McKinney B A, Pajewski Nicholas M
Department of Mathematics, Tandy School of Computer Science, University of Tulsa Tulsa, OK, USA.
Front Genet. 2012 Jan 12;2:109. doi: 10.3389/fgene.2011.00109. eCollection 2011.
There is growing evidence that much more of the genome than previously thought is required to explain the heritability of complex phenotypes. Recent studies have demonstrated that numerous common variants from across the genome explain portions of genetic variability, spawning various avenues of research directed at explaining the remaining heritability. This polygenic structure is also the motivation for the growing application of pathway and gene set enrichment techniques, which have yielded promising results. These findings suggest that the coordination of genes in pathways that are known to occur at the gene regulatory level also can be detected at the population level. Although genes in these networks interact in complex ways, most population studies have focused on the additive contribution of common variants and the potential of rare variants to explain additional variation. In this brief review, we discuss the potential to explain additional genetic variation through the agglomeration of multiple gene-gene interactions as well as main effects of common variants in terms of a network paradigm. Just as is the case for single-locus contributions, we expect each gene-gene interaction edge in the network to have a small effect, but these effects may be reinforced through hubs and other connectivity structures in the network. We discuss some of the opportunities and challenges of network methods for analyzing genome-wide association studies (GWAS) such as the study of hubs and motifs, and integrating other types of variation and environmental interactions. Such network approaches may unveil hidden variation in GWAS, improve understanding of mechanisms of disease, and possibly fit into a network paradigm of evolutionary genetics.
越来越多的证据表明，要解释复杂表型的遗传力，所需的基因组部分比以前认为的要多得多。最近的研究表明，来自全基因组的众多常见变异解释了部分遗传变异性，催生了各种旨在解释剩余遗传力的研究途径。这种多基因结构也是通路和基因集富集技术应用日益广泛的动力，这些技术已取得了有前景的成果。这些发现表明，在基因调控水平已知发生的通路中基因的协调作用，在群体水平上也能够被检测到。尽管这些网络中的基因以复杂的方式相互作用，但大多数群体研究都集中在常见变异的加性贡献以及罕见变异解释额外变异的潜力上。在这篇简短的综述中，我们从网络范式的角度讨论了通过多个基因 - 基因相互作用的聚集以及常见变异的主效应来解释额外遗传变异的潜力。就像单基因座贡献的情况一样，我们预计网络中的每个基因 - 基因相互作用边的效应都很小，但这些效应可能会通过网络中的枢纽和其他连接结构得到加强。我们讨论了用于分析全基因组关联研究（GWAS）的网络方法的一些机遇和挑战，例如枢纽和基序的研究，以及整合其他类型的变异和环境相互作用。这种网络方法可能会揭示GWAS中隐藏的变异，增进对疾病机制的理解，并可能适用于进化遗传学的网络范式。
