γ-TRIS：一种用于全面鉴定载体基因组插入位点的图算法。
γ-TRIS: a graph-algorithm for comprehensive identification of vector genomic insertion sites.
机构信息
San Raffaele Telethon Institute for Gene Therapy (SR-Tiget), IRCCS San Raffaele Scientific Institute, via Olgettina 60, 20132, Milan, Italy.
Università degli Studi di Milano Bicocca, Dipartimento di Informatica Sistemistica e Comunicazione (DiSCO), Viale Sarca, 336, 20126, Milano, Italy.
出版信息
Bioinformatics. 2020 Mar 1;36(5):1622-1624. doi: 10.1093/bioinformatics/btz747.
SUMMARY
Retroviruses and their vector derivatives integrate semi-randomly in the genome of host cells and are inherited by their progeny as stable genetic marks. The retrieval and mapping of the sequences flanking the virus-host DNA junctions allows the identification of insertion sites in gene therapy or virally infected patients, essential for monitoring the evolution of genetically modified cells in vivo. However, since ∼30% of insertions land in low complexity or repetitive regions of the host cell genome, they cannot be correctly assigned and are currently discarded, limiting the accuracy and predictive power of clonal tracking studies. Here, we present γ-TRIS, a new graph-based genome-free alignment tool for identifying insertion sites even if embedded in low complexity regions. By using γ-TRIS to reanalyze clinical studies, we observed improvements in clonal quantification and tracking.
AVAILABILITY AND IMPLEMENTATION
Source code at https://bitbucket.org/bereste/g-tris.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
摘要
逆转录病毒及其载体衍生物会以半随机的方式整合到宿主细胞的基因组中，并作为稳定的遗传标记遗传给它们的后代。检索和绘制病毒-宿主 DNA 连接处侧翼的序列，可以确定基因治疗或病毒感染患者中的插入位点，这对于监测体内基因修饰细胞的演变至关重要。然而，由于大约 30%的插入发生在宿主细胞基因组的低复杂度或重复区域，因此无法正确分配这些插入，目前这些插入被丢弃，从而限制了克隆追踪研究的准确性和预测能力。在这里，我们提出了一种新的基于图的无基因组比对工具 γ-TRIS，即使插入位于低复杂度区域，它也可以用于识别插入位点。通过使用 γ-TRIS 重新分析临床研究，我们观察到克隆定量和跟踪的改进。
可用性和实现
可在 https://bitbucket.org/bereste/g-tris 上获取源代码。
补充信息
补充数据可在“Bioinformatics”在线获取。
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