During early plant embryogenesis, precursors for all major tissues and stem cells are formed. While several components of the regulatory framework are known, how cell fates are instructed by genome-wide transcriptional activity remains unanswered—in part because of difficulties in capturing transcriptome changes at cellular resolution. Here, we have adapted a two-component transgenic labelling system to purify cell-type-specific nuclear RNA and generate a transcriptome atlas of early Arabidopsis embryo development, with a focus on root stem cell niche formation. We validated the dataset through gene expression analysis, and show that gene activity shifts in a spatio-temporal manner, probably signifying transcriptional reprogramming, to induce developmental processes reflecting cell states and state transitions. This atlas provides the most comprehensive tissue- and cell-specific description of genome-wide gene activity in the early plant embryo, and serves as a valuable resource for understanding the genetic control of early plant development.

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  • 11 January 2018

    In the version of this Resource originally published, the author information was incorrect. Jos R. Wendrich should have had a present address: Department of Plant Biotechnology and Bioinformatics and VIB Center for Plant Systems Biology, Ghent University, Technologiepark 927, 9052 Ghent, Belgium. Mark Boekschoten and Guido J. Hooiveld should have been affiliated to the Nutrition, Metabolism and Genomics Group, Division of Human Nutrition, Wageningen University, 6708 WE Wageningen, The Netherlands. In addition, the version of Supplementary Table 5 originally published with this Resource was not the intended final version and included inaccurate citations to the display items of the Resource, and the file format and extension did not match. These errors have now been corrected in all versions of the Resource.


  1. 1.

    Esua, K. Anatomy of Seed Plants. 2nd edn, 475–495 (Wiley, New York, 1977).

  2. 2.

    van den Berg, C., Willemsen, V., Hendriks, G., Weisbeek, P. & Scheres, B. Short-range control of cell differentiation in the Arabidopsis root meristem. Nature 390, 287–289 (1997).

  3. 3.

    Weigel, D. & Jürgens, G. Stem cells that make stems. Nature 14, 751–754 (2002).

  4. 4.

    Mansfield, S. G. & Briarty, L. G. Early embryogenesis in Arabidopsis thaliana. II. The developing embryo. Can. J. Bot. 69, 461–476 (1991).

  5. 5.

    Jürgens, G. & Mayer, U. in A Colour Atlas of Developing Embryos (ed. Bard, J. B. L.) 7–21 (Wolfe Publishing, London, 1994).

  6. 6.

    Yoshida, S. et al. Genetic control of plant development by overriding a geometric division rule. Dev. Cell 29, 75–87 (2014).

  7. 7.

    Gooh, K. et al. Live-cell imaging and optical manipulation of Arabidopsis early embryogenesis. Dev. Cell 34, 242–251 (2015).

  8. 8.

    Palovaara, J., de Zeeuw, T. & Weijers, D. Tissue and organ initiation in the plant embryo: a first time for everything. Annu. Rev. Cell Dev. Biol. 32, 47–75 (2016).

  9. 9.

    Kerk, N. M., Ceserani, T., Tausta, S. L., Sussex, I. M. & Nelson, T. M. Laser capture microdissection of cells from plant tissues. Plant Physiol 132, 27–35 (2003).

  10. 10.

    Belmonte, M. F. et al. Comprehensive developmental profiles of gene activity in regions and subregions of the Arabidopsis seed. Proc. Natl Acad. Sci. USA 110, E435–E444 (2013).

  11. 11.

    de Vega-Bartol, J. J. et al. Transcriptomic analysis highlights epigenetic and transcriptional regulation during zygotic embryo development of Pinus pinaster. BMC Plant Biol. 13, 123 (2013).

  12. 12.

    Venglat, P. et al. Gene expression profiles during embryo development in Brassica napus. Plant Breeding 132, 514–522 (2013).

  13. 13.

    Chen, J. et al. Dynamic transcriptome landscape of maize embryo and endosperm development. Plant Physiol. 166, 252–264 (2014).

  14. 14.

    Itoh, J.-I. et al. Genome-wide analysis of spatiotemporal gene expression patterns during early embryogenesis in rice. Development 143, 1217–1227 (2016).

  15. 15.

    Casson, S., Spencer, M., Walker, K. & Lindsey, K. Laser capture microdissection for the analysis of gene expression during embryogenesis of Arabidopsis. Plant J. 42, 111–123 (2005).

  16. 16.

    Spencer, M. W. B., Casson, S. A. & Lindsey, K. Transcriptional profiling of the Arabidopsis embryo. Plant Physiol. 143, 924–940 (2007).

  17. 17.

    Le, B. H. et al. Global analysis of gene activity during Arabidopsis seed development and identification of seed-specific transcription factors. Proc. Natl Acad. Sci. USA 107, 8063–8070 (2010).

  18. 18.

    Xiang, D. et al. Genome-wide analysis reveals gene expression and metabolic network dynamics during embryo development in Arabidopsis. Plant Physiol. 156, 346–356 (2011).

  19. 19.

    Autran, D. et al. Maternal epigenetic pathways control parental contributions to Arabidopsis early embryogenesis. Cell 145, 707–719 (2011).

  20. 20.

    Nodine, M. D. & Bartel, D. P. Maternal and paternal genomes contribute equally to the transcriptome of early plant embryos. Nature 482, 94–97 (2012).

  21. 21.

    Nodine, M. D. & Bartel, D. P. MicroRNAs prevent precocious gene expression and enable pattern formation during plant embryogenesis. Genes Dev. 24, 2678–2692 (2010).

  22. 22.

    Birnbaum, K. et al. A gene expression map of the Arabidopsis root. Science 302, 1956–1960 (2003).

  23. 23.

    Zhang, C., Barthelson, R. A., Lambert, G. M. & Galbraith, D. W. Global characterization of cell-specific gene expression through fluorescence-activated sorting of nuclei. Plant Physiol. 147, 30–40 (2008).

  24. 24.

    Zanetti, M. E., Chang, I.-F., Gong, F., Galbraith, D. W. & Bailey-Serres, J. Immunopurification of polyribosomal complexes of Arabidopsis for global analysis of gene expression. Plant Physiol. 138, 624–635 (2005).

  25. 25.

    Mustroph, A. et al. Profiling translatomes of discrete cell populations resolves altered cellular priorities during hypoxia in Arabidopsis. Proc. Natl Acad. Sci USA 106, 18843–18848 (2009).

  26. 26.

    Deal, R. B. & Henikoff, S. A simple method for gene expression and chromatin profiling of individual cell types within a tissue. Dev. Cell 18, 1030–1040 (2010).

  27. 27.

    Lin, S.-Y. et al. Profiling of translatomes of in vivo-grown pollen tubes reveals genes with roles in micropylar guidance during pollination in Arabidopsis. Plant Cell 26, 602–618 (2014).

  28. 28.

    Slane, D. Cell type-specific transcriptome analysis in the early Arabidopsis thaliana embryo. Development 141, 4831–4840 (2014).

  29. 29.

    Yadav, R. K., Tavakkoli, M., Xie, M., Girke, T. & Reddy, G. V. A high-resolution gene expression map of the Arabidopsis shoot meristem stem cell niche. Development 141, 2735–2744 (2014).

  30. 30.

    Adrian, J. et al. Transcriptome dynamics of the stomatal lineage: Birth, amplification, and termination of a self-renewing population. Dev. Cell 33, 107–118 (2015).

  31. 31.

    Antoniadi, I. et al. Cell-type-specific cytokinin distribution within the Arabidopsis primary root apex. Plant Cell 27, 1955–1967 (2015).

  32. 32.

    Vragović, K. et al. Translatome analyses capture of opposing tissue-specific brassinosteroid signals orchestrating root meristem differentiation. Proc. Natl Acad. Sci. USA 112, 923–928 (2015).

  33. 33.

    Palovaara, J., Saiga, S. & Weijers, D. Transcriptomics approaches in the early Arabidopsis embryo. Trends Plant Sci. 18, 514–521 (2013).

  34. 34.

    Foley, S. W. et al. A global view of RNA–protein interactions identifies post-transcriptional regulators of root hair cell fate. Dev. Cell 41, 204–220 (2017).

  35. 35.

    Park, K. et al. DNA demethylation is initiated in the central cells of Arabidopsis and rice. Proc. Natl Acad. Sci. USA 113, 15138–15143 (2016).

  36. 36.

    Moreno-Romero, J., Santos-González, J., Hennig, L. & Köhler, C. Applying the INTACT method to purify endosperm nuclei and to generate parental-specific epigenome profiles. Nat. Protoc. 12, 238–254 (2017).

  37. 37.

    Ron, M. et al. Hairy root transformation using Agrobacterium rhizogenes as a tool for exploring cell type-specific gene expression and function using tomato as a model. Plant Physiol. 166, 455–469 (2014).

  38. 38.

    Henry, G. L., Davis, F. P., Picard, S. & Eddy, S. R. Cell type-specific genomics of Drosophila neurons. Nucleic Acids Res. 40, 9691–9704 (2012).

  39. 39.

    Steiner, F. A., Talbert, P. B., Kasinathan, S., Deal, R. B. & Henikoff, S. Cell-type-specific nuclei purification from whole animals for genome-wide expression and chromatin profiling. Genome Res. 22, 766–777 (2012).

  40. 40.

    Amin, N. M. et al. Proteomic profiling of cardiac tissue by isolation of nuclei tagged in specific cell types (INTACT). Development 141, 962–973 (2014).

  41. 41.

    Ueda, M., Zhang, Z. & Laux, T. Transcriptional activation of Arabidopsis axis patterning genes WOX8/9 links zygote polarity to embryo development. Dev. Cell 20, 264–270 (2011).

  42. 42.

    Wysocka-Diller, J. W., Helariutta, Y., Fukaki, H., Malamy, J. E. & Benfey, P. N. Molecular analysis of SCARECROW function reveals a radial patterning mechanism common to root and shoot. Development 127, 595–603 (2000).

  43. 43.

    Beckett, D., Kovaleva, E. & Schatz, P. J. A minimal peptide substrate in biotin holoenzyme synthetase-catalyzed biotinylation. Protein Sci. 8, 921–929 (1999).

  44. 44.

    Deal, R. B. & Henikoff, S. The intact method for cell type-specific gene expression and chromatin profiling in Arabidopsis thaliana. Nat. Protoc. 6, 56–68 (2011).

  45. 45.

    Weijers, D. et al. An Arabidopsis Minute-like phenotype caused by a semi-dominant mutation in a RIBOSOMAL PROTEIN S5 gene. Development 128, 4289–4299 (2001).

  46. 46.

    Moore, M. J. & Proudfoot, N. J. Pre-mRNA processing reaches back to transcription and ahead to translation. Cell 136, 688–700 (2009).

  47. 47.

    Hocine, S., Singer, R. H. & Grünwald, D. RNA processing and export. Cold Spring Harb. Perspect. Biol. 2, a000752 (2010).

  48. 48.

    Barthelson, R. A., Lambert, G. M., Vainer, C., Lynch, R. M. & Gailbraith, D. W. Comparison of the contributions of the nuclear and cytosplasmic compartments to global gene expression in human cells. BMC Genom. 8, 340 (2007).

  49. 49.

    Grindberg, R. V. et al. RNA-sequencing from single nuclei. Proc. Natl Acad. Sci. USA 110, 19802–19807 (2013).

  50. 50.

    Clément-Ziza, M. et al. Evaluation of methods for amplification of picogram amounts of total RNA for whole genome expression profiling. BMC Genom. 10, 246 (2009).

  51. 51.

    Morse, A. M., Carballo, V., Baldwin, D. A., Taylor, C. G. & McIntyre, L. M. Comparison between NuGEN’s WT-OVATION PICO and One-Direct Amplification Systems. J. Biomol. Tech. 21, 141–147 (2010).

  52. 52.

    Lamesch, P. et al. Using the Arabidopsis information resource (TAIR) to find information about Arabidopsis genes. Curr. Protoc. Bioinform. 30, 1.11.1–1.11.51 (2002).

  53. 53.

    Schon, M. A. & Nodine, M. D. Widespread contamination of Arabidopsis embryo and endosperm transcriptome data sets. Plant Cell 29, 608–617 (2017).

  54. 54.

    Khan, D. et al. Transcriptome atlas of the Arabidopsis funiculus – a study of maternal seed subregions. Plant J. 82, 41–53 (2015).

  55. 55.

    Liu, Y. et al. Direct evidence that suspensor cells have embryogenic potential that is suppressed by the embryo proper during normal embryogenesis. Proc. Natl Acad. Sci. USA 112, 12432–12437 (2015).

  56. 56.

    Radoeva, T., ten Hove, C. A., Saiga, S. & Weijers, D. Molecular characterization of Arabidopsis GAL4/UAS enhancer trap lines identifies novel cell type-specific promoters. Plant Physiol. 171, 1169–1181 (2016).

  57. 57.

    Sarkar, A. K. et al. Conserved factors regulate signalling in Arabidopsis thaliana shoot and root stem cell organizers. Nature 446, 811–814 (2007).

  58. 58.

    Schlereth, A. et al. MONOPTEROS controls embryonic root initiation by regulating a mobile transcription factor. Nature 464, 913–916 (2010).

  59. 59.

    De Rybel, B. et al. A BHLH complex controls embryonic vascular tissue establishment and indeterminate growth in Arabidopsis. Dev. Cell 24, 426–437 (2013).

  60. 60.

    De Rybel, B. et al. Integration of growth and patterning during vascular tissue formation in Arabidopsis. Science 345, 1255215 (2014).

  61. 61.

    Crawford, B. C. W. et al. Genetic control of distal stem cell fate within root and embryonic meristems. Science 347, 655–659 (2015).

  62. 62.

    Clough, S. J. & Bent, A. F. Floral dip: A simplified method for agrobacterium-mediated transformation of Arabidopsis thaliana. Plant J. 16, 735–743 (1998).

  63. 63.

    De Rybel, B. et al. A versatile set of ligation-independent cloning vectors for functional studies in plants. Plant Physiol. 156, 1292–1299 (2011).

  64. 64.

    Wendrich, J. R., Liao, C. Y., van den Berg, W. A., De Rybel, R. & Weijers, D. Ligation-independent cloning for plant research. Methods Mol. Biol. 1284, 421–431 (2015).

  65. 65.

    Llavata-Peris, C., Lokerse, A., Möller, B., De Rybel, B. & Weijers, D. in Plant Organogenesis: Methods and Protocols (ed. De Smet, I.) 137–148 (Humana Press, Totowa, New Jersey, 2013).

  66. 66.

    Raissig, M. T., Gagliardini, V., Jaenisch, J., Grossniklaus, U. & Baroux, C. Efficient and rapid isolation of early-stage embryos from Arabidopsis thaliana seeds. J. Vis. Exp 76, e50371 (2013).

  67. 67.

    Lin, K. et al. MADMAX – Management and analysis database for multiple ~omics experiments. J Integr. Bioinform. 8, 160 (2011).

  68. 68.

    Dai, M. et al. Evolving gene/transcript definitions significantly alter the interpretation of genechip data. Nucleic Acids Res. 33, e175 (2005).

  69. 69.

    Irizarry, R. A. et al. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4, 249–264 (2003).

  70. 70.

    Sartor, M. A. et al. Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments. BMC Bioinform. 7, 1–17 (2006).

  71. 71.

    Phipson, B., Lee, S., Majewski, I. J., Alexander, W. S. & Smyth, G. K. Robust hyperparameter estimation protects against hypervariable genes and improves power to detect differential expression. Ann. App. Stat. 10, 946–963 (2016).

  72. 72.

    Storey, J. D. & Tibshirani, R. Statistical significance for genomewide studies. Proc. Natl Acad. Sci. USA 100, 9440–9445 (2003).

  73. 73.

    Orlando, D. A., Brady, S. M., Koch, J. D., Dinneny, J. R., Benfey, P. N. in Plant Systems Biology (ed. Belostotsky, A. D.) 57–77 (Humana Press, Totowa, New Jersey, 2009).

  74. 74.

    Du, Z., Zhou, X., Ling, Y., Zhang, Z. & Su, Z. agrigo: a GO analysis toolkit for the agricultural community. Nucleic Acids Res. 38, W64–W70 (2010).

  75. 75.

    Palaniswamy, S. K. et al. AGRIS and AtRegNet. a platform to link cis-regulatory elements and transcription factors into regulatory networks. Plant Physiol. 140, 818–829 (2006).

  76. 76.

    Saiga, S. et al. The Arabidopsis OBERON1 and OBERON2 genes encode plant homeodomain finger proteins and are required for apical meristem maintenance. Development 135, 1751–1759 (2008).

  77. 77.

    Hellemans, J., Mortier, G., De Paepe, A., Speleman, F. & Vandesompele, J. qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. Genome Biol. 8, 1–14 (2007).

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The authors thank T. Laux, R. Deal and S. Henikoff for sharing materials. Further, the authors thank the students M. Geerlings, D. van der Plaat, E. Asamoah Gyimah, M. Goranova, A. Kuhn, L. van der Bent, I. Papakosta, S. Thomaidou, S. Hedžet and K. Heidemeyer for their contributions. This study was supported by the Federation of European Biochemical Societies (FEBS) (J.P.), ERA-CAPS project EURO-PEC (grant number 849.13.006) and the European Research Council (ERC Starting Grant ‘CELLPATTERN’; contract number 281573 to D.W.).

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Author notes

  1. Joakim Palovaara and Shunsuke Saiga contributed equally to this work.


  1. Laboratory of Biochemistry, Wageningen University, 6708 WE, Wageningen, The Netherlands

    • Joakim Palovaara
    • , Shunsuke Saiga
    • , Jos R. Wendrich
    • , Nicole van ‘t Wout Hofland
    • , J. Paul van Schayck
    • , Friederike Hater
    • , Sumanth Mutte
    • , Jouke Sjollema
    •  & Dolf Weijers
  2. Nutrition, Metabolism and Genomics Group, Division of Human Nutrition, Wageningen University, 6708 WE, Wageningen, The Netherlands

    • Mark Boekschoten
    •  & Guido J. Hooiveld
  3. Department of Plant Biotechnology and Bioinformatics and VIB Center for Plant Systems Biology, Ghent University, Technologiepark 927, 9052, Ghent, Belgium

    • Jos R. Wendrich


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D.W. conceived the study; J.P., S.S., J.R.W. and D.W. designed research; S.S. generated INTACT lines; J.P. and N.v.W.H. optimized and adapted experimental set-up; J.P., S.S. and J.R.W. performed INTACT; F.H. and J.P. performed nuclear versus cellular RNA comparison; M.B., G.J.H. and J.P. performed transcriptomic profiling and analysed data with support from S.M.; J.P., S.S., J.R.W., J.P.v.S. and J.S. validated expression patterns; J.P.v.S. and J.P. designed and developed the AlBERTO browser; J.P. and D.W. wrote the paper with input from all other authors.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Dolf Weijers.

Supplementary information

  1. Supplementary Information

    Supplementary Figures 1–12, Supplementary Tables 1–3, Supplementary References.

  2. Life Sciences Reporting Summary

  3. Supplementary Table 4

    Linear correlation and residual analysis of nuclear and cellular whole-genome expression.

  4. Supplementary Table 5

    The atlas data set.

  5. Supplementary Table 6

    Comparison of seed tissue contamination in INTACT- and FANS-generated nuclear transcriptomes.

  6. Supplementary Table 7

    List of primers used for cloning and quantitative RT-PCR.

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