Genotype by environment interactions for Pinus radiata in New South Wales, Australia

Historical data from 26 progeny trials in the NSW breeding program was analyzed to determine the extent and practical importance of genotype by environment (G×E) interactions for a range of traits. Significant G×E interaction was present for diameter (DBH) with 75% of the 35 estimated between-site genetic correlations falling below the threshold value of 0.6 where regionalization should be considered. Estimated genetic correlations for stem straightness, branch quality, and outerwood density were much higher, indicating these traits are not as affected by G×E. Levels of G×E for DBH are sufficient to have serious impacts on the expression of genetic gain in deployed material. For DBH, altitude differences between sites appear to be the key factor driving the G×E with a difference of greater than 280 m in altitude leading to a breakdown in correlations. Two groups of sites were identified as having limited G×E within each group: one for sites above 900 m elevation plus a lower-altitude group. Sites included in the higher-altitude group were located across the entire north–south geographic range of NSW. Equations for prediction of site mean DBH indicate that altitude, prior land use, and underlying geology are key driving variables. A more complex model was developed for predicting the between-site genetic correlations for DBH with the model accounting for approximately 50% of the observed variation.     

Genome-wide association mapping of canopy wilting in diverse soybean genotypes

Key message

Genome-wide association analysis identified 61 SNP markers for canopy wilting, which likely tagged 51 different loci. Based on the allelic effects of the significant SNPs, the slowest and fastest wilting genotypes were identified.

Abstract

Drought stress is a major global constraint for crop production, and slow canopy wilting is a promising trait for improving drought tolerance. The objective of this study was to identify genetic loci associated with canopy wilting and to confirm those loci with previously reported canopy wilting QTLs. A panel of 373 maturity group (MG) IV soybean genotypes was grown in four environments to evaluate canopy wilting. Statistical analysis of phenotype indicated wide variation for the trait, with significant effects of genotype (G), environment (E), and G × E interaction. Over 42,000 SNP markers were obtained from the Illumina Infinium SoySNP50K iSelect SNP Beadchip. After filtration for quality control, 31,260 SNPs with a minor allele frequency (MAF) ≥5% were used for association mapping using the Fixed and random model Circulating Probability Unification (FarmCPU) model. There were 61 environment-specific significant SNP-canopy wilting associations, and 21 SNPs that associated with canopy wilting in more than one environment. There were 34 significant SNPs associated with canopy wilting when averaged across environments. Together, these SNPs tagged 23 putative loci associated with canopy wilting. Six of the putative loci were located within previously reported chromosomal regions that were associated with canopy wilting through bi-parental mapping. Several significant SNPs were located within a gene or very close to genes that had a reported biological connection to transpiration or water transport. Favorable alleles from significant SNPs may be an important resource for pyramiding genes to improve drought tolerance and for identifying parental genotypes for use in breeding programs.

     

Genome-wide investigation of gene–environment interactions in colorectal cancer

Colorectal cancer (CRC), one of the most frequent neoplasias worldwide, has both genetic and environmental causes. As yet, however, gene–environment (G × E) interactions in CRC have been studied mostly for a small number of candidate genes only. Therefore, we investigated the possible interaction, in CRC etiology, between single-nucleotide polymorphisms (SNPs) on the one hand, and overweight, smoking and alcohol consumption on the other, at a genome-wide level. To this end, we adopted a two-tiered approach comprising a case-only screening stage I (314 cases) and a case–control validation stage II (259 cases, 1,002 controls). Interactions with the smallest p value in stage I were verified in stage II using multiple logistic regression analysis adjusted for sex and age. In addition, we specifically studied known CRC-associated SNPs for possible G × E interactions. Upon adjustment for sex and age, and after allowing for multiple testing, however, only a single SNP (rs1944511) was found to be involved in a statistically significant interaction, namely with overweight (multiplicity-corrected p = 0.042 in stage II). Several other G × E interactions were nominally significant but failed correction for multiple testing, including a previously reported interaction between rs9929218 and alcohol consumption that also emerged in our candidate SNP study (nominal p = 0.008). Notably, none of the interactions identified in our genome-wide analysis was with a previously reported CRC-associated SNP. Our study therefore highlights the potential of an “agnostic” genome-wide approach to G × E analysis.     

Linkage and Association Mapping for Two Major Traits Used in the Maritime Pine Breeding Program: Height Growth and Stem Straightness

BackgroundIncreasing our understanding of the genetic architecture of complex traits, through analyses of genotype-phenotype associations and of the genes/polymorphisms accounting for trait variation, is crucial, to improve the integration of molecular markers into forest tree breeding. In this study, two full-sib families and one breeding population of maritime pine were used to identify quantitative trait loci (QTLs) for height growth and stem straightness, through linkage analysis (LA) and linkage disequilibrium (LD) mapping approaches.ResultsThe populations used for LA consisted of two unrelated three-generation full-sib families (n = 197 and n = 477). These populations were assessed for height growth or stem straightness and genotyped for 248 and 217 markers, respectively. The population used for LD mapping consisted of 661 founders of the first and second generations of the breeding program. This population was phenotyped for the same traits and genotyped for 2,498 single-nucleotide polymorphism (SNP) markers corresponding to 1,652 gene loci. The gene-based reference genetic map of maritime pine was used to localize and compare the QTLs detected by the two approaches, for both traits. LA identified three QTLs for stem straightness and two QTLs for height growth. The LD study yielded seven significant associations (P ≤ 0.001): four for stem straightness and three for height growth. No colocalisation was found between QTLs identified by LA and SNPs detected by LD mapping for the same trait.ConclusionsThis study provides the first comparison of LA and LD mapping approaches in maritime pine, highlighting the complementary nature of these two approaches for deciphering the genetic architecture of two mandatory traits of the breeding program.     

Genotype by environment interaction for index traits that combine growth and wood density in loblolly pine

 Genotype×environment interactions of individual traits have been assessed in numerous experiments with forest trees. However, since breeding programs rarely aim at the improvement of a single trait, the impact of G×E on index or composite traits must also be assessed. In a study with 12-year-old loblolly pine families in the southeastern U.S., G×E variance was of relatively little importance compared to genetic variance for wood density but was of greater significance for several growth traits. An index that combined stem volume and wood density to improve dry weight but maintain wood density constant (restricted selection index) resulted in substantially greater G×E variance compared to either of the component traits. The interaction variance of an index trait is shown to be a function of the index coefficients and the G×E variances and covariances for its constituent traits. As a result, for some conditions it surpasses the magnitude of G×E variance for each component trait. Received: 5 September 1996 / Accepted: 25 October 1996     

Gene-environment interactions and obesity traits among postmenopausal African-American and Hispanic women in the Women’s Health Initiative SHARe Study

Genome-wide association studies (GWAS) of obesity measures have identified associations with single nucleotide polymorphisms (SNPs). However, no large-scale evaluation of gene-environment interactions has been performed. We conducted a search of gene-environment (G × E) interactions in post-menopausal African-American and Hispanic women from the Women’s Health Initiative SNP Health Association Resource GWAS study. Single SNP linear regression on body mass index (BMI) and waist-to-hip circumference ratio (WHR) adjusted for multidimensional-scaling-derived axes of ancestry and age was run in race-stratified data with 871,512 SNPs available from African-Americans (N = 8,203) and 786,776 SNPs from Hispanics (N = 3,484). Tests of G × E interaction at all SNPs for recreational physical activity (m h/week), dietary energy intake (kcal/day), alcohol intake (categorical), cigarette smoking years, and cigarette smoking (ever vs. never) were run in African-Americans and Hispanics adjusted for ancestry and age at interview, followed by meta-analysis of G × E interaction terms. The strongest evidence for concordant G × E interactions in African-Americans and Hispanics was for smoking and marker rs10133840 (Q statistic P = 0.70, beta = ?0.01, P = 3.81 × 10^?7) with BMI as the outcome. The strongest evidence for G × E interaction within a cohort was in African-Americans with WHR as outcome for dietary energy intake and rs9557704 (SNP × kcal = ?0.04, P = 2.17 × 10^?7). No results exceeded the Bonferroni-corrected statistical significance threshold.     

Association mapping in Salix viminalis L. (Salicaceae) – identification of candidate genes associated with growth and phenology

Willow species (Salix) are important as short‐rotation biomass crops for bioenergy, which creates a demand for faster genetic improvement and breeding through deployment of molecular marker‐assisted selection (MAS). To find markers associated with important adaptive traits, such as growth and phenology, for use in MAS, we genetically dissected the trait variation of a Salix viminalis (L.) population of 323 accessions. The accessions were sampled throughout northern Europe and were established at two field sites in Pustnäs, Sweden, and at Woburn, UK, offering the opportunity to assess the impact of genotype‐by‐environment interactions (G × E) on trait–marker associations. Field measurements were recorded for growth and phenology traits. The accessions were genotyped using 1536 SNP markers developed from phenology candidate genes and from genes previously observed to be differentially expressed in contrasting environments. Association mapping between 1233 of these SNPs and the measured traits was performed taking into account population structure and threshold selection bias. At a false discovery rate (FDR) of 0.2, 29 SNPs were associated with bud burst, leaf senescence, number of shoots or shoot diameter. The percentage of accession variation () explained by these associations ranged from 0.3% to 4.4%, suggesting that the studied traits are controlled by many loci of limited individual impact. Despite this, a SNP in the EARLY FLOWERING 3 gene was repeatedly associated (FDR < 0.2) with bud burst. The rare homozygous genotype exhibited 0.4–1.0 lower bud burst scores than the other genotype classes on a five‐grade scale. Consequently, this marker could be promising for use in MAS and the gene deserves further study. Otherwise, associations were less consistent across sites, likely due to their small estimates and to considerable G × E interactions indicated by multivariate association analyses and modest trait accession correlations across sites (0.32–0.61).     

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.     

Genome-wide quantitative trait locus association scan of general cognitive ability using pooled DNA and 500K single nucleotide polymorphism microarrays

General cognitive ability ( g ), which refers to what cognitive abilities have in common, is an important target for molecular genetic research because multivariate quantitative genetic analyses have shown that the same set of genes affects diverse cognitive abilities as well as learning disabilities. In this first autosomal genome-wide association scan of g , we used a two-stage quantitative trait locus (QTL) design with pooled DNA to screen more than 500 000 single nucleotide polymorphisms (SNPs) on microarrays, selecting from a sample of 7000 7-year-old children. In stage 1, we screened for allele frequency differences between groups pooled for low and high g . In stage 2, 47 SNPs nominated in stage 1 were tested by individually genotyping an independent sample of 3195 individuals, representative of the entire distribution of g scores in the full 7000 7-year-old children. Six SNPs yielded significant associations across the normal distribution of g , although only one SNP remained significant after a false discovery rate of 0.05 was imposed. However, none of these SNPs accounted for more than 0.4% of the variance of g , despite 95% power to detect associations of that size. It is likely that QTL effect sizes, even for highly heritable traits such as cognitive abilities and disabilities, are much smaller than previously assumed. Nonetheless, an aggregated 'SNP set' of the six SNPs correlated 0.11 ( P  < 0.00000003) with g . This shows that future SNP sets that will incorporate many more SNPs could be useful for predicting genetic risk and for investigating functional systems of effects from genes to brain to behavior.     

Genetic Control of Individual Differences in Gene-Specific Methylation in Human Brain

We have observed extensive interindividual differences in DNA methylation of 8590 CpG sites of 6229 genes in 153 human adult cerebellum samples, enriched in CpG island “shores” and at further distances from CpG islands. To search for genetic factors that regulate this variation, we performed a genome-wide association study (GWAS) mapping of methylation quantitative trait loci (mQTLs) for the 8590 testable CpG sites. cis association refers to correlation of methylation with SNPs within 1 Mb of a CpG site. 736 CpG sites showed phenotype-wide significant cis association with 2878 SNPs (after permutation correction for all tested markers and methylation phenotypes). In trans analysis of methylation, which tests for distant regulation effects, associations of 12 CpG sites and 38 SNPs remained significant after phenotype-wide correction. To examine the functional effects of mQTLs, we analyzed 85 genes that were with genetically regulated methylation we observed and for which we had quality gene expression data. Ten genes showed SNP-methylation-expression three-way associations—the same SNP simultaneously showed significant association with both DNA methylation and gene expression, while DNA methylation was significantly correlated with gene expression. Thus, we demonstrated that DNA methylation is frequently a heritable continuous quantitatively variable trait in human brain. Unlike allele-specific methylation, genetic polymorphisms mark both cis- and trans-regulatory genetic sites at measurable distances from their CpG sites. Some of the genetically regulated DNA methylation is directly connected with genetically regulated gene expression variation.     

Exome sequences and multi‐environment field trials elucidate the genetic basis of adaptation in barley

Broadening the genetic base of crops is crucial for developing varieties to respond to global agricultural challenges such as climate change. Here, we analysed a diverse panel of 371 domesticated lines of the model crop barley to explore the genetics of crop adaptation. We first collected exome sequence data and phenotypes of key life history traits from contrasting multi‐environment common garden trials. Then we applied refined statistical methods, including some based on exomic haplotype states, for genotype‐by‐environment (G×E) modelling. Sub‐populations defined from exomic profiles were coincident with barley's biology, geography and history, and explained a high proportion of trial phenotypic variance. Clear G×E interactions indicated adaptation profiles that varied for landraces and cultivars. Exploration of circadian clock‐related genes, associated with the environmentally adaptive days to heading trait (crucial for the crop's spread from the Fertile Crescent), illustrated complexities in G×E effect directions, and the importance of latitudinally based genic context in the expression of large‐effect alleles. Our analysis supports a gene‐level scientific understanding of crop adaption and leads to practical opportunities for crop improvement, allowing the prioritisation of genomic regions and particular sets of lines for breeding efforts seeking to cope with climate change and other stresses.     

Genotype by environment interactions in forest tree breeding: review of methodology and perspectives on research and application

Genotype by environment interaction (G×E) refers to the comparative performances of genotypes differing among environments, representing differences in genotype rankings or differences in the level of expression of genetic differences among environments. G×E can reduce heritability and overall genetic gain, unless breeding programmes are structured to address different categories of environments. Understanding the impact of G×E, the role of environments in generating G×E and the problems and opportunities is vital to efficient breeding programme design and deployment of genetic material. We review the current main analytical methods for identifying G×E: factor analytic models, biplot analysis and reaction norm. We also review biological and statistical evidence of G×E for growth, form and wood properties in forest species of global economic importance, including some pines, eucalypts, Douglas-fir, spruces and some poplars. Among these species, high levels of G×E tend to be reported for growth traits, with low levels of G×E for form traits and wood properties. Finally, we discuss possible ways of exploiting G×E to maximise genetic gain in forest tree breeding. Characterising the role of environments in generating interactions is seen as the basic platform, allowing efficient testing of candidate genotypes. We discuss the importance of level-of-expression interaction, relative to rank-change interaction, as being greater than in many past reports, especially for deployment decisions. We examine the impacts of G×E on tree breeding, some environmental factors that cause G×E and the strategies for dealing with G×E in tree breeding, and the future role of genomics.     

A genome-wide association study identified new variants associated with mathematical abilities in Chinese children

Mathematical ability is moderately heritable, and it is a complex trait which can be evaluated in several different categories. A few genetic studies have been published on general mathematical ability. However, no genetic study focused on specific mathematical ability categories. In this study, we separately performed genome-wide association studies on 11 mathematical ability categories in 1146 students from Chinese elementary schools. We identified seven genome-wide significant single nucleotide polymorphisms (SNPs) with strong linkage disequilibrium among each other (all r² > 0.8) associated with mathematical reasoning ability (top SNP: rs34034296, p = 2.01 × 10⁻⁸, nearest gene: CUB and Sushi multiple domains 3, CSMD3). We replicated one SNP (rs133885) from 585 SNPs previously reported to be associated with general mathematical ability associated with division ability in our data (p = 1.053 × 10⁻⁵). In the gene- and gene-set enrichment analysis by MAGMA, we found three significant enrichments of associations with three mathematical ability categories for three genes (LINGO2, OAS1 and HECTD1). We also observed four significant enrichments of associations with four mathematical ability categories for three gene sets. Our results suggest new candidate genetic loci for the genetics of mathematical ability.     

Confirmation and fine‐mapping of clinical mastitis and somatic cell score QTL in Nordic Holstein cattle

A genome‐wide association study of 2098 progeny‐tested Nordic Holstein bulls genotyped for 36 387 SNPs on 29 autosomes was conducted to confirm and fine‐map quantitative trait loci (QTL) for mastitis traits identified earlier using linkage analysis with sparse microsatellite markers in the same population. We used linear mixed model analysis where a polygenic genetic effect was fitted as a random effect and single SNPs were successively included as fixed effects in the model. We detected 143 SNP‐by‐trait significant associations (P < 0.0001) on 20 chromosomes affecting mastitis‐related traits. Among them, 21 SNP‐by‐trait combinations exceeded the genome‐wide significant threshold. For 12 chromosomes, both the present association study and the previous linkage study detected QTL, and of these, six were in the same chromosomal locations. Strong associations of SNPs with mastitis traits were observed on bovine autosomes 6, 13, 14 and 20. Possible candidate genes for these QTL were identified. Identification of SNPs in linkage disequilibrium with QTL will enable marker‐based selection for mastitis resistance. The candidate genes identified should be further studied to detect candidate polymorphisms underlying these QTL.     

Genomic reaction norm models exploiting genotype × environment interaction on sexual precocity indicator traits in Nellore cattle

Brazilian beef cattle are raised predominantly on pasture in a wide range of environments. In this scenario, genotype by environment (G×E) interaction is an important source of phenotypic variation in the reproductive traits. Hence, the evaluation of G×E interactions for heifer’s early pregnancy (HP) and scrotal circumference (SC) traits in Nellore cattle, belonging to three breeding programs, was carried out to determine the animal’s sensitivity to the environmental conditions (EC). The dataset consisted of 85 874 records for HP and 151 553 records for SC, from which 1800 heifers and 3343 young bulls were genotyped with the BovineHD BeadChip. Genotypic information for 826 sires was also used in the analyses. EC levels were based on the contemporary group solutions for yearling body weight. Linear reaction norm models (RNM), using pedigree information (RNM_A) or pedigree and genomic information (RNM_H), were used to infer G×E interactions. Two validation schemes were used to assess the predictive ability, with the following training populations: (a) forward scheme—dataset was split based on year of birth from 2008 for HP and from 2011 for SC; and (b) environment-specific scheme—low EC (−3.0 and −1.5) and high EC (1.5 and 3.0). The inclusion of the H matrix in RNM increased the genetic variance of the intercept and slope by 18.55 and 23.00% on average respectively, and provided genetic parameter estimates that were more accurate than those considering pedigree only. The same trend was observed for heritability estimates, which were 0.28–0.56 for SC and 0.26–0.49 for HP, using RNM_H, and 0.26–0.52 for SC and 0.22–0.45 for HP, using RNM_A. The lowest correlation observed between unfavorable (−3.0) and favorable (3.0) EC levels were 0.30 for HP and −0.12 for SC, indicating the presence of G×E interaction. The G×E interaction effect implied differences in animals’ genetic merit and re-ranking of animals on different environmental conditions. SNP marker–environment interaction was detected for Nellore sexual precocity indicator traits with changes in effect and variance across EC levels. The RNM_H captured G×E interaction effects better than RNM_A and improved the predictive ability by around 14.04% for SC and 21.31% for HP. Using the forward scheme increased the overall predictive ability for SC (20.55%) and HP (11.06%) compared with the environment-specific scheme. The results suggest that the inclusion of genomic information combined with the pedigree to assess the G×E interaction leads to more accurate variance components and genetic parameter estimates.     

Association of a CONSTANS-LIKE gene to flowering and height in autotetraploid alfalfa

In alfalfa (Medicago sativa), an autotetraploid forage legume, stem length is a major component of forage yield, quality and competing ability. In this species, flowering date is not a breeding criterion. Association mapping based on a candidate gene approach has given good results in plants, including autotetraploid species for which genetic analyses are complex. The role of a CONSTANS-LIKE gene, identified as a candidate for stem elongation and flowering date in the model legume M. truncatula, was tested for association with the same traits in alfalfa. Four hundred genotypes from ten cultivars were evaluated for stem height and flowering date in two locations during 4 years. They were genotyped with simple sequence repeat markers and a low structuration was noticed. Primers were designed to amplify and sequence two regions of the alfalfa gene homologous to CONSTANS-LIKE. Single nucleotide polymorphisms (SNPs) were detected and their allelic dose in each genotype was scored. Linkage disequilibrium within CONSTANS-LIKE rapidly decreased as expected. Eight SNPs with a frequency above 10% were detected over 1,010 bp (one SNP every 126 bp on average) in the 400 genotypes. This number was lower than observed in a neutral gene (a SNP every 31 bp on average). Highly significant associations of three SNPs to flowering date and stem height were identified. Each SNP explained up to 4.2% of the genetic variance. Thus, as in the model species, the CONSTANS-LIKE gene was shown to be involved in flowering date and stem height in alfalfa.     

Evidence of gene–environment interaction for the IRF6 gene and maternal multivitamin supplementation in controlling the risk of cleft lip with/without cleft palate

Although multiple genes have been identified as genetic risk factors for isolated, non-syndromic cleft lip with/without cleft palate (CL/P), a complex and heterogeneous birth defect, interferon regulatory factor 6 gene (IRF6) is one of the best documented genetic risk factors. In this study, we tested for association between markers in IRF6 and CL/P in 326 Chinese case–parent trios, considering gene–environment interaction for two common maternal exposures, and parent-of-origin effects. CL/P case–parent trios from three sites in mainland China and Taiwan were genotyped for 22 single nucleotide polymorphisms (SNPs) in IRF6. The transmission disequilibrium test was used to test for marginal effects of individual SNPs. We used PBAT to screen the SNPs and haplotypes for gene–environment (G × E) interaction and conditional logistic regression models to quantify effect sizes for SNP–environment interaction. After Bonferroni correction, 14 SNPs showed statistically significant association with CL/P. Evidence of G × E interaction was found for both maternal exposures, multivitamin supplementation and environmental tobacco smoke (ETS). Two SNPs showed evidence of interaction with multivitamin supplementation in conditional logistic regression models (rs2076153 nominal P = 0.019, rs17015218 nominal P = 0.012). In addition, rs1044516 yielded evidence for interaction with maternal ETS (nominal P = 0.041). Haplotype analysis using PBAT also suggested interaction between SNPs in IRF6 and both multivitamin supplementation and ETS. However, no evidence for maternal genotypic effects or significant parent-of-origin effects was seen in these data. These results suggest IRF6 gene may influence risk of CL/P through interaction with multivitamin supplementation and ETS in the Chinese population.     

Genetic parameters and provenance variation of Pinus radiata D. Don. ‘Eldridge collection’ in Australia 1: growth and form traits

Growth and form traits data were obtained from eight provenance trials of radiata pine (Pinus radiata D. Don) planted across the radiata pine plantation estate in southeast Australia. The genetic pool included 466 open-pollinated families collected from A?o Nuevo, Monterey and Cambria provenances on the Californian mainland coast in the USA and from Guadalupe and Cedros islands off the coast of Baja California in Mexico. Early survival of all provenances was around 90%, except for Cedros (<60%). Monterey and A?o Nuevo were the best performers at almost all sites. However, good growth performance of Cambria and good stem straightness of Guadalupe on some sites are important results, because the genetic base of the present Australian plantations evidently originated from only Monterey and A?o Nuevo. The average estimated single-site heritability for diameter at breast height was 0.22 and 0.32 at juvenile and mature ages, respectively. Heritability estimates for stem straightness and branching ranged from 0.23 to 0.55. Genetic correlation estimates between diameter at breast height (DBH) at juvenile and rotation ages were all >0.80. Estimates of between-site genetic and provenance correlations for DBH were often low, indicating high genotype by environment interaction across trials, consistent with previous Australian studies. However, there was minimal G × E among trials on high-altitude high-rainfall sites and among trials on low-altitude, low-rainfall sites.     

Evidence for consistent intragenic and intergenic interactions between SNP effects in the APOA1/C3/A4/A5 gene cluster

OBJECTIVE: Evaluate the consistency of the contribution of interactions between single nucleotide polymorphism (SNP) genotype effects to variation in measures of lipid metabolism across ethnic strata within gender. METHODS AND RESULTS: We considered 80 SNPs within the apolipoprotein (APO) A1/C3/A4/A5 gene cluster using an over-parameterized general linear model to identify SNPs whose genotype effects combine non-additively to influence plasma levels of high density lipoprotein cholesterol (HDL-C), total cholesterol (TC) and triglycerides (TG) in a consistent manner across ethnic strata. We analyzed population-based samples of unrelated 18 to 30 year old African-Americans (n = 1,858) and European-Americans (n = 1,973) ascertained without regard to health at four field centers (Birmingham, Ala.; Chicago, Ill.; Minneapolis, Minn. and Oakland, Calif., USA) by the Coronary Artery Risk Development in Young Adults (CARDIA) study. To identify which SNP genotype effects combine non-additively we used a two-tier analysis strategy. We first required that pairs of SNPs show statistically significant non-additivity in both ethnic strata within a gender, where experiment-wise significance was evaluated using a permutation test to determine the probability of observing the number of tests significant in both ethnic strata by chance alone. Second, we required no significant evidence of heterogeneity of the relationship between the phenotype and the two SNP genotypes across ethnic strata and across field centers within each ethnic group. From this strategy we identified ten pairs of SNPs, involving thirteen SNPs, that displayed statistically significant non-additivity of SNP genotype effects on TC. Only one of these thirteen SNPs had statistically significant genotype effects that were consistent across samples. CONCLUSION: Our analyses suggest that ignoring the contribution of interactions between SNP genotype effects when modeling multi-SNP genotype-phenotype relationships may result in an underestimate of the contribution of genetic variation to variation in quantitative cardiovascular disease (CVD) risk factor traits.     

A novel method for identifying nonlinear gene–environment interactions in case–control association studies

The genetic influences on complex disease traits generally depend on the joint effects of multiple genetic variants, environmental factors, as well as their interplays. Gene × environment (G × E) interactions play vital roles in determining an individual’s disease risk, but the underlying genetic machinery is poorly understood. Traditional analysis assuming linear relationship between genetic and environmental factors, along with their interactions, is commonly pursued under the regression-based framework to examine G × E interactions. This assumption, however, could be violated due to nonlinear responses of genetic variants to environmental stimuli. As an extension to our previous work on continuous traits, we proposed a flexible varying-coefficient model for the detection of nonlinear G × E interaction with binary disease traits. Varying coefficients were approximated by a non-parametric regression function through which one can assess the nonlinear response of genetic factors to environmental changes. A group of statistical tests were proposed to elucidate various mechanisms of G × E interaction. The utility of the proposed method was illustrated via simulation and real data analysis with application to type 2 diabetes.