Integrating genetic and gene expression data: application to cardiovascular and metabolic traits in mice.
Integrating genetic and gene expression data: application to cardiovascular and metabolic traits in mice.
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DOI：
10.1007/s00335-005-0175-z
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发表时间：
2006-06
期刊：
影响因子：
2.5
通讯作者：
Lusis, Aldons J.
中科院分区：
文献类型：
--
作者：
Drake, Thomas A.;Schadt, Eric E.;Lusis, Aldons J.
在人类群体中或在小鼠和大鼠的近交系中发生的数百万种常见DNA变异干扰了在特定组织中表达的大部分基因的表达（转录水平）。群体中发生的数百或数千种常见的顺式作用变异反过来可能通过影响转录因子、信号分子、RNA加工和其他反式作用过程而影响数千种其他基因的表达。使用表达阵列方便地定量转录物的水平，并且可以使用数量性状基因座（QTL）分析绘制顺式和反式作用基因座，与生理或临床性状的基因座相同。在小鼠和其他实验生物的各种杂交中，已经绘制了数千个这样的表达QTL（eQTL），在人类谱系细胞的研究中绘制了不太详细的地图。这种综合遗传学方法（有时称为“遗传基因组学”）被证明可用于鉴定导致复杂临床特征的基因和途径。临床性状QTL和eQTL的重合有助于定位候选基因。更重要的是，在遗传杂交中转录水平和临床性状之间的相关性的数学建模可以允许预测因果相互作用和识别“关键驱动”基因。这些研究的一个重要目标将是模拟生理过程中的生物网络。当结合高密度单核苷酸多态性（SNP）定位，它应该是可行的，以确定基因，有助于转录水平使用关联分析在远交群体。在这篇综述中，我们讨论了这种整合基因组方法的基本概念和应用，以心血管和代谢疾病。
The millions of common DNA variations that occur in the human population, or among inbred strains of mice and rats, perturb the expression (transcript levels) of a large fraction of the genes expressed in a particular tissue. The hundreds or thousands of common cis-acting variations that occur in the population may in turn affect the expression of thousands of other genes by affecting transcription factors, signaling molecules, RNA processing, and other processes that act in trans. The levels of transcripts are conveniently quantitated using expression arrays, and the cis- and trans-acting loci can be mapped using quantitative trait locus (QTL) analysis, in the same manner as loci for physiologic or clinical traits. Thousands of such expression QTL (eQTL) have been mapped in various crosses in mice, as well as other experimental organisms, and less detailed maps have been produced in studies of cells from human pedigrees. Such an integrative genetics approach (sometimes referred to as “genetical genomics”) is proving useful for identifying genes and pathways that contribute to complex clinical traits. The coincidence of clinical trait QTL and eQTL can help in the prioritization of positional candidate genes. More importantly, mathematical modeling of correlations between levels of transcripts and clinical traits in genetic crosses can allow prediction of causal interactions and the identification of “key driver” genes. An important objective of such studies will be to model biological networks in physiologic processes. When combined with high-density single nucleotide polymorphism (SNP) mapping, it should be feasible to identify genes that contribute to transcript levels using association analysis in outbred populations. In this review we discuss the basic concepts and applications of this integrative genomic approach to cardiovascular and metabolic diseases.
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影响因子：
4.6
作者：
Drake, TA;Schadt, E;Lusis, AJ
通讯作者：
Lusis, AJ
影响因子：
15.9
作者：
Machleder, D;Ivandic, B;Lusis, AJ
通讯作者：
Lusis, AJ
影响因子：
7
作者：
Doss, S;Schadt, EE;Lusis, AJ
通讯作者：
Lusis, AJ
DOI：
10.1196/annals.1322.003
发表时间：
2004-01-01
期刊：
SIGNAL TRANSDUCTION AND COMMUNICATION IN CANCER CELLS
影响因子：
--
作者：
Bucca, G;Carruba, G;Smith, CP
通讯作者：
Smith, CP
影响因子：
7.7
作者：
Davis, RC;Schadt, EE;Lusis, AJ
通讯作者：
Lusis, AJ