Genotype by environment interactions (GxE) can form a potential source of inefficiency in animal breeding if selection decisions are made without accounting for their effects. The UK sheep industry covers an assorted range of farming systems and environments, with each flock having a unique and diverse set of resources and management styles. As a result, what may be the best performing genotype in one environment may not necessarily be the best performing genotype in another. This thesis reports on an investigation into the presence of GxE within the UK sheep industry. Pedigree and performance data, available from both hill and terminal sire breeds, were analysed using a number of different methods. When environments were defined as 2 individual hill farms, genetic correlations were estimated between farms, for a range of Scottish Blackface ewe and lamb traits. Those found to be significantly different from 1 (P<0.05), and therefore indicating the presence of GxE, were lamb birth weight and ewe premating weight. Following on from this, fine-scale information obtained by a farmer questionnaire, from 79 different terminal sire flocks was combined with nationally-available climatic data and analysed using principle coordinate analysis and non-hierarchical clustering methods. Three distinct clusters of farm environments were identified, with grazing type, climatic conditions and the use of vitamin/mineral supplements proving to be the most distinguishing factors. The presence of GxE was then investigated by estimating genetic correlations between the clusters identified, using performance data from Charollais lambs, for 21 week old weight (21WT), ultrasound back-fat (UFD) and muscle (UMD) depths. The correlations estimated between clusters 1 and 2, which had the highest number of common Charollais sires used, were all low and significantly different from 1 (P<0.05) suggesting GxE was evident in terms of both scaling and re-ranking. Finally, the relationship between the level of concentrate feed used in each flock, as obtained from the questionnaire, and performance and climatic information available nationally for all flocks was estimated using canonical correlation analysis. This allowed the development of a farm environment scale, applicable to all flocks within the UK, and the use of reaction norm analyses to investigate the presence of GxE. The reaction norm describes the phenotype of an individual animal as a function of the environment. The environment scale developed, using data from Texel flocks only, went from low performance averages and poorer weather conditions to high performance averages and improved weather conditions. The slope of the reaction norm measures the sensitivity of an animal to a change in the environment. For each trait, (21WT, UMD and UFD), evidence of both re-ranking and scaling of sires were observed. A number of “robust” sires, with a low level of environmental sensitivity, were also identified. The findings from these analyses may have implications for future sheep breeding programmes. Providing a suitable “measure of environment” can be agreed, the identification of sires that perform well in specific environments, as well as those who perform consistently across a number of different environments, would be beneficial for farmers. This would potentially remove any unwanted effects of GxE and allow the farmer to select animals best suited to their overall farm environment.

Maize grain yield is often highly influenced by the genotype-by-environment (GxE) interactions which limit plant breeders’ ability to select for superior performance as variation in line performance exists across different environments. While studies have focused on the genetic components underlining GxE interactions, few have investigated the environmental components. The focus of this thesis was to investigate the role that soil moisture stress plays in the formation of GxE patterns using a unique set of hybrid recombinant inbred lines (RIL) that exhibit minimal phenological differences. With the use of environmental groups (EG, environments with similar GxE patterns), the field trials demonstrated that different EGs form when relative soil moisture stress is moderate to high; however, relative low soil moisture stress did not appear to influence the formation of GxE patterns. Seasonal corn heat unit (CHU) accumulation among EGs was the likely cause for EG differentiation among the low moisture stress EGs. It appears that CHUs were the primary cause of different GxE patterns forming when they did not exceed the recommended CHU for a population and when CHU differed greatly from one environment to another. When CHU were not limiting different GxE patterns formed based on the relatively moderate to high soil moisture stress conditions within the growing season. / Ontario Research Fund, National Science and Engineering Research Council, and The Ontario Ministry of Agriculture, Food and Rural Affairs.

Extreme variations in cortisol reactivity are associated with multiple psychological and physiological diseases. These variations may be explained by sex, by genetic vulnerabilities, and by exposure to either recent life stressors (severe life events or ongoing difficulties) or early life adversity (e.g., antipathy; neglect; or psychological, physical, or sexual abuse). To explore interactions among these variables, a subset of 20-22 years-old individuals (N = 373) recruited for an ongoing longitudinal cohort-sequential study of substance abuse risk factors were assessed. These individuals were interviewed about early childhood abuse and recent stressful life experiences. They were also genotyped for multiple polymorphisms within genes associated with attenuated or exaggerated cortisol reactivity (5-HTTLPR and rs25532 in SERT, rs4680 in COMT, rs5522 in MR gene NR3C2, rs110402 and rs1876831 in CRHR1, rs1799971 in OPRM1, and rs1800497 in ANKK1), participated in a laboratory social stress task, and provided salivary cortisol samples throughout the task. Results indicate that cortisol reactivity may be shaped by both early and recent life experiences and genetic vulnerabilities; most interactions between these variables differed depending on an individual's sex. Specifically, carriers of two copies of minor alleles of ANKK1, COMT, and CRHR1 displayed dysregulated cortisol that varied according to sex and early life experiences. Male minor allele carriers who experienced more severe physical abuse displayed attenuated reactivity, and males who were not severely abused displayed exaggerated responses. Female minor allele carriers displayed the opposite pattern - abused females displayed exaggerated reactivity. Carriers of major alleles did not show these patterns. Attenuated cortisol reactivity was also observed in all individuals who experienced sexual abuse or neglect, and elevated responses were observed in individuals carrying two copies of minor alleles in both SERT polymorphisms and OPRM1. Together, results inform a developmental model of cortisol dysregulation. Cortisol reactivity may present a useful endophenotype for future studies of physiological and psychological disease processes and treatment outcomes.

When testing nine different sunflower cultivars in 32 South African environments (location x year), an Additive Main Effects and Multiplicative Interaction analysis (AMMI) identified sizeable genotype by environment (GxE) interaction. The first two Interaction Principal Components Axes (IPCA1 and IPCA2) were highly significant (p<0.001), but all the factors responsible for the GxE interaction could not be identified, as the causes of interaction seems to be of complex nature. IPCA1 captured 34% of the interaction SS with only 15.3% of the degrees of freedom, while IPCA2 captured 22.5% of the interaction SS with 14.5% of the degrees of freedom. This indicates that the AMMI2 model fits the data well and is parsimonious. Both cultivars and environments grouped together in quadrants according to their length of season when their respective IPCA1 and IPCA2 scores were plotted against each other. Environments from the warmer dry Western and Northern regions, including the Dry Highveld Grassland, Northern Arid and Central Bushveld, grouped in opposite quadrants, 1 and 3, while environments from the cooler moist Eastern regions, including the Moist Highveld Grassland grouped in opposite quadrants, 2 and 4. The factors responsible for the division between quadrants 1 and 3, as well as those responsible for the division between quadrants 2 and 4 could not be identified. The long-season cultivars were better adapted to the Northern and Western environments, while the medium-season cultivars were better adapted to the Eastern environments. Each quadrant was dominated by a different cultivar. Because the environments and cultivars could not be sufficiently described according to the factors responsible for the observed GxE interaction, cultivars can not be advised for specific environments. It is therefore presently recommended that cultivars which are more widely adapted to South African conditions, be selected. / Dissertation (MSc (Genetics))--University of Pretoria, 2004. / Genetics / unrestricted

Várias metodologias têm sido propostas com o intuito de medir a influência que a interação GxE exerce sobre os mais diversos caracteres de interesse e, dentre essas, as abordagens via modelos mistos utilizando REML/BLUP têm sido mencionadas como vantajosas. Ainda, o uso de informações ambientais pode ser útil para encontrar os fatores que estão por trás da real diferença entre os genótipos. O objetivo do estudo foi avaliar a resposta da produtividade de grãos em feijão-caupi frente às variações espaciais, e as variáveis ambientais mais relevantes para a interação GxE. Foram avaliados 20 genótipos em 47 locais entre os anos de 2010 a 2012 sob delineamento DBC. Após a análise conjunta, os padrões de adaptabilidade dos genótipos foram testados pelas metodologias GGE Biplot e MHPRVG e a estratificação ambiental foi feita via Análise de Fatores sobre a matriz dos efeitos aleatórios GGE. A importância das variáveis ambientais na produtividade foi verificada pela associação entre os efeitos da matriz GGE e cada variável ambiental. Após decomposição SVD, os componentes principais foram plotados em Covariáveis-Biplots. Os efeitos de genótipos e da interação tripla apresentaram elevada significância (p &le; 0,01 e p &le; 0,001, respectivamente) indicando forte influência desta última no desempenho dos genótipos avaliados. O modelo fixo GGE Biplot apresentou baixa eficiência, explicando apenas 35% da variação total, sendo os genótipos MNC03-737F-5-1, MNC03-737F-5- 4, MNC03-737F-5-9, BRS Tumucumaque, BRS Cauamé e BRS Guariba considerados os mais estáveis, e MNC03-737F-5-9 e BRS Tumucumaque apontados como amplamente adaptados. Já a estatística MHPRVG destacou os genótipos MNC02-676F-3, MNC03-737F-5-1, MNC03- 737F-5-9, BRS Tumucumaque e BRS Guariba, com adaptação ampla, e MNC02-675F-4-9, MNC02-676F-3 e MNC03-737F-5-9 como especificamente adaptados a alguns ambientes. O ajuste para o modelo aleatório revelou efeitos de genótipos e interações GxE significativos (p &le; 0,001) e foram obtidas correlações significativas (p &le; 0,01 e p &le; 0,001) entre PROD e as variáveis IT, NDP, Ptotal, Tmax, Tmin, Lat, Lon, e Alt. Os genótipos MNC03-737F-5-1, MNC03-737F-5-9, BRS Tumucumaque e BRS Guariba associaram elevada produtividade de grãos à rusticidade, sendo as variáveis \"Temperatura\", \"Insolação\" e \"Precipitação\", bem como \"Latitude\" e \"Altitude\", os mais importantes para a interação GxE. A análise MHPRVG foi adequada para a identificação dos genótipos superiores e o modelo Biplot-Covariável mostrou-se como uma ferramenta útil na identificação das variáveis ambientais importantes para a produtividade de grãos em feijão-caupi. / Several methods have been proposed to measure GxE interaction influence on various traits of interest, and among these, mixed models approaches using REML/BLUP have been mentioned as advantageous. Moreover, the use of environmental information can be useful to find factors that are behind the real difference between genotypes. The aim of this study was to evaluate the response of grain yield in cowpea to spatial variations, and the most important environmental factors for GxE interaction. Twenty genotypes were evaluated at 47 locations between the years 2010 to 2012 under RCB design. After joint analysis, genotypes adaptability patterns were tested by GGE Biplot and MHPRVG methods, and an environmental stratification was performed through factor analysis on the random effects GGE matrix. The impact of environmental factors on yield was verified by the association between the effects of the GGE matrix and environmental variables. After SVD decomposition, the principal components were plotted in Covariables-Biplots. Genotype effects and triple interaction were highly significant (p &le; 0.01 and p &le; 0.001, respectively) indicating strong GxE influence on genotypes performance. The fixed model GGE Biplot exhibits low efficiency, explaining only 35% of the total variation, and genotypes MNC03-737F-5-1, MNC03-737F-5-4, MNC03-737F-5-9, BRS Tumucumaque, BRS Cauamé, and BRS Guariba were considered the most stable, and MNC03-737F-5-9 and BRS Tumucumaque identified as widely adapted. MHPRVG method highlighted MNC02-676F-3, MNC03-737F-5-1, MNC03-737F-5-9, BRS Tumucumaque, and BRS Guariba as genotypes with broad adaptation and MNC02-675F-4-9, MNC02-676F-3, and MNC03-737F-5-9 as specifically adapted to certain environments. The fitted random effects model revealed significant genotype effects and GxE interactions (p &le; 0.001) and significant correlations were obtained (p &le; 0.01 and p &le; 0.001) between PROD and IT , NDP, Ptotal, Tmax, Tmin, Lat, Lon, and Alt variables. Genotypes MNC03-737F-5-1, MNC03-737F-5-9, BRS Tumucumaque, and BRS Guariba presented high grain yield associated with rusticity, and environmental factors \"Temperature\", \"Insolation\" and \"Precipitation\", as well as \"Latitude\" and \"Altitude\", were the most important for GxE interaction. MHPRVG analysis was adequate to identify superior genotypes, and Covariate-Biplot model proved to be a useful tool for identifying key environmental factors for grain yield in cowpea.

L’environnement est une variable essentielle de la traduction des génotypes en phénotypes: ainsi, un génotype donné peut donner naissance à des phénotypes distincts en réponse aux variations environnementales. Ce phénomène, appelé plasticité phénotypique, est universel. Mon projet avait pour objectif d’analyser de façon quantitative et intégrée la plasticité de la reproduction et son évolution chez les nématodes Caenorhabditis, en étudiant les caractéristiques de la lignée germinale. Ce travail a également mis en lumière la sensibilité à l’environnement des traits d’histoire de vie en rapport avec la fitness, et leur évolution. J’ai d’abord analysé la plasticité et les interactions génotype/environnement des traits phénotypiques d’histoire de vie et de la lignée germinale de C. elegans en réponse à des variations environnementales pertinentes sur le plan écologique. J’ai mis en évidence des effets hautement variables de l’environnement et du génotype, et des interactions génotype/environnement pour chacun de ces traits. J’ai ensuite examiné l’évolution intra- et inter-espèces de la lignée germinale et de la reproduction dans le genre Caenorhabditis, et plus particulièrement les variations évolutives dans la sensibilité thermique de la reproduction. J’ai montré que la réduction de la fertilité lors de l’exposition à des températures élevées ne s’expliquait pas seulement par des défauts de spermatogenèse mais également par un large spectre d’erreurs de l’oogenèse. Enfin, j’ai participé à des expériences d’évolution expérimentale visant à quantifier les changements de la lignée germinale qui accompagnent l’adaptation de populations C. elegans à un nouvel environnement. / The environment is an integral part of the translation of genotypes into phenotypes, and a given genotype may generate different phenotypes in response to environmental variation. This phenomenon, called developmental or phenotypic plasticity is universal. My project aimed to conduct an integrative and evolutionary analysis of developmental plasticity in reproductive and underlying germline traits of Caenorhabditis nematodes. This research thus also sheds light on the environmental sensitivity of life history traits.First, I analysed the extent of plasticity and genotype-by-environment interactions for C. elegans life history and germline traits in response to ecologically relevant environmental variation. I found highly variable effects of environment and genotype, as well as genotype-by-environment interactions for life history and germline traits. Second, I examined intra- and interspecific evolution of Caenorhabditis germline processes and reproduction, primarily in the context of evolutionary variation in thermal sensitivity of reproduction. I found that heat-induced fertility reduction is not only due to defects in spermatogenesis but also to a wide spectrum of oogenesis errors, which are strongly dependent on species and genotype. Specifically, in C. elegans, high temperature induces consistent defects in mitosis-meiosis progression due to a deregulation of Delta/Notch signalling in the germ stem cell niche. Third, I carried out a population-level study aimed at quantifying germline developmental changes underlying adaptation to a novel environment, making use of C. elegans experimental evolution populations.

Várias metodologias têm sido propostas com o intuito de medir a influência que a interação GxE exerce sobre os mais diversos caracteres de interesse e, dentre essas, as abordagens via modelos mistos utilizando REML/BLUP têm sido mencionadas como vantajosas. Ainda, o uso de informações ambientais pode ser útil para encontrar os fatores que estão por trás da real diferença entre os genótipos. O objetivo do estudo foi avaliar a resposta da produtividade de grãos em feijão-caupi frente às variações espaciais, e as variáveis ambientais mais relevantes para a interação GxE. Foram avaliados 20 genótipos em 47 locais entre os anos de 2010 a 2012 sob delineamento DBC. Após a análise conjunta, os padrões de adaptabilidade dos genótipos foram testados pelas metodologias GGE Biplot e MHPRVG e a estratificação ambiental foi feita via Análise de Fatores sobre a matriz dos efeitos aleatórios GGE. A importância das variáveis ambientais na produtividade foi verificada pela associação entre os efeitos da matriz GGE e cada variável ambiental. Após decomposição SVD, os componentes principais foram plotados em Covariáveis-Biplots. Os efeitos de genótipos e da interação tripla apresentaram elevada significância (p &le; 0,01 e p &le; 0,001, respectivamente) indicando forte influência desta última no desempenho dos genótipos avaliados. O modelo fixo GGE Biplot apresentou baixa eficiência, explicando apenas 35% da variação total, sendo os genótipos MNC03-737F-5-1, MNC03-737F-5- 4, MNC03-737F-5-9, BRS Tumucumaque, BRS Cauamé e BRS Guariba considerados os mais estáveis, e MNC03-737F-5-9 e BRS Tumucumaque apontados como amplamente adaptados. Já a estatística MHPRVG destacou os genótipos MNC02-676F-3, MNC03-737F-5-1, MNC03- 737F-5-9, BRS Tumucumaque e BRS Guariba, com adaptação ampla, e MNC02-675F-4-9, MNC02-676F-3 e MNC03-737F-5-9 como especificamente adaptados a alguns ambientes. O ajuste para o modelo aleatório revelou efeitos de genótipos e interações GxE significativos (p &le; 0,001) e foram obtidas correlações significativas (p &le; 0,01 e p &le; 0,001) entre PROD e as variáveis IT, NDP, Ptotal, Tmax, Tmin, Lat, Lon, e Alt. Os genótipos MNC03-737F-5-1, MNC03-737F-5-9, BRS Tumucumaque e BRS Guariba associaram elevada produtividade de grãos à rusticidade, sendo as variáveis \"Temperatura\", \"Insolação\" e \"Precipitação\", bem como \"Latitude\" e \"Altitude\", os mais importantes para a interação GxE. A análise MHPRVG foi adequada para a identificação dos genótipos superiores e o modelo Biplot-Covariável mostrou-se como uma ferramenta útil na identificação das variáveis ambientais importantes para a produtividade de grãos em feijão-caupi. / Several methods have been proposed to measure GxE interaction influence on various traits of interest, and among these, mixed models approaches using REML/BLUP have been mentioned as advantageous. Moreover, the use of environmental information can be useful to find factors that are behind the real difference between genotypes. The aim of this study was to evaluate the response of grain yield in cowpea to spatial variations, and the most important environmental factors for GxE interaction. Twenty genotypes were evaluated at 47 locations between the years 2010 to 2012 under RCB design. After joint analysis, genotypes adaptability patterns were tested by GGE Biplot and MHPRVG methods, and an environmental stratification was performed through factor analysis on the random effects GGE matrix. The impact of environmental factors on yield was verified by the association between the effects of the GGE matrix and environmental variables. After SVD decomposition, the principal components were plotted in Covariables-Biplots. Genotype effects and triple interaction were highly significant (p &le; 0.01 and p &le; 0.001, respectively) indicating strong GxE influence on genotypes performance. The fixed model GGE Biplot exhibits low efficiency, explaining only 35% of the total variation, and genotypes MNC03-737F-5-1, MNC03-737F-5-4, MNC03-737F-5-9, BRS Tumucumaque, BRS Cauamé, and BRS Guariba were considered the most stable, and MNC03-737F-5-9 and BRS Tumucumaque identified as widely adapted. MHPRVG method highlighted MNC02-676F-3, MNC03-737F-5-1, MNC03-737F-5-9, BRS Tumucumaque, and BRS Guariba as genotypes with broad adaptation and MNC02-675F-4-9, MNC02-676F-3, and MNC03-737F-5-9 as specifically adapted to certain environments. The fitted random effects model revealed significant genotype effects and GxE interactions (p &le; 0.001) and significant correlations were obtained (p &le; 0.01 and p &le; 0.001) between PROD and IT , NDP, Ptotal, Tmax, Tmin, Lat, Lon, and Alt variables. Genotypes MNC03-737F-5-1, MNC03-737F-5-9, BRS Tumucumaque, and BRS Guariba presented high grain yield associated with rusticity, and environmental factors \"Temperature\", \"Insolation\" and \"Precipitation\", as well as \"Latitude\" and \"Altitude\", were the most important for GxE interaction. MHPRVG analysis was adequate to identify superior genotypes, and Covariate-Biplot model proved to be a useful tool for identifying key environmental factors for grain yield in cowpea.

Doctor of Philosophy / Department of Grain Science and Industry / Yong-Cheng Shi and Jeff D. Wilson / Sorghum (Sorghum bicolor [L.] Moench) is the fifth most important cereal grain grown in the world. Sorghum is an important cereal crop for both animal feed and biofuel production in the United States. The genetic, environmental, and agronomic management influences on sorghum starch and protein chemistry and functionality were evaluated. A method was developed to determine amylose content in cereal starches that achieved the same level of accuracy and precision as traditional methods, but had the capability of analyzing 50 samples per day or approximately a 10-fold increase in throughput. The effect of kernel maturity on sorghum starch properties was conducted by collecting grain from two hybrids at various stages throughout kernel development. The samples ranged from 16.3% amylose in 10 days after anthesis (DAA) to 23.3% amylose in 35 DAA. Starch thermal properties were also altered due to DAA, most notably the ΔH was 16.1 J/g at 14 DAA and 9.45 J/g at 56 DAA. In a separate study using the same developmental samples the protein and starch digestibility was analyzed. The kernel maturity had a notable effect on digestibility with the maximum digestibility occurring at 17 DAA with 82.44% digestible protein. In another study a diverse set of 19 sorghums was grown in three locations in Kansas to evaluate the genetic, location, and genetic x location effect on grain quality attributes. The physical and chemical properties of the sorghums were greatly affected by the genotype, environment, and the GxE interaction. Protein content ranged from 11.09% to 15.17% and digestibility ranged from 45.58% to 62.05% due to genotype. The final study investigates the role of agronomic management on sorghum grain quality. A sorghum hybrid was grown on plots with varying nitrogen fertilization rates and cover cropping systems that are currently used by Kansas producers. Grain attributes such as hardness and size were variable due to the treatments but negative impacts to protein digestibility were not seen due to cropping system. Sorghum grain quality is affected by many variables and a better understanding of the variables will lead to a higher quality product.

Transvection, a chromosome pairing-dependent form of trans-based gene regulation, is widespread in the Drosophila melanogaster genome. Recent studies demonstrate that transvection is sensitive to cell environment and type in D. melanogaster, implicating transvection as a complex trait. To test this possibility, we first established that trans-interactions previously documented at the Malic enzyme (Men) locus are transvection (i.e., pairing-dependent). We then characterized the sensitivity of transvection at the Men locus to changes in the environment (temperature) and genetic background (third chromosome). Transvection varied significantly across genetic backgrounds and was significantly reduced by changes in temperature, and the two factors interacted to further modify transvection, while cis-based gene regulation remained unchanged by temperature. To determine if differences in transvection observed across genetic background and temperature are related to their effects on transcription factor expression, and possibly the presence or absence of binding sites for these transcription factors within the Men locus, we tested the relationship between Men expression and five transcription factors with binding sites near the Men transcription start sit (TSS). We found correlations between the expression of at least one transcription factor, Abd-B, and the presence of binding sites for that factor, and Men expression across changes in the environment. We also determined that changes in Abd-B expression can directly affect Men expression in cis, suggesting that cis and trans-regulation can share regulatory components in at least some cases. Together, our findings stress the importance of studying genetic interactions from a dynamic perspective by incorporating both genetic and environmental variation.

This study investigated the etiology of preschoolers’ somatic symptoms and internalizing problems, using a twin sample. A specific focus was placed on the genetic (i.e., DRD4 and 5-HTTLPR) and environmental (i.e., SES, household chaos, family conflict, and maternal emotional stability) factors that were hypothesized to be associated with these problems. This project also explored the possible gene-environmental interactions (GxE) that may exist among these contributors. It was hypothesized that children who are at greatest risk due to their genotype, environment, or a combination of the two would display elevated somatic symptoms and internalizing problems, compared to children who were less at-risk due to these factors. Data from 252 families included in the Southern Illinois Twins/Triplets and Siblings Study (SITSS) at age 5 were examined. Results indicated a significant DRD4 x household chaos interaction predicting preschoolers’ somatic symptoms, demonstrating that children with the DRD4-7r genotype exhibited less somaticizing in highly chaotic homes. Additionally, 5-year-old internalizing problems were significantly predicted by the cumulative environmental risk factor created (i.e., top 15% of scores for each environmental variable in the current sample) and marginally by the additive genotypic risk factor (i.e., a summation of the DRD4 and 5-HTTLPR “risk” scores). These results provide additional insight into the factors that may place children at greater risk for somatic symptoms and internalizing problems.