ACD can configure probes for the various manual and automated assays for SST for RNAscope Assay, or for Basescope Assay compatible for your species of interest.
Cell.
2017 Jul 13
Knowland D, Lilascharoen V, Pacia CP, Shin S, Wang EH, Lim BK.
PMID: 28689640 | DOI: 10.1016/j.cell.2017.06.015
Major depressive disorder (MDD) patients display a common but often variable set of symptoms making successful, sustained treatment difficult to achieve. Separate depressive symptoms may be encoded by differential changes in distinct circuits in the brain, yet how discrete circuits underlie behavioral subsets of depression and how they adapt in response to stress has not been addressed. We identify two discrete circuits of parvalbumin-positive (PV) neurons in the ventral pallidum (VP) projecting to either the lateral habenula or ventral tegmental area contributing to depression. We find that these populations undergo different electrophysiological adaptations in response to social defeat stress, which are normalized by antidepressant treatment. Furthermore, manipulation of each population mediates either social withdrawal or behavioral despair, but not both. We propose that distinct components of the VP PV circuit can subserve related, yet separate depressive-like phenotypes in mice, which could ultimately provide a platform for symptom-specific treatments of depression.
Cell.
2018 Aug 09
Saunders A, Macosko EZ, Wysoker A, Goldman M, Krienen FM, de Rivera H, Bien E, Baum M, Bortolin L, Wang S, Goeva A, Nemesh J, Kamitaki N, Brumbaugh S, Kulp D, McCarroll SA.
PMID: 30096299 | DOI: 10.1016/j.cell.2018.07.028
The mammalian brain is composed of diverse, specialized cell populations. To systematically ascertain and learn from these cellular specializations, we used Drop-seq to profile RNA expression in 690,000 individual cells sampled from 9 regions of the adult mouse brain. We identified 565 transcriptionally distinct groups of cells using computational approaches developed to distinguish biological from technical signals. Cross-region analysis of these 565 cell populations revealed features of brain organization, including a gene-expression module for synthesizing axonal and presynaptic components, patterns in the co-deployment of voltage-gated ion channels, functional distinctions among the cells of the vasculature and specialization of glutamatergic neurons across cortical regions. Systematic neuronal classifications for two complex basal ganglia nuclei and the striatum revealed a rare population of spiny projection neurons. This adult mouse brain cell atlas, accessible through interactive online software (DropViz), serves as a reference for development, disease, and evolution.
Transl Psychiatry
2018 Aug 22
McCullough KM, Daskalakis NP, Gafford G, Morrison FG, Ressler KJ.
PMID: 30135420 | DOI: 10.1038/s41398-018-0190-y
Behavioral and molecular characterization of cell-type-specific populations governing fear learning and behavior is a promising avenue for the rational identification of potential therapeutics for fear-related disorders. Examining cell-type-specific changes in neuronal translation following fear learning allows for targeted pharmacological intervention during fear extinction learning, mirroring possible treatment strategies in humans. Here we identify the central amygdala (CeA) Drd2-expressing population as a novel fear-supporting neuronal population that is molecularly distinct from other, previously identified, fear-supporting CeA populations. Sequencing of actively translating transcripts of Drd2 neurons using translating ribosome affinity purification (TRAP) technology identifies mRNAs that are differentially regulated following fear learning. Differentially expressed transcripts with potentially targetable gene products include Npy5r, Rxrg, Adora2a, Sst5r, Fgf3, Erbb4, Fkbp14, Dlk1, and Ssh3. Direct pharmacological manipulation of NPY5R, RXR, and ADORA2A confirms the importance of this cellpopulation and these cell-type-specific receptors in fear behavior. Furthermore, these findings validate the use of functionally identified specific cell populations to predict novel pharmacological targets for the modulation of emotional learning.
Description | ||
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sense Example: Hs-LAG3-sense | Standard probes for RNA detection are in antisense. Sense probe is reverse complent to the corresponding antisense probe. | |
Intron# Example: Mm-Htt-intron2 | Probe targets the indicated intron in the target gene, commonly used for pre-mRNA detection | |
Pool/Pan Example: Hs-CD3-pool (Hs-CD3D, Hs-CD3E, Hs-CD3G) | A mixture of multiple probe sets targeting multiple genes or transcripts | |
No-XSp Example: Hs-PDGFB-No-XMm | Does not cross detect with the species (Sp) | |
XSp Example: Rn-Pde9a-XMm | designed to cross detect with the species (Sp) | |
O# Example: Mm-Islr-O1 | Alternative design targeting different regions of the same transcript or isoforms | |
CDS Example: Hs-SLC31A-CDS | Probe targets the protein-coding sequence only | |
EnEm | Probe targets exons n and m | |
En-Em | Probe targets region from exon n to exon m | |
Retired Nomenclature | ||
tvn Example: Hs-LEPR-tv1 | Designed to target transcript variant n | |
ORF Example: Hs-ACVRL1-ORF | Probe targets open reading frame | |
UTR Example: Hs-HTT-UTR-C3 | Probe targets the untranslated region (non-protein-coding region) only | |
5UTR Example: Hs-GNRHR-5UTR | Probe targets the 5' untranslated region only | |
3UTR Example: Rn-Npy1r-3UTR | Probe targets the 3' untranslated region only | |
Pan Example: Pool | A mixture of multiple probe sets targeting multiple genes or transcripts |
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