The Drosophila brain is a work horse in neuroscience. Single-cell transcriptome analysis 1-5 , 3D morphological classification 6 , and detailed EM mapping of the connectome 7-10 have revealed an immense diversity of neuronal and glial cell types that underlie the wide array of functional and behavioral traits in the fruit fly. The identities of these cell types are controlled by -still unknowngene regulatory networks (GRNs), involving combinations of transcription factors that bind to genomic enhancers to regulate their target genes. To characterize the GRN for each cell type in the Drosophila brain, we profiled chromatin accessibility of 240,919 single cells spanning nine developmental timepoints, and integrated this data with single-cell transcriptomes. We identify more than 95,000 regulatory regions that are used in different neuronal cell types, of which around 70,000 are linked to specific developmental trajectories, involving neurogenesis, reprogramming and maturation. For 40 cell types, their uniquely accessible regions could be associated with their expressed transcription factors and downstream target genes, through a combination of motif discovery, network inference techniques, and deep learning. We illustrate how these "enhancer-GRNs" can be used to reveal enhancer architectures leading to a better understanding of neuronal regulatory diversity. Finally, our atlas of regulatory elements can be used to design genetic driver lines for specific cell types at specific timepoints, facilitating the characterization of brain cell types and the manipulation of brain function. MainThe brain consists of a myriad of different neuronal and glial types, each unique in their morphology and function. The Drosophila brain, which contains around 100,000 cells, is uniquely positioned as a model in which the diversity of brain cell types can be investigated. Recent advances in electron microscopy have allowed the creation of connectome maps of the different regions in the Drosophila brain 7-10 , while the availability of genetic driver lines 11 provides genetic access to many cell types for understanding neuronal function 12 . Furthermore, this diversity of cell types has been bolstered by single-cell transcriptomics on the adult brain 1-5 , the larval brain [13][14][15] , and the ventral nerve cord 16 . The recent development of single-cell assay for transposase accessible chromatin by sequencing (scATAC-seq), makes it possible to measure chromatin accessibility of single cells in high throughput 17,18 , providing an additional crucial layer of information underlying neuronal identity: which genomic regions encode the regulatory information to create and maintain each cell type. The integrated analysis of transcriptomics and chromatin accessibility makes it then possible to jointly study enhancers and gene expression to discover precise regulatory programs across cell types [19][20][21] .Cell type identity is defined by the activity of GRNs in which combinations of transcription factors activate or repress target genes....

The Drosophila brain is a work horse in neuroscience. Single-cell transcriptome analysis, 3D morphological classification, and detailed EM mapping of the connectome have revealed an immense diversity of neuronal and glial cell types that underlie the wide array of functional and behavioral traits in the fruit fly. The identities of these cell types are controlled by still unknown gene regulatory networks (GRNs), involving combinations of transcription factors that bind to genomic enhancers to regulate their target genes. To characterize the GRN for each cell type in the Drosophila brain, we profiled chromatin accessibility of 240,919 single cells spanning nine developmental timepoints, and integrated this data with single-cell transcriptomes. We identify more than 95,000 regulatory regions that are used in different neuronal cell types, of which around 70,000 are linked to specific developmental trajectories, involving neurogenesis, reprogramming and maturation. For 40 cell types, their uniquely accessible regions could be associated with their expressed transcription factors and downstream target genes, through a combination of motif discovery, network inference techniques, and deep learning. We illustrate how these enhancer-GRNs can be used to reveal enhancer architectures leading to a better understanding of neuronal regulatory diversity. Finally, our atlas of regulatory elements can be used to design genetic driver lines for specific cell types at specific timepoints, facilitating the characterization of brain cell types and the manipulation of brain function.

Traumatic brain injuries (TBIs) present a chief public health threat affecting nations worldwide. As numbers of patients afflicted by TBI are expected to rise, the necessity to increase our understanding of the pathophysiological mechanism(s) as a result of TBI mounts. TBI is known to augment the risk of developing a number of neurodegenerative diseases (NDs) such as Alzheimer’s disease (AD) and Parkinson’s disease (PD). Hence, it is rational to assume that a common mechanistic ground links the pathophysiology of NDs to that of TBIs. Through this review, we aim to identify the protein–protein interactions, differential proteins expression, and PTMs, mainly glycosylation, that are involved in the pathogenesis of both ND and TBI. OVID and PubMed have been rigorously searched to identify studies that utilized advanced proteomic platforms (MS based) and systems biology tools to unfold the mechanism(s) behind ND in an attempt to unveil the mysterious biological processes that occur postinjury. Various PTMs have been found to be common between TBI and AD, whereas no similarities have been found between TBI and PD. Phosphorylated tau protein, glycosylated amyloid precursor protein, and many other modifications appear to be common in both TBI and AD. PTMs, differential protein profiles, and altered biological pathways appear to have critical roles in ND processes by interfering with their pathological condition in a manner similar to TBI. Advancement in glycoproteomic studies pertaining to ND and TBI is urgently needed in order to develop better diagnostic tools, therapies, and more favorable prognoses.