Discovering altered genomic expression patterns in heart: transcriptome determination by serial analysis of gene expression.
Discovering altered genomic expression patterns in heart: transcriptome determination by serial analysis of gene expression.
复制标题
发现心脏中改变的基因组表达模式：通过基因表达的系列分析确定转录组。
DOI：
10.1016/s1388-9842(01)00131-3
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发表时间：
2001
期刊：
影响因子：
--
通讯作者：
Boheler,KR
中科院分区：
文献类型：
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作者：
Anisimov,SV;Lakatta,EG;Boheler,KR
心血管疾病（如心力衰竭）的发展涉及短期有益的功能变化，但长期可能是致命的。目前的治疗方法是针对限制疾病的进展和维持生活质量。在分子水平上，这些疾病过程涉及基因表达的定量和定性变化。虽然mRNA丰度的一些变化可能没有直接的蛋白质相关性，但分析细胞群体中存在的所有mRNA（细胞转录组）已成为基因组研究的焦点。其目的是提供有关全基因组表达动态响应环境变化的信息，并指出负责导致疾病状态的级联事件的候选基因。进行这些分析的一种方法是利用基因表达系列分析（SAGE）技术。该方法在单个测定中定量和定性地评估数千个表达的转录本。在转录组分析的两个评论的第一个，我们描述了基因组研究的现状，通过基因表达的系列分析确定的转录组，提出了第一个有限的SAGE分析啮齿动物心脏基因表达，并讨论如何与这种方法产生的结果可以应用于心血管疾病的研究和治疗。
The development of cardiovascular diseases such as heart failure involve functional changes that are beneficial short‐term, but may be fatal long‐term. Current therapeutic approaches are tailored to limit progression of a disease and to maintain quality of life. At a molecular level, these disease processes involve quantitative and qualitative changes in gene expression. Although some changes in mRNA abundance may not have direct protein correlates, analysis of all the mRNAs present in a cell population (the cells transcriptome) has become a focal point of genomic research. The aim is to provide information about the dynamics of total genome expression in response to environmental changes and point to candidate genes responsible for the cascade of events that result in a disease state. One way of performing these analyses utilizes the technique of Serial Analysis of Gene Expression (SAGE). This method evaluates thousands of expressed transcripts both quantitatively and qualitatively in a single assay. In the first of two reviews on transcriptome analysis, we describe the current state of genomic research for determination of the transcriptome by Serial Analysis of Gene Expression, present the first limited SAGE analysis of rodent heart gene expression, and discuss how results generated with this approach can be applied to the study and treatment of cardiovascular diseases.