Differences in the numbers of SNP pairs with P_int<5.0E-08 and local interaction pairs (P_int<1.0E-05) detected in each trait between ARIC and NFBC1966.

<p>Differences in the numbers of SNP pairs with P_int<5.0E-08 and local interaction pairs (P_int<1.0E-05) detected in each trait between ARIC and NFBC1966.</p

A cartoon model illustrating a haplotype tagging a recessive causal variant can generate an apparent statistical interaction between two unlinked SNPs each with limited marginal effects.

<p>(I) A recessive causative variant (black star) is associated with only the <b><i>ab</i></b> SNP haplotype, assuming Hardy-Weinberg Equilibrium, i.e. an equal allele frequency of 0.5 for each SNP so there is no LD between the two SNPs and an equal frequency of 0.25 for each of the four possible haplotypes, and the causal variant with an effect size of 1. (II) Only individuals homozygous for this haplotype (<b><i>ab</i></b>/<b><i>ab</i></b>) are genetically differentiated generating apparent epistasis (averaged trait value and joint genotype frequency in the bracket in each cell). (III) Marginal effects associated with the individual SNPs are limited with only one in four individuals of the <b><i>aa</i></b> or <b><i>bb</i></b> SNP genotype being affected with a trait value of 2 so the averaged trait value of the genotype is 0.5 (SNP genotype frequency in brackets), thus the individual SNPs may not be detected by a conventional GWAS. (IV) This resembles the interaction between rs17119975 and rs10892020 in TRI (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0071203#pone-0071203-t001" target="_blank">Table 1</a>) where neither SNP had important marginal effects and their interaction signal was mainly because of the differentiated phenotype associated with the double homozygous <b><i>aabb</i></b> genotype.</p

Local interactions captured additional genome-wide significant loci identified in GWAS of the eight traits in ARIC and/or NFBC1966.^*

*<p>: SNP₁ (SNP₂), pos₁ (pos₂) – name and position the first (second) SNP; P_int – P value of the interaction test; rep_SNP₁ (rep_SNP₂, rep_P_int) – the first (second, interaction P value) SNP of the best replicated pair; LD: r² linkage disequilibrium between two epistatic SNPs.</p>a<p>: detected in NFBC1966 and test replication in ARIC;</p>b<p>: region shared in multiple traits;</p>c<p>: genome-wide significant marginal SNP.</p

Genome-wide significant epistatic pairs identified in the ARIC cohort and their replication in the NFBC199 cohort.^*

*<p>: genome-wide significant thresholds for interactions involving marginal SNPs were 2.1E-09 for TRI and 3.5E-09 for HDL; SNP₁ (SNP₂), chr₁ (chr₂), pos₁ (pos₂), gene₁ (gene₂) – name, chromosome, position and mapped gene of the first (second) SNP; P_int – P value of the interaction test; rep_SNP₁ (rep_SNP₂, rep_P_int) – the first (second, interaction P value) SNP of the best replicated pair;</p>a<p>: the genome-wide significant single SNP with marginal effects;</p>b<p>: genome-wide suggestive.</p

Whole and regional genomic variances (Var), SNP names, and regional variance ratios, with LRT, on BTA14, BTA5, and BTA18.

<p>Whole and regional genomic variances (Var), SNP names, and regional variance ratios, with LRT, on BTA14, BTA5, and BTA18.</p

Boxplots for estimates of each component obtained from models ‘G’, ‘K’, ‘F’, ‘S’, ‘C’, ‘GK’, ‘GKC’, ‘GKSC’ and ‘GKFSC’.

<p>X-axis: the contributors to the simulated phenotype and the model used (matched model); Y-axis: proportion of total phenotypic variance captured by each design matrix. Yellow lines: simulated value for each component. Parameter settings: = 0.3, = 0.2, = 0.1, = 0.1 and = 0.05. For example, the 2^nd boxplot of the 3^rd graph means that, the simulated phenotypes are contributed by 30%, 20%, 10% and 40% of SNP-associated, pedigree-associated, couple environmental and residual effects respectively; we conducted variance component analyses for all replicates using the matched model ‘<b>GKC</b>’ and the estimates of range from about 8% to 12% with a mean of 10%, as expected.</p

Illustration of the model and matrices.

<p>The diagram shows the relationship between the tested genetic/environmental effect and the individuals in an example pedigree. Each colour represents a specific effect and individuals affected by that effect are circled with that colour. People in grey or black are the people not in or in the data. Examples of how the relationship matrices for those effects look are also given.</p