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Discovery and verification of functional single nucleotide polymorphisms in regulatory genomic regions: Current and developing technologies

机译:发现和验证监管基因组区域中功能性单核苷酸多态性:当前和正在开发的技术

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摘要

The most common form of genetic variation, single nucleotide polymorphisms or SNPs, can affect the way an individual responds to the environment and modify disease risk. Although most of the millions of SNPs have little or no effect on gene regulation and protein activity, there are many circumstances where base changes can have deleterious effects. Non-synonymous SNPs that result in amino acid changes in proteins have been studied because of their obvious impact on protein activity. It is well known that SNPs within regulatory regions of the genome can result in disregulation of gene transcription. However, the impact of SNPs located in putative regulatory regions, or rSNPs, is harder to predict for two primary reasons. First, the mechanistic roles of non-coding genomic sequence remain poorly defined. Second, experimental validation of the functional consequences of rSNPs is often slow and laborious. In this review, we summarize traditional and novel methodologies for candidate rSNPs selection, in particular in silico techniques that aid in candidate rSNP selection. Additionally we will discuss molecular biological techniques that assess the impact of rSNPs on binding of regulatory machinery, as well as functional consequences on transcription. Standard techniques such as EMSA and luciferase reporter constructs are still widely used to assess effects of rSNPs on binding and gene transcription; however, these protocols are often bottlenecks in the discovery process. Therefore, we highlight novel and developing high-throughput protocols that promise to aid in shortening the process of rSNP validation. Given the large amount of genomic information generated from a multitude of re-sequencing and genome-wide SNP array efforts, future focus should be to develop validation techniques that will allow greater understanding of the impact these polymorphisms have on human health and disease.
机译:遗传变异最常见的形式是单核苷酸多态性或SNP,可影响个体对环境的反应方式并改变疾病风险。尽管数百万个SNP中的大多数对基因调控和蛋白质活性几乎没有影响,但在许多情况下碱基的改变可能具有有害作用。已经研究了导致蛋白质氨基酸改变的非同义SNP,因为它们对蛋白质活性有明显影响。众所周知,基因组调节区内的SNP可导致基因转录失调。但是,由于两个主要原因,很难预测位于假定的调控区的SNP或rSNP的影响。首先,非编码基因组序列的机械作用仍然定义不清。其次,对rSNPs功能后果的实验验证通常是缓慢而费力的。在这篇综述中,我们总结了候选rSNPs选择的传统方法和新颖方法,特别是计算机技术中有助于候选rSNP选择的方法。另外,我们将讨论分子生物学技术,这些技术评估rSNP对调节机制结合的影响以及对转录的功能后果。诸如EMSA和荧光素酶报道基因构建体之类的标准技术仍被广泛用于评估rSNP对结合和基因转录的影响。但是,这些协议通常是发现过程中的瓶颈。因此,我们重点介绍了新颖且正在开发的高通量协议,这些协议有望帮助缩短rSNP验证过程。鉴于从大量重测序和全基因组SNP阵列工作中产生的大量基因组信息,未来的重点应该是开发验证技术,以使人们更好地了解这些多态性对人类健康和疾病的影响。

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