Skip to main content
SpringerLink
Log in
Book cover

International Symposium on Bioinformatics Research and Applications

ISBRA 2019: Bioinformatics Research and Applications pp 16–27Cite as

The Review of Bioinformatics Tool for 3D Plant Genomics Research

  • Conference paper
  • First Online:

  • 843 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 11490))

Abstract

Since the genome of the nucleus is a complicated three-dimensional spatial structure but not a single linear structure, biologists consider that 3D structure of plant chromatin is highly correlated with the function of the genome, which can be used to study the regulation mechanisms of genes and their evolutionary process. Because plants are more prone to chromosome structural variation and the 3D structure of plant chromatin are highly correlated with the function of the genome, it is important to investigate the impact of chromosome structural variation on gene expression by analyzing 3D structure. Here, we will briefly review the current bioinformatics tools for 3D plant genome study, which covers Hi-C data processing tools, then are the tools for A and B compartments identification, topologically associated domains (TAD) identification, identification of significant interactions and visualization. And then, we could provide the useful information for the related 3D plant genomics research scientists to select the appropriate tools according to their study. Finally, we discuss how to develop the future 3D genomic plant bioinformatics tools to keep up with the pace of scientific research development.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Erez, L.A., Berkum, N.L., Van, L.W., Maxim, I., Tobias, R., Agnes, T.: Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289–293 (2009)

    Google Scholar 

  2. Dixon, J.R., Siddarth, S., Feng, Y., Audrey, K., Yan, L., Yin, S.: Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature 485(7398), 376 (2012)

    Google Scholar 

  3. Job, D., Marti-Renom, M.A., Mirny, L.A.: Exploring the three-dimensional organization of genomes: interpreting chromatin interaction data. Nat. Rev. Genet. 14(6), 390–403 (2013)

    Google Scholar 

  4. Doğan, E.S., Chang, L.: Three-dimensional chromatin packing and positioning of plant genomes. Nature Plants (2018)

    Google Scholar 

  5. Rao, S.S.P., Huntley, M.H., Durand, N.C., Stamenova, E.K., Bochkov, I.D., Robinson, J.T.: A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 159(7), 1665–1680 (2014)

    Google Scholar 

  6. Xianglin, Z., Huan, F., Xiaowo, W.: The advancement of analysis methods of chromosome conformation capture data. Prog. Biochem. Biophys. 45, 1093–1105 (2018)

    Google Scholar 

  7. Liu, B., Wendel, J.F.: Epigenetic phenomena and the evolution of plant allopolyploids. Mol. Phylogenetics Evol. 29(3), 365–379 (2003)

    Google Scholar 

  8. Kellogg, E.A., Bennetzen, J.L.: The evolution of nuclear genome structure in seed plants. Am. J. Bot. 91(10), 1709–1725 (2004)

    Google Scholar 

  9. Spielmann, M., Lupiáñez, D. G., Mundlos, S.: Structural variation in the 3D genome. Nat. Rev. Genet. 19(7), 453–467 (2018)

    Google Scholar 

  10. Mishra, A., Hawkins, R.D.: Three-dimensional genome architecture and emerging technologies: looping in disease. Genome Med. 9(1), 87 (2017)

    Google Scholar 

  11. Li, X., Wu, L., Wang, J., Sun, J., Xia, X., Geng, X.: Genome sequencing of rice subspecies and genetic analysis of recombinant lines reveals regional yield- and quality-associated loci. BMC Biol. 16(1), 102 (2018)

    Google Scholar 

  12. Wang, M., Wang, P., Lin, M., Ye, Z., Li, G., Tu, L.: Evolutionary dynamics of 3D genome architecture following polyploidization in cotton. Nat. Plants 4(2), 90 (2018)

    Google Scholar 

  13. Dudchenko, O., Batra, S.S., Omer, A.D., Nyquist, S.K., Hoeger, M., Durand, N.C.: De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds. Science 356(6333), 92 (2017)

    Google Scholar 

  14. Wu, P., Li, T., Li, R., Jia, L., Zhu, P., Liu, Y.: 3D genome of multiple myeloma reveals spatial genome disorganization associated with copy number variations. Nat. Commun. 8(1), 1937 (2017)

    Google Scholar 

  15. Liu, C., Cheng, Y.-J., Wang, J.-W., Weigel, D.: Prominent topologically associated domains differentiate global chromatin packing in rice from Arabidopsis. Nat. Plants 3(9), 742 (2017)

    Google Scholar 

  16. Belton, J.M., Mccord, R.P., Gibcus, J.H., Naumova, N., Zhan, Y., Dekker, J.: Hi–C: a comprehensive technique to capture the conformation of genomes. Methods 58(3), 268–276 (2012)

    Google Scholar 

  17. Imakaev, M., Fudenberg, G., Mccord, R.P., Naumova, N., Goloborodko, A., Lajoie, B.R.: Iterative correction of Hi-C data reveals hallmarks of chromosome organization. Nat. Methods 9(10), 999 (2012)

    Google Scholar 

  18. Grob, S., Grossniklaus, U.: Chromosome conformation capture-based studies reveal novel features of plant nuclear architecture. Curr. Opin. Plant Biol. 36, 149–157 (2017)

    Google Scholar 

  19. Rodriguezgranados, N.Y., Ramirezprado, J.S., Veluchamy, A., Latrasse, D., Raynaud, C., Crespi, M.: Put your 3D glasses on: plant chromatin is on show. J. Exp. Bot. 67(11), 89 (2016)

    Google Scholar 

  20. Wang, C., Liu, C., Roqueiro, D., Grimm, D., Schwab, R., Becker, C.: Genome-wide analysis of local chromatin packing in Arabidopsis thaliana. Genome Res. 25(2), 246–256 (2015)

    Google Scholar 

  21. Mascher, M., Gundlach, H., Himmelbach, A., Beier, S., Twardziok, S.O., Wicker, T.: A chromosome conformation capture ordered sequence of the barley genome. Nature 544(7651), 427 (2017)

    Google Scholar 

  22. van Berkum, N.L., Lieberman-Aiden, E., Williams, L., Imakaev, M., Gnirke, A., Mirny, L.A.: Hi-C: a method to study the three-dimensional architecture of genomes. J. Vis. Exp. Jove 39(39), 292–296 (2010)

    Google Scholar 

  23. FastQC. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/. Accessed 21 Mar 2019

  24. Bolger, A.M., Marc, L., Bjoern, U.: Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30(15), 2114–2120 (2014)

    Google Scholar 

  25. Zhang, Y., An, L., Xu, J., Zhang, B., Zheng, W.J., Hu, M.: Enhancing Hi-C data resolution with deep convolutional neural network HiCPlus. Nat. Commun. 9(1), 750 (2018)

    Google Scholar 

  26. Li, A., Yin, X., Xu, B., Wang, D., Han, J., Yi, W.: Decoding topologically associating domains with ultra-low resolution Hi-C data by graph structural entropy. Nat. Commun. 9(1), 3265 (2018)

    Google Scholar 

  27. Wang, M., Tu, L., Yuan, D., Zhu, D., Shen, C., Li, J.: Reference genome sequences of two cultivated allotetraploid cottons, Gossypium hirsutum and Gossypium barbadense. Nat. Genet. 51, 224 (2018)

    Google Scholar 

  28. Nicolas, S., Nelle, V., Lajoie, B.R., Eric, V., Chen, C.J., Jean-Philippe, V.: HiC-Pro: an optimized and flexible pipeline for Hi-C data processing. Genome Biol. 16(1), 259 (2015)

    Google Scholar 

  29. Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y.C., Laslo, P.: Simple combinations of lineage-determining transcription factors prime -regulatory elements required for macrophage and B cell identities. Mol. Cell 38(4), 576–589 (2010)

    Google Scholar 

  30. Durand, N., Shamim, M., Machol, I., Rao, S.P., Huntley, M., Lander, E.: Juicer provides a one-click system for analyzing loop-resolution Hi-C experiments. Cell Syst. 3(1), 95–98 (2016)

    Google Scholar 

  31. Wingett, S., Ewels, P., Furlan-Magaril, M., Nagano, T., Schoenfelder, S., Fraser, P.: HiCUP: pipeline for mapping and processing Hi-C data. F1000res 4, 1310 (2015)

    Google Scholar 

  32. Schmid, M.W., Grob, S., Grossniklaus, U.: HiCdat: a fast and easy-to-use Hi-C data analysis tool. BMC Bioinform. 16(1), 1–6 (2015)

    Google Scholar 

  33. Serra, F., Baù, D., Goodstadt, M., Castillo, D., Filion, G., Marti-Renom, M.A.: Automatic analysis and 3D-modelling of Hi-C data using TADbit reveals structural features of the fly chromatin colors. PLoS Comput. Biol. 13(7), e1005665 (2017)

    Google Scholar 

  34. Dong, P., Tu, X., Chu, P.-Y., Lü, P., Zhu, N., Grierson, D.: 3D chromatin architecture of large plant genomes determined by local A/B compartments. Mol. Plant 10(12), 1497–1509 (2017)

    Google Scholar 

  35. Zhang, L., Zheng, C.Q., Li, T., Xing, L., Zeng, H., Li, T.T.: Building up a robust risk mathematical platform to predict colorectal cancer. Complexity, 14 (2017)

    Google Scholar 

  36. Yu, M., Ren, B.: The three-dimensional organization of mammalian genomes. Annu. Rev. Cell Dev. Biol. 33(1), 265–289 (2017)

    Google Scholar 

  37. Servant, N., Lajoie, B.R., Nora, E.P., Giorgetti, L., Chen, C.J., Heard, E.: HiTC: exploration of high-throughput ‘C’ experiments. Bioinformatics 28(21), 2843–2844 (2012)

    Google Scholar 

  38. Zhang, L., Xiao, M., Zhou, J., Yu, J.: Lineage-associated underrepresented permutations (LAUPs) of mammalian genomic sequences based on a Jellyfish-based LAUPs analysis application (JBLA). Bioinformatics 34(21), 3624–3630 (2018)

    Google Scholar 

  39. Franke, M., Ibrahim, D.M., Andrey, G., Schwarzer, W., Heinrich, V., Schöpflin, R.: Formation of new chromatin domains determines pathogenicity of genomic duplications. Nature 538(7624), 265–269 (2016)

    Google Scholar 

  40. Weinreb, C., Raphael, B.J.: Identification of hierarchical chromatin domains. Bioinformatics 32(11), 1601 (2015)

    Google Scholar 

  41. Zhang, L., Liu, Y., Wang, M., Wu, Z., Li, N., Zhang, J.: EZH2-, CHD4-, and IDH-linked epigenetic perturbation and its association with survival in glioma patients. J. Mol. Cell Biol. 9(6), 477–488 (2017)

    Google Scholar 

  42. Zhang, L., Qiao, M., Gao, H., Hu, B., Tan, H., Zhou, X.: Investigation of mechanism of bone regeneration in a porous biodegradable calcium phosphate (CaP) scaffold by a combination of a multi-scale agent-based model and experimental optimization/validation. Nanoscale 8(31), 14877–14887 (2016)

    Google Scholar 

  43. Zhang, L., Zhang, S.: Using game theory to investigate the epigenetic control mechanisms of embryo development: Comment on: “Epigenetic game theory: How to compute the epigenetic control of maternal-to-zygotic transition” by Qian Wang et al. Phys. Life Rev. 20, 140–142 (2017)

    Google Scholar 

  44. Shin, H., Shi, Y., Dai, C., Tjong, H., Gong, K., Alber, F.: TopDom: an efficient and deterministic method for identifying topological domains in genomes. Nucleic Acids Res. 44(7), e70–e70 (2016)

    Google Scholar 

  45. Celine, L.L., Delattre, M., Mary-Huard, T., Robin, S.: Two-dimensional segmentation for analyzing Hi-C data. Bioinformatics 30(17), 386–392 (2014)

    Google Scholar 

  46. Emily, C., Qian, B., Rachel, P.M., Lajoie, B.R., Wheeler, B.S., Ralston, E.J.: Condensin-driven remodelling of X chromosome topology during dosage compensation. Nature 523(7559), 240 (2015)

    Google Scholar 

  47. Wang, X.T., Cui, W., Peng, C.: HiTAD: detecting the structural and functional hierarchies of topologically associating domains from chromatin interactions. Nucleic Acids Res. 45(19), e163 (2017)

    Google Scholar 

  48. Mifsud, B., Martincorena, I., Darbo, E., Sugar, R., Schoenfelder, S., Fraser, P.: GOTHiC, a probabilistic model to resolve complex biases and to identify real interactions in Hi-C data. PLoS ONE 12(4), e0174744 (2017)

    Google Scholar 

  49. 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 (2017)

    Google Scholar 

  50. Carty, M., Zamparo, L., Sahin, M., González, A., Pelossof, R., Elemento, O.: An integrated model for detecting significant chromatin interactions from high-resolution Hi-C data. Nat. Commun. 8, 15454 (2017)

    Google Scholar 

  51. Liu, C., Weigel, D.: Chromatin in 3D: progress and prospects for plants. Genome Biol. 16(1), 170 (2015)

    Google Scholar 

  52. Liu, C., Wang, C., Wang, G., Becker, C., Zaidem, M., Weigel, D.: Genome-wide analysis of chromatin packing in Arabidopsis thaliana at single-gene resolution. Genome Res. 26(8), 1057 (2016)

    Google Scholar 

  53. Ay, F., Bailey, T.L., Noble, W.S.: Statistical confidence estimation for Hi-C data reveals regulatory chromatin contacts. Genome Res. 24(6), 999 (2014)

    Google Scholar 

  54. Lun, A.T.L., Smyth, G.K.: diffHic: a Bioconductor package to detect differential genomic interactions in Hi-C data. BMC Bioinform. 16, 1258 (2015)

    Google Scholar 

  55. Hwang, Y.C., Lin, C.F., Valladares, O., Malamon, J., Kuksa, P.P., Zheng, Q.: HIPPIE: a high-throughput identification pipeline for promoter interacting enhancer elements. Bioinformatics 31(8), 1290–1292 (2015)

    Google Scholar 

  56. Durand, N., Robinson, J., Shamim, M., Machol, I., Mesirov, J., Lander, E.: Juicebox provides a visualization system for Hi-C contact maps with unlimited zoom. Cell Syst. 3(1), 99–101 (2016)

    Google Scholar 

  57. Akdemir, K.C., Chin, L.: HiCPlotter integrates genomic data with interaction matrices. Genome Biol. 16(1), 198 (2015)

    Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China [61372138], the National Science and Technology Major Project [2018ZX10201002] and the Chinese Chongqing Distinguish Youth Funding [cstc2014jcyjjq40003].

Author information

Authors and Affiliations

  1. College of Computer Science, Sichuan University, Chengdu, 610065, China

    Xiangyu Yang, Jingtian Zhao & Le Zhang

  2. College of Life Sciences, Sichuan University, Chengdu, 610065, China

    Zhenghao Li & Tao Ma

  3. School of Computer and Information Science, Southwest University, Beibei District, Chongqing, 400715, China

    Pengchao Li

Authors
  1. Xiangyu Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhenghao Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jingtian Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tao Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Pengchao Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Le Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Le Zhang .

Editor information

Editors and Affiliations

  1. Georgia State University, Atlanta, GA, USA

    Zhipeng Cai

  2. Georgia State University, Atlanta, GA, USA

    Pavel Skums

  3. Central South University, Changsha, China

    Min Li

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yang, X., Li, Z., Zhao, J., Ma, T., Li, P., Zhang, L. (2019). The Review of Bioinformatics Tool for 3D Plant Genomics Research. In: Cai, Z., Skums, P., Li, M. (eds) Bioinformatics Research and Applications. ISBRA 2019. Lecture Notes in Computer Science(), vol 11490. Springer, Cham. https://doi.org/10.1007/978-3-030-20242-2_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-20242-2_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20241-5

  • Online ISBN: 978-3-030-20242-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation