Combining Feature Selection and Shape Analysis Uncovers Precise Rules for MiRNA Regulation in Huntington's Disease Mice

Overview

Journal BMC Bioinformatics

Publisher Biomed Central

Specialty Biology

Date 2020 Feb 26

PMID 32093602

Citations 3

Authors

Lucile Megret

Satish Sasidharan Nair

Julia Dancourt

Jeff Aaronson

Jim Rosinski

Christian Neri

Affiliations

Soon will be listed here.

Abstract

Background: MicroRNA (miRNA) regulation is associated with several diseases, including neurodegenerative diseases. Several approaches can be used for modeling miRNA regulation. However, their precision may be limited for analyzing multidimensional data. Here, we addressed this question by integrating shape analysis and feature selection into miRAMINT, a methodology that we used for analyzing multidimensional RNA-seq and proteomic data from a knock-in mouse model (Hdh mice) of Huntington's disease (HD), a disease caused by CAG repeat expansion in huntingtin (htt). This dataset covers 6 CAG repeat alleles and 3 age points in the striatum and cortex of Hdh mice.

Results: Remarkably, compared to previous analyzes of this multidimensional dataset, the miRAMINT approach retained only 31 explanatory striatal miRNA-mRNA pairs that are precisely associated with the shape of CAG repeat dependence over time, among which 5 pairs with a strong change of target expression levels. Several of these pairs were previously associated with neuronal homeostasis or HD pathogenesis, or both. Such miRNA-mRNA pairs were not detected in cortex.

Conclusions: These data suggest that miRNA regulation has a limited global role in HD while providing accurately-selected miRNA-target pairs to study how the brain may compute molecular responses to HD over time. These data also provide a methodological framework for researchers to explore how shape analysis can enhance multidimensional data analytics in biology and disease.

Citing Articles

Epigenetic Changes in Prion and Prion-like Neurodegenerative Diseases: Recent Advances, Potential as Biomarkers, and Future Perspectives.

Hernaiz A, Toivonen J, Bolea R, Martin-Burriel I Int J Mol Sci. 2022; 23(20).

PMID: 36293477 PMC: 9604074. DOI: 10.3390/ijms232012609.

Precision machine learning to understand micro-RNA regulation in neurodegenerative diseases.

Megret L, Mendoza C, Arrieta Lobo M, Brouillet E, Nguyen T, Bouaziz O Front Mol Neurosci. 2022; 15:914830.

PMID: 36157078 PMC: 9500540. DOI: 10.3389/fnmol.2022.914830.

Shape deformation analysis reveals the temporal dynamics of cell-type-specific homeostatic and pathogenic responses to mutant huntingtin.

Megret L, Gris B, Sasidharan Nair S, Cevost J, Wertz M, Aaronson J Elife. 2021; 10.

PMID: 33618800 PMC: 7901871. DOI: 10.7554/eLife.64984.

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