ACD can configure probes for the various manual and automated assays for INS for RNAscope Assay, or for Basescope Assay compatible for your species of interest.
Elife.
2018 Apr 20
Xiao L, Priest MF, Kozorovitskiy Y.
PMID: 29676731 | DOI: 10.7554/eLife.33892
The experience of rewarding or aversive stimuli is encoded by distinct afferents to dopamine (DA) neurons of the ventral tegmental area (VTA). Several neuromodulatory systems including oxytocin regulate DA neuron excitability and synaptic transmission that process socially meaningful stimuli. We and others have recently characterized oxytocinergic modulation of activity in mouse VTA DA neurons, but the mechanisms underlying oxytocinergic modulation of synaptic transmission in DA neurons remain poorly understood. Here, we find that oxytocin application or optogenetic release decrease excitatory synaptic transmission, via long lasting, presynaptic, endocannabinoid-dependent mechanisms. Oxytocin modulation of excitatory transmission alters the magnitude of short and long-term depression. We find that only some glutamatergic projections to DA neurons express CB1 receptors. Optogenetic stimulation of three major VTA inputs demonstrates that oxytocin modulation is limited to projections that show evidence of CB1R transcripts. Thus, oxytocin gates information flow into reward circuits in a temporally selective and pathway-specific manner.
Cell Rep
2019 May 21
Kupari J, Häring M, Agirre E, Castelo-Branco G, Ernfors P.
PMID: 31116992 | DOI: 10.1016/j.celrep.2019.04.096
Sensory functions of the vagus nerve are critical for conscious perceptions and for monitoring visceral functions in the cardio-pulmonary and gastrointestinal systems. Here, we present a comprehensive identification, classification, and validation of the neuron types in the neural crest (jugular) and placode (nodose) derived vagal ganglia by single-cell RNA sequencing (scRNA-seq) transcriptomic analysis. Our results reveal major differences between neurons derived from different embryonic origins. Jugular neurons exhibit fundamental similarities to the somatosensory spinal neurons, including major types, such as C-low threshold mechanoreceptors (C-LTMRs), A-LTMRs, Aδ-nociceptors, and cold-, and mechano-heat C-nociceptors. In contrast, the nodose ganglion contains 18 distinct types dedicated to surveying the physiological state of the internal body. Our results reveal a vast diversity of vagal neuron types, including many previously unanticipated types, as well as proposed types that are consistent with chemoreceptors, nutrient detectors, baroreceptors, and stretch and volume mechanoreceptors of the respiratory, gastrointestinal, and cardiovascular systems.
Hepatol Int
2019 Dec 12
Bakheet AMH, Zhao C, Chen JN, Zhang JY, Huang JT, Du Y, Gong LP, Bi YH, Shao CK
PMID: 31832976 | DOI: 10.1007/s12072-019-10006-z
Cell reports
2023 Mar 28
Sullivan, KE;Kraus, L;Kapustina, M;Wang, L;Stach, TR;Lemire, AL;Clements, J;Cembrowski, MS;
PMID: 36881508 | DOI: 10.1016/j.celrep.2023.112206
bioRxiv : the preprint server for biology
2023 Feb 08
Hughes, AC;Pollard, BG;Xu, B;Gammons, JW;Chapman, P;Bikoff, JB;Schwarz, LA;
PMID: 36798174 | DOI: 10.1101/2023.02.07.527312
bioRxiv : the preprint server for biology
2023 Feb 05
Su, Y;Xu, J;Zhu, Z;Yu, H;Nudell, V;Dash, B;Moya, EA;Ye, L;Nimmerjahn, A;Sun, X;
PMID: 36778350 | DOI: 10.1101/2023.02.04.527145
Sci Rep.
2017 Oct 27
Rocco BR, Oh H, Shukla R, Mechawar N, Sibille E.
PMID: 29079825 | DOI: 10.1038/s41598-017-14484-9
Cell-specific molecular investigations of the human brain are essential for understanding the neurobiology of diseases, but are hindered by postmortem conditions and technical challenges. To address these issues we developed a multi-label fluorescence in situ hybridization protocol and a novel optical filter device to identify cell types and control for tissue autofluorescence. We show that these methods can be used with laser-capture microdissection for human brain tissue cell-specific molecular analysis.
Science.
2016 Jun 24
Lake BB, Ai R, Kaeser GE, Salathia NS, Yung YC, Liu R, Wildberg A, Gao D, Fung HL, Chen S, Vijayaraghavan R, Wong J, Chen A, Sheng X, Kaper F, Shen R, Ronaghi M, Fan JB, Wang W, Chun J, Zhang K.
PMID: 27339989 | DOI: 10.1126/science.aaf1204
The human brain has enormously complex cellular diversity and connectivities fundamental to our neural functions, yet difficulties in interrogating individual neurons has impeded understanding of the underlying transcriptional landscape. We developed a scalable approach to sequence and quantify RNA molecules in isolated neuronal nuclei from a postmortem brain, generating 3227 sets of single-neuron data from six distinct regions of the cerebral cortex. Using an iterative clustering and classification approach, we identified 16 neuronal subtypes that were further annotated on the basis of known markers and cortical cytoarchitecture. These data demonstrate a robust and scalable method for identifying and categorizing single nuclear transcriptomes, revealing shared genes sufficient to distinguish previously unknown and orthologous neuronal subtypes as well as regional identity and transcriptomic heterogeneity within the human brain.
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.
Elife.
2018 Oct 30
Cembrowski MS, Wang L, Lemire AL, Copeland M, DiLisio SF, Clements J, Spruston N.
PMID: 30375971 | DOI: 10.7554/eLife.37701
In the hippocampus, the classical pyramidal cell type of the subiculum acts as a primary output, conveying hippocampal signals to a diverse suite of downstream regions. Accumulating evidence suggests that the subiculum pyramidal cell population may actually be comprised of discrete subclasses. Here, we investigated the extent and organizational principles governing pyramidal cell heterogeneity throughout the mouse subiculum. Using single-cell RNA-seq, we find that the subiculum pyramidal cell population can be deconstructed into eight separable subclasses. These subclasses were mapped onto abutting spatial domains, ultimately producing a complex laminar and columnar organization with heterogeneity across classical dorsal-ventral, proximal-distal, and superficial-deep axes. We further show that these transcriptomically defined subclasses correspond to differential protein products and can be associated with specific projection targets. This work deconstructs the complex landscape of subiculum pyramidal cells into spatially segregated subclasses that may be observed, controlled, and interpreted in future experiments.
Nature communications
2022 Nov 12
Wei, JR;Hao, ZZ;Xu, C;Huang, M;Tang, L;Xu, N;Liu, R;Shen, Y;Teichmann, SA;Miao, Z;Liu, S;
PMID: 36371428 | DOI: 10.1038/s41467-022-34590-1
Nature
2022 Mar 01
Zhao, Q;Yu, CD;Wang, R;Xu, QJ;Dai Pra, R;Zhang, L;Chang, RB;
PMID: 35296859 | DOI: 10.3760/cma.j.cn112151-20210719-00516
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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