Retroviral integration process in the human genome: is it really non-random? A new statistical approach.
Retroviral integration process in the human genome: is it really non-random? A new statistical approach.
复制标题
DOI：
10.1371/journal.pcbi.1000144
复制
发表时间：
2008-08-08
影响因子：
4.3
通讯作者：
Di Serio C
中科院分区：
文献类型：
--
作者：
Ambrosi A;Cattoglio C;Di Serio C
逆转录病毒载体广泛用于基因治疗以将治疗基因引入患者细胞中，因为一旦递送至细胞核，感兴趣的基因就稳定地插入（整合）到靶细胞基因组中。现在有令人信服的证据表明，逆转录病毒载体的整合遵循哺乳动物基因组中的非随机模式，优先选择活性基因和调控区域。特别地，莫洛尼白血病病毒（MLV）衍生的载体显示出在基因的转录起始位点（TSS）附近整合的趋势，偶尔导致基因表达的失调，并且在靶向原癌基因的情况下导致肿瘤起始。这引起了科学界对逆转录病毒整合过程的分子决定因素以及评估整合位点的全基因组分布的统计方法的注意。在最近的方法中，通过与由计算模拟程序生成的随机分布进行经验比较，假设从最近基因的TSS观察到的MLV整合距离（ID）的分布是非随机的。为了提供一个统计过程来测试的随机性的逆转录病毒插入模式，我们提出了一个概率模型（Beta分布）的基础上ID两个连续的基因。我们将该程序应用于从人造血干/祖细胞中检索的一组595个独特的MLV插入位点。统计拟合优度检验表明该分布对观测数据的适用性。我们的统计分析证实了MLV为基础的载体的偏好，整合在启动子近端区域。了解逆转录病毒载体（如基于莫洛尼白血病病毒的载体）如何整合到人类基因组中成为基因治疗领域的一个主要安全问题，因为在临床环境中评估了与整合过程相关的发展肿瘤的具体风险。基于莫洛尼白血病病毒的载体的明显特征在于非随机整合模式，偏好于活性基因转录起始位点附近。我们从概率的角度来处理非随机逆转录病毒整合的问题。我们从最近的上游或下游基因的转录起始位点建模一个归一化的整合距离。从这个模型中，我们得到一个简单而直接的测试程序来估计如何一个给定的基因的转录起始位点可能会或可能不会吸引整合事件。我们的方法克服了不同的基因长度，基因方向和基因密度的问题，这往往是关键的分析整合距离转录起始位点。该方法是测试从人类造血干/祖细胞检索的真实的实验数据。
Retroviral vectors are widely used in gene therapy to introduce therapeutic genes into patients' cells, since, once delivered to the nucleus, the genes of interest are stably inserted (integrated) into the target cell genome. There is now compelling evidence that integration of retroviral vectors follows non-random patterns in mammalian genome, with a preference for active genes and regulatory regions. In particular, Moloney Leukemia Virus (MLV)–derived vectors show a tendency to integrate in the proximity of the transcription start site (TSS) of genes, occasionally resulting in the deregulation of gene expression and, where proto-oncogenes are targeted, in tumor initiation. This has drawn the attention of the scientific community to the molecular determinants of the retroviral integration process as well as to statistical methods to evaluate the genome-wide distribution of integration sites. In recent approaches, the observed distribution of MLV integration distances (IDs) from the TSS of the nearest gene is assumed to be non-random by empirical comparison with a random distribution generated by computational simulation procedures. To provide a statistical procedure to test the randomness of the retroviral insertion pattern, we propose a probability model (Beta distribution) based on IDs between two consecutive genes. We apply the procedure to a set of 595 unique MLV insertion sites retrieved from human hematopoietic stem/progenitor cells. The statistical goodness of fit test shows the suitability of this distribution to the observed data. Our statistical analysis confirms the preference of MLV-based vectors to integrate in promoter-proximal regions. Understanding how retroviral vectors (such as Moloney Leukemia Virus–based vectors) integrate in the human genome became a major safety issue in the field of gene therapy, since a concrete risk of developing tumors associated with the integration process was assessed in the clinical setting. Moloney Leukemia Virus–based vectors are apparently characterized by a non-random integration pattern, with a preference for the vicinities of active gene transcription start sites. We approach the problem of non-random retroviral integration from a probabilistic point of view. We model a normalized integration distance from the transcription start site of the nearest upstream or downstream gene. From this model, we derive a simple and straightforward testing procedure to estimate how the transcription start site of a given gene may or may not attract integration events. Our approach overcomes the issues of different gene length, gene orientation, and gene density, which are often critical in analyzing integration distances from transcription start sites. The approach is tested on real experimental data retrieved from human hematopoietic stem/progenitor cells.
登录
查看更多内容
影响因子：
4.3
作者：
Needham CJ;Bradford JR;Bulpitt AJ;Westhead DR
通讯作者：
Westhead DR
影响因子：
9.8
作者：
Hematti P;Hong BK;Ferguson C;Adler R;Hanawa H;Sellers S;Holt IE;Eckfeldt CE;Sharma Y;Schmidt M;von Kalle C;Persons DA;Billings EM;Verfaillie CM;Nienhuis AW;Wolfsberg TG;Dunbar CE;Calmels B
通讯作者：
Calmels B
影响因子：
46.9
作者：
Needham, CJ;Bradford, JR;Westhead, DR
通讯作者：
Westhead, DR
影响因子：
20.3
作者：
Modlich, Ute;Bohne, Jens;Baum, Christopher
通讯作者：
Baum, Christopher
影响因子：
56.9
作者：
Wu, XL;Li, Y;Burgess, SM
通讯作者：
Burgess, SM