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
2020 Feb 11
Wallace ML, Huang KW, Hochbaum D, Hyun M, Radeljic G, Sabatini BL
PMID: 32043968 | DOI: 10.7554/eLife.51271
Molecular psychiatry
2023 Jun 26
Cho, H;Yoo, T;Moon, H;Kang, H;Yang, Y;Kang, M;Yang, E;Lee, D;Hwang, D;Kim, H;Kim, D;Kim, JY;Kim, E;
PMID: 37365244 | DOI: 10.1038/s41380-023-02129-5
Neuron
2023 May 10
Lowenstein, ED;Ruffault, PL;Misios, A;Osman, KL;Li, H;Greenberg, RS;Thompson, R;Song, K;Dietrich, S;Li, X;Vladimirov, N;Woehler, A;Brunet, JF;Zampieri, N;Kühn, R;Liberles, SD;Jia, S;Lewin, GR;Rajewsky, N;Lever, TE;Birchmeier, C;
PMID: 37192624 | DOI: 10.1016/j.neuron.2023.04.025
Cell reports methods
2022 Oct 24
Ali Marandi Ghoddousi, R;Magalong, VM;Kamitakahara, AK;Levitt, P;
PMID: 36313803 | DOI: 10.1016/j.crmeth.2022.100316
Nature communications
2022 Aug 12
Teng, S;Zhen, F;Wang, L;Schalchli, JC;Simko, J;Chen, X;Jin, H;Makinson, CD;Peng, Y;
PMID: 35961989 | DOI: 10.1038/s41467-022-32461-3
Cell
2021 Dec 22
Wang, Y;Eddison, M;Fleishman, G;Weigert, M;Xu, S;Wang, T;Rokicki, K;Goina, C;Henry, FE;Lemire, AL;Schmidt, U;Yang, H;Svoboda, K;Myers, EW;Saalfeld, S;Korff, W;Sternson, SM;Tillberg, PW;
PMID: 34875226 | DOI: 10.1016/j.cell.2021.11.024
Development (Cambridge, England)
2021 Dec 15
Negretti, NM;Plosa, EJ;Benjamin, JT;Schuler, BA;Habermann, AC;Jetter, CS;Gulleman, P;Bunn, C;Hackett, AN;Ransom, M;Taylor, CJ;Nichols, D;Matlock, BK;Guttentag, SH;Blackwell, TS;Banovich, NE;Kropski, JA;Sucre, JMS;
PMID: 34927678 | DOI: 10.1242/dev.199512
Nature communications
2021 Sep 30
Zhang, X;Liu, Y;Hong, X;Li, X;Meshul, CK;Moore, C;Yang, Y;Han, Y;Li, WG;Qi, X;Lou, H;Duan, S;Xu, TL;Tong, X;
PMID: 34593806 | DOI: 10.1038/s41467-021-25956-y
Cell reports
2021 Nov 02
Maksymetz, J;Byun, NE;Luessen, DJ;Li, B;Barry, RL;Gore, JC;Niswender, CM;Lindsley, CW;Joffe, ME;Conn, PJ;
PMID: 34731619 | DOI: 10.1016/j.celrep.2021.109950
eLife
2021 Aug 16
Erwin, SR;Bristow, BN;Sullivan, KE;Kendrick, RM;Marriott, B;Wang, L;Clements, J;Lemire, AL;Jackson, J;Cembrowski, MS;
PMID: 34397382 | DOI: 10.7554/eLife.68967
Curr Biol.
2018 Aug 16
Atlan G, Terem A, Peretz-Rivlin N, Sehrawat K, Gonzales BJ, Pozner G, Tasaka G, Goll Y, Refaeli R, Zviran O, Lim BK, Groysman M, Goshen I, Mizrahi A, Nelken I, Citri A.
PMID: 30122531 | DOI: 10.1016/j.cub.2018.06.068
A barrage of information constantly assaults our senses, of which only a fraction is relevant at any given point in time. However, the neural circuitry supporting the suppression of irrelevant sensory distractors is not completely understood. The claustrum, a circuit hub with vast cortical connectivity, is an intriguing brain structure, whose restrictive anatomy, thin and elongated, has precluded functional investigation. Here, we describe the use of Egr2-CRE mice to access genetically defined claustral neurons. Utilizing conditional viruses for anterograde axonal labeling and retrograde trans-synaptic tracing, we validated this transgenic model for accessing the claustrum and extended the known repertoire of claustral input/output connectivity. Addressing the function of the claustrum, we inactivated CLEgr2+ neurons, chronically as well as acutely, in mice performing an automated two-alternative forced-choice behavioral task. Strikingly, inhibition of CLEgr2+ neurons did not significantly impact task performance under varying delay times and cue durations, but revealed a selective role for the claustrum in supporting performance in the presence of an irrelevant auditory distractor. Further investigation of behavior, in the naturalistic maternal pup-retrieval task, replicated the result of sensitization to an auditory distractor following inhibition of CLEgr2+ neurons. Initiating investigation into the underlying mechanism, we found that activation of CLEgr2+ neurons modulated cortical sensory processing, suppressing tone representation in the auditory cortex. This functional study, utilizing selective genetic access, implicates the claustrum in supporting resilienceto distraction, a fundamental aspect of attention.
Biological Psychiatry
2018 Oct 05
Shukla R, Prevot TD, French L, Isserlin R, Rocco BR, Banasr M, Bader GD, Sibille E.
PMID: - | DOI: 10.1016/j.celrep.2018.09.034
Background Aging is accompanied by altered thinking (cognition) and feeling (mood), functions that depend on information processing by brain cortical cell microcircuits. We hypothesized that age-associated long-term functional and biological changes are mediated by gene transcriptomic changes within neuronal cell-types forming cortical microcircuits, namely excitatory pyramidal cells (PYC) and inhibitory GABAergic neurons expressing vasoactive intestinal peptide (Vip), somatostatin (Sst) and parvalbumin (Pvalb). Methods To test this hypothesis, we assessed locomotor, anxiety-like and cognitive behavioral changes between young (2 months, n=9) and old (22 months, n=12) male C57BL/6 mice, and performed frontal cortex cell-type specific molecular profiling, using laser-capture microscopy and RNA sequencing. Results were analyzed by neuroinformatics and validated by fluorescent in situ hybridization. Results Old-mice displayed increased anxiety and reduced working memory. The four cell-types displayed distinct age-related transcriptomes and biological pathway profiles, affecting metabolic and cell signaling pathways, and selective markers of neuronal vulnerability (Ryr3), resilience (Oxr1), and mitochondrial dynamics (Opa1), suggesting high age-related vulnerability of PYCs, and variable degree of adaptation in GABAergic neurons. Correlations between gene expression and behaviors suggest that changes in cognition and anxiety associated with age are partly mediated by normal age-related cell changes, and that additional age-independent decreases in synaptic and signaling pathways, notably in PYC and SST-neurons further contribute to behavioral changes. Conclusions Our study demonstrates cell-dependent differential vulnerability and coordinated cell-specific cortical microcircuit molecular changes with age. Collectively, the results suggest intrinsic molecular links between aging, cognition and mood-related behaviors with SST-neurons contributing evenly to both behavioral conditions.
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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