An improved catalogue of putative synaptic genes defined exclusively by temporal transcription profiles through an ensemble machine learning approach

Abstract

BackgroundAssembly and function of neuronal synapses require the coordinated expression of a yet undetermined set of genes. Previously, we had trained an ensemble machine learning model to assign a probability of having synaptic function to every protein-coding gene in Drosophila melanogaster. This approach resulted in the publication of a catalogue of 893 genes which we postulated to be very enriched in genes with a still undocumented synaptic function. Since then, the scientific community has experimentally identified 79 new synaptic genes. Here we use these new empirical data to evaluate our original prediction. We also implement a series of changes to the training scheme of our model and using the new data we demonstrate that this improves its predictive power. Finally, we added the new synaptic genes to the training set and trained a new model, obtaining a new, enhanced catalogue of putative synaptic genes.ResultsThe retrospective analysis demonstrate that our original catalogue was significantly enriched in new synaptic genes. When the changes to the training scheme were implemented using the original training set we obtained even higher enrichment. Finally, applying the new training scheme with a training set including the 79 new synaptic genes, resulted in an enhanced catalogue of putative synaptic genes. Here we present this new catalogue and announce that a regularly updated version will be available online at: http://synapticgenes.bnd.edu.uyConclusionsWe show that training an ensemble of machine learning classifiers solely with the whole-body temporal transcription profiles of known synaptic genes resulted in a catalogue with a significant enrichment in undiscovered synaptic genes. Using new empirical data provided by the scientific community, we validated our original approach, improved our model an obtained an arguably more precise prediction. This approach reduces the number of genes to be tested through hypothesis-driven experimentation and will facilitate our understanding of neuronal function.Availability http://synapticgenes.bnd.edu.uy

The E3 ligase Thin controls homeostatic plasticity through neurotransmitter release repression

“…In short, we created a literature-based list of known synaptic genes and calculated an interaction probability between each putative E3 ligase-encoding gene and all synaptic genes using STRING ( von Mering et al, 2005 ) ( ω 3 ). Fourth, we considered the probability of synaptic function predicted by machine-learning based analysis of transcriptomics data ( Pazos Obregón et al, 2015 ; Pazos Obregón et al, 2019 ) ( ω 4 ). The list of putative E3 ligase-encoding genes was sorted according to the sum of the four scores for each gene.…”

Building the embryo of Developmental Biology in Uruguay

“…On the large field of neural development, we find research on vertebrates, such as spinal cord neurogenesis and regeneration in turtles and rats (Fabbiani et al, 2018;Fabbiani et al, 2020), neurogenesis and late development of the olfactory/visual systems in annual fishes (Torres-Pérez et al, 2017), neurogenesis in the electric fish Gymnotus omarorum (Olivera-Pasilio et al, 2017), the innervation plasticity of the rat uterus (Brauer, 2016;Richeri et al, 2020), developmental plasticity of the visual pathway in mice (Vierci et al, 2016), the role of oxidative stress-response genes in neural development in rats and zebrafish (López et al, 2018), the role of cell polarity in neurulation and retinal differentiation in chick and zebrafish (Aparicio et al, 2018;Lepanto et al, 2016; see also Aparicio et al in this issue), and synaptogenesis and different aspects of neural development in Drosophila (Cantera et al, 2014;Pazos Obregón et al, 2019). On reproductive aspects of development, other groups are working on mammalian spermatogenesis and meiosis from a molecular point of view (Trovero et al, 2020), sex differentiation and gonadal development in fishes (Vizziano-Cantonnet et al, 2016) and on the neuroendocrine regulation of ovarian innervation in rats (Chávez-Genaro and Anesetti, 2018).…”

Ensamblando el embrión de la biología del desarrollo en Uruguay

“…En el amplio campo del desarrollo neural, encontramos investigaciones en vertebrados, como la neurogénesis y regeneración de la médula espinal en tortugas y ratas (Fabbiani et al, 2018;Fabbiani et al, 2020), neurogénesis y desarrollo tardío de los sistemas olfatorio y visual en peces anuales (Torres-Pérez et al, 2017), neurogénesis en el pez eléctrico Gymnotus omarorum (Olivera-Pasilio et al, 2017), plasticidad en la inervación del útero de rata (Brauer, 2016;Richeri et al, 2020), plasticidad del desarrollo de la vía visual en ratón (Vierci et al, 2016), el papel de los genes de respuesta al estrés oxidativo en el desarrollo neuronal en rata y pez cebra (López et al, 2018), el papel de la polaridad celular en la neurulación y en la diferenciación retiniana en pollo y pez cebra (Aparicio et al, 2018;Lepanto et al, 2016), y sinaptogénesis y otros aspectos del desarrollo neuronal en Drosophila (Cantera et al, 2014;Pazos Obregón et al, 2019). En los aspectos reproductivos del desarrollo, otros grupos están trabajando en la espermatogénesis y la meiosis de mamíferos desde un punto de vista molecular (Trovero et al, 2020), la diferenciación sexual y el desarrollo gonadal en peces (Vizziano-Cantonnet et al, 2016) y la regulación neuroendócrina de la inervación ovárica en ratas (Chávez-Genaro y Anesetti, 2018).…”