Abstract 241: An efficient probe design algorithm for direct fusion targeting from RNA

C. Magnan, S. Rivera, F. Lopez-Diaz, Chenhui Ou, Kenneth B. Thomas, Hyunjun Nam, L. Weiss, Segun Jung, V. Funari
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Abstract

Background: The use of sequencing technologies to detect gene fusions (GFs) from RNA shows promising results for the future of cancer diagnosis and treatment. Major obstacles for this approach include target design and lack of well-curated databases of RNA breakpoints. Currently, off-the-shelf designs include full transcript targeting that results in massive and costly amounts of data. Directly targeting the known GFs from RNA by designing probes targeting the fusion junction sequence is studied here as an alternative to whole-exome sequencing (WES). We present notably a novel algorithm capable of designing the probes to accurately target the desired fusions from RNA. Methods: For a given GF detected either from DNA or from RNA, the algorithm is as follows: (1) Collect gene and isoform information for both partners from seven public databases; (2) For each candidate pair of isoforms, locate where the breakpoints will be observed and assign a score based on various criteria such as sequence completion, coding information, transcript support level, % identity with and % visible on hg38; (3) Select the top scoring pair of transcripts and extract the chimeric probe sequence. Two sets of probes extracted with this protocol targeting 524 and 1632 known GFs were synthetized and tested on several samples (Table 1). The Agilent SureSelect Human All Exon V6 capture kit was used to compare targeting efficiency against WES. Results: Targeted enrichment of a SeraSeq control showed a 5 to 20 fold increase in supporting evidence over WES. On 10 clinical samples, we observed 10-30x increase in supporting reads. A higher sensitivity is observed in both cases. Conclusion: We developed a novel algorithm capable of accurately identifying the most likely location of an RNA fusion junction and generating the probe sequences for oligo synthesis. This method not only enriches for more supporting data but also reduces the associated costs. Citation Format: Christophe N. Magnan, Steven P. Rivera, Fernando J. Lopez-Diaz, Chen-Yin Ou, Kenneth B. Thomas, Hyunjun Nam, Lawrence M. Weiss, Segun C. Jung, Vincent A. Funari. An efficient probe design algorithm for direct fusion targeting from RNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 241.
基于RNA直接融合靶向的高效探针设计算法
背景:利用测序技术从RNA中检测基因融合(GFs),在未来的癌症诊断和治疗中显示出有希望的结果。这种方法的主要障碍包括目标设计和缺乏精心策划的RNA断点数据库。目前,现成的设计包括完整的转录目标,导致大量和昂贵的数据量。本文研究了通过设计靶向融合连接序列的探针直接靶向RNA中的已知基因,作为全外显子组测序(WES)的替代方法。值得注意的是,我们提出了一种新颖的算法,能够设计探针来准确地靶向RNA的所需融合。方法:对于从DNA或RNA中检测到的给定GF,算法如下:(1)从7个公共数据库中收集伴侣双方的基因和同工异构体信息;(2)对每一对候选同工异构体,根据序列完成度、编码信息、转录支持水平、与hg38的同源性%、在hg38上的可见性%等标准,定位观察到断点的位置,并给出评分;(3)选择得分最高的转录本对,提取嵌合探针序列。用该方案提取的两组探针分别靶向524和1632个已知基因,并在几个样品上进行了测试(表1)。使用Agilent SureSelect Human All Exon V6捕获试剂盒与WES比较靶向效率。结果:SeraSeq对照的靶向富集显示支持证据比WES增加5至20倍。在10个临床样本中,我们观察到支持读数增加了10-30倍。在这两种情况下观察到更高的灵敏度。结论:我们开发了一种新的算法,能够准确地识别RNA融合连接的最可能位置,并生成用于寡核苷酸合成的探针序列。该方法不仅丰富了更多的支持数据,而且降低了相关成本。引用格式:Christophe N. Magnan, Steven P. Rivera, Fernando J. Lopez-Diaz, Chen-Yin Ou, Kenneth B. Thomas, Hyunjun Nam, Lawrence M. Weiss, Segun C. Jung, Vincent A. Funari一种有效的RNA直接融合靶向探针设计算法[摘要]。见:美国癌症研究协会2021年年会论文集;2021年4月10日至15日和5月17日至21日。费城(PA): AACR;癌症杂志,2021;81(13 -增刊):摘要第241期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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