Chromatin Insulator Function and Nuclear Organization

National Institute Of Diabetes And Digestive And Kidney Diseases

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Abstract

Identification of trans-acting factors regulating barrier activity of the Homie chromatin insulator DNA-protein complexes termed chromatin insulators help maintain genome organization by creating boundaries that separate active and inactive chromatin and controlling promotor-enhancer interactions. Homing insulator at eve (Homie) is an insulator sequence that can regulate interactions between even-skipped (eve), a Polycomb Group (PcG) regulated gene, and its cis-regulatory elements. Homie also acts as a barrier to prevent PcG repressive chromatin spreading into the neighboring essential TER94 ubiquitously expressed gene. The mechanism behind Homie insulator activity and the requirement of trans-acting factors is unknown. We developed a novel quantitative and tissue-specific in vivo reporter of Homie insulator function, demonstrating that Homie can act as a barrier to the spread of PcG repressive chromatin at an ectopic genomic locus. We found that Homie barrier activity in all tissues tested relies on Rumpelstiltskin (Rump), the hnRNP M homolog in Drosophila, as well as two canonical insulator proteins, Centrosomal Protein 190kD (Cp190) and CCCTC-binding factor (CTCF). We next wanted to address whether chromatin compaction at the eve-TER94 locus may be altered; therefore, we performed 3C analysis in Kc cells after depletion of Rump, Cp190, or CTCF. We found an increase in cis looping throughout this region after Rump but not Cp190 or CTCF depletion. We also detected H3K27me3 spreading into the TER94 locus in Rump-depleted cells and increased H3K27me3 levels at PcG domains genome-wide by ChIP-seq. To visualize potential changes in 3D genome organization after Rump depletion, we utilized Oligopaint DNA FISH to analyze pairwise PcG domain interactions in single Kc cells. This analysis revealed that after Rump depletion, distal PcG domains become closer together in 3D space. However, we did not observe similar changes after either Cp190 or CTCF depletion, suggesting that Rump regulates PcG through a different mechanism than that of the canonical insulator proteins. Taken together, we observe increased compaction of PcG domains in both cis and trans in Rump-depleted cells. Future experiments will address whether Rump-dependent barrier activity at Homie requires Cp190 and/or CTCF. The motif-1 interacting protein (M1IP) colocalizes with CP190 and M1BP near TAD borders The interphase genome is organized in three-dimensional space at various levels, including compartments, territories, and topologically associated domains (TADs). Active transcription is observed at many TAD borders, and various chromatin insulator proteins are also enriched at these locations, particularly CP190. The core promoter motif-1 is enriched at these sites, and the transcription factor M1BP that binds to motif-1 is also present. It was recently shown that both CP190 and M1BP physically interact and are both required for motif-1 dependent gene expression and transcription near TAD borders. In this study, we evaluate Motif-1 interacting protein (M1IP), which was previously identified as a motif-1 binding protein that was copurified along with CP190 and M1BP. M1IP contains a BED-type zinc finger domain also found in the BEAF-32 insulator protein. Using ChIP-seq data produced by the ENCODE project, we found that M1IP overlaps extensively with CP190, M1BP, and BEAF-32. Using MEME-ChIP, we verified that motif-1 is enriched at M1IP chromatin binding sites across the genome. Additionally, we found that M1IP is also highly enriched at TAD borders. Current studies are underway to elucidate the possible function of M1IP in transcription regulation by performing euRNA-seq after depleting M1IP. We will also assess whether M1IP physically interacts with M1BP and/or CP190. Deciphering the contribution of 3D interactions between cis-regulatory elements and promoters to regulate gene expression using graph neural networks Gene expression is regulated by various factors including nearby histone modifications (HMs), binding of transcription factors (TFs), and interplay of diverse cis-regulatory elements (CREs) in a cooperative manner. Two previous methods (GC-MERGE and Chromoformer) have been developed to predict gene expression by constructing a promoter-centered network based on 3D physical contacts between the promoter and CREs. However, these published models lack transferability to various sizes of promoter-centered graphs and do not quantify the influence of 3D physical contacts on gene expression. In our approach, by jointly modeling multi-omics data, we can determine the main factors that regulate gene expression and can identify important CREs for each gene. We present a novel deep learning architecture creExplainer based on a graph transformer network. The attention mechanism was applied to each pair of nodes in a graph. We used 800 ChIP-seq datasets of HMs and TFs, Hi-C/micro-C, ATAC-seq and RNA-seq data from human, mouse and fly genomes. Promoter-centered graphs were built for each gene based on the regions across the genome that contact the promoter in 3D space. First, we trained a model based on the HMs and calculated the Pearson correlation, AUC, and AUPRC between raw gene expression and predicted gene expression in four cell lines. The creExplainer method showed better prediction performance relative to other existing methods. Second, we trained another model based on TFs, which showed slightly lower performance relative to HMs. By ranking node importance, we found that TFs and HMs co-regulate gene expression by binding to different CREs. Third, we tested the effect of 3D contacts on gene expression. 3D contact frequency showed low correlation with attention scores. Our results suggest that gene expression is dictated by promoter region activation or repression by CREs and that 3D contacts are necessary in specific cases but provide a lower relative contribution to overall gene expression than promoters and CREs themselves. Compared to previously developed methods, creExplainer exhibited higher accuracy and good transferability. Our method provides new insights into the function of specific CREs on respective gene promoters based on multi-omics data, and we systematically estimated the feature importance and node importance of 3D genome contacts, CREs, and epigenomic features. We aspire to use our method to identify novel specific 3D contacts among promoters and CREs that contribute to the regulation of specific genes. This predictive power should not only contribute to our knowledge of specific gene regulatory mechanisms on the 3D level but also allow us to design targeted strategies to modify gene expression within individual cells. Compared to previously developed methods, creExplainer exhibited higher accuracy and good transferability. Our method provides new insights into the function of specific CREs on respective gene promoters based on multi-omics data, and we systematically estimated the feature importance and node importance of 3D genome contacts, CREs, and epigenomic features. We aspire to use our method to identify novel specific 3D contacts among promoters and CREs that contribute to the regulation of specific genes. This predictive power should not only contribute to our knowledge of specific gene regulatory mechanisms on the 3D level but also allow us to design targeted strategies to modify gene expression within individual cells.