Using the Phenogen website for 'in silico' analysis of morphine-induced analgesia: identifying candidate genes.
Using the Phenogen website for 'in silico' analysis of morphine-induced analgesia: identifying candidate genes.
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DOI：
10.1111/j.1369-1600.2010.00254.x
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发表时间：
2011-07
影响因子：
3.4
通讯作者：
Tabakoff B
中科院分区：
文献类型：
--
作者：
Hoffman PL;Bennett B;Saba LM;Bhave SV;Carosone-Link PJ;Hornbaker CK;Kechris KJ;Williams RW;Tabakoff B
识别影响多基因(复杂)行为表型的基因是当前遗传学研究的一个关键目标。实现这一目标的一种方法是将基因表达信息与遗传信息相结合，即绘制调控基因表达水平的染色体区域。这种方法被称为“遗传基因组学”，当它与调控被研究的复杂生理性状的基因组区域(QTL)相结合时，为候选基因的发现提供了强有力的基础。在这篇论文中，我们描述了在BXD重组近交系小鼠中应用遗传基因组/表型方法来确定对吗啡镇痛作用敏感的候选基因。我们的分析是使用名为PhenoGen(http://phenogen.ucdenver.edu).)的在线互动资源进行的我们详细描述了这一资源的使用，它确定了一组候选基因，其中一些产物调节Mu阿片受体的细胞定位和活性。结果表明，PhenoGen可以用来识别一组新的基因，这些基因可以进一步研究它们在疼痛、吗啡镇痛和/或吗啡耐受中的潜在作用。
The identification of genes that contribute to polygenic (complex) behavioral phenotypes is a key goal of current genetic research. One approach to this goal is to combine gene expression information with genetic information, i.e., to map chromosomal regions that regulate gene expression levels. This approach has been termed “genetical genomics”, and, when used in conjunction with the identification of genomic regions (QTLs) that regulate the complex physiological trait under investigation, provides a strong basis for candidate gene discovery. In this paper, we describe the implementation of the genetical genomic/phenotypic approach to identify candidate genes for sensitivity to the analgesic effect of morphine in BXD recombinant inbred mice. Our analysis was performed “in silico”, using an online interactive resource called PhenoGen (http://phenogen.ucdenver.edu). We describe in detail the use of this resource, which identified a set of candidate genes, some of whose products regulate the cellular localization and activity of the mu opiate receptor. The results demonstrate how PhenoGen can be used to identify a novel set of genes that can be further investigated for their potential role in pain, morphine analgesia and/or morphine tolerance.
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影响因子：
16.2
作者：
Charlton, Joanna J.;Allen, Patrick B.;Zachariou, Venetia
通讯作者：
Zachariou, Venetia
影响因子：
2.5
作者：
Bergeson, SE;Helms, ML;Belknap, JK
通讯作者：
Belknap, JK
影响因子：
12.3
作者：
Gentleman RC;Carey VJ;Bates DM;Bolstad B;Dettling M;Dudoit S;Ellis B;Gautier L;Ge Y;Gentry J;Hornik K;Hothorn T;Huber W;Iacus S;Irizarry R;Leisch F;Li C;Maechler M;Rossini AJ;Sawitzki G;Smith C;Smyth G;Tierney L;Yang JY;Zhang J
通讯作者：
Zhang J
影响因子：
2.9
作者：
Cui, Y;Chen, Y;Chen, PX
通讯作者：
Chen, PX
影响因子：
30.8
作者：
Chesler, EJ;Lu, L;Williams, RW
通讯作者：
Williams, RW