Gene-environment interaction for childhood asthma and exposure to farming in Central Europe

Asthma is a disease in which both genetic and environmental factors play important roles. The farming environment has consistently been associated with protection from childhood asthma and atopy, and interactions have been reported with polymorphisms in innate immunity genes.

Rapid assessment of genotype-by-environment interactions and heritability for growth rate in aquaculture species using in vitro fertilisation and DNA tagging

Commercial environments may receive only a fraction of expected genetic gains for growth rate as predicted from the selection environment This fraction is the result of undesirable genotype-by-environment interactions (G x E) and measured by the genetic correlation (r(g)) of growth between environments. Rapid estimates of genetic correlation achieved in one generation are notoriously difficult to estimate with precision. A new design is proposed where genetic correlations can be estimated by utilising artificial mating from cryopreserved semen and unfertilised eggs stripped from a single female. We compare a traditional phenotype analysis of growth to a threshold model where only the largest fish are genotyped for sire identification. The threshold model was robust to differences in family mortality differing up to 30%. The design is unique as it negates potential re-ranking of families caused by an interaction between common maternal environmental effects and growing environment. The design is suitable for rapid assessment of G x E over one generation with a true 0.70 genetic correlation yielding standard errors as low as 0.07. Different design scenarios were tested for bias and accuracy with a range of heritability values, number of half-sib families created, number of progeny within each full-sib family, number of fish genotyped, number of fish stocked, differing family survival rates and at various simulated genetic correlation levels

Environment characterization as an aid to wheat improvement: interpreting genotype-environment interactions by modelling water-deficit patterns in North-Eastern Australia.

Genotype-environment interactions (GEI) limit genetic gain for complex traits such as tolerance to drought. Characterization of the crop environment is an important step in understanding GEI. A modelling approach is proposed here to characterize broadly (large geographic area, long-term period) and locally (field experiment) drought-related environmental stresses, which enables breeders to analyse their experimental trials with regard to the broad population of environments that they target. Water-deficit patterns experienced by wheat crops were determined for drought-prone north-eastern Australia, using the APSIM crop model to account for the interactions of crops with their environment (e.g. feedback of plant growth on water depletion). Simulations based on more than 100 years of historical climate data were conducted for representative locations, soils, and management systems, for a check cultivar, Hartog. The three main environment types identified differed in their patterns of simulated water stress around flowering and during grain-filling. Over the entire region, the terminal drought-stress pattern was most common (50% of production environments) followed by a flowering stress (24%), although the frequencies of occurrence of the three types varied greatly across regions, years, and management. This environment classification was applied to 16 trials relevant to late stages testing of a breeding programme. The incorporation of the independently-determined environment types in a statistical analysis assisted interpretation of the GEI for yield among the 18 representative genotypes by reducing the relative effect of GEI compared with genotypic variance, and helped to identify opportunities to improve breeding and germplasm-testing strategies for this region.

Classifying genotype by environment interactions for targeted germplasm deployment with a focus on Eucalyptus

A novel methodology for describing genotype by environment interactions estimated from multi-environment field trials is described and an empirical example using an extensive trial network of eucalypts is presented. The network of experiments containing 65 eucalypts was established in 38 replicated field trials across the tropics and subtropics of eastern Australia, with a selection of well-tested species used to provide a more detailed examination of productivity differentials across environmental gradients. By focusing on changes in species’ productivity across environmental gradients, the results are applicable for all species established across the range of environments evaluated in the trial network and simultaneously classify species and environments so that results may be applied across the landscape. The methodology developed was able to explain most (93 %) of the variation in the selected species relative changes in productivity across the various environmental variables examined. Responses were primarily regulated by changes in variables related to water availability and secondarily by temperature related variables. Clustering and ordination can identify groups of species with similar physiological responses to environment and may also guide the parameterisation and calibration of process based models of plant growth. Ordination was particularly useful in the identification of species with distinct environmental response patterns that would be useful as probes for extracting more information from future trials.

Rapid assessment of genotype-by-environment interactions and heritability for growth rate in aquaculture species using in vitro fertilisation and DNA tagging

Commercial environments may receive only a fraction of expected genetic gains for growth rate as predicted from the selection environment. This fraction is result of undesirable genotype-by-environment interactions (GxE) and measured by the genetic correlation (rg) of growth between environments. Rapid estimates of genetic correlation achieved in one generation are notoriously difficult to estimate with precision. A new design is proposed where genetic correlations can be estimated by utilising artificial mating from cryopreserved semen and unfertilised eggs stripped from a single female. We compare a traditional phenotype analysis of growth to a threshold model where only the largest fish are genotyped for sire identification. The threshold model was robust to differences in family mortality differing up to 30%. The design is unique as it negates potential re-ranking of families caused by an interaction between common maternal environmental effects and growing environment. The design is suitable for rapid assessment of GxE over one generation with a true 0.70 genetic correlation yielding standard errors as low as 0.07. Different design scenarios were tested for bias and accuracy with a range of heritability values, number of half-sib families created, number of progeny within each full-sib family, number of fish genotyped, number of fish stocked, differing family survival rates and at various simulated genetic correlation levels.

Livelihood, land use and environment interactions in the highlands of East Africa

This study aims at improving understanding of the interactions of livelihoods and the environment focusing on both socio-economic and biodiversity implications of land use change in the context of population pressure, global and local markets, climate change, cultural and regional historical factors in the highlands of East Africa. The study is based on three components (1) two extensive livelihood surveys, one on Mt. Kilimanjaro in Tanzania and the other in the Taita Hills of Kenya, (2) a land use change study of the southern slopes of Mt. Kilimanjaro focusing on land use trends between 1960s and 1980s and 1980s and 2000 and (3) a bird diversity study focusing on the potential impacts of the future land use change on birds in the main land use types on the slopes and the adjacent plains of Mt. Kilimanjaro. In addition, information on the highlands in Embu and the adjacent lowlands in Mbeere of Kenya are added to the discussion. Some general patterns of livelihood, land use and environment interactions can be found in the three sites. However, the linkages are very complex. Various external factors at different times in history have influenced most of the major turning points. Farmers continually make small adaptations to their farming practices, but the locally conceived alternatives are too few. Farmers lack specific information and knowledge on the most suitable crops, market opportunities and the quality requirements for growing the crops for markets. Population growth emerges as the most forceful driver of land use and environmental change. The higher altitudes have become extremely crowded with population densities in some areas higher than typical urban population densities. Natural vegetation has almost totally been replaced by farmland. Decreasing farm size due to population pressure is currently threatening the viability of whole farming systems. In addition, capital-poor intensification has lead to soil fertility depletion. Agricultural expansion to the agriculturally marginal lowlands has created a new and distinct group of farmers struggling constantly with climate variability causing frequent crop failures. Extensification to the fragile drylands is the major cause of fragmentation and loss of wildlife habitat. The linkages between livelihoods, land use and the environment generally point to degradation of the environment leading to reduced environmental services and ecosystem functions. There is no indication that the system is self-regulating in this respect. Positive interventions will be needed to maintain ecosystem integrity.

Rastreamento de mutações no gene GBA como fator de risco ao desenvolvimento da doença de Parkinson na população brasileira

A doença de Parkinson (DP) é a segunda doença neurodegenerativa mais frequente, depois da doença de Alzheimer, com uma incidência de aproximadamente 3,3% na população brasileira acima dos 60 anos. Ela é caracterizada por uma perda dos neurônios dopaminérgicos da parte compacta da substância negra e pela presença de inclusões protéicas intracelulares denominadas corpúsculos de Lewy nos neurônios sobreviventes. A DP tem uma etiologia complexa que envolve interações genes-ambiente e múltiplos genes de susceptibilidade. Nesse contexto, mutações de perda de função no gene da glicocerebrosidase (GBA) têm sido bem validadas como importantes fatores de risco para a DP. Esse gene está localizado na região 1q21 e compreende 11 exons que codificam a enzima lisossômica glicocerebrosidase. O principal objetivo deste estudo foi investigar se alterações no gene GBA constituem um fator de predisposição para o desenvolvimento da DP na população brasileira. Para isso, um grupo de 126 pacientes brasileiros, não-aparentados, com DP (24 casos familiares e 102 isolados; idade média 66,4 11,4) foram analisados para mutações no GBA através do seqüenciamento completo de todos os exons e alguns íntrons. Sete alterações e um alelo recombinante, anteriormente encontrados em pacientes com a DP analisados em outros estudos, foram detectados (K(-)27R, IVS2+1G>A, N370S, L444P, T369M, A456P, E326K e RecNciI), assim como, uma variante nunca antes identificada associada à DP (G325G) e uma nova mutação (W378C), num total de 18 pacientes (14,3%). Além disso, foram encontradas três alterações intrônicas (c.454+47G>A, c.589-86A>G e c.1225-34C>A), que constam do banco de SNPs, entretanto, não foram associadas a nenhuma doença. Dentre todas as variantes identificadas, três são comprovadamente patogênicas (IVS2+1G>A, L444P e N370S) e foram encontradas em 5,5% da amostra, não sendo detectadas na amostra controle, indicando uma freqüência significativamente alta dessas mutações em pacientes com DP quando comparadas aos controles (P=0,0033). Esses resultados reforçam a associação entre o gene GBA e a DP na população brasileira, além de apoiar a hipótese de que alterações nesse gene representam um importante fator de susceptibilidade ao desenvolvimento da DP

ACC2 gene polymorphisms, metabolic syndrome, and gene-nutrient interactions with dietary fat.

Acetyl-CoA carboxylase β (ACC2) plays a key role in fatty acid synthesis and oxidation pathways. Disturbance of these pathways is associated with impaired insulin responsiveness and metabolic syndrome (MetS). Gene-nutrient interactions may affect MetS risk. This study determined the relationship between ACC2 polymorphisms (rs2075263, rs2268387, rs2284685, rs2284689, rs2300453, rs3742023, rs3742026, rs4766587, and rs6606697) and MetS risk, and whether dietary fatty acids modulate this in the LIPGENE-SU.VI.MAX study of MetS cases and matched controls (n = 1754). Minor A allele carriers of rs4766587 had increased MetS risk (OR 1.29 [CI 1.08, 1.58], P = 0.0064) compared with the GG homozygotes, which may in part be explained by their increased body mass index (BMI), abdominal obesity, and impaired insulin sensitivity (P < 0.05). MetS risk was modulated by dietary fat intake (P = 0.04 for gene-nutrient interaction), where risk conferred by the A allele was exacerbated among individuals with a high-fat intake (>35% energy) (OR 1.62 [CI 1.05, 2.50], P = 0.027), particularly a high intake (>5.5% energy) of n-6 polyunsaturated fat (PUFA) (OR 1.82 [CI 1.14, 2.94], P = 0.01; P = 0.05 for gene-nutrient interaction). Saturated and monounsaturated fat intake did not modulate MetS risk. Importantly, we replicated some of these findings in an independent cohort. In conclusion, the ACC2 rs4766587 polymorphism influences MetS risk, which was modulated by dietary fat, suggesting novel gene-nutrient interactions.

Gene-nutrient interactions with dietary fat modulate the association between genetic variation of the ACSL1 gene and metabolic syndrome

Long-chain acyl CoA synthetase 1 (ACSL1) plays an important role in fatty acid metabolism and triacylglycerol (TAG) synthesis. Disturbance of these pathways may result in dyslipidemia and insulin resistance, hallmarks of the metabolic syndrome (MetS). Dietary fat is a key environmental factor that may interact with genetic determinants of lipid metabolism to affect MetS risk. We investigated the relationship between ACSL1 polymorphisms (rs4862417, rs6552828, rs13120078, rs9997745, and rs12503643) and MetS risk and determined potential interactions with dietary fat in the LIPGENE-SU.VI.MAX study of MetS cases and matched controls (n = 1,754). GG homozygotes for rs9997745 had increased MetS risk {odds ratio (OR) 1.90 [confidence interval (CI) 1.15, 3.13]; P = 0.01}, displayed elevated fasting glucose (P = 0.001) and insulin concentrations (P = 0.002) and increased insulin resistance (P = 0.03) relative to the A allele carriers. MetS risk was modulated by dietary fat, whereby the risk conferred by GG homozygosity was abolished among individuals consuming either a low-fat (<35% energy) or a high-PUFA diet (>5.5% energy). In conclusion, ACSL1 rs9997745 influences MetS risk, most likely via disturbances in fatty acid metabolism, which was modulated by dietary fat consumption, particularly PUFA intake, suggesting novel gene-nutrient interactions.

Gene-nutrient interactions on the phosphoenolpyruvate carboxykinase influence insulin sensitivity in metabolic syndrome subjects

Genetic background may interact with habitual dietary fat composition, and affect development of the metabolic syndrome (MetS). The phosphoenolpyruvate carboxykinase gene (PCK1) plays a significant role regulating glucose metabolism, and fatty acids are key metabolic regulators, which interact with transcription factors and influence glucose metabolism. We explored genetic variability at the PCK1 gene locus in relation to degree of insulin resistance and plasma fatty acid levels in MetS subjects. Moreover, we analyzed the PCK1 gene expression in the adipose tissue of a subgroup of MetS subjects according to the PCK1 genetic variants.

New approaches to gene discovery with animal models of obesity and diabetes

DNA-based approaches to the discovery of genes contributing to the development of type 2 diabetes have not been very successful despite substantial investments of time and money. The multiple gene-gene and gene-environment interactions that influence the development of type 2 diabetes mean that DNA approaches are not the ideal tool for defining the etiology of this complex disease. Gene expression-based technologies may prove to be a more rewarding strategy to identify diabetes candidate genes. There are a number of RNA-based technologies available to identify genes that are differentially expressed in various tissues in type 2 diabetes. These include differential display polymerase chain reaction (ddPCR), suppression subtractive hybridization (SSH), and cDNA microarrays. The power of new technologies to detect differential gene expression is ideally suited to studies utilizing appropriate animal models of human disease. We have shown that the gene expression approach, in combination with an excellent animal model such as the Israeli sand rat (Psammomys obesus), can provide novel genes and pathways that may be important in the disease process and provide novel therapeutic approaches. This paper will describe a new gene discovery, beacon, a novel gene linked with energy intake. As the functional characterization of novel genes discovered in our laboratory using this approach continues, it is anticipated that we will soon be able to compile a definitive list of genes that are important in the development of obesity and type 2 diabetes.

Modeling gene-environment interaction in longitudinal data : risk for neuroticism due to interaction between maternal care and the Dopamine 4 Receptor gene (DRD4)

The purpose of this study was to investigate risk for neuroticism due to the joint action of low maternal care and compromised mesocorticolimbic ‘reward’ system function linked to a variable number tandem repeat (VNTR) in the dopamine 4 receptor gene (DRD4). Data were drawn from the Victorian Adolescent Health Cohort Study, a longitudinal study of the health and well-being of 2,000 young Australians followed from adolescence to young adulthood across 8 waves from 14- to 28-years. Genetic risk was defined by carriage of at least one copy of the 7-repeat allele or derivative alleles 5, 6, and 8 (labeled 7R+). Neuroticism was assessed in adolescence and young adulthood. We observed an approximately fourfold increase in the odds of reporting neurotic symptoms in carriers of the 7R+ disposition who reported low maternal care compared with non-carriers who reported high maternal care. The percentage of risk attributable to mechanisms in which both factors played a role was 35%. Findings are discussed in terms of implications for prevention.