Dynamic neurotransmitter specific transcription factor expression profiles duringDrosophiladevelopment

Abstract

8The remarkable diversity of neurons in the nervous system is generated during development, when 9properties such as cell morphology, receptor profiles and neurotransmitter identities are specified. 10Neurotransmitters are essential for neuronal communication, and transcription factors are the key 11 determinants of neurotransmitter fate. In order to gain a greater understanding of neurotransmitter 12 specification we profiled the transcription state of cholinergic, GABAergic and glutamatergic neurons 13 in vivo at multiple developmental time points. We identified 86 differentially expressed transcription 14 factors that are uniquely enriched, or uniquely depleted, in a specific neurotransmitter subtype. Some 15 transcription factors show a similar profile across development, others only show enrichment or 16 depletion at specific developmental stages. Profiling of acj6 (cholinergic enriched) and Ets65A 17 (cholinergic depleted) binding sites in vivo reveals that they both directly bind the ChAT locus, in 18 addition to a wide spectrum of other key neuronal differentiation genes. Our data underlines that, 19 similar to C. elegans, there are no simple transcription factor codes for neurotransmitter type 20 specification, and provides a useful resource for studying the developmental basis of neurotransmitter 21 specification in Drosophila and other model systems. 22 enrichment of the GAL4-trapped genes (ChAT, Gad1 and VGlut) ( Figure S1) that provide subtype 126 specific expression for the TaDa experiments. 127 CATaDa profiling of chromatin accessibility (Aughey et al., 2018) reveals that, similar to RNA Pol II, 128 global chromatin accessibility does not vary greatly between cell types (Figure 2) but shows more 129 differences between developmental stages. Correspondingly, when examining regions of the genome 130 that display robust changes in chromatin accessibility (>10 RPM differences across 3 consecutive 131 GATC fragments) during embryo development, only 37 GATC fragments (13 individual peaks) are 132 identified, with 62% mapping to the loci of the three neurotransmitter synthesis genes (ChAT, Gad1 133

Decoding gene regulation in the fly brain

“…There are hundreds of cell types in the fly brain, impeding the use of bulk datasets for accurately deciphering diversity. Even more, compared to the embryo 58,[83][84][85][86][87] or imaginal discs 59,[88][89][90][91][92][93][94] , the number of ChIP-seq or other epigenomic datasets is very limited in the brain 24,[95][96][97] . In contrast, in this study we constructed 40 eGRNs at once, covering 88 transcription factors with 7833 enhancers that are linked to 3776 target genes.…”

“…This patterning of neural progenitors is presumed to give rise to the diverse cell types found in the adult brain. The combinatorial expression of transcription factors also governs key neuronal features by guiding dendritic targeting and neurotransmitter determination 2,[24][25][26][27] and changing expression of a single TF can lead to a change in neuronal fate 28,29 . Whereas transcriptomic studies in Drosophila have led to the inference of TFs and their putative target genes, they suffer from high false positive rates.…”

“…One difference we observe is in neurotransmitter usage, where cell types from branch 4 and 5 tend to be non-cholinergic. One of the eGRNs that overlaps with these branches is Ets65A, a factor previously hypothesized to be involved in noncholinergic fate 24 . We further note a correlation with neuropils, with most Tm neurons of the medulla and the T-neurons of the lobula plate belonging to separate branches 73 .…”

Escargot controls somatic stem cell maintenance through the attenuation of the insulin receptor pathway in Drosophila

“…Log2 mean ratios of each spot were median normalized. The data were binned to GATC fragments (DNA fragments between each GATC site) before a peak finding algorithm with false discovery rate (FDR) was used to identify significant binding sites ( https://github.com/tonysouthall/Peak_calling_DamID ) ( Estacio-Gómez et al, 2020 ). A summary of the statistically significant results is presented on Table S1 .…”