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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
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相关实验视频

Updated: Sep 14, 2025

Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing
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结合基于面板和基于全转录基因组的基因融合检测,通过长读测序测序.

Karleena Rybacki1, Feng Xu2, Hannah M Deutsch3

  • 1Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA; Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, USA.

Cell reports methods
|July 22, 2025
PubMed
概括

这项研究引入了一个新的工作流程,用于检测癌症中的基因融合 (GF),使用长读序列. 该方法结合了目标面板和全转录组分析,以更快,更全面地识别GF.

关键词:
CP:癌症生物学 癌症生物学科普:遗传学 遗传学牛津纳米孔技术公司计算管道的计算管道基因融合 基因融合长时间阅读序列排序.转录组分析转录组分析

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科学领域:

  • 基因组学就是基因组学.
  • 癌症研究 癌症研究
  • 生物信息学是一种生物信息学.

背景情况:

  • 基因融合 (GFs) 是各种癌症的关键驱动因素.
  • 准确检测GF对于有针对性的治疗至关重要.
  • 目前的方法可能在灵敏度和范围上有局限性.

研究的目的:

  • 开发和验证一个全面的基因融合检测和分析工作流程.
  • 结合针对性的基于面板和全转录组的长读序列测序,以增强GF发现.
  • 改善处理时间,并在具有挑战性的癌症病例中识别新型GF.

主要方法:

  • 适应一个短读癌症融合面板的长读测序 (牛津纳米孔技术).
  • 基于面板的长读序列的应用,用于已知的GF检测.
  • 对面板阴性质瘤样本的全转录组长读测序分析.
  • 为GF分析开发量身定制的计算管道.

主要成果:

  • 使用适应面板和长读序列,成功检测已知的GF,缩短了周转时间.
  • 在24个面板阴性质瘤样本中识别了20个新型候选GF.
  • 对所有已识别的候选GF进行实验验证.
  • 证明了长读序列用于GF检测的兼容性.

结论:

  • 提出的工作流集成基于面板和全转录组的长读序列为全面的GF检测.
  • 这种方法可以快速准确地识别癌症中已知和新型基因融合.
  • 这种工作流在临床上具有挑战性的病例中是有效的,包括面板负样本.