MicroRNAs (miRs) are small non-coding RNA molecules that are directly involved in regulation of gene expression. Their mechanism relies on complementary sequence between each miR and its mRNA target. Many lines of evidence indicate the involvement of miRs in human disease, particularly in neurological disorders. The long-term objective of this application is to better understand the role of genetic variation in miRs in neurological disorders. Currently, there is no systematic analysis of miRs that provides a way to determine the disease relevance of variants in different miR or miR-target sequences. Here, we will develop and subsequently apply a method that ranks brain-expressed miRs by their likelihood of carrying disease causing mutations. The central hypothesis of this application is that certain miRs, and by extension their associated targets, are more or less likely to carry disease causing mutations than others, and that these can be discriminated by integrated population genetic data and conservation data. This hypothesis will be tested by pursuing the following specific aims: (1) Rank brain-expressed miRs by their relative tolerance to variation, and; (2) Identify candidate disease-causal miRs in neurological disorders. Upon completion, this application will provide a novel way to detect causal variants in neurological disorders and a better understanding of the mechanisms of neurological disorders. Additionally, the findings from this application could help identify new strategies for the development of treatments for these diseases.
These studies will help researchers detect candidate causal microRNA or microRNA-target variants in neurological disorders. This is relevant to public health, as detection of causal variants is a difficult and crucial step in both understanding a disease's mechanism and developing a treatment. Further, these studies will directly implicate causal microRNAs in patients with epilepsy or amyotrophic lateral sclerosis (ALS). This will help in understanding these specific disorders' mechanisms, and by extension, their possible treatments. Thus, the proposed research is relevant to the part of the NINDS's mission that seeks to pursue fundamental knowledge about the brain and use that knowledge to reduce the burden of neurological disease.
| Gussow, Ayal B; Petrovski, Slavé; Wang, Quanli et al. (2016) The intolerance to functional genetic variation of protein domains predicts the localization of pathogenic mutations within genes. Genome Biol 17:9 |
| McSweeney, K Melodi; Gussow, Ayal B; Bradrick, Shelton S et al. (2016) Inhibition of microRNA 128 promotes excitability of cultured cortical neuronal networks. Genome Res 26:1411-1416 |
| Petrovski, Slavé; Gussow, Ayal B; Wang, Quanli et al. (2015) The Intolerance of Regulatory Sequence to Genetic Variation Predicts Gene Dosage Sensitivity. PLoS Genet 11:e1005492 |
