Harmonized cross-species cell atlases of trigeminal and dorsal root ganglia
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Abstract
Peripheral sensory neurons in the dorsal root ganglion (DRG) and trigeminal ganglion (TG) are specialized to detect and transduce diverse environmental stimuli including touch, temperature, and pain to the central nervous system. Recent advances in single-cell RNA-sequencing (scRNA-seq) have provided new insights into the diversity of sensory ganglia cell types in rodents, non-human primates, and humans, but it remains difficult to compare transcriptomically defined cell types across studies and species. Here, we built cross-species harmonized atlases of DRG and TG cell types that describe 18 neuronal and 11 non-neuronal cell types across 6 species and 19 studies. We then demonstrate the utility of this harmonized reference atlas by using it to annotate newly profiled DRG nuclei/cells from both human and the highly regenerative axolotl. We observe that the transcriptomic profiles of sensory neuron subtypes are broadly similar across vertebrates, but the expression of functionally important neuropeptides and channels can vary notably. The new resources and data presented here can guide future studies in comparative transcriptomics, simplify cell type nomenclature differences across studies, and help prioritize targets for future pain therapy development.
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Harmonized cross-species cell atlases of trigeminal and dorsal root ganglia
Did you consider incorporating additional vertebrate RNA-seq data into your atlas in order to minimize bias or was this possibility not available? If not, did you consider a re-harmonized atlas after generating the axolotl DRG RNA-seq data?
Summary: The authors constructed cross-species harmonized cell atlases of DRG and TG neuronal and non-neuronal cell types using sc/snRNA-seq data from 19 mammalian studies. (Available at https://harmonized.painseq.com) Cell types were characterized based on mouse DRG marker genes. The final reference only included cells or nuclei with consistent cell type annotations from both the LIGER and Seurat computational pipelines. Generated clusters included 18 neuronal DRG subtypes, 14 neuronal TG subtypes, 7 non-neuronal DRG …
Harmonized cross-species cell atlases of trigeminal and dorsal root ganglia
Did you consider incorporating additional vertebrate RNA-seq data into your atlas in order to minimize bias or was this possibility not available? If not, did you consider a re-harmonized atlas after generating the axolotl DRG RNA-seq data?
Summary: The authors constructed cross-species harmonized cell atlases of DRG and TG neuronal and non-neuronal cell types using sc/snRNA-seq data from 19 mammalian studies. (Available at https://harmonized.painseq.com) Cell types were characterized based on mouse DRG marker genes. The final reference only included cells or nuclei with consistent cell type annotations from both the LIGER and Seurat computational pipelines. Generated clusters included 18 neuronal DRG subtypes, 14 neuronal TG subtypes, 7 non-neuronal DRG subtypes and 11 non-neuronal TG subtypes. The authors then sequenced nuclei from human DRG samples from Harvard Medical School, the University of Texas-Dallas and Washington University in St. Louis and compared the annotations generated by the harmonized atlas and the 10X Genomics Cellranger v7 pipelines. Finally, scRNA-seq was performed on axolotl DRGs in order to evaluate conservation of subtypes in vertebrates.
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anchors between identify anchors between Nefhhigh
Small Typo: “identify anchors between Nefh…”
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I would be more interested in knowing what range of similarity is expected for evolutionarily distant species and what outliers exist. E.g. Are there similarities higher than what would be expected due to evolutionary distance?
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It would be interesting to see which neuronal cell types were identified when the three datasets were individually annotated versus when they were anchored to your atlas. I would be interested to see if anchoring to the atlas resolved the rare neuronal subtypes like Mrgpra3+Mrgprb4, Mrgpra3+Trpv1, Calca+Oprk1, and Calca+Dcn.
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