@article {Smith519694, author = {Stephen J Smith and Uygar S{\"u}mb{\"u}l and Lucas Graybuck and Forrest Collman and Sharmishtaa Seshamani and Rohan Gala and Olga Gliko and Leila Elabbady and Jeremy Miller and Trygve Bakken and Zizhen Yao and Ed Lein and Hongkui Zeng and Bosiljka Tasic and Michael Hawrylycz}, title = {Transcriptomic evidence for dense peptidergic neuromodulation networks in mouse cortex}, elocation-id = {519694}, year = {2019}, doi = {10.1101/519694}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Seeking new insights into intracortical neuromodulation, we have analyzed results from deep RNA-Seq analysis of 22,439 individual mouse neocortical neurons. With special interest in ways that cortical neurons may use paracrine neuropeptide (NP) signaling to modulate one anothers{\textquoteright} synaptic and electrical function, we have concentrated on neocortical expression of genes encoding 18 neuropeptide precursor proteins (NPPs) and 29 cognate G-protein-coupled neuropeptide receptors (NP-GPCRs). We find that over 97\% of sampled neurons express at least one of these NPP genes and that 98\% express at least one NP-GPCR gene, with almost all neurons expressing several genes in each category. Reference to a transcriptomic taxonomy suggests that neocortical neuron types should be distinguishable by unique combinatorial signatures of NPP and NP-GPCR expression. We use these neuron-type-specific NP expression signatures to generate testable predictions regarding dense peptidergic neuromodulatory networks that may play prominent roles in cortical activity homeostasis and memory engram storage.}, URL = {https://www.biorxiv.org/content/early/2019/01/13/519694}, eprint = {https://www.biorxiv.org/content/early/2019/01/13/519694.full.pdf}, journal = {bioRxiv} }