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.
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.
ENEURO
2017 Nov 20
Mancarci BO, Toker L, Tripathy SJ, Li B, Rocco B, Sibille E, Pavlidis P.
PMID: - | DOI: 10.1523/ENEURO.0212-17.2017
Establishing the molecular diversity of cell types is crucial for the study of the nervous system. We compiled a cross-laboratory database of mouse brain cell type-specific transcriptomes from 36 major cell types from across the mammalian brain using rigorously curated published data from pooled cell type microarray and single cell RNA-sequencing studies. We used these data to identify cell type-specific marker genes, discovering a substantial number of novel markers, many of which we validated using computational and experimental approaches. We further demonstrate that summarized expression of marker gene sets in bulk tissue data can be used to estimate the relative cell type abundance across samples. To facilitate use of this expanding resource, we provide a user-friendly web interface at Neuroexpresso.org.
Significance Statement Cell type markers are powerful tools in the study of the nervous system that help reveal properties of cell types and acquire additional information from large scale expression experiments. Despite their usefulness in the field, known marker genes for brain cell types are few in number. We present NeuroExpresso, a database of brain cell type specific gene expression profiles, and demonstrate the use of marker genes for acquiring cell type specific information from whole tissue expression. The database will prove itself as a useful resource for researchers aiming to reveal novel properties of the cell types and aid both laboratory and computational scientists to unravel the cell type specific components of brain disorders.
Nature communications
2022 Nov 11
Dietrich, S;Company, C;Song, K;Lowenstein, ED;Riedel, L;Birchmeier, C;Gargiulo, G;Zampieri, N;
PMID: 36369193 | DOI: 10.1038/s41467-022-34589-8
PLoS One. 2018 Dec 26;13(12):e0209648.
2018 Dec 26
Bakken TE, Hodge RD, Miller JA, Yao Z, Nguyen TN, Aevermann B, Barkan E, Bertagnolli D, Casper T, Dee N, Garren E, Goldy J, Graybuck LT, Kroll M, Lasken RS, Lathia K, Parry S, Rimorin C, Scheuermann RH, Schork NJ, Shehata SI, Tieu M, Phillips JW, Bernard A, Smith KA, Zeng H, Lein ES, Tasic B.
PMID: 30586455 | DOI: 10.1371/journal.pone.0209648
Cell Rep.
2019 Mar 05
Mehta P, Kreeger L, Wylie DC, Pattadkal JJ, Lusignan T, Davis MJ, Turi GF, Li WK, Whitmire MP, Chen Y, Kajs BL, Seidemann E, Priebe NJ, Losonczy A, Zemelman BV.
PMID: 30840900 | DOI: 10.1016/j.celrep.2019.02.011
Viral vectors enable foreign proteins to be expressed in brains of non-genetic species, including non-human primates. However, viruses targeting specific neuron classes have proved elusive. Here we describe viral promoters and strategies for accessing GABAergic interneurons and their molecularly defined subsets in the rodent and primate. Using a set intersection approach, which relies on two co-active promoters, we can restrict heterologous protein expression to cortical and hippocampal somatostatin-positive and parvalbumin-positive interneurons. With an orthogonal set difference method, we can enrich for subclasses of neuropeptide-Y-positive GABAergic interneurons by effectively subtracting the expression pattern of one promoter from that of another. These methods harness the complexity of gene expression patterns in the brain and significantly expand the number of genetically tractable neuron classes across mammals.
Cell reports
2022 Mar 01
Jeon, H;Lee, H;Kwon, DH;Kim, J;Tanaka-Yamamoto, K;Yook, JS;Feng, L;Park, HR;Lim, YH;Cho, ZH;Paek, SH;Kim, J;
PMID: 35235786 | DOI: 10.1016/j.celrep.2022.110439
PLoS One.
2018 Jun 12
Kisner A, Slocomb JE, Sarsfield S, Zuccoli ML, Siemian J, Gupta JF, Kumar A, Aponte Y.
PMID: 29894514 | DOI: 10.1371/journal.pone.0198991
Cracking the cytoarchitectural organization, activity patterns, and neurotransmitter nature of genetically-distinct cell types in the lateral hypothalamus (LH) is fundamental to develop a mechanistic understanding of how activity dynamics within this brain region are generated and operate together through synaptic connections to regulate circuit function. However, the precise mechanisms through which LH circuits orchestrate such dynamics have remained elusive due to the heterogeneity of the intermingled and functionally distinct cell types in this brain region. Here we reveal that a cell type in the mouse LH identified by the expression of the calcium-binding protein parvalbumin (PVALB; LHPV) is fast-spiking, releases the excitatory neurotransmitter glutamate, and sends long range projections throughout the brain. Thus, our findings challenge long-standing concepts that define neurons with a fast-spiking phenotype as exclusively GABAergic. Furthermore, we provide for the first time a detailed characterization of the electrophysiological properties of these neurons. Our work identifies LHPV neurons as a novel functional component within the LH glutamatergic circuitry.
Neuron
2023 Jan 04
Schroeder, A;Pardi, MB;Keijser, J;Dalmay, T;Groisman, AI;Schuman, EM;Sprekeler, H;Letzkus, JJ;
PMID: 36610397 | DOI: 10.1016/j.neuron.2022.12.010
Science (New York, N.Y.)
2022 Nov 25
Bernard, C;Exposito-Alonso, D;Selten, M;Sanalidou, S;Hanusz-Godoy, A;Aguilera, A;Hamid, F;Oozeer, F;Maeso, P;Allison, L;Russell, M;Fleck, RA;Rico, B;Marín, O;
PMID: 36423280 | DOI: 10.1126/science.abm7466
Nature immunology
2022 May 12
Doke, T;Abedini, A;Aldridge, DL;Yang, YW;Park, J;Hernandez, CM;Balzer, MS;Shrestra, R;Coppock, G;Rico, JMI;Han, SY;Kim, J;Xin, S;Piliponsky, AM;Angelozzi, M;Lefebvre, V;Siracusa, MC;Hunter, CA;Susztak, K;
PMID: 35552540 | DOI: 10.1038/s41590-022-01200-7
Nature neuroscience
2021 Dec 20
Yang, NJ;Isensee, J;Neel, DV;Quadros, AU;Zhang, HB;Lauzadis, J;Liu, SM;Shiers, S;Belu, A;Palan, S;Marlin, S;Maignel, J;Kennedy-Curran, A;Tong, VS;Moayeri, M;Röderer, P;Nitzsche, A;Lu, M;Pentelute, BL;Brüstle, O;Tripathi, V;Foster, KA;Price, TJ;Collier, RJ;Leppla, SH;Puopolo, M;Bean, BP;Cunha, TM;Hucho, T;Chiu, IM;
PMID: 34931070 | DOI: 10.1038/s41593-021-00973-8
Cell Rep.
2018 Aug 21
Muñoz-Manchado AB, Bengtsson Gonzales C, Zeisel A, Munguba H, Bekkouche B, Skene NG, Lönnerberg P, Ryge J, Harris KD, Linnarsson S, Hjerling-Leffler J.
PMID: 30134177 | DOI: 10.1016/j.celrep.2018.07.053
Striatal locally projecting neurons, or interneurons, act on nearby circuits and shape functional output to the rest of the basal ganglia. We performed single-cell RNA sequencing of striatal cells enriching for interneurons. We find seven discrete interneuron types, six of which are GABAergic. In addition to providing specific markers for the populations previously described, including those expressing Sst/Npy, Th, Npy without Sst, and Chat, we identify two small populations of cells expressing Cck with or without Vip. Surprisingly, the Pvalb-expressing cells do not constitute a discrete cluster but rather are part of a larger group of cells expressing Pthlh with a spatial gradient of Pvalb expression. Using PatchSeq, we show that Pthlh cells exhibit a continuum of electrophysiological properties correlated with expression of Pvalb. Furthermore, we find significant molecular differences that correlate with differences in electrophysiological properties between Pvalb-expressing cells of the striatum and those of the cortex.
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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