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功能基因组分析中最常用的技术和工具。

The most common technologies and tools for functional genome analysis.

作者信息

Gasperskaja Evelina, Kučinskas Vaidutis

机构信息

Department of Human and Medical Genetics, Faculty of Medicine, Vilnius University Vilnius, Lithuania.

出版信息

Acta Med Litu. 2017;24(1):1-11. doi: 10.6001/actamedica.v24i1.3457.

Abstract

Since the sequence of the human genome is complete, the main issue is how to understand the information written in the DNA sequence. Despite numerous genome-wide studies that have already been performed, the challenge to determine the function of genes, gene products, and also their interaction is still open. As changes in the human genome are highly likely to cause pathological conditions, functional analysis is vitally important for human health. For many years there have been a variety of technologies and tools used in functional genome analysis. However, only in the past decade there has been rapid revolutionizing progress and improvement in high-throughput methods, which are ranging from traditional real-time polymerase chain reaction to more complex systems, such as next-generation sequencing or mass spectrometry. Furthermore, not only laboratory investigation, but also accurate bioinformatic analysis is required for reliable scientific results. These methods give an opportunity for accurate and comprehensive functional analysis that involves various fields of studies: genomics, epigenomics, proteomics, and interactomics. This is essential for filling the gaps in the knowledge about dynamic biological processes at both cellular and organismal level. However, each method has both advantages and limitations that should be taken into account before choosing the right method for particular research in order to ensure successful study. For this reason, the present review paper aims to describe the most frequent and widely-used methods for the comprehensive functional analysis.

摘要

由于人类基因组序列已完整,主要问题在于如何理解DNA序列中所写的信息。尽管已经开展了大量全基因组研究,但确定基因、基因产物的功能及其相互作用的挑战仍然存在。由于人类基因组的变化极有可能引发病理状况,功能分析对人类健康至关重要。多年来,功能基因组分析中使用了各种技术和工具。然而,仅在过去十年中,高通量方法才取得了快速变革性的进展和改进,这些方法涵盖从传统的实时聚合酶链反应到更复杂的系统,如下一代测序或质谱分析。此外,为了获得可靠的科学结果,不仅需要实验室研究,还需要精确的生物信息学分析。这些方法为准确而全面的功能分析提供了机会,这种分析涉及多个研究领域:基因组学、表观基因组学、蛋白质组学和相互作用组学。这对于填补细胞和生物体水平上动态生物学过程知识的空白至关重要。然而,每种方法都有其优缺点,在为特定研究选择正确方法之前应予以考虑,以确保研究成功。因此,本综述旨在描述最常用且广泛应用的综合功能分析方法。

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