Authors:
A. Razetti
1
;
X. Descombes
2
;
C. Medioni
3
and
F. Besse
3
Affiliations:
1
University of Nice Sophia Antipolis, France
;
2
Inria, France
;
3
Institute of Biology Valrose, France
Keyword(s):
Gamma Neurons, Remodelling, Stochastic Models, Likelihood Analysis.
Related
Ontology
Subjects/Areas/Topics:
Bioinformatics
;
Biomedical Engineering
;
Biostatistics and Stochastic Models
;
Pattern Recognition, Clustering and Classification
Abstract:
In Drosophila brain, gamma neurons in the mushroom body are involved in higher functions such as olfactory learning and memory. During metamorphosis, they undergo remodelling after which they adopt their adult shape. Some mutations alter remodelling and therefore neuronal final morphology, causing behavioural dysfunctions. The RNA binding protein Imp, for example, was shown to control this remodelling process at least partly by regulating profilin expression. This work aims at precisely characterizing the morphological changes observed upon imp knockdown in order to further understand the role of this protein. We develop a methodological framework that consists in the selection of relevant morphological features, their modelling and parameter estimation. We thus perform a statistical comparison and a likelihood analysis to quantify similarities and differences between wild type and mutated neurons. We show that imp mutant neurons can be classified into two phenotypic groups (called
Imp L and Imp Sh) that differ in several morphological aspects. We also demonstrate that, although Imp L and wild-type neurons show similarities, branch length distribution is discriminant between these populations. Finally, we study biological samples in which Profilin was reintroduced in imp mutant neurons, and show that defects in main axon and branch lengths are partially suppressed.
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