Cross-cellular analysis of chromatin accessibility markers H3K4me3 and DNase in the context of detecting cell-identity genes: An "all-or-nothing" approach.

IF 0.7 4区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY Journal of Bioinformatics and Computational Biology Pub Date : 2025-02-01 DOI:10.1142/S0219720025400025
Boon How Low, Kaushal Krishna Kaliskar, Stefano Perna, Bernett Lee
{"title":"Cross-cellular analysis of chromatin accessibility markers H3K4me3 and DNase in the context of detecting cell-identity genes: An \"all-or-nothing\" approach.","authors":"Boon How Low, Kaushal Krishna Kaliskar, Stefano Perna, Bernett Lee","doi":"10.1142/S0219720025400025","DOIUrl":null,"url":null,"abstract":"<p><p>Cell identity is often associated to a subset of highly-expressed genes that define the cell processes, as opposed to essential genes that are always active. Cell-specific genes may be defined in opposition to essential genes, or via experimental means. Detection of said cell-specific genes is often a primary goal in the study of novel biosamples. Chromatin accessibility markers (such as DNase and H3K4me3) help identify actively transcribed genes, but data can be difficult to come by for entirely novel biosamples. In this study, we investigate the possibility of associating the cell-specificity status of genes with chromatin accessibility markers from different cell lines, and we suggest that the number of cell lines in which a gene is found to be marked by DNase/H3K4me3 is predictive of the essentiality status itself. We define a measure called the Cross-cellular Chromatin Openness (CCO) level, and show that it is associated with the essentiality status using two differentiation experiments. We then compare the CCO-level predictive power to existing scRNA-Seq and bulk RNA-Seq methods, showing it has good concordance when applicable.</p>","PeriodicalId":48910,"journal":{"name":"Journal of Bioinformatics and Computational Biology","volume":"23 1","pages":"2540002"},"PeriodicalIF":0.7000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Bioinformatics and Computational Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1142/S0219720025400025","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Cell identity is often associated to a subset of highly-expressed genes that define the cell processes, as opposed to essential genes that are always active. Cell-specific genes may be defined in opposition to essential genes, or via experimental means. Detection of said cell-specific genes is often a primary goal in the study of novel biosamples. Chromatin accessibility markers (such as DNase and H3K4me3) help identify actively transcribed genes, but data can be difficult to come by for entirely novel biosamples. In this study, we investigate the possibility of associating the cell-specificity status of genes with chromatin accessibility markers from different cell lines, and we suggest that the number of cell lines in which a gene is found to be marked by DNase/H3K4me3 is predictive of the essentiality status itself. We define a measure called the Cross-cellular Chromatin Openness (CCO) level, and show that it is associated with the essentiality status using two differentiation experiments. We then compare the CCO-level predictive power to existing scRNA-Seq and bulk RNA-Seq methods, showing it has good concordance when applicable.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
在检测细胞特征基因的背景下对染色质可及性标记物 H3K4me3 和 DNase 进行跨细胞分析:一种 "全有或全无 "的方法
细胞身份通常与定义细胞过程的高表达基因子集相关,而不是始终活跃的必需基因。细胞特异性基因可以相对于基本基因来定义,或者通过实验手段来定义。检测细胞特异性基因通常是研究新型生物样品的主要目标。染色质可接近性标记(如DNase和H3K4me3)有助于识别活性转录基因,但对于全新的生物样本来说,数据很难获得。在这项研究中,我们研究了将基因的细胞特异性状态与来自不同细胞系的染色质可及性标记联系起来的可能性,我们认为dna酶/H3K4me3标记的基因在细胞系中的数量可以预测其本质状态本身。我们定义了一种称为跨细胞染色质开放(CCO)水平的测量,并通过两个分化实验表明它与必要性状态相关。然后,我们将cco水平的预测能力与现有的scRNA-Seq和散装RNA-Seq方法进行了比较,表明它在适用时具有良好的一致性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Journal of Bioinformatics and Computational Biology
Journal of Bioinformatics and Computational Biology MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
2.10
自引率
0.00%
发文量
57
期刊介绍: The Journal of Bioinformatics and Computational Biology aims to publish high quality, original research articles, expository tutorial papers and review papers as well as short, critical comments on technical issues associated with the analysis of cellular information. The research papers will be technical presentations of new assertions, discoveries and tools, intended for a narrower specialist community. The tutorials, reviews and critical commentary will be targeted at a broader readership of biologists who are interested in using computers but are not knowledgeable about scientific computing, and equally, computer scientists who have an interest in biology but are not familiar with current thrusts nor the language of biology. Such carefully chosen tutorials and articles should greatly accelerate the rate of entry of these new creative scientists into the field.
期刊最新文献
Predicting ncRNA-Protein interactions with a graph attention model exploiting personalized subgraphs. Early lifespan prediction in Caenorhabditis elegans via contrastive learning and channel attention. Study of the mechanism of step-by-step interaction of viral proteins during replication and transcription. Mendelian randomization and AlphaFold3 analysis suggest putative causal plasma proteins in graves' disease. PLMABFW: A deep learning framework for predicting Antibody-Antigen interactions using protein language model.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1