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基于配对基序分析鉴定共定位转录因子。

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

作者信息

Liu Li, Han Lu, Han Kaiyuan, Zhang Zheng, Zhang Haojiang, Zhang Lirong

机构信息

Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China.

School of Physical Science and Technology, Inner Mongolia University, Hohhot, China.

出版信息

IET Syst Biol. 2024 Dec;18(6):238-249. doi: 10.1049/syb2.12104. Epub 2024 Nov 26.

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.

摘要

转录因子(TFs)与DNA的相互作用精确地调控基因转录。在哺乳动物细胞中,数千种转录因子通常以组合方式与DNA顺式调控元件相互作用,而非单独发挥作用。确定转录因子之间的协同作用有助于探索转录调控机制。然而,对于基因组中转录因子的协同模式却知之甚少。为了确定哪些转录因子倾向于共定位,作者基于泊松背景模型在人类基因组的可及区域进行了配对基序分析。特别地,作者根据转录因子基序之间的距离区分协同结合的转录因子和竞争性结合的转录因子。在K562细胞系中,作者发现来自同一家族的转录因子总是竞争相同的结合位点,如FOS_JUN家族,而KLF家族转录因子在相邻区域显示出显著的协同结合。此外,对16种人类细胞系的比较分析表明,大多数转录因子组合模式是保守的,但仍存在一些细胞系特异性模式。最后,在人前列腺癌细胞(PC-3)和人前列腺正常细胞(RWPE-2)中,作者研究了疾病细胞和正常细胞中的特定转录因子组合模式。结果表明,PC-3和RWPE-2共有的协同结合转录因子对占比超过90%。同时,作者还在PC-3癌细胞中鉴定出26个特定的转录因子组合对。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ce2/11665839/0b9dcca87be0/SYB2-18-238-g001.jpg

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