Genome-Wide Prediction of Functional Gene-Gene Interactions Inferred from Patterns of Genetic Differentiation in Mice and Men

The human genome encodes a limited number of genes yet contributes to individual differences in a vast array of heritable traits. A possible explanation for the capacity our genome to generate this virtually unlimited range of phenotypic variation in complex traits is to assume functional interactions between genes. Therefore we searched two mammalian genomes to identify potential epistatic interactions by looking for co-adapted genes marked by excess two-locus genetic differentiation between populations/lineages using publicly available SNP genotype data. The practical motivation for this effort is to reduce the number of pair-wise tests that need to be performed in genome-wide association studies aimed at detecting G×G interactions, by focusing on pairs predicted to be more likely to jointly affect variation in complex traits. Hence, this approach generates a list of candidate interactions that can be empirically tested. In both the mouse and human data we observed two-locus genetic differentiation in excess of what can be expected from chance alone based on simulations. In an attempt to validate our hypothesis that pairs of genes showing excess genetic divergence represent potential functional interactions, we selected a small set of gene combinations postulated to be interacting based on our analyses and looked for a combined effect of the selected genes on variation in complex traits in both mice and man. In both cases the individual effect of the genes were not significant, instead we observed marginally significant interaction effects. These results show that genome wide searches for gene-gene interactions based on population genetic data are feasible and can generate interesting candidate gene pairs to be further tested for their contribution to phenotypic variation in complex traits.

人类基因组编码的基因数量有限，却可在众多可遗传性状中造就个体间的广泛差异。对于基因组为何能够在复杂性状中产生近乎无限范围的表型变异，一种合理的解释是基因间存在功能互作。为此，我们借助公开可用的单核苷酸多态性(Single Nucleotide Polymorphism, SNP)基因型数据，通过搜寻以种群/谱系间过量双位点遗传分化为标记的共适应基因，在两种哺乳动物基因组中筛选潜在的上位互作(epistatic interactions)。本研究的实际动机在于，针对旨在检测基因×基因(G×G)互作的全基因组关联研究，通过聚焦于更有可能共同影响复杂性状变异的基因对，减少所需开展的两两检验次数。因此，本方法可生成一系列候选互作对，供后续实验验证。在小鼠与人类的两组数据集里，我们均观察到双位点遗传分化程度超出了基于模拟的随机预期阈值。为验证“显示过量遗传分化的基因对代表潜在功能互作”这一假说，我们基于本研究的分析结果选取了一小批被推测存在互作的基因组合，并在小鼠与人类群体中分别检测所选基因对复杂性状变异的联合效应。在两种场景下，单个基因的效应均未达到显著水平，而我们却观测到了边际显著的互作效应。上述结果表明，基于群体遗传学数据开展全基因组基因-基因互作筛查具备可行性，且可生成一批具有研究价值的候选基因对，用于后续复杂性状表型变异贡献度的验证研究。