基因变异的3D基因组图谱及其在癌症中的病理影响
Li Tang1, Matthew C Hill2,3, Mingxing He1
1School of Computer Science and Engineering, Central South University, Changsha, 410083, China.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|March 26, 2025
概括
这项研究全面列出了遗传异常及其对3D基因组的影响,揭示了这些变化如何影响基因表达和癌症发展. 一个名为3DFunc的新工具有助于识别癌症中的病原性变异基因相互作用.
科学领域:
- 基因组学就是基因组学.
- 癌症生物学 癌症生物学
- 结构生物学 结构生物学
背景情况:
- 细胞基因组的3D组织对于细胞功能和发育至关重要.
- 遗传异常可以破坏这种架构,导致瘤发生.
- 现有的研究往往缺乏整体观点,专注于有限的突变类型或结构层面.
研究的目的:
- 系统地列出从染色体到核酸的病态基因组变化.
- 分析这些异常对3D基因组组织和基因表达的影响.
- 开发计算工具,在3D基因组背景下评估变异性病原性.
主要方法:
- 编目了10789个染色体间转位 (ICTs),18863个结构变异 (SVs) 和162769个单核酸多态 (SNP).
- 对3D基因组相互作用和基因表达变化的多层分析.
- 开发3DFunc算法,用于评估癌症中变异基因对的致病性.
- 介绍3DGAtlas资源用于3D基因组探索.
主要成果:
- 只有不到10%的ICT通过强烈的3D交互破坏了领土;最小的SV影响了区间或拓相关的域,但却显著改变了基因表达.
- 致病性SNP通常在3D基因组内表现出减少的相互作用.
- 3DFunc确定了IGHV3-23在慢性淋巴细胞白血病中的作用,以及与DEFA3相互作用的三个SNP.
- 3DGAtlas提供了一个可访问的3D基因组地图.
结论:
- 遗传异常对3D基因组结构有不同的影响,甚至像SNP这样的微妙变化也会影响基因表达.
- 3DFunc算法和3DGAtlas资源为了解癌症遗传变异的病理后果提供了新的方法.
- 这一全面的分析为癌症基因组学研究和3D基因组组织研究提供了宝贵的资源.
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