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Characterising the structure-function relationship of the human transcriptome



Distribution of evolutionarily conserved elements in the human genome

Less than 2% of the human genome harbours the genetic information required to produce proteins. The relative amount of non-protein coding DNA in multicellular organisms increases proportionately to their developmental complexity, suggesting that non-coding DNA is required for coordinated regulation of gene expression [1]. Furthermore, recent high-throughput methodologies have revealed that over 85% of the human genome is transcribed into RNA, which occurs in a developmentally coordinated and tissue-specific manner [2]. We, and others, have shown that non-coding RNAs (ncRNA) are associated to several complex diseases and developmental disorders, in both mouse and human (more references).

Our lab studies the function of non-coding regions of the genome through a combination of molecular biology, next generation high-throughput sequencing technologies, and bioinformatics. Recently, we have shown that a substantial proportion of mammalian genomes present the evolutionary signatures of function through conserved RNA secondary structures [3]. We currently have two PhD projects focused on elucidating the structure-function relationship of long non-coding RNAs (lncRNAs).

Available PhD projects

There are currently 2 available projects on this topic for outstanding and highly motivated PhD candidates.

Graphical summary of the lncRNA-HMC hypothesis

Project 1: Unraveling the HMC-bound transcriptome (molecular biology/biochemistry)

Histone Modification Complexes (HMCs) are proteins complexes that alter a chromosome's chromatin structure through the post-translational chemical modification of histones. There are several reports demonstrating that lncRNAs associate with HMCs, potentially guiding their action to distinct genomic loci. This project will combine tissue culture with breast cancer cell lines, RNA immuno-precipitation, biochemical assays, and next generation sequencing techniques to characterise the discrete RNA structures required for recognition by HMCs.

Project 2: Computational optimisation and analysis of functional RNA secondary structures (bioinformatics/computer science).

We have recently identified over 4 million evolutionarily conserved RNA secondary structures in the human genome, suggesting that RNA base-pairings are an important biological feature in multicellular organisms. Given that RNA secondary and tertiary structure prediction algorithms display significantly more time and memory complexity than sequence alignment algorithms, high-throughput comparison of RNA structures can be very computationaly intensive. This project will involve applying/modifying/developing methods and algorithms for the massiveley parallel analysis/discovery of RNA secondary structures on various computational platforms (local cluster/GPGPU and elastic cloud).


[1] Liu G, Mattick JS, Taft RJ. meta-analysis of the genomic and transcriptomic composition of complex life. Cell Cycle 2013 PDF

[2] Mercer TR, Dinger ME, Sunkin SM, Mehler MF, Mattick JS (2008). Specific expression of long noncoding RNAs in the adult mouse brain. Proc Natl Acad Sci USA 105: 716-721. PDF

[3] Smith MA, Gesell T, Stadler PF, Mattick JS (2013). Widespread purifying selection on RNA structure in mammals. Nucl. Acids Res. 2013 41 (17): 8220-8236. doi: 10.1093/nar/gkt596 PDF

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