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.
Kidney international
2022 May 26
Kaneko, K;Sato, Y;Uchino, E;Toriu, N;Shigeta, M;Kiyonari, H;Endo, S;Fukuma, S;Yanagita, M;
PMID: 35644281 | DOI: 10.1016/j.kint.2022.04.026
Cell Rep.
2018 Jan 09
Chevée M, Robertson JJ, Cannon GH, Brown SP, Goff LA.
PMID: 29320739 | DOI: 10.1016/j.celrep.2017.12.046
Single-cell RNA sequencing has generated catalogs of transcriptionally defined neuronal subtypes of the brain. However, the cellular processes that contribute to neuronal subtype specification and transcriptional heterogeneity remain unclear. By comparing the gene expression profiles of single layer 6 corticothalamic neurons in somatosensory cortex, we show that transcriptional subtypes primarily reflect axonal projection pattern, laminar position within the cortex, and neuronal activity state. Pseudotemporal ordering of 1,023 cellular responses to sensory manipulation demonstrates that changes in expression of activity-induced genes both reinforced cell-type identity and contributed to increased transcriptional heterogeneity within each cell type. This is due to cell-type biased choices of transcriptional states following manipulation of neuronal activity. These results reveal that axonal projection pattern, laminar position, and activity state define significant axes of variation that contribute both to the transcriptional identity of individual neurons and to the transcriptional heterogeneity within each neuronal subtype.
Nat Med.
2018 Sep 17
Zanconato F, Battilana G, Forcato M, Filippi L, Azzolin L, Manfrin A, Quaranta E, Di Biagio D, Sigismondo G, Guzzardo V, Lejeune P, Haendler B, Krijgsveld J, Fassan M, Bicciato S, Cordenonsi M, Piccolo S.
PMID: 30224758 | DOI: 10.1038/s41591-018-0158-8
Cancer cells rely on dysregulated gene expression. This establishes specific transcriptional addictions that may be therapeutically exploited. Yet, the mechanisms that are ultimately responsible for these addictions are poorly understood. Here, we investigated the transcriptional dependencies of transformed cells to the transcription factors YAP and TAZ. YAP/TAZ physically engage the general coactivator bromodomain-containing protein 4 (BRD4), dictating the genome-wide association of BRD4 to chromatin. YAP/TAZ flag a large set of enhancers with super-enhancer-like functional properties. YAP/TAZ-bound enhancers mediate the recruitment of BRD4 and RNA polymerase II at YAP/TAZ-regulated promoters, boosting the expression of a host of growth-regulating genes. Treatment with small-molecule inhibitors of BRD4 blunts YAP/TAZ pro-tumorigenic activity in several cell or tissue contexts, causes the regression of pre-established, YAP/TAZ-addicted neoplastic lesions and reverts drug resistance. This work sheds light on essential mediators, mechanisms and genome-wide regulatory elements that are responsible for transcriptional addiction in cancer and lays the groundwork for a rational use of BET inhibitors according to YAP/TAZ biology.
Nature Neuroscience (2018)
2018 Oct 15
Venniro M, Zhang M, Caprioli D, Hoots JK, Golden SA, Heins C, Morales M, Epstein DH, Shaham Y.
PMID: - | DOI: 10.1038/s41593-018-0246-6
Cell metabolism
2023 Mar 16
Grzelka, K;Wilhelms, H;Dodt, S;Dreisow, ML;Madara, JC;Walker, SJ;Wu, C;Wang, D;Lowell, BB;Fenselau, H;
PMID: 36965483 | DOI: 10.1016/j.cmet.2023.03.002
Nature neuroscience
2021 May 17
Biglari, N;Gaziano, I;Schumacher, J;Radermacher, J;Paeger, L;Klemm, P;Chen, W;Corneliussen, S;Wunderlich, CM;Sue, M;Vollmar, S;Klöckener, T;Sotelo-Hitschfeld, T;Abbasloo, A;Edenhofer, F;Reimann, F;Gribble, FM;Fenselau, H;Kloppenburg, P;Wunderlich, FT;Brüning, JC;
PMID: 34002087 | DOI: 10.1038/s41593-021-00854-0
Neuron.
2017 Jan 31
François A, Low SA, Sypek EI, Christensen AJ, Sotoudeh C, Beier KT, Ramakrishnan C, Ritola KD, Sharif-Naeini R, Deisseroth K, Delp SL, Malenka RC, Luo L, Hantman AW, Scherrer G.
PMID: 28162807 | DOI: 10.1016/j.neuron.2017.01.008
Pain thresholds are, in part, set as a function of emotional and internal states by descending modulation of nociceptive transmission in the spinal cord. Neurons of the rostral ventromedial medulla (RVM) are thought to critically contribute to this process; however, the neural circuits and synaptic mechanisms by which distinct populations of RVM neurons facilitate or diminish pain remain elusive. Here we used in vivo opto/chemogenetic manipulations and trans-synaptic tracing of genetically identified dorsal horn and RVM neurons to uncover an RVM-spinal cord-primary afferent circuit controlling pain thresholds. Unexpectedly, we found that RVM GABAergic neurons facilitate mechanical pain by inhibiting dorsal horn enkephalinergic/GABAergic interneurons. We further demonstrate that these interneurons gate sensory inputs and control pain through temporally coordinated enkephalin- and GABA-mediated presynaptic inhibition of somatosensory neurons. Our results uncover a descending disynaptic inhibitory circuit that facilitates mechanical pain, is engaged during stress, and could be targeted to establish higher pain thresholds.
Neuron.
2017 Mar 22
Kim J, Zhang X, Muralidhar S, LeBlanc SA, Tonegawa S.
PMID: 28334609 | DOI: 10.1016/j.neuron.2017.02.034
Basolateral amygdala (BLA) principal cells are capable of driving and antagonizing behaviors of opposing valence. BLA neurons project to the central amygdala (CeA), which also participates in negative and positive behaviors. However, the CeA has primarily been studied as the site for negative behaviors, and the causal role for CeA circuits underlying appetitive behaviors is poorly understood. Here, we identify several genetically distinct populations of CeA neurons that mediate appetitive behaviors and dissect the BLA-to-CeA circuit for appetitive behaviors. Protein phosphatase 1 regulatory subunit 1B+ BLA pyramidal neurons to dopamine receptor 1+ CeA neurons define a pathway for promoting appetitive behaviors, while R-spondin 2+ BLA pyramidal neurons to dopamine receptor 2+ CeA neurons define a pathway for suppressing appetitive behaviors. These data reveal genetically defined neural circuits in the amygdala that promote and suppress appetitive behaviors analogous to the direct and indirect pathways of the basal ganglia.
Cell Rep.
2018 Feb 20
Sathyamurthy A, Johnson KR, Matson KJE, Dobrott CI, Li L, Ryba AR, Bergman TB, Kelly MC, Kelley MW, Levine AJ.
PMID: 29466745 | DOI: 10.1016/j.celrep.2018.02.003
To understand the cellular basis of behavior, it is necessary to know the cell types that exist in the nervous system and their contributions to function. Spinal networks are essential for sensory processing and motor behavior and provide a powerful system for identifying the cellular correlates of behavior. Here, we used massively parallel single nucleus RNA sequencing (snRNA-seq) to create an atlas of the adult mouse lumbar spinal cord. We identified and molecularly characterized 43 neuronal populations. Next, we leveraged the snRNA-seq approach to provide unbiased identification of neuronal populations that were active following a sensory and a motor behavior, using a transcriptional signature of neuronal activity. This approach can be used in the future to link single nucleus gene expression data with dynamic biological responses to behavior, injury, and disease.
Neuron
2022 Oct 26
Albisetti, GW;Ganley, RP;Pietrafesa, F;Werynska, K;Magalhaes de Sousa, M;Sipione, R;Scheurer, L;Bösl, MR;Pelczar, P;Wildner, H;Zeilhofer, HU;
PMID: 36323322 | DOI: 10.1016/j.neuron.2022.10.008
Cell reports
2022 May 31
Mu, R;Tang, S;Han, X;Wang, H;Yuan, D;Zhao, J;Long, Y;Hong, H;
PMID: 35649349 | DOI: 10.1016/j.celrep.2022.110882
Nature metabolism
2022 Apr 01
Haddad-Tóvolli, R;Ramírez, S;Muñoz-Moreno, E;Milà-Guasch, M;Miquel-Rio, L;Pozo, M;Chivite, I;Altirriba, J;Obri, A;Gómez-Valadés, AG;Toledo, M;Eyre, E;Bortolozzi, A;Valjent, E;Soria, G;Claret, M;
PMID: 35379970 | DOI: 10.1038/s42255-022-00557-1
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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