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Published on: September 15, 2018
Combining feature selection and shape analysis uncovers precise rules for miRNA regulation in Huntington's disease
Lucile Mégret1, Satish Sasidharan Nair2, Julia Dancourt2
1Sorbonne Université, CNRS UMR8256, INSERM ERL U1164, Brain-C Lab, Paris, France. lucile.megret@sorbonne-universite.fr.
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.
Insights
Huntington's disease (HD) research identified key microRNA (miRNA)-mRNA pairs using a novel shape analysis method. This approach precisely models molecular responses to HD over time in mouse models.
Area of Science:
- Neuroscience
- Genetics
- Molecular Biology
Background:
- MicroRNA (miRNA) dysregulation is implicated in neurodegenerative diseases like Huntington's disease (HD).
- Existing methods for modeling miRNA regulation may lack precision with multidimensional data.
- Huntington's disease is caused by CAG repeat expansion in the huntingtin (HTT) gene.
Purpose of the Study:
- To develop and apply a novel methodology integrating shape analysis and feature selection for analyzing multidimensional RNA-seq and proteomic data.
- To identify specific microRNA-messenger RNA (mRNA) interactions associated with the temporal progression of Huntington's disease in a mouse model.
Main Methods:
- Integration of shape analysis and feature selection into the miRAMINT methodology.
- Analysis of multidimensional RNA-seq and proteomic data from Hdh mice with varying CAG repeat lengths and ages.
- Focus on striatal and cortical tissues to identify disease-specific molecular signatures.
Main Results:
- The miRAMINT approach identified 31 key miRNA-mRNA pairs in the striatum, specifically linked to the temporal dynamics of CAG repeat influence.
- Five of these pairs demonstrated significant changes in target expression levels.
- These identified miRNA-mRNA interactions were associated with neuronal homeostasis and HD pathogenesis, and were notably absent in cortical tissue.
Conclusions:
- MicroRNA regulation plays a limited global role in Huntington's disease pathogenesis.
- The study provides a refined set of miRNA-target pairs for investigating the brain's molecular response to HD over time.
- The findings offer a methodological framework for leveraging shape analysis to improve multidimensional data interpretation in biological and disease research.
