Identification of novel regulators of dendrite arborization using cell type-specific RNA metabolic labeling.
- Author(s): Aboukilila, Mohamed Y;
- Sami, Josephine D;
- Wang, Jingtian;
- England, Whitney;
- Spitale, Robert C;
- Cleary, Michael D
- et al.
Published Web Locationhttps://doi.org/10.1371/journal.pone.0240386
Obtaining neuron transcriptomes is challenging; their complex morphology and interconnected microenvironments make it difficult to isolate neurons without potentially altering gene expression. Multidendritic sensory neurons (md neurons) of Drosophila larvae are commonly used to study peripheral nervous system biology, particularly dendrite arborization. We sought to test if EC-tagging, a biosynthetic RNA tagging and purification method that avoids the caveats of physical isolation, would enable discovery of novel regulators of md neuron dendrite arborization. Our aims were twofold: discover novel md neuron transcripts and test the sensitivity of EC-tagging. RNAs were biosynthetically tagged by expressing CD:UPRT (a nucleobase-converting fusion enzyme) in md neurons and feeding 5-ethynylcytosine (EC) to larvae. Only CD:UPRT-expressing cells are competent to convert EC into 5-ethynyluridine-monophosphate which is subsequently incorporated into nascent RNA transcripts. Tagged RNAs were purified and used for RNA-sequencing. Reference RNA was prepared in a similar manner using 5-ethynyluridine (EUd) to tag RNA in all cells and negative control RNA-seq was performed on "mock tagged" samples to identify non-specifically purified transcripts. Differential expression analysis identified md neuron enriched and depleted transcripts. Three candidate genes encoding RNA-binding proteins (RBPs) were tested for a role in md neuron dendrite arborization. Loss-of-function for the m6A-binding factor Ythdc1 did not cause any dendrite arborization defects while RNAi of the other two candidates, the poly(A) polymerase Hiiragi and the translation regulator Hephaestus, caused significant defects in dendrite arborization. This work provides an expanded view of transcription in md neurons and a technical framework for combining EC-tagging with RNA-seq to profile transcription in cells that may not be amenable to physical isolation.