确定和推断真核转录因子序列特异性的结论
Matthew T Weirauch1, Ally Yang2, Mihai Albu2
1Center for Autoimmune Genomics and Etiology (CAGE) and Divisions of Biomedical Informatics and Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA; Banting and Best Department of Medical Research and Donnelly Centre, University of Toronto, Toronto ON M5S 3E1, Canada.
Cell
|September 13, 2014
概括
研究人员在真核生物中为超过1000个转录因子 (TF) 绘制了DNA序列偏好. 这扩大了对TF结合动机的了解,有助于理解基因调节和疾病关联.
科学领域:
- 基因组学就是基因组学.
- 分子生物学分子生物学
- 生物信息学是一种生物信息学.
背景情况:
- 转录因子 (TF) DNA序列偏好对于基因调节至关重要,但已知只有很小一部分真核细胞的TF.
- 了解TF绑定对于破译复杂的转录网络至关重要.
研究的目的:
- 确定大量真核细胞TF的DNA序列偏好.
- 开发一种方法来推断TF对更广泛的TF的约束动机.
- 为绘制真核细胞转录网络的绘制创造一个有价值的资源.
主要方法:
- 确定了来自131种不同的真核生物的1000多个TF的DNA序列偏好,涵盖54个DNA结合域 (DBD) 类.
- 利用密切相关的DBDs的序列相似性来推断TF绑定动机.
- 分析了染色体免疫沉测序 (ChIP-seq) 峰值和促进体区域中TF结合位点的丰富.
主要成果:
- 建立了对>1,000个TF的DNA序列偏好,显著扩展了已知的TF动图景观.
- 开发了一种基于DBD相似性的方法来推断大约34%已知或预测的真核细胞TF的动机.
- 监管区域中测量和推断的TF结合部位的丰富性已被证明,并通过与疾病相关的SNP确定了TF结合部位的改变.
结论:
- 这项研究提供了一个全面的资源TF DNA序列偏好和结合动机跨真核细胞.
- 这些发现可以更准确地预测TF结合,并促进对基因调节的研究.
- 开发的图案库是识别受遗传变异影响的TFs的强大工具,包括人类疾病风险等位基因.
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