Field measurements of genotype by environment interaction for fitness caused by spontaneous mutations in Arabidopsis thaliana

As the ultimate source of genetic diversity, spontaneous mutation is critical to the evolutionary process. The fitness effects of spontaneous mutations are almost always studied under controlled laboratory conditions rather than under the evolutionarily relevant conditions of the field. Of particular interest is the conditionality of new mutations—that is, is a new mutation harmful regardless of the environment in which it is found? In other words, what is the extent of genotype–environment interaction for spontaneous mutations? We studied the fitness effects of 25 generations of accumulated spontaneous mutations in Arabidopsis thaliana in two geographically widely separated field environments, in Michigan and Virginia. At both sites, mean total fitness of mutation accumulation lines exceeded that of the ancestors, contrary to the expected decrease in the mean due to new mutations but in accord with prior work on these MA lines. We observed genotype–environment interactions in the fitness effects of new mutations, such that the effects of mutations in Michigan were a poor predictor of their effects in Virginia and vice versa. In particular, mutational variance for fitness was much larger in Virginia compared to Michigan. This strong genotype–environment interaction would increase the amount of genetic variation maintained by mutation‐selection balance.     

Crop diagnosis and probe genotypes for interpreting genotype environment interaction in winter wheat trials

Genotype*environment interaction has been analyzed with 12 genotypes and four probe genotypes in French wheat trials. An integrated approach was developed which combined crop diagnosis with the analysis of interaction by factorial regression. Crop diagnosis was helpful to characterize the environments and to select environmental variables. Such an approach succeeded in providing an agronomic explanation of genotype*environment interaction and in defining the responses or parameters for each genotype and each environment. Earliness at heading, susceptibility to powdery mildew and susceptibility to lodging were the three major genotypic covariates. Interaction could also be related to environment features, measured indirectly by the behavior of the four probe genotypes during the formation of yield, what we called the outputs of a simplified crop diagnosis, or described directly by indicators of yield-limiting factors. Two important crop diagnosis covariates were analyzed in order to characterize interaction during the formation of yield: the reduction in kernel number, which described the time-period until flowering, and the reduction in thousand kernel weight, which corresponded to the period after flowering. These variates were estimated for each probe genotype and allowed us to compare the behavior of the 12 genotypes to that of the probe genotypes. Both periods of the formation of yield contributed to the interaction, and ’Camp-Rémy’ was the probe of particular interest for the comparisons. When true environmental variates were used, factorial regression revealed that water deficits during the formation of grain number and level of nitrogen were predominant. Such an integrated approach could be exploited when varieties are tested in a network where numerous and diverse yield-limiting factors may occur. Received: 3 August 1998 / Accepted: 16 March 1999     

An APL procedure to estimate genotype by environment interaction when two environments are considered

Genotype by environment interaction (GEI) is a relevant topicin many fields of applied biology. Normal parametric approachesfollowing analysis of variance are not suitable when large differencesbetween error variances within environments are present. Weillustrate an APL program following Yamada's approach to estimateGEIs and ancillary statistics when two environments are considered.The choice of APL environment is based on its value as a usefultool in algorithm implementation and problem-solving. Its useis suggested in biological applications where matrix algebrais involved and an understanding of the computing complexityof problems is generally not required.     

Paternal HLA genotype and offspring sex ratio.

For twenty years, W.H. James has been proposing that the sex hormone level of both parents could control at least a quota of the secondary sex ratio variation at the time of conception. Observations supporting this hypothesis have come from investigations on some diseases related to the human leukocyte antigen (HLA). In the present study on 1102 healthy Italian families, we investigated the potential effect on the offspring sex ratio of HLA-B alleles on the basis of a genetic model. We defined three subsets of HLA-B alleles and hypothesized a locus (L) with three alleles, L(H), L(N), L(B15), on the basis of the positive, neutral, or negative effect on the testosterone level. According to the genetic model and the dominance relation L(H) > L(B15) > L(N), six genotypic and three phenotypic classes (H, N, B15) can be expected. We found a significantly high number of daughters (66%) born to fathers carrying the B15 phenotype. This result suggests an effect of the HLA-B15 allele on the secondary sex ratio, mediated by a low testosterone level.     

Genetic variance of sexually selected traits in waxmoths: maintenance by genotype x environment interaction

When traits experience directional selection, such as that imposed by sexual selection, their genetic variance is expected to diminish. Nonetheless, theory and findings from sexual selection predict and demonstrate that male traits favored by female choice retain substantial amounts of additive genetic variance. We explored this dilemma through an ecological genetic approach and focused on the potential contributions of genotype x environment interaction (GEI) to maintenance of additive genetic variance for male signal characters in the lesser waxmoth, Achroia grisella (Lepidoptera: Pyralidae). We artificially selected genetic variants for two male signal characters, signal rate (SR) and peak amplitude (PA), that influence female attraction and then examined the phenotypic plasticity of these variants (high- and low-SR and high- and low-PA lines) under a range of environmental conditions expected in natural populations. Our split-family breeding experiments indicated that two signal characters, SR and PA, and several developmental characters in both high- and low-SR and high- and low-PA lines displayed considerable phenotypic plasticity among the environments tested. Moreover, strong GEIs leading to crossover between high- and low-SR lines were found for SR and developmental period. Therefore, neither high- nor low-SR genetic variants would achieve maximum attractiveness and fitness in every environment, and those variants producing unattractive signals with low SRs under normal conditions may remain in populations provided that gene flow across environments or generation overlap are sufficiently high. We speculate that the phenotypic plasticity for SR and developmental period is adaptive in A. grisella populations experiencing a range of temperature and density conditions. Females mating with attractive (high-SR) males may be assured of obtaining good genes because these males sire offspring that develop more rapidly and a crossover for developmental period may parallel that for SR. Such parallel crossovers may be expected wherever good-genes sexual selection mechanisms operate.     

Study on the limitation for detecting anaerobic threshold by respiratory frequency]

It has been reported that respiratory frequency (F) serves to determine anaerobic threshold (AT). The purpose of this study was to investigate whether the method detecting AT by using F is influenced by the subject's condition such as the existence of sport experiences. Ten healthy adults volunteered to perform progressive cycle ergometer exercise with workloads increased by 30-W (female:20-W) every 2 min at 60 rpm. VO2 at AT were determined by four different methods, which detect the point of 1)nonlinear increase in VE, VCO2, and increase in VE/VO2 without increasing in VE/VCO2 (AT-v), 2) nonlinear increase in F (visual estimation: AT-VF), 3) inflection in F by multisegment linear regression (AT-CF), 4) inflection with omitting above RC point as with 3) (AT-CF2). The mean VO2 at AT-VF (40.8 +/- 9.2 ml/kg/min) and AT-CF (42.7 +/- 9.9 ml/kg/min) was significantly higher compared with AT-V (28.2 +/- 10.4 ml/kg/min) and not RC (42.3 +/- 10.0 ml/kg/min). It would be possible that AT-VF and AT-CF indicated RC, but not AT. There were no significant differences between AT-CF2 (28.2 +/- 10.9 ml/kg/min) and AT-V, and a highly positive correlation (r = 0.79, p less than 0.05) was observed between them. It was recognized that F reached a plateau at AT in four of the subjects. The error between AT-V and AT-CF2 was observed individual variations and the error between them within 5% was observed in only one subject. These results suggest that F is inadequate as an indicator of the AT, because F may be influenced by entrainment of breathing and pedalling frequency.     

Simultaneously accounting for population structure, genotype by environment interaction, and spatial variation in marker-trait associations in sugarcane

Few association mapping studies have simultaneously accounted for population structure, genotype by environment interaction (GEI), and spatial variation. In this sugarcane association mapping study we tested models accounting for these factors and identified the impact that each model component had on the list of markers declared as being significantly associated with traits. About 480 genotypes were evaluated for cane yield and sugar content at three sites and scored with DArT markers. A mixed model was applied in analysis of the data to simultaneously account for the impacts of population structure, GEI, and spatial variation within a trial. Two forms of the DArT marker data were used in the analysis: the standard discrete data (0, 1) and a continuous DArT score, which is related to the marker dosage. A large number of markers were significantly associated with cane yield and sugar content. However, failure to account for population structure, GEI, and (or) spatial variation produced both type I and type II errors, which on the one hand substantially inflated the number of significant markers identified (especially true for failing to account for GEI) and on the other hand resulted in failure to detect markers that could be associated with cane yield or sugar content (especially when failing to account for population structure). We concluded that association mapping based on trials from one site or analysis that failed to account for GEI would produce many trial-specific associated markers that would have low value in breeding programs.     

Association of single-nucleotide polymorphisms at the Delta locus with genotype by environment interaction for sensory bristle number in drosophila Melanogaster

The nature of forces maintaining variation for quantitative traits can only be assessed at the level of individual genes affecting variation in the traits. Identification of single-nucleotide polymorphisms (SNPs) associated with variation in Drosophila sensory bristle number at the Delta (Dl) locus provides us with the opportunity to test a model for the maintenance of variation in bristle number by genotype by environment interaction (GEI). Under this model, genetic variation is maintained at a locus under stabilizing selection if phenotypic values of heterozygotes are more stable than homozygotes across a range of environments, and the mean allelic effect is much smaller than the standard deviation of allelic effects across environments. Homozygotes and heterozygotes for two SNPs at Dl, one affecting sternopleural and the other abdominal bristle number, were reared in five different environments. There was significant GEI for both bristle traits. Neither condition of the model was satisfied for Dl SNPs exhibiting GEI for sternopleural bristle number. Heterozygotes for the abdominal bristle number SNPs were indeed the most stable genotype for two of the three environment pairs exhibiting GEI, but the mean genotypic effect was greater than the standard deviation of effects across environments. Therefore, this mechanism of GEI seems unlikely to be responsible for maintaining the common bristle number polymorphisms at Dl.     

A religious upbringing reduces the influence of genetic factors on disinhibition: evidence for interaction between genotype and environment on personality.

Information on personality, on anxiety and depression and on several aspects of religion was collected in 1974 Dutch families consisting of adolescent and young adult twins and their parents. Analyses of these data showed that differences between individuals in religious upbringing, in religious affiliation and in participation in church activities are not influenced by genetic factors. The familial resemblance for different aspects of religion is high, but can be explained entirely by environmental influences common to family members. Shared genes do not contribute to familial resemblances in religion. The absence of genetic influences on variation in several dimensions of religion is in contrast to findings of genetic influences on a large number of other traits that were studied in these twin families. Differences in religious background are associated with differences in personality, especially in Sensation Seeking. Subjects with a religious upbringing, who are currently religious and who engage in church activities score lower on the scales of the Sensation Seeking Questionnaire. The most pronounced effect is on the Disinhibition scale. The resemblances between twins for the Disinhibition scale differ according to their religious upbringing. Receiving a religious upbringing seems to reduce the influence of genetic factors on Disinhibition, especially in males.     

Quantitative trait loci and candidate genes underlying genotype by environment interaction in the response of Arabidopsis thaliana to drought

Drought stress was imposed on two sets of Arabidopsis thaliana genotypes grown in sand under short‐day conditions and analysed for several shoot and root growth traits. The response to drought was assessed for quantitative trait locus (QTL) mapping in a genetically diverse set of Arabidopsis accessions using genome‐wide association (GWA) mapping, and conventional linkage analysis of a recombinant inbred line (RIL) population. Results showed significant genotype by environment interaction (G×E) for all traits in response to different watering regimes. For the RIL population, the observed G×E was reflected in 17 QTL by environment interactions (Q×E), while 17 additional QTLs were mapped not showing Q×E. GWA mapping identified 58 single nucleotide polymorphism (SNPs) associated with loci displaying Q×E and an additional 16 SNPs associated with loci not showing Q×E. Many candidate genes potentially underlying these loci were suggested. The genes for RPS3C and YLS7 were found to contain conserved amino acid differences when comparing Arabidopsis accessions with strongly contrasting drought response phenotypes, further supporting their candidacy. One of these candidate genes co‐located with a QTL mapped in the RIL population.     

Response to mass selection when the genotype by environment interaction is modelled as a linear reaction norm

A breeding goal accounting for the effects of genotype by environment interaction (G × E) has to define not only traits but also the environment in which those traits are to be improved. The aim of this study was to predict the selection response in the coefficients of a linear reaction norm, and response in average phenotypic value in any environment, when mass selection is applied to a trait where G × E is modelled as a linear reaction norm. The optimum environment in which to test the selection candidates for a given breeding objective was derived. Optimisation of the selection environment can be used as a means to either maximise genetic progress in a certain response environment, to keep the change in environmental sensitivity at a desired rate, or to reduce the proportion of animals performing below an acceptance level. The results showed that the optimum selection environment is not always equal to the environment in which the response is to be realised, but depends on the degree of G × E (determined by the ratio of variances in slope and level of a linear reaction norm), the correlation between level and slope, and the heritability of the trait.     

Parametric relationships between genotype x environment interaction and genetic correlation when two environments are involved

Summary Parametric relationships between the genotype x environment interaction and the genetic correlation of the same attribute measured in two different environments are derived. It is shown that the criticism by Fernando et al. (1984) of Yamada's method (1962) in the case of unbalanced data is irrelevant.     

Interpreting genotype × environment interaction in tropical maize using linked molecular markers and environmental covariables

An understanding of the genetic and environmental basis of genotype×environment interaction (GEI) is of fundamental importance in plant breeding. In mapping quantitative trait loci (QTLs), suitable genetic populations are grown in different environments causing QTLs×environment interaction (QEI). The main objective of the present study is to show how Partial Least Squares (PLS) regression and Factorial Regression (FR) models using genetic markers and environmental covariables can be used for studying QEI related to GEI. Biomass data were analyzed from a multi-environment trial consisting of 161 lines from a F_3:4 maize segregating population originally created with the purpose of mapping QTLs loci and investigating adaptation differences between highland and lowland tropical maize. PLS and FR methods detected 30 genetic markers (out of 86) that explained a sizeable proportion of the interaction of maize lines over four contrasting environments involving two low-altitude sites, one intermediate-altitude site, and one high-altitude site for biomass production. Based on a previous study, most of the 30 markers were associated with QTLs for biomass and exhibited significant QEI. It was found that marker loci in lines with positive GEI for the highland environments contained more highland alleles, whereas marker loci in lines with positive GEI for intermediate and lowland environments contained more lowland alleles. In addition, PLS and FR models identified maximum temperature as the most-important environmental covariable for GEI. Using a stepwise variable selection procedure, a FR model was constructed for GEI and QEI that exclusively included cross products between genetic markers and environmental covariables. Higher maximum temperature in low- and intermediate-altitude sites affected the expression of some QTLs, while minimum temperature affected the expression of other QTLs. Received: 10 January 1999 / Accepted: 12 March 1999     

A QTL for genotype by sex interaction for anthropometric measurements in Alaskan Eskimos (GOCADAN Study) on chromosome 19q12-13

Variation in anthropometric measurements due to sexual dimorphism can be the result of genotype by sex interactions (G×S). The purpose of this study was to examine the sex-specific genetic architecture in anthropometric measurements in Alaskan Eskimos from the Genetics of Coronary Artery Disease in Alaska Natives (GOCADAN) study. Maximum likelihood-based variance components decomposition methods, implemented in SOLAR, were used for G×S analyses. Anthropometric measurements included BMI, waist circumference (WC), waist/height ratio, percent body fat (%BF), and subscapular and triceps skinfolds. Except for WC, mean values of all phenotypes were significantly different in men and women (P < 0.05). All anthropometric measures were significantly heritable (P < 0.001). In a preliminary analysis not allowing for G×S interaction, evidence of linkage was detected between markers D19S414 and D19S220 on chromosome 19 for WC (logarithm of odds (lod) = 3.5), %BF (lod = 1.7), BMI (lod = 2.4), waist/height ratio (lod = 2.5), subscapular (lod = 2.1), and triceps skinfolds (lod = 1.9). In subsequent analyses which allowed for G×S interaction, linkage was again found between these traits and the same two markers on chromosome 19 with significantly improved lod scores for: WC (lod = 4.5), %BF (lod = 3.8), BMI (lod = 3.5), waist/height ratio (lod = 3.2), subscapular (lod = 3.0), and triceps skinfolds (lod = 2.9). These results support the evidence of a G×S interaction in the expression of genetic effects resulting in sexual dimorphism in anthropometric phenotypes and identify the chromosome 19q12-13 region as important for adiposity-related traits in Alaskan Eskimos.     

Contrasting levels of genotype by environment interaction for life history and morphological traits in invasive populations of Zaprionus indianus (Diptera: Drosophilidae)

It has been demonstrated that phenotypic plasticity and genotype by environment interaction are important for coping with new and heterogeneous environments during invasions. Zaprionus indianus Gupta (Diptera: Drosophilidae) is an Afrotropical invasive fly species introduced to the South American continent in 1999. This species is generalist and polyphagous, since it develops and feeds in several different fruit species. These characteristics of Z. indianus suggest that phenotypic plasticity and genotype by environment interaction may be important in this species invasion process. In this sense, our aim was to investigate the role of genetic variation for phenotypic plasticity (genotype by environment interaction) in Z. indianus invasion of the South American continent. Specifically, we quantified quantitative genetic variation and genotype by environment interactions of morphological and life history traits in different developmental environments, that is, host fruits. This was done in different populations in the invasive range of Z. indianus in Argentina. Results showed that Z. indianus populations have considerable amounts of quantitative genetic variation. Also, genotype by environment interactions was detected for the different traits analyzed in response to the different developmental environments. Interestingly, the amounts and patterns of these parameters differed between populations. We interpreted these results as the existence of differences in evolutionary potential between populations that have an important role in the short‐ and long‐term success of the Z. indianus invasion process.     

Efficient algorithms for detecting signaling pathways in protein interaction networks.

The interpretation of large-scale protein network data depends on our ability to identify significant substructures in the data, a computationally intensive task. Here we adapt and extend efficient techniques for finding paths and trees in graphs to the problem of identifying pathways in protein interaction networks. We present linear-time algorithms for finding paths and trees in networks under several biologically motivated constraints. We apply our methodology to search for protein pathways in the yeast protein-protein interaction network. We demonstrate that our algorithm is capable of reconstructing known signaling pathways and identifying functionally enriched paths and trees in an unsupervised manner. The algorithm is very efficient, computing optimal paths of length 8 within minutes and paths of length 10 in about three hours.     

B cell genotype determines interaction preference with T cells: no effect of maturation environment

B cell development in the bursa of Fabricius of the chicken was examined. We constructed neonatal bursa cell chimeras (F1 leads to parent, parent leads to F1) and studied the in vivo interaction of these chimeric B cells with host-derived T cells in adoptive cell transfer to determine whether there exists any environmental effect on B cells for MHC-restricted T-B cell interaction. The results indicate that F1 B cells that have developed in a parental host bursa still behave as normal F1 B cells and do not show any change in their MHC-restriction pattern. In addition, parent leads to F1 chimeric B cells were indistinguishable from normal parental B cells. B cells from all constructed chimeras, including fully allogeneic, responded well to the T-independent antigen Brucella. We conclude that the genotype of the B cell, and not the developmental environment, determines the MHC restriction phenotype of mature B cells.