in terms of mean response or as changes in spatial variance. These results indicated that integrating methods to examine present and past events of disturbance, including analyses to detect changes in spatial variance of response variables, may provide a powerful approach to the analysis of environmental impacts on P. oceanica.     

Comparison of the power between microsatellite and single-nucleotide polymorphism markers for linkage and linkage disequilibrium mapping of an electrophysiological phenotype

We performed linkage and linkage disequilibrium (LD) mapping analyses to compare the power between microsatellite and single nucleotide polymorphism (SNP) markers. Chromosome-wide analyses were performed for a quantitative electrophysiological phenotype, ttth1, on chromosome 7. Multipoint analysis of microsatellite markers using the variance component (VC) method showed the highest LOD score of 4.20 at 162 cM, near D7S509 (163.7 cM). Two-point analysis of SNPs using the VC method yielded the highest LOD score of 3.98 in the Illumina SNP data and 3.45 in the Affymetrix SNP data around 152-153 cM. In family-based single SNP and SNP haplotype LD analysis, we identified seven SNPs associated with ttth1. We searched for any potential candidate genes in the location of the seven SNPs. The SNPs rs1476640 and rs768055 are located in the FLJ40852 gene (a hypothetical protein), and SNP rs1859646 is located in the TAS2R5 gene (a taste receptor). The other four SNPs are not located in any known or annotated genes. We found the high density SNP scan to be superior to microsatellites because it is effective in downstream fine mapping due to a better defined linkage region. Our study proves the utility of high density SNP in genome-wide mapping studies.     

Selection Indices and Multivariate Analysis Show Similar Results in the Evaluation of Growth and Carcass Traits in Beef Cattle

This research evaluated a multivariate approach as an alternative tool for the purpose of selection regarding expected progeny differences (EPDs). Data were fitted using a multi-trait model and consisted of growth traits (birth weight and weights at 120, 210, 365 and 450 days of age) and carcass traits (longissimus muscle area (LMA), back-fat thickness (BF), and rump fat thickness (RF)), registered over 21 years in extensive breeding systems of Polled Nellore cattle in Brazil. Multivariate analyses were performed using standardized (zero mean and unit variance) EPDs. The k mean method revealed that the best fit of data occurred using three clusters (k = 3) (P < 0.001). Estimates of genetic correlation among growth and carcass traits and the estimates of heritability were moderate to high, suggesting that a correlated response approach is suitable for practical decision making. Estimates of correlation between selection indices and the multivariate index (LD1) were moderate to high, ranging from 0.48 to 0.97. This reveals that both types of indices give similar results and that the multivariate approach is reliable for the purpose of selection. The alternative tool seems very handy when economic weights are not available or in cases where more rapid identification of the best animals is desired. Interestingly, multivariate analysis allowed forecasting information based on the relationships among breeding values (EPDs). Also, it enabled fine discrimination, rapid data summarization after genetic evaluation, and permitted accounting for maternal ability and the genetic direct potential of the animals. In addition, we recommend the use of longissimus muscle area and subcutaneous fat thickness as selection criteria, to allow estimation of breeding values before the first mating season in order to accelerate the response to individual selection.     

Prediction of breeding values and selection responses with genetic heterogeneity of environmental variance

There is empirical evidence that genotypes differ not only in mean, but also in environmental variance of the traits they affect. Genetic heterogeneity of environmental variance may indicate genetic differences in environmental sensitivity. The aim of this study was to develop a general framework for prediction of breeding values and selection responses in mean and environmental variance with genetic heterogeneity of environmental variance. Both means and environmental variances were treated as heritable traits. Breeding values and selection responses were predicted with little bias using linear, quadratic, and cubic regression on individual phenotype or using linear regression on the mean and within-family variance of a group of relatives. A measure of heritability was proposed for environmental variance to standardize results in the literature and to facilitate comparisons to "conventional" traits. Genetic heterogeneity of environmental variance can be considered as a trait with a low heritability. Although a large amount of information is necessary to accurately estimate breeding values for environmental variance, response in environmental variance can be substantial, even with mass selection. The methods developed allow use of the well-known selection index framework to evaluate breeding strategies and effects of natural selection that simultaneously change the mean and the variance.