Advances in non-coding RNA profiling for neurological diseases

Over the past decade, the classifications and volume of non-coding RNA (ncRNA) transcripts have grown profoundly, spurred by transcriptomic sequencing efforts (Bartel, 2009; Guttman et al., 2009; Djebali et al., 2012). This has identified an array of human disorders associated with some degree of ncRNA dysregulation (Taft et al., 2010), prompting an expanding need to characterize ncRNA expression in targeted tissues. Brain disorders, including neurodegenerative and psychiatric disease, have increasingly been the subject of ncRNA profiling studies (Kocerha et al., 2009a,b; Beveridge et al., 2010; Im and Kenny, 2012). The technology to probe for ncRNA expression, however, varies, depending on the class of transcripts to be examined. Arguably, to date, the resources to assess microRNA (miRNA) expression are the most comprehensive, spanning from classic hybridization arrays to real-time PCR arrays. However, with the discovery of long ncRNAs (lncRNAs) in the brain, such as natural antisense transcripts (NATs) and large intergenic non-coding (Linc) RNAs (Guttman et al., 2009; Modarresi et al., 2012), the access to new technology for examination of those transcripts is also expanding.