A10 Accurate data-driven approaches for modeling MIRNA regulation in the brain of huntington's disease mice. (September 2018)

• Record Type: Journal Article
• Authors: Mégret, Lucile; Nair, Satish Sasidharan; Aaronson, Jeff; Rosinski, Jim; Néri, Christian
• Is Part Of: Journal of neurology, neurosurgery and psychiatry. Volume 89(2018)Supplement 1
• Page Start: A4
• Page End: A4
• Publication Date: 2018-09
• Subjects: 'Molecular pathogenesis -- computer model; Neurology -- Periodicals; Nervous system -- Surgery -- Periodicals; Psychiatry -- Periodicals; 616.8
• DOI: 10.1136/jnnp-2018-EHDN.10
• Languages: English
• ISSNs: 0022-3050

Abstract

Abstract : MicroRNA regulation could play important roles in modulating the dynamics of the Huntington's disease (HD) process. The problems in question include those about the role of specific miRNAs in significantly modulating selective target genes and about the relations between these effects and the cellular context in which they operate. To address this question, we developed a data-driven approach based on network- and tree-based concepts for the unbiased and accurate characterization of miRNA regulation in the brain of HD knock-in mice (allelic series). This approach does not make use of prior knowledge on the relationships between miRNAs and their targets. Rather, it aims at predicting the miRNA-target pairs that are most strongly associated with the temporal dynamics of the HD process based on the in-depth analysis of age- and CAG repeat-dependent profiles of miRNA expression and target gene expression. Our results suggest that on a global level miRNA regulation may poorly explain gene deregulation in the cortex and striatum of HD knock-in mice. Nonetheless, our model retained a small number of miRNA-target pairs that in the striatum of HD knock-in mice are well anti-correlated in terms of change of expression level across age points and CAG-repeat lengths and that may be relevant to the modulation of neuronal activity in these HD mice.