• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

BINDER通过全面表征共有TAD边界实现了对分层TAD的准确识别。

BINDER achieves accurate identification of hierarchical TADs by comprehensively characterizing consensus TAD boundaries.

作者信息

Liu Yangyang, Liu Bingqiang, Liu Juntao

机构信息

School of Mathematics and Statistics, Shandong University (Weihai), Weihai, 264209, China.

School of Mathematics, Shandong University, Jinan, 250100, China

出版信息

Genome Res. 2025 May 2;35(5):1194-1208. doi: 10.1101/gr.279647.124.

DOI:10.1101/gr.279647.124
PMID:40097199
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12047538/
Abstract

As crucial chromatin structures, hierarchical TADs play important roles in epigenetic organization, transcriptional activity, gene regulation, and cell differentiation. Currently, it remains a highly challenging task to accurately identify hierarchical TADs in a computational manner. The key bottleneck for existing TAD callers lies in the difficulty in the prediction of precise TAD boundaries. We solve this problem by introducing a novel algorithm, called BINDER, which conducts a boundary consensus approach, and then precisely locate hierarchical TAD boundaries by developing a multifaceted boundary characterization strategy. In comparison with other leading TAD callers, BINDER shows significant improvement in identifying hierarchical TADs and exhibits the strongest robustness with ultrasparse data, which supports the importance of boundary identification in calling hierarchical TADs. Applying BINDER to experimental data and mouse hematopoietic cases, we find that the hierarchical TADs identified by BINDER show strong biological relevance in their epigenetic organization, transcriptional activity, DNA motifs, and coregulation during cellular differentiation. BINDER discovers differences in the enrichment of two specific transcription factors, CHD1 and CHD2, at TAD boundaries with different hierarchies. It also observes variations in the gene expression of TADs with different hierarchies during cellular differentiation.

摘要

作为关键的染色质结构，层级拓扑相关结构域（TADs）在表观遗传组织、转录活性、基因调控和细胞分化中发挥着重要作用。目前，以计算方式准确识别层级TADs仍然是一项极具挑战性的任务。现有TAD调用工具的关键瓶颈在于精确预测TAD边界存在困难。我们通过引入一种名为BINDER的新算法解决了这个问题，该算法采用边界共识方法，然后通过开发多方面的边界特征化策略来精确定位层级TAD边界。与其他领先的TAD调用工具相比，BINDER在识别层级TADs方面有显著改进，并且在超稀疏数据下表现出最强的稳健性，这支持了边界识别在调用层级TADs中的重要性。将BINDER应用于实验数据和小鼠造血案例中，我们发现BINDER识别出的层级TADs在其表观遗传组织、转录活性、DNA基序以及细胞分化过程中的共调控方面显示出很强的生物学相关性。BINDER发现了两种特定转录因子CHD1和CHD2在不同层级的TAD边界处富集的差异。它还观察到在细胞分化过程中不同层级的TADs基因表达的变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6435/12047538/2a806de05e73/1194f07.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6435/12047538/297420f8ad27/1194f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6435/12047538/2d25367ce46e/1194f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6435/12047538/46c7d4adc967/1194f03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6435/12047538/1c2c672d9ff5/1194f04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6435/12047538/3ed85cf23dec/1194f05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6435/12047538/247d10f71302/1194f06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6435/12047538/2a806de05e73/1194f07.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6435/12047538/297420f8ad27/1194f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6435/12047538/2d25367ce46e/1194f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6435/12047538/46c7d4adc967/1194f03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6435/12047538/1c2c672d9ff5/1194f04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6435/12047538/3ed85cf23dec/1194f05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6435/12047538/247d10f71302/1194f06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6435/12047538/2a806de05e73/1194f07.jpg

相似文献

1
BINDER achieves accurate identification of hierarchical TADs by comprehensively characterizing consensus TAD boundaries.BINDER通过全面表征共有TAD边界实现了对分层TAD的准确识别。
Genome Res. 2025 May 2;35(5):1194-1208. doi: 10.1101/gr.279647.124.
2
MrTADFinder: A network modularity based approach to identify topologically associating domains in multiple resolutions.MrTADFinder：一种基于网络模块性的方法，用于在多个分辨率下识别拓扑关联结构域。
PLoS Comput Biol. 2017 Jul 24;13(7):e1005647. doi: 10.1371/journal.pcbi.1005647. eCollection 2017 Jul.
3
SpectralTAD: an R package for defining a hierarchy of topologically associated domains using spectral clustering.SpectralTAD：一个使用谱聚类定义层次结构拓扑关联域的 R 包。
BMC Bioinformatics. 2020 Jul 20;21(1):319. doi: 10.1186/s12859-020-03652-w.
4
deepTAD: an approach for identifying topologically associated domains based on convolutional neural network and transformer model.深度TAD：一种基于卷积神经网络和Transformer模型识别拓扑相关结构域的方法。
Brief Bioinform. 2025 Mar 4;26(2). doi: 10.1093/bib/bbaf127.
5
5C analysis of the Epidermal Differentiation Complex locus reveals distinct chromatin interaction networks between gene-rich and gene-poor TADs in skin epithelial cells.表皮分化复合体基因座的5C分析揭示了皮肤上皮细胞中基因丰富和基因贫乏的拓扑相关结构域之间不同的染色质相互作用网络。
PLoS Genet. 2017 Sep 1;13(9):e1006966. doi: 10.1371/journal.pgen.1006966. eCollection 2017 Sep.
6
TAD boundary and strength prediction by integrating sequence and epigenetic profile information.通过整合序列和表观遗传特征信息来预测 TAD 边界和强度。
Brief Bioinform. 2021 Sep 2;22(5). doi: 10.1093/bib/bbab139.
7
A Comparison of Topologically Associating Domain Callers Based on Hi-C Data.基于 Hi-C 数据的拓扑关联域调用器比较。
IEEE/ACM Trans Comput Biol Bioinform. 2023 Jan-Feb;20(1):15-29. doi: 10.1109/TCBB.2022.3147805. Epub 2023 Feb 3.
8
A comparison of topologically associating domain callers over mammals at high resolution.在高分辨率下比较哺乳动物的拓扑关联结构域调用器。
BMC Bioinformatics. 2022 Apr 12;23(1):127. doi: 10.1186/s12859-022-04674-2.
9
Identification of hierarchical chromatin domains.分层染色质结构域的鉴定。
Bioinformatics. 2016 Jun 1;32(11):1601-9. doi: 10.1093/bioinformatics/btv485. Epub 2015 Aug 26.
10
coiTAD: Detection of Topologically Associating Domains Based on Clustering of Circular Influence Features from Hi-C Data.coiTAD：基于 Hi-C 数据中环化影响特征聚类的拓扑关联域检测。
Genes (Basel). 2024 Sep 30;15(10):1293. doi: 10.3390/genes15101293.

本文引用的文献

1
CATAD: exploring topologically associating domains from an insight of core-attachment structure.CATAD：从核心附着结构的角度探索拓扑关联结构域。
Brief Bioinform. 2023 Jul 20;24(4). doi: 10.1093/bib/bbad204.
2
H3K4me3 regulates RNA polymerase II promoter-proximal pause-release.H3K4me3 调控 RNA 聚合酶 II 启动子近端暂停释放。
Nature. 2023 Mar;615(7951):339-348. doi: 10.1038/s41586-023-05780-8. Epub 2023 Mar 1.
3
The UCSC Genome Browser database: 2023 update.UCSC 基因组浏览器数据库：2023 年更新。
Nucleic Acids Res. 2023 Jan 6;51(D1):D1188-D1195. doi: 10.1093/nar/gkac1072.
4
Runx2 regulates chromatin accessibility to direct the osteoblast program at neonatal stages.Runx2 调节染色质可及性以在新生儿期指导成骨细胞程序。
Cell Rep. 2022 Sep 6;40(10):111315. doi: 10.1016/j.celrep.2022.111315.
5
TADfit is a multivariate linear regression model for profiling hierarchical chromatin domains on replicate Hi-C data.TADfit 是一种多元线性回归模型，用于在重复 Hi-C 数据上对层次化染色质结构域进行分析。
Commun Biol. 2022 Jun 20;5(1):608. doi: 10.1038/s42003-022-03546-y.
6
SBTD: A Novel Method for Detecting Topological Associated Domains from Hi-C Data.SBTD：一种从 Hi-C 数据中检测拓扑关联域的新方法。
Interdiscip Sci. 2021 Dec;13(4):638-651. doi: 10.1007/s12539-021-00453-4. Epub 2021 Jun 23.
7
The Myc-associated zinc finger protein (MAZ) works together with CTCF to control cohesin positioning and genome organization.Myc 相关锌指蛋白 (MAZ) 与 CTCF 共同控制着黏连蛋白的定位和基因组的组织。
Proc Natl Acad Sci U S A. 2021 Feb 16;118(7). doi: 10.1073/pnas.2023127118.
8
tagHi-C Reveals 3D Chromatin Architecture Dynamics during Mouse Hematopoiesis.标签 Hi-C 揭示了小鼠造血过程中 3D 染色质结构的动态变化。
Cell Rep. 2020 Sep 29;32(13):108206. doi: 10.1016/j.celrep.2020.108206.
9
SpectralTAD: an R package for defining a hierarchy of topologically associated domains using spectral clustering.SpectralTAD：一个使用谱聚类定义层次结构拓扑关联域的 R 包。
BMC Bioinformatics. 2020 Jul 20;21(1):319. doi: 10.1186/s12859-020-03652-w.
10
HSPG2 overexpression independently predicts poor survival in patients with acute myeloid leukemia.HSPG2 过表达独立预测急性髓系白血病患者的不良生存。
Cell Death Dis. 2020 Jun 30;11(6):492. doi: 10.1038/s41419-020-2694-7.