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外显子跳跃事件中组蛋白修饰的组合模式。

Combinatorial Pattern of Histone Modifications in Exon Skipping Event.

作者信息

Chen Wei, Song Xiaoming, Lin Hao

机构信息

Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, China.

Center for Genomics and Computational Biology, School of Life Sciences, North China University of Science and Technology, Tangshan, China.

出版信息

Front Genet. 2019 Feb 18;10:122. doi: 10.3389/fgene.2019.00122. eCollection 2019.

DOI:10.3389/fgene.2019.00122
PMID:30833963
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6387913/
Abstract

Histone modifications are associated with alternative splicing. It has been suggested that histone modifications act in combinational patterns in gene expression regulation. However, how they interact with each other and what is their casual relationships in the process of RNA splicing remain unclear. In this study, the combinatorial patterns of 38 kinds of histone modifications in the exon skipping event of the CD4 T cell were analyzed by constructing Bayesian networks. Distinct combinatorial patterns of histone modifications that illustrating their casual relationships were observed in excluded/included exons and the surrounding intronic regions. The Bayesian networks also indicate that some histone modifications directly correlate with RNA splicing. We anticipate that this work could provide novel insights into the effects of histone modifications on RNA splicing regulation.

摘要

组蛋白修饰与可变剪接相关。有人提出，组蛋白修饰在基因表达调控中以组合模式起作用。然而，它们如何相互作用以及在RNA剪接过程中的因果关系仍不清楚。在本研究中，通过构建贝叶斯网络分析了CD4 T细胞外显子跳跃事件中38种组蛋白修饰的组合模式。在排除/包含的外显子和周围的内含子区域中观察到了说明其因果关系的不同组蛋白修饰组合模式。贝叶斯网络还表明，一些组蛋白修饰与RNA剪接直接相关。我们预计这项工作可以为组蛋白修饰对RNA剪接调控的影响提供新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2cf/6387913/9830d1c58c1d/fgene-10-00122-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2cf/6387913/572880590141/fgene-10-00122-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2cf/6387913/ba2fcde35ee3/fgene-10-00122-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2cf/6387913/9830d1c58c1d/fgene-10-00122-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2cf/6387913/572880590141/fgene-10-00122-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2cf/6387913/ba2fcde35ee3/fgene-10-00122-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2cf/6387913/9830d1c58c1d/fgene-10-00122-g003.jpg

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iRNA(m6A)-PseDNC: Identifying N-methyladenosine sites using pseudo dinucleotide composition.基于伪二核苷酸组成的 m6A-psiDNC：识别 N6-甲基腺苷位点。
Anal Biochem. 2018 Nov 15;561-562:59-65. doi: 10.1016/j.ab.2018.09.002. Epub 2018 Sep 8.
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4mCPred: machine learning methods for DNA N4-methylcytosine sites prediction.
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Pediatr Res. 2022 Nov;92(5):1299-1308. doi: 10.1038/s41390-022-01962-8. Epub 2022 Feb 4.
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Bioinformatics. 2017 Nov 15;33(22):3518-3523. doi: 10.1093/bioinformatics/btx479.
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