Genetic correlates of gene expression in recombinant inbred strains - A relational model system to explore neurobehavioral phenotypes
Genetic correlates of gene expression in recombinant inbred strains - A relational model system to explore neurobehavioral phenotypes
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DOI：
10.1385/ni:1:4:343
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发表时间：
2003-12-01
期刊：
影响因子：
3
通讯作者：
Williams, RW
中科院分区：
文献类型：
--
作者：
Chesler, EJ;Wang, JT;Williams, RW
全基因组测序、高密度基因分型、扩大微阵列检测以及神经解剖和行为特征的系统表型分析正在产生大量关于小鼠中枢神经系统（CNS）的数据。这些不同的资源仍然没有很好地整合。一种解决方案是使用小鼠等基因系的共同参考群体来获取这些数据，从而提供数据类型之间的整合点。重组近交 (RI) 小鼠是通过近交杂交后代近交而衍生的，是复杂性状图谱和神经科学领域具有挑战性的表型分析的强大工具。这些同基因 RI 系是可回收的遗传资源，可以使用多种检测方法进行重复研究。不同的数据集可以通过固定和已知的基因组关联起来，使用诸如用于复杂性状分析的交互式网络系统www.WebQTL.org等工具。在本报告中，我们展示了使用 WebQTL 来探索各种性状之间的复杂相互作用 - 从 mRNA 转录本到 RI 菌株之间令人印象深刻的行为和药理学变异。利用一组常见菌株的关系方法有助于研究单基因的多重效应（多效性），而无需先验假设。在这里，我们通过基因表达与通过 20 多年的实验在这些小鼠品系中收集的神经行为表型数据库的遗传相关性来展示这项技术的威力。通过重复研究同一组小鼠，可以根据最初收集时未预见到的技术进步重新检查早期数据。
Full genome sequencing, high-density genotyping, expanding sets of microarray assays, and systematic phenotyping of neuroanatomical and behavioral traits are producing a wealth of data on the mouse central nervous system (CNS). These disparate resources are still poorly integrated. One solution is to acquire these data using a common reference population of isogenic lines of mice, providing a point of integration between the data types. Recombinant inbred (RI) mice, derived through inbreeding of progeny from an inbred cross, are a powerful tool for complex trait mapping and analysis of the challenging phenotypes of neuroscientific interest. These isogenic RI lines are a retrievable genetic resource that can be repeatedly studied using a wide variety of assays. Diverse data sets can be related through fixed and known genomes, using tools such as the interactive web-based system for complex trait analysis, www.WebQTL.org. In this report, we demonstrate the use of WebQTL to explore complex interactions among a wide variety of traits-from from mRNA transcripts to the impressive behavioral and pharmacological variation among RI strains. The relational approach exploiting a common set of strains facilitates study of multiple effects of single genes (pleiotropy) without a priori hypotheses required. Here we demonstrate the power of this technique through genetic correlation of gene expression with a database of neurobehavioral phenotypes collected in these strains of mice through more than 20 years of experimentation. By repeatedly studying the same panel, of mice, early data can be re-examined in light of technological advances unforeseen at the time of their initial collection.