de Jong Johann, Wessels Lodewyk F A, van Lohuizen Maarten, de Ridder Jeroen, Akhtar Waseem
Computational Cancer Biology Group; Division of Molecular Carcinogenesis; The Netherlands Cancer Institute ; Amsterdam, The Netherlands.
Computational Cancer Biology Group; Division of Molecular Carcinogenesis; The Netherlands Cancer Institute ; Amsterdam, The Netherlands ; Delft Bioinformatics Lab; TU Delft ; Delft, The Netherlands.
Mob Genet Elements. 2015 Mar 9;4(6):1-6. doi: 10.4161/2159256X.2014.992694. eCollection 2014 Nov-Dec.
Retroviruses and DNA transposons are an important part of molecular biologists' toolbox. The applications of these elements range from functional genomics to oncogene discovery and gene therapy. However, these elements do not integrate uniformly across the genome, which is an important limitation to their use. A number of genetic and epigenetic factors have been shown to shape the integration preference of these elements. Insight into integration bias can significantly enhance the analysis and interpretation of results obtained using these elements. For three different applications, we outline how bias can affect results, and can potentially be addressed.
逆转录病毒和DNA转座子是分子生物学家工具箱中的重要组成部分。这些元件的应用范围从功能基因组学到癌基因发现和基因治疗。然而,这些元件并非均匀地整合到整个基因组中,这是其应用的一个重要限制。已证明许多遗传和表观遗传因素会影响这些元件的整合偏好。深入了解整合偏差可显著增强对使用这些元件获得的结果的分析和解读。对于三种不同的应用,我们概述了偏差如何影响结果以及如何可能解决这些偏差。