Genome biologyCell BiologyPeer-reviewed journal article
Dissecting the Contribution of Transposable Elements to Interphase Chromosome Structure
Liyang ShiiD, Zhen Xiao, Isaac A. BabarindeiD, Fu Xiuling, Gang MaiD, Zhouqi Huang, Li SuniD, Xuemeng ZhouiD, Jiangping He, Alexander V. StrunnikoviD, Andrew P. HutchinsiD
Abstract
Transposable elements (TEs) occupy nearly half of the human genome and play diverse biological roles. Despite their abundance, the extent to which TEs contribute to three-dimensional (3D) genome structure remains unclear. To investigate this, we developed te_hic, a computational pipeline that integrates genomic data with chromatin interactions. Our analysis reveals that TE sequences are responsible for 3D genome structure in interphase nuclei. This phenomenon is mediated by the recruitment of specific transcription factors to TEs, which enables both the formation and disruption of chromatin contacts. We computationally identified known contact-forming proteins (CTCF, RAD21, SMC3) and breaking proteins (RNF2), as well as novel candidate contact-formers (SMARCA4, MAFK). Knockdown of the predicted contact-formers SMARCA4 and MAFK decreased contacts and loops at and between TEs. Notably, SMARCA4 knockdown selectively reduced short-range contacts, highlighting its role in maintaining 3D genome structure mediated by TE binding. Overall, our findings demonstrate that TEs are crucial determinants of 3D genome organization in mammalian cells. Key findingsO_LITEs determine 48% of the 3D genome structure alone, and 70% of heterotypic contacts. C_LIO_LIA/B compartments, TADs, and loop signatures can be retrieved using TE-mapped reads only. C_LIO_LITFs can be divided into contact formers and breakers at TEs. C_LIO_LISMARCA4 and MAFK build chromatin contacts between TE sequences. C_LI
- organism: human
- assay: Hi-C
- research focus: chromatin & epigenetic regulation
- research focus: gene regulatory network inference
- research focus: clustering
- research focus: differential expression
- approach: deep learning
- approach: statistical model
- Citations
- 1
- FWCI
- 1.72
- Field percentile
- top 23%
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