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Identification of neuron lineage-specific PRC1 targets in olfactory neuron precursors

ABSTRACT: Identification of neuron lineage-specific PRC1 targets in olfactory neuron precursors

PROVIDER: PRJNA512019 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR8375270.fastq.gz	Fastqsanger.gz
	SRR8375261.fastq.gz	Fastqsanger.gz
	SRR8375271.fastq.gz	Fastqsanger.gz
	SRR8375262.fastq.gz	Fastqsanger.gz
	SRR8375272.fastq.gz	Fastqsanger.gz

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Identification of neuron lineage-specific PRC1 targets in olfactory neuron precursors

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Project description:Sensory neuron diversity is required for organisms to decipher complex environmental cues. In Drosophila, olfactory environment is detected by 50 different olfactory receptor neuron (ORN) classes that are clustered in combinations within distinct sensilla subtypes. Each sensilla subtype houses stereotypically clustered 1-4 ORN identities that arise through asymmetric divisions from a single multipotent sensory organ precursor (SOP). How each class of SOPs acquires a unique differentiation potential that accounts for ORN diversity is unknown. Previously, we reported a critical component of SOP diversification program, Rotund (Rn), which functions to increase ORN diversity by generating novel developmental trajectories from existing precursors within each independent sensilla type lineages. Here, we show that Rn, along with BarH1/H2, Bric-à-brac (Bab), Apterous (Ap) and Dachshund (Dac), constitute a functionally conserved transcription factor (TF) network, previously shown to pattern the segmentation of the leg, that patterns the developing olfactory tissue. Precursors with diverse ORN differentiation potentials are selected from concentric rings defined by unique combinations of these TFs along the proximodistal axis of the developing antennal disc. The combinatorial code that demarcates each precursor field is set up by cross-regulatory interactions among different factors within the network. Modifications of this network lead to predictable changes in the diversity of sensilla subtypes and ORN pools. In light of our data, we propose a molecular map that defines

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