Dr Chris Brown
|Department||Department of Biochemistry|
|Research summary||Regulatory genomics|
|Teaching||Genetics and Biochemistry: BIOC 221, GENE 223, BIOC 352, BIOC 451, GENE 400, PLBI 401, MICN 201 (Genetics, Blood), MICN 301 (Genetics).|
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.
- 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.
Kina Genome Project (A New Zealand Taonga)
Lim, C. S., Wardell, S. J. T., Kleffmann, T., & Brown, C. M. (2018). The exon-intron gene structure upstream of the initiation codon predicts translation efficiency. Nucleic Acids Research. Advance online publication. doi: 10.1093/nar/gky282
Lim, C. S., & Brown, C. M. (2018). Know your enemy: Successful bioinformatic approaches to predict functional RNA structures in viral RNAs. Frontiers in Microbiology, 8, 2582. doi: 10.3389/fmicb.2017.02582
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
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, 356. doi: 10.1186/s12864-016-2627-0
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