Decoding the genome: Dissecting the regulatory repertoire of the genome through high resolution transcriptomics — University of Technology
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Decoding the genome: Dissecting the regulatory repertoire of the genome through high resolution transcriptomics

Decoding the genome: Dissecting the regulatory repertoire of the genome through high resolution transcriptomics

Marcel E. Dinger1,2

1 Garvan Institute of Medical Research, Darlinghurst NSW 2010

2 St Vincent’s Clinical School, University of New South Wales, Kensington NSW 2052, Australia.

Approximately 98% of the human genome comprises noncoding DNA, the function of which is largely unknown. Transcriptomic studies, empowered by increasingly sophisticated molecular techniques, reveal that the majority of these noncoding regions are expressed as noncoding RNAs.  However, as many of these transcripts are either lowly expressed or expressed only in very specific cell or tissue types, their annotation and functional study has proved very challenging.

To improve our understanding of these noncoding regions of the genome, we have developed novel methods to experimentally interrogate the transcripts that are expressed from them. First, we developed a technique termed RNA-Capture-Seq, which targets RNA sequencing to specific areas of the genome. This technique dramatically increases the sensitivity of RNA-Seq analysis and improves the qualitative and quantitative analysis of rare transcripts. Second, to identify the presence and measure the regulation of transcripts that are dynamically transcribed, we have developed approaches to interrogate high-resolution temporal transcriptomic profiles. This method provides a means to dissect driver and passenger changes through key biological transitions in both disease progression and development.

The implementation of these approaches in several experimental contexts challenges traditional definitions of the gene and brings an intriguing perspective into our understanding of how information in the genome is encoded. As well as improving our understanding of cellular regulatory processes, these approaches show considerable potential in the identification of biomarkers and therapeutic targets.