Bao Lei, Peirce Jeremy L, Zhou Mi, Li Hongqiang, Goldowitz Dan, Williams Robert W, Lu Lu, Cui Yan
Department of Molecular Sciences, University of Tennessee Health Science Center, Memphis, TN 38163, USA.
Hum Mol Genet. 2007 Jun 1;16(11):1381-90. doi: 10.1093/hmg/ddm089. Epub 2007 Apr 11.
Naturally occurring genetic variations may affect certain phenotypes through influencing transcript levels of the genes that are causally related to those phenotypes. Genomic regions harboring common sequence variants that modulate gene expression can be mapped as quantitative trait loci (QTLs) using a newly developed genetical genomics approach. This enables a new strategy for systematically mapping novel genetic loci underlying various phenotypes. In this work, we started from a seed set of genes with variants that are known to affect behavioral and neurological phenotypes (as recorded in Mammalian Phenotype Ontology Database) and used microarrays to analyze their expression levels in brain samples of a panel of BXD recombinant inbred mouse strains. We then systematically mapped the QTLs controlling the expression of these genes. Candidate causal genes in the QTL intervals were evaluated for evidence of functional genetic polymorphisms. Using this method, we were able to predict novel genetic loci and causal genes for a number of behavioral and neurological phenotypes. Lines of independent evidence supporting some of our results were provided by transcription factor binding site analysis and by biomedical literature. This strategy integrates gene-phenotype relations from decades of experimental mutagenesis studies and new genomic resources to provide an approach to rapidly expand knowledge on genetic loci modulating phenotypes.
自然发生的基因变异可能通过影响与某些表型因果相关的基因的转录水平来影响这些表型。利用新开发的遗传基因组学方法，携带调节基因表达的常见序列变异的基因组区域可被定位为数量性状基因座（QTL）。这为系统地定位各种表型背后的新遗传位点提供了一种新策略。在这项工作中，我们从一组已知具有影响行为和神经表型的变异的基因（如哺乳动物表型本体数据库中所记录）开始，使用微阵列分析它们在一组BXD重组近交小鼠品系的脑样本中的表达水平。然后，我们系统地定位了控制这些基因表达的QTL。对QTL区间内的候选因果基因进行了功能遗传多态性证据的评估。使用这种方法，我们能够预测许多行为和神经表型的新遗传位点和因果基因。转录因子结合位点分析和生物医学文献为支持我们一些结果的独立证据提供了线索。该策略整合了数十年来实验诱变研究中的基因-表型关系和新的基因组资源，以提供一种快速扩展关于调节表型的遗传位点知识的方法。
