Toward an understanding of the relation between gene regulation and 3D genome organization

Abstract

Background: High-order chromatin structure has been shown to play a vital role in gene regulation. Previously we identified two types of sequence domains, CGI (CpG island) forest and CGI prairie, which tend to spatially segregate, but to different extent in different tissues. Here we aim to further quantify the association of domain segregation with gene regulation and therefore differentiation.

Methods: By means of the published RNA-seq and Hi-C data, we identified tissue-specific genes and quantitatively investigated how their regulation is relevant to chromatin structure. Besides, two types of gene networks were constructed and the association between gene pair co-regulation and genome organization is discussed.

Results: We show that compared to forests, tissue-specific genes tend to be enriched in prairies. Highly specific genes also tend to cluster according to their functions in a relatively small number of prairies. Furthermore, tissue-specific forest-prairie contact formation was associated with the regulation of tissue-specific genes, in particular those in the prairie domains, pointing to the important role of gene positioning, in the linear DNA sequence as well as in 3D chromatin structure, in gene regulatory network formation.

Conclusion: We investigated how gene regulation is related to genome organization from the perspective of forest-prairie spatial interactions. Since unlike compartments A and B, forest and prairie are identified solely based on sequence properties. Therefore, the simple and uniform framework (forest-prairie domain segregation) provided here can be utilized to further understand the chromatin structure changes as well as the underlying biological significances in different stages, such as tumorgenesis.

Graphical abstract

Keywords

CGI forest / CGI prairie / domain segregation / chromatin structure / gene regulation

References

[1] Lieberman-Aiden, E., van Berkum, N. L., Williams, L., Imakaev, M., Ragoczy, T., Telling, A., Amit, I., Lajoie, B. R., Sabo, P. J., Dorschner, M. O., (2009) Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science, 326, 289–293

[2] Fullwood, M. J., Liu, M. H., Pan, Y. F., Liu, J., Xu, H., Mohamed, Y. B., Orlov, Y. L., Velkov, S., Ho, A., Mei, P. H., (2009) An oestrogen-receptor-alpha-bound human chromatin interactome. Nature, 462, 58–64

[3] Dixon, J. R., Selvaraj, S., Yue, F., Kim, A., Li, Y., Shen, Y., Hu, M., Liu, J. S. and Ren, B. (2012) Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature, 485, 376–380

[4] Rao, S. S., Huntley, M. H., Durand, N. C., Stamenova, E. K., Bochkov, I. D., Robinson, J. T., Sanborn, A. L., Machol, I., Omer, A. D., Lander, E. S., (2014) A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell, 159, 1665–1680

[5] Dowen, J. M., Fan, Z. P., Hnisz, D., Ren, G., Abraham, B. J., Zhang, L. N., Weintraub, A. S., Schuijers, J., Lee, T. I., Zhao, K., (2014) Control of cell identity genes occurs in insulated neighborhoods in mammalian chromosomes. Cell, 159, 374–387

[6] Hnisz, D., Day, D. S. and Young, R. A. (2016) Insulated neighborhoods: structural and functional units of mammalian gene control. Cell, 167, 1188–1200

[7] Hnisz, D., Weintraub, A. S., Day, D. S., Valton, A.-L., Bak, R. O., Li, C. H., Goldmann, J., Lajoie, B. R., Fan, Z. P., Sigova, A. A., (2016) Activation of proto-oncogenes by disruption of chromosome neighborhoods. Science, 351, 1454–1458

[8] Ji, X., Dadon, D. B., Powell, B. E., Fan, Z. P., Borges-Rivera, D., Shachar, S., Weintraub, A. S., Hnisz, D., Pegoraro, G., Lee, T. I., (2016) 3D chromosome regulatory landscape of human pluripotent cells. Cell Stem Cell, 18, 262–275

[9] Lupiáñez, D. G., Kraft, K., Heinrich, V., Krawitz, P., Brancati, F., Klopocki, E., Horn, D., Kayserili, H., Opitz, J. M., Laxova, R., (2015) Disruptions of topological chromatin domains cause pathogenic rewiring of gene-enhancer interactions. Cell, 161, 1012–1025

[10] Schwarzer, W., Abdennur, N., Goloborodko, A., Pekowska, A., Fudenberg, G., Loe-Mie, Y., Fonseca, N. A., Huber, W., Haering, C. H., Mirny, L., (2017) Two independent modes of chromatin organization revealed by cohesin removal. Nature, 551, 51–56

[11] Smol, T., Sigé J., Thuillier, C., Frénois, F., Brunelle, P., Rama, M., Roche-Lestienne, C., Manouvrier-Hanu, S., Petit, F. and Ghoumid, J. (2020) Lessons from the analysis of TAD boundary deletions in normal population. bioRxiv, 021188

[12] Li, G., Ruan, X., Auerbach, R. K., Sandhu, K. S., Zheng, M., Wang, P., Poh, H. M., Goh, Y., Lim, J., Zhang, J., (2012) Extensive promoter-centered chromatin interactions provide a topological basis for transcription regulation. Cell, 148, 84–98

[13] Wang, S., Su, J.-H., Beliveau, B. J., Bintu, B., Moffitt, J. R., Wu, C. T. and Zhuang, X. (2016) Spatial organization of chromatin domains and compartments in single chromosomes. Science, 353, 598–602

[14] Stadhouders, R., Vidal, E., Serra, F., Di Stefano, B., Le Dily, F., Quilez, J., Gomez, A., Collombet, S., Berenguer, C., Cuartero, Y., (2018) Transcription factors orchestrate dynamic interplay between genome topology and gene regulation during cell reprogramming. Nat. Genet., 50, 238–249

[15] Bertero, A., Fields, P. A., Ramani, V., Bonora, G., Yardimci, G. G., Reinecke, H., Pabon, L., Noble, W. S., Shendure, J. and Murry, C. E. (2019) Dynamics of genome reorganization during human cardiogenesis reveal an RBM20-dependent splicing factory. Nat. Commun., 10, 1538

[16] Liu, S., Zhang, L., Quan, H., Tian, H., Meng, L., Yang, L., Feng, H. and Gao, Y. Q. (2018) From 1D sequence to 3D chromatin dynamics and cellular functions: a phase separation perspective. Nucleic Acids Res., 46, 9367–9383

[17] Zhan, Y., Mariani, L., Barozzi, I., Schulz, E. G., Blüthgen, N., Stadler, M., Tiana, G. and Giorgetti, L. (2017) Reciprocal insulation analysis of Hi-C data shows that TADs represent a functionally but not structurally privileged scale in the hierarchical folding of chromosomes. Genome Res., 27, 479–490

[18] Ibn-Salem, J., Muro, E. M. and Andrade-Navarro, M. A. (2017) Co-regulation of paralog genes in the three-dimensional chromatin architecture. Nucleic Acids Res., 45, 81–91

[19] Soler-Oliva, M. E., Guerrero-Martínez, J. A., Bachetti, V. and Reyes, J. C. (2017) Analysis of the relationship between coexpression domains and chromatin 3D organization. PLOS Comput. Biol., 13, e1005708

[20] Belcastro, V., Siciliano, V., Gregoretti, F., Mithbaokar, P., Dharmalingam, G., Berlingieri, S., Iorio, F., Oliva, G., Polishchuck, R., Brunetti-Pierri, N., (2011) Transcriptional gene network inference from a massive dataset elucidates transcriptome organization and gene function. Nucleic Acids Res., 39, 8677–8688

[21] Hnisz, D., Shrinivas, K., Young, R. A., Chakraborty, A. K. and Sharp, P. A. (2017) A phase separation model for transcriptional control. Cell, 169, 13–23

[22] Boija, A., Klein, I. A., Sabari, B. R., Dall’Agnese, A., Coffey, E. L., Zamudio, A. V., Li, C. H., Shrinivas, K., Manteiga, J. C., Hannett, N. M., (2018) Transcription factors activate genes through the phase-separation capacity of their activation domains. Cell, 175, 1842–1855.e16

[23] Hnisz, D. and Young, R. A. (2017) New insights into genome structure: genes of a feather stick together. Mol. Cell, 67, 730–731

[24] de Wit, E., Bouwman, B. A. M., Zhu, Y., Klous, P., Splinter, E., Verstegen, M. J. A. M., Krijger, P. H. L., Festuccia, N., Nora, E. P., Welling, M., (2013) The pluripotent genome in three dimensions is shaped around pluripotency factors. Nature, 501, 227–231

[25] Monahan, K., Horta, A. and Lomvardas, S. (2019) LHX2- and LDB1-mediated trans interactions regulate olfactory receptor choice. Nature, 565, 448–453

[26] Hahn, M. A., Wu, X., Li, A. X., Hahn, T. and Pfeifer, G. P. (2011) Relationship between gene body DNA methylation and intragenic H3K9me3 and H3K36me3 chromatin marks. PLoS One, 6, e18844

[27] Wang, Z. and Willard, H. F. (2012) Evidence for sequence biases associated with patterns of histone methylation. BMC Genomics, 13, 367–379

[28] Kustatscher, G., Grabowski, P. and Rappsilber, J. (2017) Pervasive coexpression of spatially proximal genes is buffered at the protein level. Mol. Syst. Biol., 13, 937–950

[29] Schmitt, A. D., Hu, M., Jung, I., Xu, Z., Qiu, Y., Tan, C. L., Li, Y., Lin, S., Lin, Y., Barr, C. L., (2016) A compendium of chromatin contact maps reveals spatially active regions in the human genome. Cell Rep., 17, 2042–2059

[30] Sonawane, A. R., Platig, J., Fagny, M., Chen, C.-Y., Paulson, J. N., Lopes-Ramos, C. M., DeMeo, D. L., Quackenbush, J., Glass, K. and Kuijjer, M. L. (2017) Understanding tissue-specific gene regulation. Cell Rep., 21, 1077–1088

[31] Hurst, L. D., Pál, C. and Lercher, M. J. (2004) The evolutionary dynamics of eukaryotic gene order. Nat. Rev. Genet., 5, 299–310

[32] Xu, H., Liu, J.-J., Liu, Z., Li, Y., Jin, Y.-S. and Zhang, J. (2019) Synchronization of stochastic expressions drives the clustering of functionally related genes. Sci. Adv., 5, eaax6525

[33] Shwan, N. A. A., Louzada, S., Yang, F. and Armour, J. A. L. (2017) Recurrent Rearrangements of Human Amylase Genes Create Multiple Independent CNV Series. Hum. Mutat., 38, 532–539

[34] Ponomarev, I., Wang, S., Zhang, L., Harris, R. A. and Mayfield, R. D. (2012) Gene coexpression networks in human brain identify epigenetic modifications in alcohol dependence. J. Neurosci., 32, 1884–1897

[35] Rosa, B. A., Jasmer, D. P. and Mitreva, M. (2014) Genome-wide tissue-specific gene expression, co-expression and regulation of co-expressed genes in adult nematode Ascaris suum. PLoS Negl. Trop. Dis., 8, e2678

[36] Satoh, J., Yamamoto, Y., Asahina, N., Kitano, S. and Kino, Y. (2014) RNA-Seq data mining: downregulation of NeuroD6 serves as a possible biomarker for alzheimer’s disease brains. Dis. Markers, 2014, 123165

[37] Yevshin, I., Sharipov, R., Kolmykov, S., Kondrakhin, Y. and Kolpakov, F. (2019) GTRD: a database on gene transcription regulation-2019 update. Nucleic Acids Res., 47, D100–D105

[38] Sanborn, A. L., Rao, S. S. P., Huang, S.-C., Durand, N. C., Huntley, M. H., Jewett, A. I., Bochkov, I. D., Chinnappan, D., Cutkosky, A., Li, J., (2015) Chromatin extrusion explains key features of loop and domain formation in wild-type and engineered genomes. Proc. Natl. Acad. Sci. USA, 112, E6456–E6465

[39] Fudenberg, G., Imakaev, M., Lu, C., Goloborodko, A., Abdennur, N. and Mirny, L. A. (2016) Formation of chromosomal domains by loop extrusion. Cell Rep., 15, 2038–2049

[40] Yusufzai, T. M., Tagami, H., Nakatani, Y. and Felsenfeld, G. (2004) CTCF tethers an insulator to subnuclear sites, suggesting shared insulator mechanisms across species. Mol. Cell, 13, 291–298

[41] Weintraub, A. S., Li, C. H., Zamudio, A. V., Sigova, A. A., Hannett, N. M., Day, D. S., Abraham, B. J., Cohen, M. A., Nabet, B., Buckley, D. L., (2017) YY1 is a structural regulator of enhancer-promoter loops. Cell, 171, 1573–1588.e28

[42] Shrinivas, K., Sabari, B. R., Coffey, E. L., Klein, I. A., Boija, A., Zamudio, A. V., Schuijers, J., Hannett, N. M., Sharp, P. A., Young, R. A., (2019) Enhancer features that drive formation of transcriptional condensates. Mol. Cell, 75, 549–561.e7

[43] Duran-Aniotz, C. and Hetz, C. (2016) Glucose metabolism: A sweet relief of Alzheimer’s disease. Curr. Biol., 26, R806–R809

[44] Di Paolo, G. and Kim, T.-W. (2011) Linking lipids to Alzheimer’s disease: cholesterol and beyond. Nat. Rev. Neurosci., 12, 284–296

[45] Tynkkynen, J., Chouraki, V., van der Lee, S. J., Hernesniemi, J., Yang, Q., Li, S., Beiser, A., Larson, M. G., Sääksjärvi, K., Shipley, M. J., (2018) Association of branched-chain amino acids and other circulating metabolites with risk of incident dementia and Alzheimer’s disease: A prospective study in eight cohorts. Alzheimers Dement., 14, 723–733

[46] MahmoudianDehkordi, S., Arnold, M., Nho, K., Ahmad, S., Jia, W., Xie, G., Louie, G., Kueider-Paisley, A., Moseley, M. A., Thompson, J. W., (2019) Altered bile acid profile associates with cognitive impairment in Alzheimer’s disease—An emerging role for gut microbiome. Alzheimers Dement., 15, 76–92

[47] Lu, L., Liu, X., Huang, W.-K., Giusti-Rodríguez, P., Cui, J., Zhang, S., Xu, W., Wen, Z., Ma, S., Rosen, J. D., (2020) Robust Hi-C maps of enhancer-promoter interactions reveal the function of non-coding genome in neural development and diseases. Mol. Cell, 79, 521–534.e15

[48] Qi, Y. and Zhang, B. (2019) Predicting three-dimensional genome organization with chromatin states. PLOS Comput. Biol., 15, e1007024

[49] Zhang, X., Jeong, M., Huang, X., Wang, X. Q., Wang, X., Zhou, W., Shamim, M. S., Gore, H., Himadewi, P., Liu, Y., (2020) Large DNA methylation nadirs anchor chromatin loops maintaining hematopoietic stem cell identity. Mol. Cell, 78, 506–521.e6

[50] David, Wang, X.Q., Gore, H., Himadewi, P., Feng, F., Yang, L., Zhou, W., Liu, Y., Wang, X., Chen, C-w., Su, J., (2020) Three-dimensional regulation of HOXA cluster genes by a cis-element in hematopoietic stem cell and leukemia. bioRxiv, 017533

[51] Cai, Y., Zhang, Y., Loh, Y. P., Tng, J. Q., Lim, M. C., Cao, Z., Raju, A., Li, S., Manikandan, L., Tergaonkar, V., (2020) H3K27me3-rich genomic regions can function as silencers to repress gene expression via chromatin interactions.bioRxiv, 684712

[52] Servant, N., Varoquaux, N., Lajoie, B. R., Viara, E., Chen, C.-J., Vert, J.-P., Heard, E., Dekker, J. and Barillot, E. (2015) HiC-Pro: an optimized and flexible pipeline for Hi-C data processing. Genome Biol., 16, 259–269

[53] Xie, W. J., Meng, L., Liu, S., Zhang, L., Cai, X. and Gao, Y. Q. (2017) Structural modeling of chromatin integrates genome features and reveals chromosome folding principle. Sci. Rep., 7, 2818–2828

RIGHTS & PERMISSIONS

Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature