Biotechnology Center, Technische Universität Dresden, Dresden, Germany.
PLoS One. 2010 Nov 10;5(11):e13920. doi: 10.1371/journal.pone.0013920.
The study of expression quantitative trait loci (eQTL) is a powerful way of detecting transcriptional regulators at a genomic scale and for elucidating how natural genetic variation impacts gene expression. Power and genetic resolution are heavily affected by the study population: whereas recombinant inbred (RI) strains yield greater statistical power with low genetic resolution, using diverse inbred or outbred strains improves genetic resolution at the cost of lower power. In order to overcome the limitations of both individual approaches, we combine data from RI strains with genetically more diverse strains and analyze hippocampus eQTL data obtained from mouse RI strains (BXD) and from a panel of diverse inbred strains (Mouse Diversity Panel, MDP). We perform a systematic analysis of the consistency of eQTL independently obtained from these two populations and demonstrate that a significant fraction of eQTL can be replicated. Based on existing knowledge from pathway databases we assess different approaches for using the high-resolution MDP data for fine mapping BXD eQTL. Finally, we apply this framework to an eQTL hotspot on chromosome 1 (Qrr1), which has been implicated in a range of neurological traits. Here we present the first systematic examination of the consistency between eQTL obtained independently from the BXD and MDP populations. Our analysis of fine-mapping approaches is based on 'real life' data as opposed to simulated data and it allows us to propose a strategy for using MDP data to fine map BXD eQTL. Application of this framework to Qrr1 reveals that this eQTL hotspot is not caused by just one (or few) 'master regulators', but actually by a set of polymorphic genes specific to the central nervous system.
表达数量性状基因座（eQTL）的研究是一种在基因组范围内检测转录调控因子的有力方法，并阐明自然遗传变异如何影响基因表达。研究群体极大地影响了功率和遗传分辨率：重组近交（RI）品系在遗传分辨率低的情况下产生更大的统计功率，而使用不同的近交或远交品系则以降低功率为代价提高了遗传分辨率。为了克服这两种方法的局限性，我们将 RI 品系的数据与遗传上更加多样化的品系的数据相结合，并分析了从小鼠 RI 品系（BXD）和一系列多样化的近交品系（Mouse Diversity Panel，MDP）获得的海马体 eQTL 数据。我们对这两个群体独立获得的 eQTL 一致性进行了系统分析，并证明了相当一部分 eQTL 可以被复制。基于来自途径数据库的现有知识，我们评估了使用高分辨率 MDP 数据对 BXD eQTL 进行精细映射的不同方法。最后，我们将该框架应用于 1 号染色体（Qrr1）上的一个 eQTL 热点，该热点与一系列神经特征有关。在这里，我们首次系统地检查了从 BXD 和 MDP 群体中独立获得的 eQTL 之间的一致性。我们对精细映射方法的分析是基于“真实”数据，而不是模拟数据，这使我们能够提出一种使用 MDP 数据对 BXD eQTL 进行精细映射的策略。将该框架应用于 Qrr1 揭示了这个 eQTL 热点不是由一个（或几个）“主调控因子”引起的，而是由一组特定于中枢神经系统的多态基因引起的。
