Pathway Analysis of the Human Brain Transcriptome in Disease
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Pathway Analysis of the Human Brain Transcriptome in Disease Tomas Kavanagh & James D. Mills & Woojin S. Kim & Glenda M. Halliday & Michael Janitz
Received: 3 November 2012 / Accepted: 10 December 2012 / Published online: 22 December 2012 # Springer Science+Business Media New York 2012
Abstract Pathway analysis is a powerful method for discerning differentially regulated genes and elucidating their biological importance. It allows for the identification of perturbed or aberrantly expressed genes within a biological context from extensive data sets and offers a simplistic approach for interrogating such data sets. With the growing use of microarrays and RNA-Seq, data for genome-wide studies are growing at an alarming rate, and the use of deep sequencing is revealing elements of the genome previously uncharacterised. Through the employment of pathway analysis, mechanisms in complex diseases may be explored and novel causatives found primarily through differentially regulated genes. Further, with the implementation of next generation sequencing, a deeper resolution may be attained, particularly in identification of isoform diversity and SNPs. Here, we look at a broad overview of pathway analysis in the human brain transcriptome and its relevance in teasing out underlying causes of complex diseases. We will outline processes in data gathering and analysis of particular diseases in which these approaches have been successful. Keywords Transcriptome . Pathway analysis . Human brain . Brain disorders . Gene expression . RNA-Seq
T. Kavanagh : J. D. Mills : M. Janitz (*) School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia e-mail: [email protected] W. S. Kim : G. M. Halliday Neuroscience Research Australia, Sydney, New South Wales 2031, Australia W. S. Kim : G. M. Halliday School of Medical Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia
Introduction In the complex transcriptional environment of the brain, identification of differentially regulated genes is a significant challenge. This is especially true in cases of neurodegenerative diseases in which ageing itself is causative of many of the changes seen (Lu et al. 2004). To complicate the identification of causative genes in neurodegenerative diseases further, the brain has an enormous range of transcript isoforms, and many differentially expressed isoforms have been linked to neurodegenerative diseases (Courtney et al. 2010; Faustino and Cooper 2003; Mills and Janitz 2012; Tollervey et al. 2011; Twine et al. 2011). These isoforms may be differentially expressed across tissues or in disease, or alternative splicing and erroneous splicing may have an impact on disease (Mills and Janitz 2012; Tollervey et al. 2011; Twine et al. 2011). It is imperative that a deep understanding of the brain transcriptome be developed so that diseases of the brain might be better treated. In identifying key differences in complex disease states, systems biology looks to identify differe
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