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解码复杂性在生物分子识别的DNAi-动机与微阵列的解码复杂性

Kamyar Yazdani1, Srinath Seshadri1, Desiree Tillo2

  • 1Chemical Biology Laboratory, National Cancer Institute, 1050 Boyle St., Frederick, MD 21702, USA.

Nucleic acids research
|November 14, 2023
PubMed

Insights

这项研究揭示了蛋白质和小分子如何与DNAi-motifs (iMs) 结合. hnRNP K 蛋白选择性地识别了多种不同的 iM 序列,这表明它在基因调节中的作用.

科学领域:

  • 基因组学就是基因组学.
  • 分子生物学分子生物学
  • 生物化学 生化学

背景情况:

  • DNA i-motifs (iMs) 是在基因组中发现的非正规的C丰富结构.
  • 蛋白质和小分子对IM识别的理解是有限的.

研究的目的:

  • 综合调查生物分子与基因组iM序列的结合概况.
  • 为了确定IM-结合蛋白和小分子的特定识别模式.

主要方法:

  • 一个含有10976个基因组iM序列的DNA微阵列的设计.
  • 使用iMab抗体查四种iM结合蛋白和线粒的结合概况.
  • 微阵列选条件的优化 (pH 6.5,5% BSA缓冲区).

主要成果:

  • hnRNP K 广泛地识别了各种IMs,有利于特定的细胞因子重复长度和循环大小.
  • 对于 hnRNP K 的数组绑定数据与公开的 ChIP-Seq 数据集相关联.
  • 其他蛋白质的结合较弱或偏好G-四重复 (G4) 序列.
  • 米托克桑连结了IMs和G4s,这表明存在一个间隔机制.

结论:

  • hnRNP K可能通过iMs在体内调节基因表达.
  • hnRNP A1和ASF/SF2表现出更有选择性的绑定偏好.
  • DNA微阵列方法为研究iM识别提供了一个全面的方法.
抽象的

No abstract available in PubMed .

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