bioRxivNeurosciencePreprint
Transcriptomic profiling of sex-specific olfactory neurons reveals subset-specific receptor expression in C. elegans
Douglas K. ReillyiD, Erich M. SchwarziD, Caroline S. Muirhead, Annalise N. Robidoux, Anusha Narayan, Meenakshi K. Doma, Paul W. SternbergiD, Jagan SrinivasaniD
Abstract
SummaryThe nematode Caenorhabditis elegans utilizes chemosensation to navigate an ever-changing environment for its survival. A class of secreted small-molecule pheromones, termed ascarosides, play an important role in olfactory perception by affecting biological functions ranging from development to behavior. The ascaroside ascr#8 mediates sex-specific behaviors, driving avoidance in hermaphrodites and attraction in males. Males sense ascr#8 via the ciliated male-specific cephalic sensory (CEM) neurons, which exhibit radial symmetry along dorsal-ventral and left-right axes. Calcium imaging studies suggest a complex neural coding mechanism that translates stochastic physiological responses in these neurons to reliable behavioral outputs. To test the hypothesis that neurophysiological complexity arises from differential expression of genes, we performed cell-specific transcriptomic profiling; this revealed between 18 and 62 genes with at least two-fold higher expression in a specific CEM neuron type versus both other CEM neurons and adult males. These included two G protein coupled receptor (GPCR) genes, srw-97 and dmsr-12, that were specifically expressed in non-overlapping subsets of CEM neurons and whose expression was confirmed by GFP reporter analysis. Single CRISPR-Cas9 knockouts of either srw-97 or dmsr-12 resulted in partial defects, while a double knockout of both srw-97 and dmsr-12 completely abolished the attractive response to ascr#8. Together, our results suggest that the evolutionarily distinct GPCRs SRW-97 and DMSR-12 act non-redundantly in discrete olfactory neurons to facilitate male-specific sensation of ascr#8.
- organism: C. elegans
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
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