Heritability and gene-environment interactions for melanocytic nevus density examined in a U.K. adolescent twin study

Risk factors for melanoma include environmental (particularly ultraviolet exposure) and genetic factors. In rare families, susceptibility to melanoma is determined by high penetrance mutations in the genes CDKN2A or CDK4, with more common, less penetrant genes also postulated. A further, potent risk factor for melanoma is the presence of large numbers of melanocytic nevi so that genes controlling nevus phenotype could be such melanoma susceptibility genes. A large Australian study involving twins aged 12 y of predominantly U.K. ancestry showed strong evidence for genetic influence on nevus number and density. We carried out essentially the same study in the U.K. to gain insight into gene-environment interactions for nevi. One hundred and three monozygous (MZ) and 118 dizygous (DZ) twin pairs aged 10-18 y were examined in Yorkshire and Surrey, U.K. Nevus counts were, on average, higher in boys (mean = 98.6) than girls (83.8) (p = 0.009) and higher in Australia (110.4) than in the U.K. (79.2, adjusted to age 12 y, p < 0.0001), and nevus densities were higher on sun-exposed sites (92 per m(2)) than sun-protected sites (58 per m(2)) (p < 0.0001). Correlations in sex and age adjusted nevus density were higher in MZ pairs (0.94, 95% CI 0.92-0.96) than in DZ pairs (0.61, 95%CI 0.49-0.72), were notably similar to those of the Australian study (MZ = 0.94, DZ = 0.60), and were consistent with high heritability (65% in the U.K., 68% in Australia). We conclude that emergence of nevi in adolescents is under strong genetic control, whereas environmental exposures affect the mean number of nevi.

The E(NK) model: extending the NK model to incorporate gene-by-environment interactions and epistasis for diploid genomes

The haploid NK model developed by Kauffman can be extended to diploid genomes and to incorporate gene-by-environment interaction effects in combination with epistasis. To provide the flexibility to include a wide range of forms of gene-by-environment interactions, a target population of environment types (TPE) is defined. The TPE consists of a set of E different environment types, each with their own frequency of occurrence. Each environment type conditions a different NK gene network structure or series of gene effects for a given network structure, providing the framework for defining gene-by-environment interactions. Thus, different NK models can be partially or completely nested within the E environment types of a TPE, giving rise to the E(NK) model for a biological system. With this model it is possible to examine how populations of genotypes evolve in context with properties of the environment that influence the contributions of genes to the fitness values of genotypes. We are using the E(NK) model to investigate how both epistasis and gene-by-environment interactions influence the genetic improvement of quantitative traits by plant breeding strategies applied to agricultural systems. © 2002 Wiley Periodicals, Inc.

Analysis of line x environment interactions for yield in navy beans. 2. Pattern analysis of lines and environment within years

Seven years of multi-environment yield trials of navy bean (Phaseolus vulgaris L.) grown in Queensland were examined. As is common with plant breeding evaluation trials, test entries and locations varied between years. Grain yield data were analysed for each year using cluster and ordination analyses (pattern analyses). These methods facilitate descriptions of genotype performance across environments and the discrimination among genotypes provided by the environments. The observed trends for genotypic yield performance across environments were partly consistent with agronomic and disease reactions at specific environments and also partly explainable by breeding and selection history. In some cases, similarities in discrimination among environments were related to geographic proximity, in others management practices, and in others similarities occurred between geographically widely separated environments which differed in management practices. One location was identified as having atypical line discrimination. The analysis indicated that the number of test locations was below requirements for adequate representation of line x environment interaction. The pattern analyses methods used were an effective aid in describing the patterns in data for each year and illustrated the variations in adaptive patterns from year to year. The study has implications for assessing the number and location of test sites for plant breeding multi-environment trials, and for the understanding of genetic traits contributing to line x environment interactions.

Evaluating plant breeding strategies by simulating gene action and dryland environment effects

Functional genomics is the systematic study of genome-wide effects of gene expression on organism growth and development with the ultimate aim of understanding how networks of genes influence traits. Here, we use a dynamic biophysical cropping systems model (APSIM-Sorg) to generate a state space of genotype performance based on 15 genes controlling four adaptive traits and then search this spice using a quantitative genetics model of a plant breeding program (QU-GENE) to simulate recurrent selection. Complex epistatic and gene X environment effects were generated for yield even though gene action at the trait level had been defined as simple additive effects. Given alternative breeding strategies that restricted either the cultivar maturity type or the drought environment type, the positive (+) alleles for 15 genes associated with the four adaptive traits were accumulated at different rates over cycles of selection. While early maturing genotypes were favored in the Severe-Terminal drought environment type, late genotypes were favored in the Mild-Terminal and Midseason drought environment types. In the Severe-Terminal environment, there was an interaction of the stay-green (SG) trait with other traits: Selection for + alleles of the SG genes was delayed until + alleles for genes associated with the transpiration efficiency and osmotic adjustment traits had been fixed. Given limitations in our current understanding of trait interaction and genetic control, the results are not conclusive. However, they demonstrate how the per se complexity of gene X gene X environment interactions will challenge the application of genomics and marker-assisted selection in crop improvement for dryland adaptation.

Case-only study of interactions between genetic polymorphisms of GSTM1, P1, T1 and Z1 and smoking in Parkinson's disease

Current opinion contends that complex interactions between genetic and environmental factors play a role in the etiology of Parkinson's disease (PD). Cigarette smoking is thought to reduce risk of PD, and emerging evidence suggests that genetic factors may modulate smoking's effect. We used a case-only design, an approach not previously used to study gene-environment interactions in PD, specifically to study interactions between glutathione-S-transferase (GST) gene polymorphisms and smoking in relation to PD. Four-hundred PD cases (age at onset: 60.0 +/- 10.7 years) were genotyped for common polymorphisms in GSTM1, PI, T1 and Z1 using well-established methods. Smoking exposure data were collected in face-to-face interviews. The independence of the studied GST genotypes and smoking exposure was confirmed by studying 402 healthy, aged individuals. No differences were observed in the distributions of GSTM1, T1 or Z1 polymorphisms between ever-smoked and never-smoked PD cases using logistic regression (all P > 0.43). However, GSTP1 *C haplotypes were over-represented among PD cases who ever smoked (odds ratio for interaction (ORi) = 2.00 (95% Cl: 1.11-3.60, P = 0.03)). Analysis revealed that ORi between smoking and the GSTP1-114Val carrier status increased with increasing smoking dose (P = 0.02 for trend). These data suggest that one or more GSTP1 polymorphisms may interact with cigarette smoking to influence the risk for PD. (C) 2004 Elsevier Ireland Ltd. All rights reserved.

Measurement and management of genotype-environment interaction (GxE) for the improvement of rainfed lowland rice yield in Cambodia

The magnitude and nature of genotype-by-environment interactions (G×E) for grain yield (GY) and days to flower (DTF) in Cambodia were examined using a random population of 34 genotypes taken from the Cambodian rice improvement program. These genotypes were evaluated in multi-environment trials (MET) conducted across three years (2000 to 2002) and eight locations in the rainfed lowlands. The G×E interaction was partitioned into components attributed to genotype-by-location (G×L), genotype-by-year (G×Y) and genotype-by-location-by-year (G×L×Y) interactions. The G×L×Y interaction was the largest component of variance for GY. The G×L interaction was also significant and comparable in size to the genotypic component (G). The G×Y interaction was small and non significant. A major factor contributing to the large G×L×Y interactions for GY was the genotypic variation for DTF in combination with environmental variation for the timing and intensity of drought. Some of the interactions for GY associated with timing of plant development and exposure to drought were repeatable across the environments enabling the identification of three-target populations of environments (TPE) for consideration in the breeding program. Four genotypes were selected for wide adaptation in the rainfed lowlands in Cambodia.

Partial automation of database processing of simulation outputs from L-systems models of plant morphogenesis

Models of plant architecture allow us to explore how genotype environment interactions effect the development of plant phenotypes. Such models generate masses of data organised in complex hierarchies. This paper presents a generic system for creating and automatically populating a relational database from data generated by the widely used L-system approach to modelling plant morphogenesis. Techniques from compiler technology are applied to generate attributes (new fields) in the database, to simplify query development for the recursively-structured branching relationship. Use of biological terminology in an interactive query builder contributes towards making the system biologist-friendly. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

Yield response of rice (Oryza sativa L.) genotypes to different types of drought under rainfed lowlands - Part 1. Grain yield and yield components

Responses of rice genotypes to drought stress may be different when characteristics of the drought stress environments differ. The performance of 128 genotypes was examined under irrigation and four different types of drought stress, to determine genotypic consistency in yield and factors determining yields under different drought stress conditions. The different drought conditions were mild drought during grain filling, short and severe drought at flowering, prolonged severe drought during the reproductive to grain filling, and prolonged mild drought during vegetative and grain filling. Genotypic grain yield under mild stress conditions was associated with yield under irrigated conditions, indicating the importance of potential yield in environments where the yield reduction was less than 50%. However, yields under irrigated conditions differed over time and locations. Under prolonged or severe drought conditions, flowering time was an important determinant of grain yield. Earlier flowering genotypes escaped the severe stress and had higher grain yields indicating large genotype by environment (G x E) interactions which have implications for plant breeding even for mild stress. It is suggested that variations in flowering time, potential yields and drought patterns need to be considered for development of drought-resistant cultivars using specific physiological traits. (C) 2002 Elsevier Science B.V. All rights reserved.

Yield response of rice (Oryza sativa L.) genotypes to different types of drought under rainfed lowlands - Part 2. Selection of drought resistant genotypes

Drought frequently reduces grain yield of rainfed lowland rice. A series of experiments were conducted in drought-prone northeast Thailand to study the magnitude and consistency of yield responses of diverse, rainfed lowland rice genotypes to drought stress environments and to examine ways to identify genotypes that confer drought resistance. One hundred and twenty-eight genotypes were grown under non-stress and four different types of drought stress conditions. The relationship of genotypic variation in yield under drought conditions to genetic yield potential, flowering time and flowering delay, and to a drought response index (DRI) that removed the effect of potential yield and flowering time on yield under stress was examined. Drought stress that developed prior to flowering generally delayed the time of flowering of genotypes, and the delay in flowering was negatively associated with grain yield, fertile panicle percentage and filled grain percentage. Genotypes with a longer delay in flowering time had extracted more water during the early drought period, and as a consequence, had higher water deficits. They were consistently associated with a larger yield reduction under drought and in one experiment with a smaller DRI. Genotypes, however, responded differently to the different drought stress conditions and there was no consistency in the DRI estimates for the different genotypes across the drought stress experiments. The results indicate that with the use of irrigated-control and drought test environments, genotypes with drought resistance can be identified by using DRI or delay in flowering. However, selections will differ depending on the type of drought condition. The inconsistency of the estimates in DRI and flowering delay across different drought conditions reflects the nature of the large genotype-by-environment interactions observed for grain yield under various types of drought in rainfed lowland conditions. (C), 2002 Elsevier Science B.V. All rights reserved.

Identification of research to improve the efficiency of breeding strategies for white clover in Australia - a review

A major challenge faced by today's white clover breeder is how to manage resources within a breeding program. It is essential to utilise these resources with sufficient flexibility to build on past progress from conventional breeding strategies, but also take advantage of emerging opportunities from molecular breeding tools such as molecular markers and transformation. It is timely to review white clover breeding strategies. This background can then be used as a foundation for considering how to continue conventional plant improvement activities and complement them with molecular breeding opportunities. In this review, conventional white clover breeding strategies relevant to the Australian dryland target population environments are considered. Attention is given to: (i) availability of genetic variation, (ii) characterisation of germplasm collections, (iii) quantitative models for estimation of heritability, (iv) the role of multi-environment trials to accommodate genotype-by-environment interactions, (v) interdisciplinary research to understand adaptation to dryland environments, (vi) breeding and selection strategies, and (vii) cultivar structure. Current achievements in biotechnology with specific reference to white clover breeding in Australia are considered, and computer modelling of breeding programs is discussed as a useful integrative tool for the joint evaluation of conventional and molecular breeding strategies and optimisation of resource use in breeding programs. Four areas are identified as future research priorities: (i) capturing the potential genetic diversity among introduced accessions and ecotypes that are adapted to key constraints such as summer moisture stress and the use of molecular markers to assess the genetic diversity, (ii) understanding the underlying physiological/morphological root and shoot mechanisms involved in water use efficiency of white clover, with the objective of identifying appropriate selection criteria, (iii) estimation of quantitative genetic parameters of important morphological/physiological attributes to enable prediction of response to selection in target environments, and (iv) modelling white clover breeding strategies to evaluate the opportunities for integration of molecular breeding strategies with conventional breeding programs.