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序列表达方法用于识别P53和cMYC驱动疾病中的病因性非编码DNA变异

Katherine Kin¹, Shounak Bhogale², Lisha Zhu³

¹Department of Diagnostic and Biomedical Sciences, Center for Craniofacial Research, School of Dentistry, University of Texas Health Science Center at Houston, 7500 Cambridge St, Houston, TX 77054, United States.

Human molecular genetics

|July 17, 2024

概括

识别与疾病相关的非编码DNA变异具有挑战性. 这项研究揭示了P53和cMYC对DNA的结合如何影响基因表达,有助于从基因组数据中预测疾病风险.

科学领域:

基因组学就是基因组学.
分子生物学分子生物学
计算生物学计算生物学

背景情况:

在疾病风险预测方面,区分常见疾病的有害非编码DNA变异仍然是一个重大挑战.
了解像P53和cMYC这样的转录因子在共享的目标基因上的相互作用,对于破译基因调节至关重要.

研究的目的:

调查P53和cMYC占用和竞争性结合对共同目标基因的意义.
开发一种计算方法来过与常见疾病相关的病因学非编码变异.

主要方法:

对胚胎干细胞中P53和cMYC的公开可用的ChIP-seq数据的分析.
在U2OS和Raji细胞中进行ChIP-seq分析 (未经处理和经过多克索鲁比辛治疗),以评估动态结合变化.
RNA-seq分析以评估在共同占用区域附近的mRNA水平变化.
计算模式匹配方法与记者基因表达和GTEx数据相关联结合亲和力变化.

主要成果:

在胚胎干细胞中的344-366个区域中确定了P53和cMYC的保守共存,每个区域平均有两个cis重叠动机 (CisOMs).
在多克索鲁比治疗后,观察到共同占用区域 (16到922) 的动态变化和cMYC的P53替代.
在CisOMs中改变的P53/cMYC结合亲和力和记者基因表达和GTEx衍生基因表达的变化之间发现了显著的相关性.
报告的mRNA水平的变化 ~187基因附近的共同占有地区.

结论:

P53和cMYC在目标基因上表现出保守的共同占用,由细胞条件影响的动态结合变化.
在cis重叠基因内转录因子结合亲缘关系的变化显著影响基因表达.
这项研究为一种可通用的方法提供了基础,用于过与常见疾病相关的非编码变异.

关键词:

在Cis中重叠的图案.计算建模计算建模非编码DNA变体的非编码DNA变体这是一种原始原基因.这是一种瘤抑制剂.

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