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Department of Biochemistry profile

Dr Chris Brown

PositionSenior Lecturer
DepartmentDepartment of Biochemistry
QualificationsMSc PhD(Otago)
Research summaryRegulatory genomics
TeachingGenetics and Biochemistry: BIOC 221, GENE 223, BIOC 352, BIOC 451, GENE 400, PLBI 401, MICN 201 (Genetics, Blood), MICN 301 (Genetics).

Research

Regulatory Genomics

The identification of novel regulatory elements in mRNA and noncoding RNA sequences

Translational control is a critical type of regulation of gene expression in all species. We are investigating this regulation in human, viral, plant, microbial and fungal systems.

These projects involve the use of both computer (list of Brown group bioinformatic tools) and experimental tools to test for new types of translational control mechanisms. The recent availability of large amounts of sequence data, particularly complete genome sequences and transcriptomes and proteomes, has revolutionised the study of gene expression in many organisms.

For human studies, we take the approach of generating hypotheses regarding translational control from bioinformatics, then testing the ideas experimentally in tissue culture cells. We have developed new assays which utilise the power of modern microscopic, cell biological, and genomic techniques. The elements investigated include stability / instabilty elements e.g. Iron Responsive Elements ana AU rich elements and those for mRNA localisation in mammalian and yeast cells.

In human viral pathogens, for example HBV, we are focussing on discovering critical regulatory elements that may provide antiviral targets.

It is now possible to generate genome scale transcriptome and proteomic datasets for human cells. A striking finding from analysis of these studies is that the level of an mRNA typically predicts no more than 40% of the abundance of protein. This correlation represents the overall figure for all genes. We have developed a bioinformatic approach that distinguishes broad classes of genes using calculated translation efficiency (Translation Efficiency).

We are currently generating and analysing genome scale expression data from diverse species (RNA-Seq, microarrays) and proteomic data (pSILAC). These systems biology studies utilise whole transcriptome reference guided and de novo assembly and bioinformatic analysis of quantitative expression. They are aimed at finding not only changes in protein coding genes but also in regulatory RNAs and elements in mRNAs.

Databases and tools for cis-regulatory translational control element discovery in mRNAs and viral genomes

Our first tool (TransTerm) began over 20 years ago, it contains data related to translation. More recently a complementary database of known translational control elements has been established and included (TransTerm). We have recently extended this to include a curated database of structured Cis-regulatory RNA elements (CisRegRNA, 2012), and putative novel elements using CisRNA-SVM. Virus research tools and databases include HBVRegDB, VirusRegDB, MLOGD, CRISPRTarget.

Software, web servers, and datasets from the Brown group are available though our servers, by download, or through collaborators.

Genome annotation using comparative genomics

We are using high throughput RNA-Seq analysis to identify and characterise both mRNAs and ncRNAs from several diverse organisms, in collaboration with other groups (see collaborations). These studies include aiming to identify coding and non-coding RNAs and regulatory elements in these genomes. Applications include - plant pathogen and endophyte interactions, methanogen genomes, and pathogenic viral genomes and viromes.

Potential PhD (Doctoral) or MSc projects

There are several exciting projects available to students including Bioinformatics, Virology or Cell Biology or a mix of these. The balance of the approach would depend on the skills and interests of the person (e.g. Bioinformatics, Genetics, Genomics). These could be supervised in a collaboration (e.g. with CRIs or other Otago Researchers). Please send a CV including academic references and reason why you are interested in that project to me.

Indicative projects (for 2017–2018)

  • Discovery of viruses in metagenomic and virome sequences
  • Discovery of regulatory elements affecting human gene expression
  • Genomic and transcriptomic approaches to reducing agricultural greenhouse gas emissions (jointly supervised with collaborators).
  • Discovery of key features of the bacterial adaptive immune system (CRISPR-Cas). Jointly supervised by Dr Peter Fineran (Microbiology and Immunology).
  • Plant/Fungal interactions and genomics (with David Orlovich, Botany)

More information on fellowships and scholarships can be found on the University of Otago postgraduate pages.

Current collaborations

  • Artemio Mendoza (Bio-Protection, Lincoln) Genomics of fungal-plant interactions - Gene expression bioinformatics. Fungal non-coding RNAs.
  • Roger Hellens (QUT) and Richard MacKnight (Otago). Regulation of gene expression - mRNA analysis.
  • Torsten Kleffmann (Otago, Centre for Protein Research). The relationship between mRNA and protein levels in cells. High-throughput proteomic and RNA-Seq approaches.
  • Peter Fineran (Otago, Microbiology). The discovery of CRISPR elements in bacterial genomes and their targets in viral (bacteriophage) genomes.
  • Shannon Clark (AgResearch) and Prof Neil Gemmell (Anatomy). Greenshell Mussel genomics, Perna canalicula (Taonga).
  • David Orlovich and Tina Summerfield (Botany) New Zealand native mushroom genomes (Taonga).
  • Dan Garama (Monash) New Zealand Kina genomics, Evechinus chloroticus (Taonga)
  • Abigail Smith (Marine Science) Bryzoan genomics
  • Herve Le Hir (Paris) Gene Expression
  • Peter Revill (Melbourne) HBV expression

Thanks to past and present funding agencies

  • Dunedin School of Medicine Bequest Funds
  • University of Otago Research Grants
  • Human Frontier Science Organisation
  • Health Research Council
  • Lotteries Health
  • The Marsden Fund
  • Joint Genome Institute

I am interested in contacts from potential collaborators, postdoctoral fellows, and graduate students.

Kinda Genome Project (A New Zealand Taonga)

Publications

Lim, C. S., & Brown, C. (2017). A new class of ribozyme from hepatitis B virus. FEBS Journal, 284(8), 1182-1183. doi: 10.1111/febs.14062

Schmoll, M., Dattenböck, C., Carreras-Villaseñor, N., Mendoza-Mendoza, A., Tisch, D., Alemán, M. I., … Brown, C., … Herrara-Estrella, A. (2016). The genomes of three uneven siblings: Footprints of the lifestyles of three Trichoderma species. Microbiology & Molecular Biology Reviews, 80(1), 205-327. doi: 10.1128/mmbr.00040-15

Bond, D. M., Albert, N. W., Lee, R. H., Gillard, G. B., Brown, C. M., Hellens, R. P., & Macknight, R. C. (2016). Infiltration-RNAseq: Transcriptome profiling of agrobacterium-mediated infiltration of transcription factors to discover gene function and expression networks in plants. Plant Methods, 12, 41. doi: 10.1186/s13007-016-0141-7

Staals, R. H. J., Jackson, S. A., Biswas, A., Brouns, S. J. J., Brown, C. M., & Fineran, P. C. (2016). Interference-driven spacer acquisition is dominant over naive and primed adaptation in a native CRISPR–Cas system. Nature Communications, 7, 12853. doi: 10.1038/ncomms12853

Lim, C. S., & Brown, C. M. (2016). Hepatitis B virus nuclear export elements: RNA stem-loop α and β, key parts of the HBV post-transcriptional regulatory element. RNA Biology, 13(9), 743-747. doi: 10.1080/15476286.2016.1166330

Chapter in Book - Research

Biswas, A., Fineran, P. C., & Brown, C. M. (2015). Computational detection of CRISPR/crRNA targets. In M. Lundgren, E. Charpentier & P. C. Fineran (Eds.), CRISPR: Methods in molecular biology (Vol. 1311). (pp. 77-89). Springer. doi: 10.1007/978-1-4939-2687-9_5

Stevens, S. G., & Brown, C. M. (2014). Bioinformatic methods to discover Cis-regulatory elements in mRNAs. In N. K. Kasabov (Ed.), Springer handbook of bio-/neuro-informatics. (pp. 151-169). Dordrecht, The Netherlands: Springer. doi: 10.1007/978-3-642-30574-0_10

Brown, C., Schreiber, M. J., Chapman (Nee Hobbs), B., & Jacobs, G. H. (2000). Information Science and Bioinformatics. In Future Directions for Intelligent Systems and Information Science. (pp. 251-287). Heidelberg, Germany: Springer-Verlag.

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Journal - Research Article

Schmoll, M., Dattenböck, C., Carreras-Villaseñor, N., Mendoza-Mendoza, A., Tisch, D., Alemán, M. I., … Brown, C., … Herrara-Estrella, A. (2016). The genomes of three uneven siblings: Footprints of the lifestyles of three Trichoderma species. Microbiology & Molecular Biology Reviews, 80(1), 205-327. doi: 10.1128/mmbr.00040-15

Lim, C. S., & Brown, C. M. (2016). Hepatitis B virus nuclear export elements: RNA stem-loop α and β, key parts of the HBV post-transcriptional regulatory element. RNA Biology, 13(9), 743-747. doi: 10.1080/15476286.2016.1166330

Staals, R. H. J., Jackson, S. A., Biswas, A., Brouns, S. J. J., Brown, C. M., & Fineran, P. C. (2016). Interference-driven spacer acquisition is dominant over naive and primed adaptation in a native CRISPR–Cas system. Nature Communications, 7, 12853. doi: 10.1038/ncomms12853

Bond, D. M., Albert, N. W., Lee, R. H., Gillard, G. B., Brown, C. M., Hellens, R. P., & Macknight, R. C. (2016). Infiltration-RNAseq: Transcriptome profiling of agrobacterium-mediated infiltration of transcription factors to discover gene function and expression networks in plants. Plant Methods, 12, 41. doi: 10.1186/s13007-016-0141-7

Hellens, R. P., Brown, C. M., Chisnall, M. A. W., Waterhouse, P. M., & Macknight, R. C. (2016). The emerging world of small ORFs. Trends in Plant Science, 21(4), 317-328. doi: 10.1016/j.tplants.2015.11.005

Biswas, A., Staals, R. H. J., Morales, S. E., Fineran, P. C., & Brown, C. M. (2016). CRISPRDetect: A flexible algorithm to define CRISPR arrays. BMC Genomics, 17(1), 356. doi: 10.1186/s12864-016-2627-0

Davies, C., Brown, C. M., Westphal, D., Ward, J. M., & Ward, V. K. (2015). Murine norovirus replication induces a G0/G1 cell cycle arrest in asynchronous growing cells. Journal of Virology, 89(11), 6057-6066. doi: 10.1128/jvi.03673-14

Waugh, E., Chen, A., Baird, M. A., Brown, C. M., & Ward, V. K. (2014). Characterization of the chemokine response of RAW264.7 cells to infection by murine norovirus. Virus Research, 181, 27-34. doi: 10.1016/j.virusres.2013.12.025

Gillard, G. B., Garama, D. J., & Brown, C. M. (2014). The transcriptome of the NZ endemic sea urchin Kina (Evechinus chloroticus). BMC Genomics, 15, 45. doi: 10.1186/1471-2164-15-45

Biswas, A., Fineran, P. C., & Brown, C. M. (2014). Accurate computational prediction of the transcribed strand of CRISPR noncoding RNAs. Bioinformatics, 30(13), 1805-1813. doi: 10.1093/bioinformatics/btu114

Chen, A., T-Thienprasert, N. P., & Brown, C. M. (2014). Prospects for inhibiting the post-transcriptional regulation of gene expression in hepatitis B virus. World Journal of Gastroenterology, 20(25), 7993-8004. doi: 10.3748/wjg.v20.i25.7993

Biswas, A., & Brown, C. M. (2014). Scan for Motifs: A webserver for the analysis of post-transcriptional regulatory elements in the 3’ untranslated regions (3’ UTRs) of mRNAs. BMC Bioinformatics, 15, 174. doi: 10.1186/1471-2105-15-174

Stevens, S. G., & Brown, C. M. (2013). In silico estimation of translation efficiency in human cell lines: Potential evidence for widespread translational control. PLoS ONE, 8(2), e57625. doi: 10.1371/journal.pone.0057625

Biswas, A., Gagnon, J. N., Brouns, S. J. J., Fineran, P. C., & Brown, C. M. (2013). CRISPRTarget: Bioinformatic prediction and analysis of crRNA targets. RNA Biology, 10(5), 817-827. doi: 10.4161/rna.24046

Chen, X. S., & Brown, C. M. (2012). Computational identification of new structured cis-regulatory elements in the 3’-untranslated region of human protein coding genes. Nucleic Acids Research, 40(18), 8862-8873. doi: 10.1093/nar/gks684

Pilbrow, A. P., Folkersen, L., Pearson, J. F., Brown, C. M., McNoe, L., Wang, N. M., … Black, M. A., Troughton, R. W., Richards, A. M., … Cameron, V. A. (2012). The chromosome 9p21.3 coronary heart disease risk allele is associated with altered gene expression in normal heart and vascular tissues. PLoS ONE, 7(6), e39574. doi: 10.1371/journal.pone.0039574

Lange, S. J., Maticzka, D., Möhl, M., Gagnon, J. N., Brown, C. M., & Backofen, R. (2012). Global or local? Predicting secondary structure and accessibility in mRNAs. Nucleic Acids Research, 40(12), 5215-5226. doi: 10.1093/nar/gks181

Chen, A., & Brown, C. (2012). Distinct families of cis-acting RNA replication epsilon elements from hepatitis B viruses. RNA Biology, 9(2), 130-136. doi: 10.4161/rna.9.2.18649

Stevens, S. G., Gardner, P. P., & Brown, C. (2011). Two covariance models for iron-responsive elements. RNA Biology, 8(5), 792-801. doi: 10.4161/rna.8.5.16037

Panjaworayan, N., & Brown, C. M. (2011). Effects of HBV genetic variability on RNAi strategies. Hepatitis Research & Treatment, 2011, 367908. doi: 10.1155/2011/367908

Milev, M. P., Brown, C. M., & Mouland, A. J. (2010). Live cell visualization of the interactions between HIV-1 Gag and the cellular RNA-binding protein Staufen1. Retrovirology, 7, 41. doi: 10.1186/1742-4690-7-41

Panjaworayan, N., Payungporn, S., Poovorawan, Y., & Brown, C. M. (2010). Identification of an effective siRNA target site and functional regulatory elements, within the hepatitis B virus posttranscriptional regulatory element. Virology Journal, 7, 216. doi: 10.1186/1743-422x-7-216

Jacobs, G. H., Chen, A., Stevens, S. G., Stockwell, P. A., Black, M. A., Tate, W. P., & Brown, C. M. (2009). Transterm: A database to aid the analysis of regulatory sequences in mRNAs. Nucleic Acids Research, 37(Database issue), D72-D76. doi: 10.1093/nar/gkn763

Panjaworayan, N., Roessner, S. K., Firth, A. E., & Brown, C. M. (2007). HBVRegDB: Annotation, comparison, detection and visualization of regulatory elements in hepatitis B virus sequences. Virology Journal, 4, 136. Retrieved from http://www.virologyj.com/content/4/1/136

Zadissa, A., McEwan, J. C., & Brown, C. M. (2007). Inference of transcriptional regulation using gene expression data from the bovine and human genomes. BMC Genomics, 8, 265. doi: 10.1186/1471-2164-8-265

Jacobs, G. H., Stockwell, P. A., Tate, W. P., & Brown, C. M. (2006). Transterm: Extended search facilities and improved integration with other databases. Nucleic Acids Research, 34(Database), D37-D40.

Firth, A. E., & Brown, C. M. (2006). Detecting overlapping coding sequences in virus genomes. BMC Bioinformatics, 7, 75. doi: 10.1186/1471-2105-7-75

Chung, B. Y. W., Simons, C., Firth, A. E., Brown, C. M., & Hellens, R. P. (2006). Effect of 5'UTR introns on gene expression in Arabidopsis thaliana. BMC Genomics, 7, 120. doi: 10.1186/1471-2164-7-120

Chen, A., Kao, Y. F., & Brown, C. M. (2005). Translation of the first upstream ORF in the hepatitis B virus pregenomic RNA modulates translation at the core and polymerase initiation codons. Nucleic Acids Research, 33(4), 1169-1181.

Firth, A. E., & Brown, C. M. (2005). Detecting overlapping coding sequences with pairwise alignments. Bioinformatics, 21(3), 282-292.

Rackham, O., & Brown, C. M. (2004). Visualization of RNA-protein interactions in living cells: FMRP and IMP1 interact on mRNAs. EMBO Journal, 23(16), 3346-3355.

Chapman, B., & Brown, C. (2004). Translation termination in Arabidopis thaliana: Characterisation of three versions of release factor 1. Gene, 341, 219-225.

Jacobs, G. H., Rackham, O., Stockwell, P. A., Tate, W. P., & Brown, C. M. (2002). Transterm: a database of mRNAs and translational control elements. Nucleic Acids Research, 30, 310-311.

Schreiber, M., & Brown, C. (2002). Compensation for nucleotide bias in a genome by representation as a discrete channel with noise. Bioinformatics, 18(4), 507-512.

Jacobs, G. H., Stockwell, P. A., Schreiber, M. J., Tate, W. P., & Brown, C. M. (2000). Transterm: A database of messenger RNA components and signals. Nucleic Acids Research, 28, 293-295.

Dalphin, M. E., Stockwell, P. A., Tate, W. P., & Brown, C. M. (1999). TransTerm, the translational signal database, extended to include full coding sequences and untranslated regions. Nucleic Acids Research, 27, 293-294.

Brown, C. M., Jacobs, G. H., Schreiber, M. J. J., Magnum, J., McNaughton, J. C., Cambray, M., Futschik, M., Major, L. L., Rackham, O., Tate, W. P., … Stockwell, P. A., & Kasabov, N. K. (1999). Using bioinformatics to investigate post-transcriptional control of gene expression. New Zealand BioScience, 7, 11-12.

Dalphin, M. E., Brown, C. M., Stockwell, P. A., & Tate, W. P. (1998). The translational signal database, TransTerm, is now a relational database. Nucleic Acids Research, 26, 335-337.

Dalphin, M. E., Brown, C. M., Stockwell, P. A., & Tate, W. P. (1997). The translational signal database, TransTerm: more organisms, complete genomes. Nucleic Acids Research, 25, 246-247.

Miller, W. A., Brown, C., & Wang, S. (1997). New punctuation for the genetic code: Luteovirus gene expression. Seminars in Virology, 8, 3-13.

Dalphin, M. E., Brown, C., Stockwell, P. A., & Tate, W. P. (1996). TransTerm: a database of translational signals. Nucleic Acids Research, 24, 216-218.

Brown, C. M., Dinesh-Kumar, S. P., & Miller, W. A. (1996). Local and distant sequences are required for efficient readthrough of the barley yellow dwarf virus PAV coat protein gene stop codon. Journal of Virology, 70, 5884-5892.

Tate, W. P., Poole, E. S., Horsfield, J. A., Mannering, S. A., Brown, C. M., Moffat, J. G., Dalphin, M. E., … Major, L. L., & Wilson, D. N. (1995). Translational termination efficiency in both bacteria and mammals is regulated by the base following the stop codon. Biochemistry & Cell Biology, 73, 1095-1103. doi: 10.1139/o95-118

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Journal - Research Other

Lim, C. S., & Brown, C. (2017). A new class of ribozyme from hepatitis B virus. FEBS Journal, 284(8), 1182-1183. doi: 10.1111/febs.14062

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