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The 3D Genome: New Technologies and Emerging Insights

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  • The 3D Genome: New Technologies and Emerging Insights

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    The study of three-dimensional (3D) genomics explores the spatial structure of genomes and their role in processes like gene expression and DNA replication. By employing innovative technologies, researchers can study these arrangements to discover their role in various biological processes. Scientists continue to find new ways in which the organization of DNA is involved in processes like development1 and disease2.

    Basic Organization and Structure
    Understanding the significance of the genome's 3D organization starts by exploring its various elements, like loops, regions, structures, and compartments. At the basic level, DNA is bound by histone proteins to form nucleosomes3. Chromatin fibers consist of DNA wrapped around the nucleosomes and form loops and domains across various scales4. These loops facilitate regulatory element interactions and contribute heavily to gene regulation5.

    From here the chromatin can be broken into domains, like topologically associated domains (TADs), which act as regulatory units and influence gene expression through boundaries marked by specific proteins and histone modifications6. Then chromatin domain groups can be separated into higher-order (A/B) compartments7. The activation (A) and repression (B) areas are functional domains that interact differently based on chromosomal characteristics8. Finally, the individual chromosomes are organized into territories, which are regions occupied by a single chromosome within the nucleus9. These structures demonstrate only a portion of the genome's intricate spatial organization that is essential for cellular functions and gene regulation. For a more detailed view of genome architecture and function, read this review from Misteli.


    Technologies for Studying 3D Genomics
    Among the growing list of approaches studying the 3D genome, 3C (chromosome conformation capture) and its wide spectrum of derivatives are some of the most prominent technologies. 3C utilizes proximity ligation to reveal how genomic regions, though distant in their linear sequence, are physically close in three-dimensional space10. Specifically, it detects chromatin loops, revealing spatial contact between DNA segments, including regulatory elements and gene start/endpoints11. These loops vary with transcriptional changes, linking structure to function. However, the initial 3C technology had several limitations, which led to the development of many higher-throughput, 3C-derived methods.

    These resulting methods include 4C (chromosome conformation capture-on-chip)12, 5C (chromosome conformation capture carbon copy)13, ChIA-PET (chromatin interaction analysis by paired-end tag sequencing)14, and Hi-C (high-throughput chromosome conformation capture)15, among others. Each 3C-based technology has its distinct advantages for studying chromosomal interactions and genomic architecture.

    Other methods like SPRITE (split-pool recognition of interactions by tag extension)16 and GAM (genome architecture mapping)17 were developed to address some restrictions of Hi-C. In particular, SPRITE can identify complex higher-order structures and long-range inter-chromosomal interactions, and GAM measures 3D chromatin contacts without ligation, using DNA sequencing from thinly sliced nuclear sections. Microscopy-based techniques are also common strategies for studying genome organization.

    DNA FISH (DNA fluorescence in situ hybridization) is one of the more popular imaging-based tools that utilizes fluorescently labeled DNA probes to assess the three-dimensional distances between genomic locations and their positioning relative to specific nuclear markers18. Advancements in DNA FISH and combinations with other technologies have led to even more insights into imaging-based 3D genomics methods. Additional 3D techniques like ChIP-Seq (chromatin immunoprecipitation followed by sequencing), HiChIP, and more are covered in-depth in part one and part two of our previous epigenetics article series.

    Each of the previous methods is effective for mapping the 3D structure of the genome; however, they primarily offer associative data. A thorough review by Wang et al. highlights many of the various technologies employed to engineer genomes that can be used to provide important functional information. This includes techniques such as ZFNs (zinc-finger nucleases), TALENs (transcription activator-like effector nuclease), and various CRISPR (clustered regularly interspaced short palindromic repeats) systems.


    Applications of 3D Genomics
    The Ecker Lab, a leading 3D-omics group from the Salk Institute, is responsible for the development and application of numerous techniques. In particular, sn-m3C-seq (single-nucleus methyl-3C sequencing) is a method they designed for simultaneously profiling chromatin conformation and DNA methylation in single cells19. Additionally, it reveals the association of specific chromatin interactions with differential DNA methylation patterns and has the potential to determine cell-type-specific regulatory mechanisms.

    More recently, the Ecker Lab employed this technique to build a single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain20. After analyzing over 300,000 methylomes and 176,000 chromatin conformation–methylome joint profiles from various brain regions, they identified 2.6 million differentially methylated regions and constructed a methylation-based cell taxonomy with 4673 cell groups. The researchers also explored spatial epigenomic diversity, chromosomal conformation dynamics, and the association of these elements with transcriptional activity to provide a comprehensive resource for understanding the cellular, spatial, and regulatory genome diversity of the mouse brain.

    Another leading 3D-omics group is the Aiden Lab from Baylor College of Medicine. In a recent collaborative study, they successfully assembled the genome of a Late Pleistocene woolly mammoth using a novel "reference-assisted 3D genome assembly" technique named PaleoHi-C21. This method was optimized for ancient DNA and allowed for the reconstruction of the mammoth's chromosomal structure. Key findings from the 3D architecture of the mammoth genome revealed similarities with Asian elephants and unique features like a tetradic structure of the inactive X chromosome. This work demonstrated the potential of ancient DNA to uncover cell-type specific epigenetic information and opens possibilities for de novo genome assembly of extinct species.

    Other notable applications include a study that examined the effects of epigenetic therapy on the 3D epigenome in endocrine-resistant breast cancer22. This research highlighted the potential of targeting DNA methylation to rewire chromatin interactions and suppress tumor growth in this cancer type.


    Conclusion
    Research in the field of 3D genomics has led to new discoveries in genome organization and its impact on cellular processes. Crucial technologies like 3C, DNA FISH, and numerous others have provided key insights into chromatin interactions and gene regulation. The application of these methods highlights the significance of 3D genomic studies in diverse areas, including developmental biology, disease research, and evolutionary studies. This rapidly developing field continues to expand our understanding of the complex relationship between genome structure and function.

    Recommended Reading: References
    1. Zheng, H., & Xie, W. (2019). The role of 3D genome organization in development and cell differentiation. Nature reviews. Molecular cell biology, 20(9), 535–550. https://doi.org/10.1038/s41580-019-0132-4
    2. Chakraborty, A., & Ay, F. (2019). The role of 3D genome organization in disease: From compartments to single nucleotides. Seminars in cell & developmental biology, 90, 104–113. https://doi.org/10.1016/j.semcdb.2018.07.005
    3. Olins, D. E., & Olins, A. L. (2003). Chromatin history: our view from the bridge. Nature reviews. Molecular cell biology, 4(10), 809–814. https://doi.org/10.1038/nrm1225
    4. Maeshima, K., Ide, S., & Babokhov, M. (2019). Dynamic chromatin organization without the 30-nm fiber. Current opinion in cell biology, 58, 95–104. https://doi.org/10.1016/j.ceb.2019.02.003
    5. Dekker, J., & Misteli, T. (2015). Long-Range Chromatin Interactions. Cold Spring Harbor perspectives in biology, 7(10), a019356. https://doi.org/10.1101/cshperspect.a019356
    6. Long, H. S., Greenaway, S., Powell, G., Mallon, A. M., Lindgren, C. M., & Simon, M. M. (2022). Making sense of the linear genome, gene function and TADs. Epigenetics & chromatin, 15(1), 4. https://doi.org/10.1186/s13072-022-00436-9
    7. 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., Sandstrom, R., Bernstein, B., Bender, M. A., Groudine, M., Gnirke, A., Stamatoyannopoulos, J., Mirny, L. A., Lander, E. S., & Dekker, J. (2009). Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science (New York, N.Y.), 326(5950), 289–293. https://doi.org/10.1126/science.1181369
    8. Fortin, J. P., & Hansen, K. D. (2015). Reconstructing A/B compartments as revealed by Hi-C using long-range correlations in epigenetic data. Genome biology, 16(1), 180. https://doi.org/10.1186/s13059-015-0741-y
    9. Cremer, T., & Cremer, M. (2010). Chromosome territories. Cold Spring Harbor perspectives in biology, 2(3), a003889. https://doi.org/10.1101/cshperspect.a003889
    10. Dekker, J., Rippe, K., Dekker, M., & Kleckner, N. (2002). Capturing chromosome conformation. Science (New York, N.Y.), 295(5558), 1306–1311. https://doi.org/10.1126/science.1067799
    11. Han, J., Zhang, Z., & Wang, K. (2018). 3C and 3C-based techniques: the powerful tools for spatial genome organization deciphering. Molecular cytogenetics, 11, 21. https://doi.org/10.1186/s13039-018-0368-2
    12. Simonis, M., Klous, P., Splinter, E., Moshkin, Y., Willemsen, R., de Wit, E., van Steensel, B., & de Laat, W. (2006). Nuclear organization of active and inactive chromatin domains uncovered by chromosome conformation capture-on-chip (4C). Nature genetics, 38(11), 1348–1354. https://doi.org/10.1038/ng1896
    13. Dostie, J., Richmond, T. A., Arnaout, R. A., Selzer, R. R., Lee, W. L., Honan, T. A., Rubio, E. D., Krumm, A., Lamb, J., Nusbaum, C., Green, R. D., & Dekker, J. (2006). Chromosome Conformation Capture Carbon Copy (5C): a massively parallel solution for mapping interactions between genomic elements. Genome research, 16(10), 1299–1309. https://doi.org/10.1101/gr.5571506
    14. Li, G., Cai, L., Chang, H., Hong, P., Zhou, Q., Kulakova, E. V., Kolchanov, N. A., & Ruan, Y. (2014). Chromatin Interaction Analysis with Paired-End Tag (ChIA-PET) sequencing technology and application. BMC genomics, 15 Suppl 12(Suppl 12), S11. https://doi.org/10.1186/1471-2164-15-S12-S11
    15. Belton, J. M., McCord, R. P., Gibcus, J. H., Naumova, N., Zhan, Y., & Dekker, J. (2012). Hi-C: a comprehensive technique to capture the conformation of genomes. Methods (San Diego, Calif.), 58(3), 268–276. https://doi.org/10.1016/j.ymeth.2012.05.001
    16. Quinodoz, S. A., Ollikainen, N., Tabak, B., Palla, A., Schmidt, J. M., Detmar, E., Lai, M. M., Shishkin, A. A., Bhat, P., Takei, Y., Trinh, V., Aznauryan, E., Russell, P., Cheng, C., Jovanovic, M., Chow, A., Cai, L., McDonel, P., Garber, M., & Guttman, M. (2018). Higher-Order Inter-chromosomal Hubs Shape 3D Genome Organization in the Nucleus. Cell, 174(3), 744–757.e24. https://doi.org/10.1016/j.cell.2018.05.024
    17. Beagrie, R. A., Scialdone, A., Schueler, M., Kraemer, D. C., Chotalia, M., Xie, S. Q., Barbieri, M., de Santiago, I., Lavitas, L. M., Branco, M. R., Fraser, J., Dostie, J., Game, L., Dillon, N., Edwards, P. A., Nicodemi, M., & Pombo, A. (2017). Complex multi-enhancer contacts captured by genome architecture mapping. Nature, 543(7646), 519–524. https://doi.org/10.1038/nature21411
    18. Xie, L., & Liu, Z. (2021). Single-cell imaging of genome organization and dynamics. Molecular systems biology, 17(7), e9653. https://doi.org/10.15252/msb.20209653
    19. Lee, D. S., Luo, C., Zhou, J., Chandran, S., Rivkin, A., Bartlett, A., Nery, J. R., Fitzpatrick, C., O'Connor, C., Dixon, J. R., & Ecker, J. R. (2019). Simultaneous profiling of 3D genome structure and DNA methylation in single human cells. Nature methods, 16(10), 999–1006. https://doi.org/10.1038/s41592-019-0547-z
    20. Liu, H., Zeng, Q., Zhou, J., Bartlett, A., Wang, B. A., Berube, P., Tian, W., Kenworthy, M., Altshul, J., Nery, J. R., Chen, H., Castanon, R. G., Zu, S., Li, Y. E., Lucero, J., Osteen, J. K., Pinto-Duarte, A., Lee, J., Rink, J., Cho, S., … Ecker, J. R. (2023). Single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain. Nature, 624(7991), 366–377. https://doi.org/10.1038/s41586-023-06805-y
    21. Sandoval-Velasco, M., Dudchenko, O., Antonio Rodríguez, J., Pérez Estrada, C., Dehasque, M., Fontsere, C., ... & Aiden, E. L. (2023). Three-dimensional genome architecture persists in a 52,000-year-old woolly mammoth skin sample. bioRxiv, 2023-06.
    22. Achinger-Kawecka, J., Stirzaker, C., Portman, N., Campbell, E., Chia, K. M., Du, Q., Laven-Law, G., Nair, S. S., Yong, A., Wilkinson, A., Clifton, S., Milioli, H. H., Alexandrou, S., Caldon, C. E., Song, J., Khoury, A., Meyer, B., Chen, W., Pidsley, R., Qu, W., … Clark, S. J. (2024). The potential of epigenetic therapy to target the 3D epigenome in endocrine-resistant breast cancer. Nature structural & molecular biology, 10.1038/s41594-023-01181-7. Advance online publication. https://doi.org/10.1038/s41594-023-01181-7

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    About the Author

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    seqadmin Benjamin Atha holds a B.A. in biology from Hood College and an M.S. in biological sciences from Towson University. With over 9 years of hands-on laboratory experience, he's well-versed in next-generation sequencing systems. Ben is currently the editor for SEQanswers. Find out more about seqadmin

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