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.
Cell
2018 Sep 27
Kinchen J, Chen HH, Parikh K, Antanaviciute A, Jagielowicz M, Fawkner-Corbett D, Ashley N, Cubitt L, Mellado-Gomez E, Attar M, Sharma E, Wills Q, Bowden R, Richter FC, Ahern D, Puri KD, Henault J, Gervais F, Koohy H, Simmons A.
PMID: - | DOI: 10.1016/j.cell.2018.08.067
Intestinal mesenchymal cells play essential roles in epithelial homeostasis, matrix remodeling, immunity, and inflammation. But the extent of heterogeneity within the colonic mesenchyme in these processes remains unknown. Using unbiased single-cell profiling of over 16,500 colonic mesenchymal cells, we reveal four subsets of fibroblasts expressing divergent transcriptional regulators and functional pathways, in addition to pericytes and myofibroblasts. We identified a niche population located in proximity to epithelial crypts expressing SOX6, F3 (CD142), and WNT genes essential for colonic epithelial stem cellfunction. In colitis, we observed dysregulation of this niche and emergence of an activated mesenchymal population. This subset expressed TNF superfamily member 14 (TNFSF14), fibroblastic reticular cell-associated genes, IL-33, and Lysyl oxidases. Further, it induced factors that impaired epithelial proliferation and maturation and contributed to oxidative stress and disease severity in vivo. Our work defines how the colonic mesenchyme remodels to fuel inflammation and barrier dysfunction in IBD.
Cell Rep.
2019 Mar 12
Mishra D, Richard JE, Maric I, Porteiro B, Häring M, Kooijman S, Musovic S, Eerola K, López-Ferreras L, Peris E, Grycel K, Shevchouk OT, Micallef P, Olofsson CS, Wernstedt Asterholm I, Grill HJ, Nogueiras R, Skibicka KP.
PMID: 30865890 | DOI: 10.1016/j.celrep.2019.02.044
Chronic low-grade inflammation and increased serum levels of the cytokine IL-6 accompany obesity. For brain-produced IL-6, the mechanisms by which it controls energy balance and its role in obesity remain unclear. Here, we show that brain-produced IL-6 is decreased in obese mice and rats in a neuroanatomically and sex-specific manner. Reduced IL-6 mRNA localized to lateral parabrachial nucleus (lPBN) astrocytes, microglia, and neurons, including paraventricular hypothalamus-innervating lPBN neurons. IL-6 microinjection into lPBN reduced food intake and increased brown adipose tissue (BAT) thermogenesis in male lean and obese rats by increasing thyroid and sympathetic outflow to BAT. Parabrachial IL-6 interacted with leptin to reduce feeding. siRNA-mediated reduction of lPBN IL-6 leads to increased weight gain and adiposity, reduced BAT thermogenesis, and increased food intake. Ambient cold exposure partly normalizes the obesity-induced suppression of lPBN IL-6. These results indicate that lPBN-produced IL-6 regulates feeding and metabolism and pinpoints (patho)physiological contexts interacting with lPBN IL-6.
Cell host & microbe
2022 Aug 25
Gao, J;Zhao, X;Hu, S;Huang, Z;Hu, M;Jin, S;Lu, B;Sun, K;Wang, Z;Fu, J;Weersma, RK;He, X;Zhou, H;
PMID: 36049483 | DOI: 10.1016/j.chom.2022.08.002
Aging cell
2021 Sep 01
Aguado, J;Chaggar, HK;Gómez-Inclán, C;Shaker, MR;Leeson, HC;Mackay-Sim, A;Wolvetang, EJ;
PMID: 34459078 | DOI: 10.1111/acel.13468
Nature communications
2023 Feb 08
Horii, Y;Matsuda, S;Toyota, C;Morinaga, T;Nakaya, T;Tsuchiya, S;Ohmuraya, M;Hironaka, T;Yoshiki, R;Kasai, K;Yamauchi, Y;Takizawa, N;Nagasaka, A;Tanaka, A;Kosako, H;Nakaya, M;
PMID: 36754961 | DOI: 10.1038/s41467-023-36189-6
Nature communications
2022 Aug 20
Yerly, L;Pich-Bavastro, C;Di Domizio, J;Wyss, T;Tissot-Renaud, S;Cangkrama, M;Gilliet, M;Werner, S;Kuonen, F;
PMID: 35986012 | DOI: 10.1038/s41467-022-32670-w
Nature metabolism
2023 Jun 01
Palani, NP;Horvath, C;Timshel, PN;Folkertsma, P;Grønning, AGB;Henriksen, TI;Peijs, L;Jensen, VH;Sun, W;Jespersen, NZ;Wolfrum, C;Pers, TH;Nielsen, S;Scheele, C;
PMID: 37337126 | DOI: 10.1038/s42255-023-00820-z
SSRN Electronic Journal
2022 Sep 10
O'Toole, A;Mohamed, F;Zhang, J;Brown, C;
| DOI: 10.2139/ssrn.4199232
Research square
2021 Nov 24
Gajewski, T;Rouhani, S;Trujillo, J;Pyzer, A;Yu, J;Fessler, J;Cabanov, A;Higgs, E;Cron, K;Zha, Y;Lu, Y;Bloodworth, J;Abasiyanik, M;Okrah, S;Flood, B;Hatogai, K;Leung, M;Pezeshk, A;Kozloff, L;Reschke, R;Strohbehn, G;Chervin, CS;Kumar, M;Schrantz, S;Madariaga, ML;Beavis, K;Yeo, KT;Sweis, R;Segal, J;Tay, S;Izumchenko, E;Mueller, J;Chen, L;
PMID: 34845442 | DOI: 10.21203/rs.3.rs-1083825/v1
Cell Syst.
2016 Sep 14
Joost S, Zeisel A, Jacob T, Sun X, La Manno G, Lönnerberg P, Linnarsson S, Kasper M.
PMID: 27641957 | DOI: 10.1016/j.cels.2016.08.010
The murine epidermis with its hair follicles represents an invaluable model system for tissue regeneration and stem cell research. Here we used single-cell RNA-sequencing to reveal how cellular heterogeneity of murine telogen epidermis is tuned at the transcriptional level. Unbiased clustering of 1,422 single-cell transcriptomes revealed 25 distinct populations of interfollicular and follicular epidermal cells. Our data allowed the reconstruction of gene expression programs during epidermal differentiation and along the proximal-distal axis of the hair follicle at unprecedented resolution. Moreover, transcriptional heterogeneity of the epidermis can essentially be explained along these two axes, and we show that heterogeneity in stem cell compartments generally reflects this model: stem cell populations are segregated by spatial signatures but share a common basal-epidermal gene module. This study provides an unbiased and systematic view of transcriptional organization of adult epidermis and highlights how cellular heterogeneity can be orchestrated in vivo to assure tissue homeostasis.
Allergy
2022 Mar 27
Schaller, T;Märkl, B;Claus, R;Sholl, L;Hornick, JL;Giannetti, MP;Schweizer, L;Mann, M;Castells, M;
PMID: 35340030 | DOI: 10.1111/all.15293
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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