Essay On Risk-Dependent Lncrnas - 727 Words

3) Risk-dependent lncRNAs transcripts significantly recaptured both neural tube-specific enhancers that were validated in-vivo and the neuroblastoma-susceptibility variations that were found by GWASs. In order to discover oncogenic noncoding loci, we first asked whether deregulated noncoding transcripts between two distinct risk-groups over-represent functional enhancers that have been evident by tissue-specific enhancer activities and disease-susceptibility alleles in neuroblastoma. To identify functional enhancers from transcriptome profiling, we have reanalyzed dysregulated transcripts derived from total RNA-seq data (GSE49711, n=498, tumor cell content 60%) pertaining to neuroblastoma patients with risk-stratifications (28). To†¦show more content†¦Specifically, over 1400 positively validated tissue-specific enhancers were downloaded from the VISTA Enhancer Browser (31). These in-vivo validation was tissue-specific, thus an empirical p-value was also calculated per type of tissue and enriched for neural tube (empirical P0.005, Fig 3D). We conclude that risk-group dependent lncRNAs are a powerful metric to indicate tissue-specific functional enhancers. A â€Å"risk-dependent enhancer† was hereafter defined from the neuro-tube-specific enhancers if its locus overlaps with any risk-dependent lncRNAs. Oncogenic signaling underlying these tissue-specific and risk-dependent enhancers is ready for interpretation. We identified 37 neural tube-specific risk-dependent enhancers, of which we observed three strong associations to oncogenesis below: - We first inquired the TF binding potency, as the binding of sequence-specific TFs to cognate motifs is typically required by enhancers to regulate gene expression (32). 70 human TFs showed significant binding potency (odds1.5, FDR0.001, with more than 10% instance proportion), with tumorigenic regulator FoxM1 among the top 5 (Fig 3E). - None housekeeping genes were captured, agreeing with the idea that housekeeping genes are in general regulated by simple promoters (1). In contrast, these TFs significantly over-represent known oncogenes (P=0.01, odds=5) and tumor suppressor genes (P=0.0003, odds=7.5, Fig