Abstract
The three-dimensional structure of the Drosophila chromatin has been shown to change at the early stages of embryogenesis from the state with no local structures to compartmentalized chromatin segregated into topologically associated domains (TADs). However, the dynamics of TAD formation and its association with the expression and epigenetics dynamics is not fully understood. As TAD calling and analysis of TAD dynamics have no standard, universally accepted solution, we have developed HiChew, a specialized tool for segmentation of Hi-C maps into TADs of a given expected size and subsequent clustering of TADs based on their dynamics during the embryogenesis. To validate the approach, we demonstrate that HiChew clusters correlate with genomic and epigenetic characteristics. Particularly, in accordance with previous findings, the maturation rate of TADs is positively correlated with the number of housekeeping genes per TAD and negatively correlated with the length of housekeeping genes. We also report a high positive correlation of the maturation rate of TADs with the growth rate of the associated ATAC-Seq signal.
This work is supported by RFBR grant 19-34-90136, and by Skoltech Systems Biology Fellowship for Aleksandra Galitsyna.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Abdennur, N., Mirny, L.: Cooler: scalable storage for Hi-C data and other genomically labeled arrays. Bioinformatics 36(1), 311–316 (2020). https://doi.org/10.1093/bioinformatics/btz540
Blythe, S.A., Wieschaus, E.F.: Zygotic genome activation triggers the DNA replication checkpoint at the midblastula transition. Cell 160(6), 1169–1181 (2015). https://doi.org/10.1016/j.cell.2015.01.050
Bonev, B., et al.: Multiscale 3D genome rewiring during mouse neural development. Cell 171(3), 557–572 (2017). https://doi.org/10.1016/j.cell.2017.09.043
Brandes, U., et al.: On finding graph clusterings with maximum modularity. In: Brandstädt, A., Kratsch, D., Müller, H. (eds.) WG 2007. LNCS, vol. 4769, pp. 121–132. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-74839-7_12
Buenrostro, J.D., Giresi, P.G., Zaba, L.C., Chang, H.Y., Greenleaf, W.J.: Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10(12), 1213–1218 (2013). https://doi.org/10.1038/nmeth.2688
Flyamer, I.M., et al.: Single-nucleus Hi-C reveals unique chromatin reorganization at oocyte-to-zygote transition. Nature 544(7648), 110–114 (2017). https://doi.org/10.1038/nature21711
Forcato, M., Nicoletti, C., Pal, K., Livi, C.M., Ferrari, F., Bicciato, S.: Comparison of computational methods for Hi-C data analysis. Nat. Methods 14(7), 679–685 (2017). https://doi.org/10.1038/nmeth.4325
Fulco, C.P., et al.: Activity-by-contact model of enhancer-promoter regulation from thousands of CRISPR perturbations. Nat. Genet. 51(12), 1664–1669 (2019). https://doi.org/10.1038/s41588-019-0538-0
Heyn, P., et al.: The earliest transcribed zygotic genes are short, newly evolved, and different across species. Cell Rep. 6(2), 285–292 (2014). https://doi.org/10.1016/j.celrep.2013.12.030
Hug, C.B., Grimaldi, A.G., Kruse, K., Vaquerizas, J.M.: Chromatin architecture emerges during zygotic genome activation independent of transcription. Cell 169(2), 216–228 (2017). https://doi.org/10.1016/j.cell.2017.03.024
Imakaev, M., et al.: Iterative correction of Hi-C data reveals hallmarks of chromosome organization. Nat. Methods 9(10), 999–1003 (2012). https://doi.org/10.1038/nmeth.2148
Lavaburst. https://github.com/nvictus/lavaburst (Accessed 10 Feb 2020)
Sauerwald, N., Singhal, A., Kingsford, C.: Analysis of the structural variability of topologically associated domains as revealed by Hi-C. NAR Genom. Bioinform. 2(1) (2020). https://doi.org/10.1093/nargab/lqz008
Schulz, K.N., Harrison, M.M.: Mechanisms regulating zygotic genome activation. Nat. Rev. Genet. 20(4), 221–234 (2019). https://doi.org/10.1038/s41576-018-0087-x
Stadhouders, R., et al.: Transcription factors orchestrate dynamic interplay between genome topology and gene regulation during cell reprogramming. Nat. Genet. 50(2), 238–249 (2018). https://doi.org/10.1038/s41588-017-0030-7
Ulianov, S.V., et al.: Active chromatin and transcription play a key role in chromosome partitioning into topologically associating domains. Genome Res. 26(1), 70–84 (2016). https://doi.org/10.1101/gr.196006.115
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Bykov, N.S., Sigalova, O.M., Gelfand, M.S., Galitsyna, A.A. (2020). HiChew: a Tool for TAD Clustering in Embryogenesis. In: Cai, Z., Mandoiu, I., Narasimhan, G., Skums, P., Guo, X. (eds) Bioinformatics Research and Applications. ISBRA 2020. Lecture Notes in Computer Science(), vol 12304. Springer, Cham. https://doi.org/10.1007/978-3-030-57821-3_37
Download citation
DOI: https://doi.org/10.1007/978-3-030-57821-3_37
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-57820-6
Online ISBN: 978-3-030-57821-3
eBook Packages: Computer ScienceComputer Science (R0)