Identification of co-localised transcription factors based on paired motifs analysis.

IF 1.9 4区 生物学 Q4 CELL BIOLOGY IET Systems Biology Pub Date : 2024-11-26 DOI:10.1049/syb2.12104
Li Liu, Lu Han, Kaiyuan Han, Zheng Zhang, Haojiang Zhang, Lirong Zhang
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Abstract

The interaction of transcription factors (TFs) with DNA precisely regulates gene transcription. In mammalian cells, thousands of TFs often interact with DNA cis-regulatory elements in a combinatorial manner rather than act alone. The identification of cooperativity between TFs can help to explore the mechanism of transcriptional regulation. However, little is known about the cooperative patterns of TFs in the genome. To identify which TFs prefer co-localisation, the authors conducted a paired motif analysis in the accessible regions of the human genome based on the Poisson background model. Especially, the authors distinguish the cooperative binding TFs and the competitive binding TFs according to the distance between TF motifs. In the K562 cell line, the authors find that TFs from a same family are always competing the same binding sites, such as FOS_JUN family, whereas KLF family TFs show significant cooperative binding in the adjacency region. Furthermore, the comparative analysis across 16 human cell lines indicates that most TF combination patterns are conserved, but there are still some cell-line-specific patterns. Finally, in human prostate cancer cells (PC-3) and human prostate normal cells (RWPE-2), the authors investigate the specific TF combination patterns in the disease cell and normal cell. The results show that the cooperative binding TF pairs shared by PC-3 and RWPE-2 account for over 90%. Simultaneously, the authors also identify 26 specific TF combination pairs in PC-3 cancer cells.

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基于配对图案分析鉴定共定位转录因子
转录因子(TFs)与 DNA 的相互作用可精确调控基因转录。在哺乳动物细胞中,数以千计的转录因子往往以组合方式与 DNA 顺式调节元件相互作用,而不是单独发挥作用。识别 TF 之间的协同作用有助于探索转录调控机制。然而,人们对基因组中 TFs 的合作模式知之甚少。为了确定哪些 TFs 更喜欢共定位,作者基于泊松背景模型对人类基因组的可访问区域进行了配对图案分析。特别是,作者根据TF基序之间的距离区分了合作结合TF和竞争结合TF。在 K562 细胞系中,作者发现同一家族的 TFs 总是竞争相同的结合位点,如 FOS_JUN 家族,而 KLF 家族 TFs 则在邻接区表现出明显的合作结合。此外,对 16 个人类细胞系的比较分析表明,大多数 TF 组合模式是保守的,但仍有一些细胞系特有的模式。最后,作者在人类前列腺癌细胞(PC-3)和人类前列腺正常细胞(RWPE-2)中研究了疾病细胞和正常细胞中特定的 TF 组合模式。结果显示,PC-3 和 RWPE-2 共享的合作结合 TF 对占 90% 以上。同时,作者还在 PC-3 癌细胞中发现了 26 对特异性 TF 组合。
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来源期刊
IET Systems Biology
IET Systems Biology 生物-数学与计算生物学
CiteScore
4.20
自引率
4.30%
发文量
17
审稿时长
>12 weeks
期刊介绍: IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells. The scope includes the following topics: Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.
期刊最新文献
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