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.
The European journal of neuroscience
2022 Jun 08
Quirion, B;Beaulieu, C;Côté, L;Parent, JL;Gendron, L;
PMID: 35674691 | DOI: 10.1111/ejn.15733
Immunity.
2018 Nov 21
Hammond TR, Dufort C, Dissing-Olesen L, Giera S, Young A, Wysoker A, Walker AJ, Gergits F, Segel M, Nemesh J, Marsh SE, Saunders A, Macosko E, Ginhoux F, Chen J, Franklin RJM, Piao X, McCarroll SA, Stevens B.
PMID: 30471926 | DOI: 10.1016/j.immuni.2018.11.004
Microglia, the resident immune cells of the brain, rapidly change states in response to their environment, but we lack molecular and functional signatures of different microglial populations. Here, we analyzed the RNA expression patterns of more than 76,000 individual microglia in mice during development, in old age, and after brain injury. Our analysis uncovered at least nine transcriptionally distinct microglial states, which expressed unique sets of genes and were localized in the brain using specific markers. The greatest microglial heterogeneity was found at young ages; however, several states-including chemokine-enriched inflammatory microglia-persisted throughout the lifespan or increased in the aged brain. Multiple reactive microglial subtypes were also found following demyelinating injury in mice, at least one of which was also found in human multiple sclerosis lesions. These distinct microglia signatures can be used to better understand microglia function and to identify and manipulate specific subpopulations in health and disease.
Pain
2022 May 11
Polgár, E;Dickie, AC;Gutierrez-Mecinas, M;Bell, AM;Boyle, KA;Quillet, R;Rashid, EA;Clark, RA;German, MT;Watanabe, M;Riddell, JS;Todd, AJ;
PMID: 35543635 | DOI: 10.1097/j.pain.0000000000002677
PNAS 2018
2018 Feb 07
Clarke LE, Liddelow SA, Chakraborty C, Münch AE, Heiman M, Barres BA.
PMID: - | DOI: 10.1073/pnas.1800165115
The decline of cognitive function occurs with aging, but the mechanisms responsible are unknown. Astrocytes instruct the formation, maturation, and elimination of synapses, and impairment of these functions has been implicated in many diseases. These findings raise the question of whether astrocyte dysfunction could contribute to cognitive decline in aging. We used the Bac-Trap method to perform RNA sequencing of astrocytes from different brain regions across the lifespan of the mouse. We found that astrocytes have region-specific transcriptional identities that change with age in a region-dependent manner. We validated our findings using fluorescence in situ hybridization and quantitative PCR. Detailed analysis of the differentially expressed genes in aging revealed that aged astrocytes take on a reactive phenotype of neuroinflammatory A1-like reactive astrocytes. Hippocampal and striatal astrocytes up-regulated a greater number of reactive astrocyte genes compared with cortical astrocytes. Moreover, aged brains formed many more A1 reactive astrocytes in response to the neuroinflammation inducer lipopolysaccharide. We found that the aging-induced up-regulation of reactive astrocyte genes was significantly reduced in mice lacking the microglial-secreted cytokines (IL-1α, TNF, and C1q) known to induce A1 reactive astrocyte formation, indicating that microglia promote astrocyte activation in aging. Since A1 reactive astrocytes lose the ability to carry out their normal functions, produce complement components, and release a toxic factor which kills neurons and oligodendrocytes, the aging-induced up-regulation of reactive genes by astrocytes could contribute to the cognitive decline in vulnerable brain regions in normal aging and contribute to the greater vulnerability of the aged brain to injury.
Progress in neurobiology
2021 Mar 22
Zhang, D;Zhao, W;Liu, J;Ou, M;Liang, P;Li, J;Chen, Y;Liao, D;Bai, S;Shen, J;Chen, X;Huang, H;Zhou, C;
PMID: 33766679 | DOI: 10.1016/j.pneurobio.2021.102041
The American Journal of Pathology
2016 Dec 10
Ha Y, Liu H, Zhu S, Yi P, Liu W, Nathanson J, Kayed R, Loucas B, Sun J, Frishman LJ, Motamedi M, Zhang W.
PMID: 27960090 | DOI: 10.1016/j.ajpath.2016.10.009
Traumatic optic neuropathy (TON) is an acute injury of the optic nerve secondary to trauma. Loss of retinal ganglion cells (RGCs) is a key pathological process in TON, yet mechanisms responsible for RGC death remain unclear. In a mouse model of TON, real-time noninvasive imaging revealed a dramatic increase in leukocyte rolling and adhesion in veins near the optic nerve (ON) head at 9 hours after ON injury. Although RGC dysfunction and loss were not detected at 24 hours after injury, massive leukocyte infiltration was observed in the superficial retina. These cells were identified as T cells, microglia/monocytes, and neutrophils but not B cells. CXCL10 is a chemokine that recruits leukocytes after binding to its receptor C-X-C chemokine receptor (CXCR) 3. The levels of CXCL10 and CXCR3 were markedly elevated in TON, and up-regulation of CXCL10 was mediated by STAT1/3. Deleting CXCR3 in leukocytes significantly reduced leukocyte recruitment, and prevented RGC death at 7 days after ON injury. Treatment with CXCR3 antagonist attenuated TON-induced RGC dysfunction and cell loss. In vitro co-culture of primary RGCs with leukocytes resulted in increased RGC apoptosis, which was exaggerated in the presence of CXCL10. These results indicate that leukocyte recruitment in retinal vessels near the ON head is an early event in TON and the CXCL10/CXCR3 axis has a critical role in recruiting leukocytes and inducing RGC death.
J Neurosci.
2017 Jan 10
Hennessy ML, Corcoran A, Brust RD, Nattie EE, Dymecki S.
PMID: 28073937 | DOI: 10.1523/JNEUROSCI.2316-16.2016
Cell reports
2021 Jul 27
Weglage, M;Wärnberg, E;Lazaridis, I;Calvigioni, D;Tzortzi, O;Meletis, K;
PMID: 34320355 | DOI: 10.1016/j.celrep.2021.109437
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
2023 Mar 24
Yi, T;Wang, N;Huang, J;Wang, Y;Ren, S;Hu, Y;Xia, J;Liao, Y;Li, X;Luo, F;Ouyang, Q;Li, Y;Zheng, Z;Xiao, Q;Ren, R;Yao, Z;Tang, X;Wang, Y;Chen, X;He, C;Li, H;Hu, Z;
PMID: 36961096 | DOI: 10.1002/advs.202300189
eLife
2022 Feb 15
Zhu, YB;Wang, Y;Hua, XX;Xu, L;Liu, MZ;Zhang, R;Liu, PF;Li, JB;Zhang, L;Mu, D;
PMID: 35167440 | DOI: 10.7554/eLife.68372
Cell (2018)
2018 Dec 06
Gibson EM, Nagaraja S, Ocampo A, Tam LT, Wood LS, Pallegar PN, Greene JJ, Geraghty AC, Goldstein AK, Ni L, Woo PJ, Barres BA, Liddelow S, Vogel H, Monje M.
| DOI: 10.1016/j.cell.2018.10.049
Nature
2017 May 17
Chung S, Weber F, Zhong P, Tan CL, Nguyen TN, Beier KT, Hörmann N, Chang WC, Zhang Z, Do JP, Yao S, Krashes MJ, Tasic B, Cetin A, Zeng H, Knight ZA, Luo L, Dan Y.
PMID: 28514446 | DOI: 10.1038/nature22350
In humans and other mammalian species, lesions in the preoptic area of the hypothalamus cause profound sleep impairment, indicating a crucial role of the preoptic area in sleep generation. However, the underlying circuit mechanism remains poorly understood. Electrophysiological recordings and c-Fos immunohistochemistry have shown the existence of sleep-active neurons in the preoptic area, especially in the ventrolateral preoptic area and median preoptic nucleus. Pharmacogenetic activation of c-Fos-labelled sleep-active neurons has been shown to induce sleep. However, the sleep-active neurons are spatially intermingled with wake-active neurons, making it difficult to target the sleep neurons specifically for circuit analysis. Here we identify a population of preoptic area sleep neurons on the basis of their projection target and discover their molecular markers. Using a lentivirus expressing channelrhodopsin-2 or a light-activated chloride channel for retrograde labelling, bidirectional optogenetic manipulation, and optrode recording, we show that the preoptic area GABAergic neurons projecting to the tuberomammillary nucleus are both sleep active and sleep promoting. Furthermore, translating ribosome affinity purification and single-cell RNA sequencing identify candidate markers for these neurons, and optogenetic and pharmacogenetic manipulations demonstrate that several peptide markers (cholecystokinin, corticotropin-releasing hormone, and tachykinin 1) label sleep-promoting neurons. Together, these findings provide easy genetic access to sleep-promoting preoptic area neurons and a valuable entry point for dissecting the sleep control circuit.
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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