Dr Scott   Berry
Senior Lecturer

Dr Scott Berry

  • 2016 Ph.D. Plant Science and Microbiology. John Innes Centre, Norwich, U.K.
  • 2010 B.Sc. (Hons.) Theoretical Physics, The University of Western Australia.
  • 2007 B.Sc. Theoretical Physics and Biochemistry, The University of Adelaide.
Medicine & Health
Single Molecule Science Lab

Scott has a background in both Theoretical Physics and Molecular Biology and currently leads a research group in Single Molecule Science at the University of New South Wales. Scott studied his PhD at the John Innes Centre with Caroline Dean and Martin Howard, combining theoretical and experimental biology approaches to understand mechanisms of epigenetic memory in Arabidopsis thaliana. He then moved to Switzerland as a HFSP postdoctoral fellow, working with Lucas Pelkmans at the University of Zurich. There, he shifted model systems from plants to mammalian cells, and became immersed in the wonderful world of modern single-cell biology. Scott is interested in using quantitative techniques particularly microscopy and mathematical modelling to pursue a deeper understanding of how individual cells regulate the expression of the genome

+61-2-9385 0790
Single Molecule Science - EMBL Australia Lowy Cancer Research Centre - Level 3
  • Journal articles | 2021
    Müller M; Pelkmans L; Berry S, 2021, 'High content genome-wide siRNA screen to investigate the coordination of cell size and RNA production', Scientific Data, vol. 8, http://dx.doi.org/10.1038/s41597-021-00944-5
    Journal articles | 2021
    Müller M; Avar M; Heinzer D; Emmenegger M; Aguzzi A; Pelkmans L; Berry S, 2021, 'Author Correction: High content genome-wide siRNA screen to investigate the coordination of cell size and RNA production (Scientific Data, (2021), 8, 1, (162), 10.1038/s41597-021-00944-5)', Scientific Data, vol. 8, pp. 313, http://dx.doi.org/10.1038/s41597-021-01096-2
    Journal articles | 2017
    Berry S; Dean C; Howard M, 2017, 'Slow Chromatin Dynamics Allow Polycomb Target Genes to Filter Fluctuations in Transcription Factor Activity', Cell Systems, vol. 4, pp. 445 - 457.e8, http://dx.doi.org/10.1016/j.cels.2017.02.013
    Journal articles | 2017
    Berry S; Rosa S; Howard M; Bühler M; Dean C, 2017, 'Disruption of an RNA-binding hinge region abolishes LHP1-mediated epigenetic repression', Genes and Development, vol. 31, pp. 2115 - 2120, http://dx.doi.org/10.1101/gad.305227.117
    Journal articles | 2017
    Yang H; Berry S; Olsson TSG; Hartley M; Howard M; Dean C, 2017, 'Distinct phases of Polycomb silencing to hold epigenetic memory of cold in Arabidopsis', Science, vol. 357, pp. 1142 - 1145, http://dx.doi.org/10.1126/science.aan1121
    Journal articles | 2015
    Berry S; Dean C, 2015, 'Environmental perception and epigenetic memory: Mechanistic insight through FLC', Plant Journal, vol. 83, pp. 133 - 148, http://dx.doi.org/10.1111/tpj.12869
    Journal articles | 2015
    Berry S; Hartley M; Olsson TSG; Dean C; Howard M, 2015, 'Local chromatin environment of a Polycomb target gene instructs its own epigenetic inheritance', eLife, vol. 4, http://dx.doi.org/10.7554/eLife.07205
    Journal articles | 2014
    King JD; Berry S; Clarke BR; Morris RJ; Whitfield C, 2014, 'Lipopolysaccharide O antigen size distribution is determined by a chain extension complex of variable stoichiometry in Escherichia coli O9a', Proceedings of the National Academy of Sciences of the United States of America, vol. 111, pp. 6407 - 6412, http://dx.doi.org/10.1073/pnas.1400814111
    Journal articles | 2012
    Richards D; Berry S; HOward M, 2012, 'Illustrations of mathematical modeling in biology: Epigenetics, meiosis, and an outlook', Cold Spring Harbor Symposia on Quantitative Biology, vol. 77, pp. 175 - 181, http://dx.doi.org/10.1101/sqb.2013.77.015941
    Journal articles | 2011
    Berry SD; Wang JB, 2011, 'Two-particle quantum walks: Entanglement and graph isomorphism testing', Physical Review A - Atomic, Molecular, and Optical Physics, vol. 83, http://dx.doi.org/10.1103/PhysRevA.83.042317
    Journal articles | 2011
    Berry SD; Bourke P; Wang JB, 2011, 'QwViz: Visualisation of quantum walks on graphs', Computer Physics Communications, vol. 182, pp. 2295 - 2302, http://dx.doi.org/10.1016/j.cpc.2011.06.002
    Journal articles | 2010
    Berry SD; Wang JB, 2010, 'Quantum-walk-based search and centrality', Physical Review A - Atomic, Molecular, and Optical Physics, vol. 82, http://dx.doi.org/10.1103/PhysRevA.82.042333
  • Preprints |
    Berry S; Müller M; Pelkmans L, Nuclear RNA concentration coordinates RNA production with cell size in human cells, http://dx.doi.org/10.1101/2021.05.17.444432

  • 2019 Early-career researcher award (Lorne genome conference, Australia)
  • 2017-2021 HFSP Long Term Fellowship (University of Zurich, Switzerland)
  • 2017-2019 EMBO Long Term Fellowship (University of Zurich, Switzerland)
  • 2016 John Innes Foundation prize for excellence in scientific research – annual Ph.D. thesis prize (Norwich, U.K.)
  • 2014 EMBO Short Term Fellowship (FMI, Basel, Switzerland)
  • 2011-2015 John Innes Foundation Rotation PhD Scholarship
  • 2010 Maslen Physics Prize (University of Western Australia)
  • 2010 John and Patricia Farrant Scholarship
  • 2007 Silver Bragg Medal (Australian Institute of Physics)
  • 2007 R.K. Morton Scholarship (University of Adelaide – Biochemistry)
  • 2007 Angus Hurst Prize (University of Adelaide – Physics)

Quantitative regulation of gene expression in single cells

We are interested in the mechanisms used by cells to regulate gene-specific and global RNA abundance – ranging from epigenetic memory and cellular decision-making to global RNA metabolism in the context of cellular physiology. We seek to generate a quantitative understanding of these processes.

Our research methodology is a combination of ‘top-down’ (data-driven) and ‘bottom-up’ (hypothesis-driven) approaches. We make extensive use of high-throughput microscopy and automated image analysis, which enables detailed measurement of quantitative cellular phenotypes (for example, the abundance and localisations of specific proteins or RNAs) across large cell populations. Resulting datasets are then analysed using a variety of methods from data science. We complement these image-based approaches with functional genomics experiments, based on next-generation sequencing – providing exquisite genomic resolution, and use perturbation experiments including genome and epigenome-editing to test specific hypotheses.