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Species

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Gene

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Platform

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Channel

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HiPlex Channel

  • T1 (85058) Apply T1 filter
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  • T11 (85039) Apply T11 filter
  • T9 (82563) Apply T9 filter
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  • S1 (32) Apply S1 filter
  • 8 (17) Apply 8 filter
  • 1 (1) Apply 1 filter
  • 10 (1) Apply 10 filter
  • 6 (1) Apply 6 filter

Product

  • RNAscope Multiplex Fluorescent Assay (1035) Apply RNAscope Multiplex Fluorescent Assay filter
  • RNAscope (998) Apply RNAscope filter
  • RNAscope Fluorescent Multiplex Assay (732) Apply RNAscope Fluorescent Multiplex Assay filter
  • RNAscope 2.5 HD Red assay (704) Apply RNAscope 2.5 HD Red assay filter
  • RNAscope 2.0 Assay (497) Apply RNAscope 2.0 Assay filter
  • RNAscope 2.5 HD Brown Assay (293) Apply RNAscope 2.5 HD Brown Assay filter
  • TBD (193) Apply TBD filter
  • RNAscope 2.5 LS Assay (191) Apply RNAscope 2.5 LS Assay filter
  • RNAscope 2.5 HD Duplex (160) Apply RNAscope 2.5 HD Duplex filter
  • RNAscope 2.5 HD Reagent Kit - BROWN (108) Apply RNAscope 2.5 HD Reagent Kit - BROWN filter
  • RNAscope Multiplex Fluorescent v2 (97) Apply RNAscope Multiplex Fluorescent v2 filter
  • BASEscope Assay RED (91) Apply BASEscope Assay RED filter
  • RNAscope 2.5 VS Assay (85) Apply RNAscope 2.5 VS Assay filter
  • Basescope (53) Apply Basescope filter
  • RNAscope HiPlex v2 assay (30) Apply RNAscope HiPlex v2 assay filter
  • miRNAscope (26) Apply miRNAscope filter
  • DNAscope HD Duplex Reagent Kit (15) Apply DNAscope HD Duplex Reagent Kit filter
  • RNAscope 2.5 HD duplex reagent kit (13) Apply RNAscope 2.5 HD duplex reagent kit filter
  • BaseScope Duplex Assay (12) Apply BaseScope Duplex Assay filter
  • RNAscope Multiplex fluorescent reagent kit v2 (6) Apply RNAscope Multiplex fluorescent reagent kit v2 filter
  • RNAscope Fluorescent Multiplex Reagent kit (5) Apply RNAscope Fluorescent Multiplex Reagent kit filter
  • RNAscope ISH Probe High Risk HPV (5) Apply RNAscope ISH Probe High Risk HPV filter
  • CTCscope (4) Apply CTCscope filter
  • RNAscope 2.5 HD Reagent Kit (4) Apply RNAscope 2.5 HD Reagent Kit filter
  • RNAscope HiPlex12 Reagents Kit (3) Apply RNAscope HiPlex12 Reagents Kit filter
  • DNAscope Duplex Assay (2) Apply DNAscope Duplex Assay filter
  • RNAscope 2.5 HD Assay (2) Apply RNAscope 2.5 HD Assay filter
  • RNAscope 2.5 LS Assay - RED (2) Apply RNAscope 2.5 LS Assay - RED filter
  • RNAscope Multiplex Fluorescent Assay v2 (2) Apply RNAscope Multiplex Fluorescent Assay v2 filter
  • BOND RNAscope Brown Detection (1) Apply BOND RNAscope Brown Detection filter
  • HybEZ Hybridization System (1) Apply HybEZ Hybridization System filter
  • miRNAscope Assay Red (1) Apply miRNAscope Assay Red filter
  • RNA-Protein CO-Detection Ancillary Kit (1) Apply RNA-Protein CO-Detection Ancillary Kit filter
  • RNAscope 2.0 HD Assay - Chromogenic (1) Apply RNAscope 2.0 HD Assay - Chromogenic filter
  • RNAscope 2.5 HD- Red (1) Apply RNAscope 2.5 HD- Red filter
  • RNAscope 2.5 LS Reagent Kits (1) Apply RNAscope 2.5 LS Reagent Kits filter
  • RNAScope HiPlex assay (1) Apply RNAScope HiPlex assay filter
  • RNAscope HiPlex Image Registration Software (1) Apply RNAscope HiPlex Image Registration Software filter
  • RNAscope LS Multiplex Fluorescent Assay (1) Apply RNAscope LS Multiplex Fluorescent Assay filter
  • RNAscope Multiplex Fluorescent Reagent Kit V3 (1) Apply RNAscope Multiplex Fluorescent Reagent Kit V3 filter
  • RNAscope Multiplex Fluorescent Reagent Kit v4 (1) Apply RNAscope Multiplex Fluorescent Reagent Kit v4 filter
  • RNAscope Multiplex Fluorescent v1 (1) Apply RNAscope Multiplex Fluorescent v1 filter
  • RNAscope Target Retrieval Reagents (1) Apply RNAscope Target Retrieval Reagents filter

Research area

  • Neuroscience (1849) Apply Neuroscience filter
  • Cancer (1385) Apply Cancer filter
  • Development (509) Apply Development filter
  • Inflammation (472) Apply Inflammation filter
  • Infectious Disease (410) Apply Infectious Disease filter
  • Other (406) Apply Other filter
  • Stem Cells (258) Apply Stem Cells filter
  • Covid (237) Apply Covid filter
  • Infectious (220) Apply Infectious filter
  • HPV (187) Apply HPV filter
  • lncRNA (135) Apply lncRNA filter
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  • Immunotherapy (72) Apply Immunotherapy filter
  • Other: Methods (67) Apply Other: Methods filter
  • HIV (64) Apply HIV filter
  • CGT (62) Apply CGT filter
  • Pain (62) Apply Pain filter
  • diabetes (57) Apply diabetes filter
  • LncRNAs (46) Apply LncRNAs filter
  • Aging (43) Apply Aging filter
  • Other: Heart (40) Apply Other: Heart filter
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  • Obesity (29) Apply Obesity filter
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  • Behavior (27) Apply Behavior filter
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  • Other: Kidney (27) Apply Other: Kidney filter
  • Alzheimer's Disease (26) Apply Alzheimer's Disease filter
  • Bone (24) Apply Bone filter
  • Stress (21) Apply Stress filter
  • Other: Zoological Disease (20) Apply Other: Zoological Disease filter
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  • Fibrosis (17) Apply Fibrosis filter
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  • Other: Endocrinology (16) Apply Other: Endocrinology filter
  • Other: Skin (16) Apply Other: Skin filter
  • Injury (15) Apply Injury filter
  • Anxiety (14) Apply Anxiety filter
  • Memory (14) Apply Memory filter
  • Reproductive Biology (14) Apply Reproductive Biology filter

Product sub type

  • Target Probes (256568) Apply Target Probes filter
  • Control Probe - Automated Leica (409) Apply Control Probe - Automated Leica filter
  • Control Probe - Automated Leica Multiplex (284) Apply Control Probe - Automated Leica Multiplex filter
  • Control Probe - Automated Leica Duplex (168) Apply Control Probe - Automated Leica Duplex filter
  • Control Probe- Manual RNAscope Multiplex (148) Apply Control Probe- Manual RNAscope Multiplex filter
  • Control Probe - Automated Ventana (143) Apply Control Probe - Automated Ventana filter
  • Control Probe - Manual RNAscope Singleplex (142) Apply Control Probe - Manual RNAscope Singleplex filter
  • Control Probe - Manual RNAscope Duplex (137) Apply Control Probe - Manual RNAscope Duplex filter
  • Control Probe (73) Apply Control Probe filter
  • Control Probe - Manual BaseScope Singleplex (51) Apply Control Probe - Manual BaseScope Singleplex filter
  • Control Probe - VS BaseScope Singleplex (41) Apply Control Probe - VS BaseScope Singleplex filter
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  • L-HBsAG (15) Apply L-HBsAG filter
  • Cancer (13) Apply Cancer filter
  • Automated Assay 2.5: Leica System (8) Apply Automated Assay 2.5: Leica System filter
  • Control Probe- Manual BaseScope Duplex (8) Apply Control Probe- Manual BaseScope Duplex filter
  • 1765 (8) Apply 1765 filter
  • 1379 (8) Apply 1379 filter
  • 2184 (8) Apply 2184 filter
  • 38322 (8) Apply 38322 filter
  • Manual Assay 2.5: Pretreatment Reagents (5) Apply Manual Assay 2.5: Pretreatment Reagents filter
  • Controls: Manual Probes (5) Apply Controls: Manual Probes filter
  • Control Probe- Manual RNAscope HiPlex (5) Apply Control Probe- Manual RNAscope HiPlex filter
  • Manual Assay RNAscope Brown (4) Apply Manual Assay RNAscope Brown filter
  • Manual Assay RNAscope Duplex (4) Apply Manual Assay RNAscope Duplex filter
  • Manual Assay RNAscope Multiplex (4) Apply Manual Assay RNAscope Multiplex filter
  • Manual Assay BaseScope Red (4) Apply Manual Assay BaseScope Red filter
  • IA: Other (4) Apply IA: Other filter
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  • Manual Assay miRNAscope Red (4) Apply Manual Assay miRNAscope Red filter
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  • Control Probe - Automated Ventana Duplex (3) Apply Control Probe - Automated Ventana Duplex filter
  • Manual Assay BaseScope Duplex (3) Apply Manual Assay BaseScope Duplex filter
  • Manual Assay RNAscope Red (2) Apply Manual Assay RNAscope Red filter
  • Controls: Control Slides (2) Apply Controls: Control Slides filter
  • Control Probe- Manual BaseScope Singleplex (2) Apply Control Probe- Manual BaseScope Singleplex filter
  • Control Probe - Manual BaseScope™Singleplex (2) Apply Control Probe - Manual BaseScope™Singleplex filter
  • Manual Assay: Accessory Reagent (1) Apply Manual Assay: Accessory Reagent filter
  • Accessory Reagent (1) Apply Accessory Reagent filter
  • Controls: Manual RNAscope Multiplex (1) Apply Controls: Manual RNAscope Multiplex filter
  • IA: HybEZ (1) Apply IA: HybEZ filter
  • Automated Assay BaseScope: LS (1) Apply Automated Assay BaseScope: LS filter
  • Automated Assay BaseScope: VS (1) Apply Automated Assay BaseScope: VS filter
  • Software: RNAscope HiPlex Image Registration (1) Apply Software: RNAscope HiPlex Image Registration filter
  • miRNAscope Automated Assay: Leica System (1) Apply miRNAscope Automated Assay: Leica System filter
  • Automated Assay: VS (1) Apply Automated Assay: VS filter
  • Control Probe - VS BaseScope™Singleplex (1) Apply Control Probe - VS BaseScope™Singleplex filter
  • Controls:2.5VS Probes (1) Apply Controls:2.5VS Probes filter
  • Control Probe - Manual RNAscope Multiplex (1) Apply Control Probe - Manual RNAscope Multiplex filter

Sample Compatibility

  • Cell pellets (49) Apply Cell pellets filter
  • FFPE (41) Apply FFPE filter
  • Fixed frozen tissue (31) Apply Fixed frozen tissue filter
  • TMA (31) Apply TMA filter
  • Adherent cells (26) Apply Adherent cells filter
  • Freshfrozen tissue (18) Apply Freshfrozen tissue filter
  • Fresh frozen tissue (13) Apply Fresh frozen tissue filter
  • Cell Cultures (12) Apply Cell Cultures filter
  • TMA(Tissue Microarray) (9) Apply TMA(Tissue Microarray) filter
  • FFPE,Freshfrozen tissue,Fixed frozen tissue,TMA,Cell pellets,Adherent cells (7) Apply FFPE,Freshfrozen tissue,Fixed frozen tissue,TMA,Cell pellets,Adherent cells filter
  • CTC (4) Apply CTC filter
  • PBMC's (4) Apply PBMC's filter
  • Adherent or Cultured Cells (1) Apply Adherent or Cultured Cells filter
  • Fixed frozen (1) Apply Fixed frozen filter
  • FFPE,TMA (1) Apply FFPE,TMA filter
  • Fixed frozen tissues (for chromogenic assays) (1) Apply Fixed frozen tissues (for chromogenic assays) filter

Category

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Application

  • Cancer (139875) Apply Cancer filter
  • Neuroscience (51010) Apply Neuroscience filter
  • Cancer, Neuroscience (32227) Apply Cancer, Neuroscience filter
  • Non-coding RNA (24365) Apply Non-coding RNA filter
  • Cancer, Inflammation (16436) Apply Cancer, Inflammation filter
  • Cancer, Inflammation, Neuroscience (12591) Apply Cancer, Inflammation, Neuroscience filter
  • Inflammation (9879) Apply Inflammation filter
  • Cancer, Stem Cell (7932) Apply Cancer, Stem Cell filter
  • Cancer, Neuroscience, Stem Cell (7028) Apply Cancer, Neuroscience, Stem Cell filter
  • Cancer, Immunotherapy, Inflammation, Neuroscience, Stem Cell (6854) Apply Cancer, Immunotherapy, Inflammation, Neuroscience, Stem Cell filter
  • Cancer, Inflammation, Neuroscience, Stem Cell (5424) Apply Cancer, Inflammation, Neuroscience, Stem Cell filter
  • Immunotherapy (5368) Apply Immunotherapy filter
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  • Cancer, Immunotherapy, Inflammation (2844) Apply Cancer, Immunotherapy, Inflammation filter
  • Cancer, Immunotherapy, Inflammation, Neuroscience (1878) Apply Cancer, Immunotherapy, Inflammation, Neuroscience filter
  • Cancer, Immunotherapy, Neuroscience (1786) Apply Cancer, Immunotherapy, Neuroscience filter
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TGFBI Production by Macrophages Contributes to an Immunosuppressive Microenvironment in Ovarian Cancer

Cancer research

2021 Nov 15

Lecker, LSM;Berlato, C;Maniati, E;Delaine-Smith, R;Pearce, OMT;Heath, O;Nichols, SJ;Trevisan, C;Novak, M;McDermott, J;Brenton, JD;Cutillas, PR;Rajeeve, V;Hennino, A;Drapkin, R;Loessner, D;Balkwill, FR;
PMID: 34561272 | DOI: 10.1158/0008-5472.CAN-21-0536

The tumor microenvironment evolves during malignant progression, with major changes in nonmalignant cells, cytokine networks, and the extracellular matrix (ECM). In this study, we aimed to understand how the ECM changes during neoplastic transformation of serous tubal intraepithelial carcinoma lesions (STIC) into high-grade serous ovarian cancers (HGSOC). Analysis of the mechanical properties of human fallopian tubes (FT) and ovaries revealed that normal FT and fimbria had a lower tissue modulus, a measure of stiffness, than normal or diseased ovaries. Proteomic analysis of the matrisome fraction between FT, fimbria, and ovaries showed significant differences in the ECM protein TGF beta induced (TGFBI, also known as βig-h3). STIC lesions in the fimbria expressed high levels of TGFBI, which was predominantly produced by CD163-positive macrophages proximal to STIC epithelial cells. In vitro stimulation of macrophages with TGFβ and IL4 induced secretion of TGFBI, whereas IFNγ/LPS downregulated macrophage TGFBI expression. Immortalized FT secretory epithelial cells carrying clinically relevant TP53 mutations stimulated macrophages to secrete TGFBI and upregulated integrin αvβ3, a putative TGFBI receptor. Transcriptomic HGSOC datasets showed a significant correlation between TGFBI expression and alternatively activated macrophage signatures. Fibroblasts in HGSOC metastases expressed TGFBI and stimulated macrophage TGFBI production in vitro. Treatment of orthotopic mouse HGSOC tumors with an anti-TGFBI antibody reduced peritoneal tumor size, increased tumor monocytes, and activated β3-expressing unconventional T cells. In conclusion, TGFBI may favor an immunosuppressive microenvironment in STICs that persists in advanced HGSOC. Furthermore, TGFBI may be an effector of the tumor-promoting actions of TGFβ and a potential therapeutic target. SIGNIFICANCE: Analysis of ECM changes during neoplastic transformation reveals a role for TGFBI secreted by macrophages in immunosuppression in early ovarian cancer.
TAMI-70. METABOLIC VULNERABILITY TO GPX4 INHIBITION AND FERROPTOSIS OF QUIESCENT ASTROCYTE-LIKE GLIOMA CELL POPULATIONS

Neuro-Oncology

2021 Nov 12

Banu, M;Dovas, A;Argenziano, M;Zhao, W;Higgins, D;Upadhyayula, P;Mahajan, A;Humala, N;Nguyen, T;Zandkarimi, F;Siegelin, M;Brent, S;Sims, P;Bruce, J;Canoll, P;
| DOI: 10.1093/neuonc/noab196.852

Diversity is a key feature in the glioma ecosystem. Adaptation to a changing tumor microenvironment is achieved through cellular and metabolic plasticity. Here we show that slow-cycling, astrocyte-like glioma cell subpopulations activate distinct metabolic programs, rendering them susceptible to novel treatments. We performed multi-omics analysis on transgenic murine glioma models to characterize cellular heterogeneity. Bulk RNAseq on targeted time-dependent biopsies combined with scRNAseq uncovered distinct tumor cell populations, including a quiescent, astrocyte-like population relatively insensitive to conventional chemotherapy targeting proliferating cells. Using scRNAseq, we identified a persistently conserved astrocytic population in human IDH1-mt/wt high-grade gliomas. This astrocytic tumor population was more abundant in mouse models with constitutive Notch activation, however it was associated with alterations in several other transcriptional programs, suggesting that targeted therapies would likely be ineffective at eradicating it. Gene ontology analysis revealed enrichment in mitochondrial genes specifically regulating oxidative phosphorylation and tricarboxylic acid cycle. Energetic, lipidomic and metabolomic analyses revealed significant mitochondrial β-fatty acid oxidation and lipid catabolism, with less effective oxygen consumption rate and higher basal oxidative stress. Furthermore, this astrocytic tumor population had depleted levels of basal GSH and was more sensitive to reactive oxygen species. Leveraging this metabolic vulnerability, we performed drug screens and found that therapeutic inhibition of complex I or GPX4 was highly effective and synergistic. GPX4 inhibition induced ferroptosis, a newly-discovered form of programmed non-necroptotic cell death mediated by iron-driven lipid peroxidation. Using scRNAseq and RNAscope on ex vivo slice cultures from murine and human gliomas, we found that GPX4 inhibition and ferroptosis induction in the glioma microenvironment selectively eradicated the quiescent astrocytic subpopulation whereas proliferating glioma were less sensitive. Our data therefore supports a novel treatment paradigm, employing metabolic strategies, such as ferroptosis, in conjunction with chemotherapy and RT to target distinct tumor cell populations with different therapeutic vulnerabilities.
Postnatal expression of the lysine methyltransferase SETD1B is essential for learning and the regulation of neuron-enriched genes

The EMBO journal

2021 Nov 22

Michurina, A;Sakib, MS;Kerimoglu, C;Krüger, DM;Kaurani, L;Islam, MR;Joshi, PD;Schröder, S;Centeno, TP;Zhou, J;Pradhan, R;Cha, J;Xu, X;Eichele, G;Zeisberg, EM;Kranz, A;Stewart, AF;Fischer, A;
PMID: 34806773 | DOI: 10.15252/embj.2020106459

In mammals, histone 3 lysine 4 methylation (H3K4me) is mediated by six different lysine methyltransferases. Among these enzymes, SETD1B (SET domain containing 1b) has been linked to syndromic intellectual disability in human subjects, but its role in the mammalian postnatal brain has not been studied yet. Here, we employ mice deficient for Setd1b in excitatory neurons of the postnatal forebrain, and combine neuron-specific ChIP-seq and RNA-seq approaches to elucidate its role in neuronal gene expression. We observe that Setd1b controls the expression of a set of genes with a broad H3K4me3 peak at their promoters, enriched for neuron-specific genes linked to learning and memory function. Comparative analyses in mice with conditional deletion of Kmt2a and Kmt2b histone methyltransferases show that SETD1B plays a more pronounced and potent role in regulating such genes. Moreover, postnatal loss of Setd1b leads to severe learning impairment, suggesting that SETD1B-dependent regulation of H3K4me levels in postnatal neurons is critical for cognitive function.
Altered cell and RNA isoform diversity in aging Down syndrome brains

Proceedings of the National Academy of Sciences of the United States of America

2021 Nov 23

Palmer, CR;Liu, CS;Romanow, WJ;Lee, MH;Chun, J;
PMID: 34795060 | DOI: 10.1073/pnas.2114326118

Down syndrome (DS), trisomy of human chromosome 21 (HSA21), is characterized by lifelong cognitive impairments and the development of the neuropathological hallmarks of Alzheimer's disease (AD). The cellular and molecular modifications responsible for these effects are not understood. Here we performed single-nucleus RNA sequencing (snRNA-seq) employing both short- (Illumina) and long-read (Pacific Biosciences) sequencing technologies on a total of 29 DS and non-DS control prefrontal cortex samples. In DS, the ratio of inhibitory-to-excitatory neurons was significantly increased, which was not observed in previous reports examining sporadic AD. DS microglial transcriptomes displayed AD-related aging and activation signatures in advance of AD neuropathology, with increased microglial expression of C1q complement genes (associated with dendritic pruning) and the HSA21 transcription factor gene RUNX1 Long-read sequencing detected vast RNA isoform diversity within and among specific cell types, including numerous sequences that differed between DS and control brains. Notably, over 8,000 genes produced RNAs containing intra-exonic junctions, including amyloid precursor protein (APP) that had previously been associated with somatic gene recombination. These and related results illuminate large-scale cellular and transcriptomic alterations as features of the aging DS brain.
Molecular characterization of Barrett's esophagus at single-cell resolution

Proceedings of the National Academy of Sciences of the United States of America

2021 Nov 23

Busslinger, GA;de Barbanson, B;Oka, R;Weusten, BLA;de Maat, M;van Hillegersberg, R;Brosens, LAA;van Boxtel, R;van Oudenaarden, A;Clevers, H;
PMID: 34795059 | DOI: 10.1073/pnas.2113061118

Barrett's esophagus (BE) is categorized, based on morphological appearance, into different stages, which correlate with the risk of developing esophageal adenocarcinoma. More advanced stages are more likely to acquire chromosomal instabilities, but stage-specific markers remain elusive. Here, we performed single-cell DNA-sequencing experiments (scDNAseq) with fresh BE biopsies. Dysplastic BE cells frequently contained chromosomal instability (CIN) regions, and these CIN cells carried mutations corresponding to the COSMIC mutational signature SBS17, which were not present in biopsy-matched chromosomally stable (CS) cells or patient-matched nondiseased control cells. CS cells were predominantly found in nondysplastic BE biopsies. The single-base substitution (SBS) signatures of all CS BE cells analyzed were indistinguishable from those of nondiseased esophageal or gastric cells. Single-cell RNA-sequencing (scRNAseq) experiments with BE biopsies identified two sets of marker genes which facilitate the distinction between columnar BE epithelium and nondysplastic/dysplastic stages. Moreover, histological validation confirmed a correlation between increased CLDN2 expression and the presence of dysplastic BE stages. Our scDNAseq and scRNAseq datasets, which are a useful resource for the community, provide insight into the mutational landscape and gene expression pattern at different stages of BE development.
Autism-associated mutations in KV7 channels induce gating pore current

Proceedings of the National Academy of Sciences of the United States of America

2021 Nov 09

Gamal El-Din, TM;Lantin, T;Tschumi, CW;Juarez, B;Quinlan, M;Hayano, JH;Li, J;Zweifel, LS;Catterall, WA;
PMID: 34728568 | DOI: 10.1073/pnas.2112666118

Autism spectrum disorder (ASD) adversely impacts >1% of children in the United States, causing social interaction deficits, repetitive behaviors, and communication disorders. Genetic analysis of ASD has advanced dramatically through genome sequencing, which has identified >500 genes with mutations in ASD. Mutations that alter arginine gating charges in the voltage sensor of the voltage-gated potassium (KV) channel KV7 (KCNQ) are among those frequently associated with ASD. We hypothesized that these gating charge mutations would induce gating pore current (also termed ω-current) by causing an ionic leak through the mutant voltage sensor. Unexpectedly, we found that wild-type KV7 conducts outward gating pore current through its native voltage sensor at positive membrane potentials, owing to a glutamine in the third gating charge position. In bacterial and human KV7 channels, gating charge mutations at the R1 and R2 positions cause inward gating pore current through the resting voltage sensor at negative membrane potentials, whereas mutation at R4 causes outward gating pore current through the activated voltage sensor at positive potentials. Remarkably, expression of the KV7.3/R2C ASD-associated mutation in vivo in midbrain dopamine neurons of mice disrupts action potential generation and repetitive firing. Overall, our results reveal native and mutant gating pore current in KV7 channels and implicate altered control of action potential generation by gating pore current through mutant KV7 channels as a potential pathogenic mechanism in autism.
Interspecies transcriptomics identify genes that underlie disproportionate foot growth in jerboas

Current biology : CB

2021 Nov 12

Saxena, A;Sharma, V;Muthuirulan, P;Neufeld, SJ;Tran, MP;Gutierrez, HL;Chen, KD;Erberich, JM;Birmingham, A;Capellini, TD;Cobb, J;Hiller, M;Cooper, KL;
PMID: 34793695 | DOI: 10.1016/j.cub.2021.10.063

Despite the great diversity of vertebrate limb proportion and our deep understanding of the genetic mechanisms that drive skeletal elongation, little is known about how individual bones reach different lengths in any species. Here, we directly compare the transcriptomes of homologous growth cartilages of the mouse (Mus musculus) and bipedal jerboa (Jaculus jaculus), the latter of which has "mouse-like" arms but extremely long metatarsals of the feet. Intersecting gene-expression differences in metatarsals and forearms of the two species revealed that about 10% of orthologous genes are associated with the disproportionately rapid elongation of neonatal jerboa feet. These include genes and enriched pathways not previously associated with endochondral elongation as well as those that might diversify skeletal proportion in addition to their known requirements for bone growth throughout the skeleton. We also identified transcription regulators that might act as "nodes" for sweeping differences in genome expression between species. Among these, Shox2, which is necessary for proximal limb elongation, has gained expression in jerboa metatarsals where it has not been detected in other vertebrates. We show that Shox2 is sufficient to increase mouse distal limb length, and a nearby putative cis-regulatory region is preferentially accessible in jerboa metatarsals. In addition to mechanisms that might directly promote growth, we found evidence that jerboa foot elongation may occur in part by de-repressing latent growth potential. The genes and pathways that we identified here provide a framework to understand the modular genetic control of skeletal growth and the remarkable malleability of vertebrate limb proportion.
Spatial mapping of cancer tissues by OMICS technologies

Biochimica et biophysica acta. Reviews on cancer

2021 Nov 30

Ahmed, R;Augustine, R;Valera, E;Ganguli, A;Mesaeli, N;Ahmad, IS;Bashir, R;Hasan, A;
PMID: 34861353 | DOI: 10.1016/j.bbcan.2021.188663

Spatial mapping of heterogeneity in gene expression in cancer tissues can improve our understanding of cancers and help in the rapid detection of cancers with high accuracy and reliability. Significant advancements have been made in recent years in OMICS technologies, which possess the strong potential to be applied in the spatial mapping of biopsy tissue samples and their molecular profiling to a single-cell level. The clinical application of OMICS technologies in spatial profiling of cancer tissues is also advancing. The current review presents recent advancements and prospects of applying OMICS technologies to the spatial mapping of various analytes in cancer tissues. We benchmark the current state of the art in the field to advance existing OMICS technologies for high throughput spatial profiling. The factors taken into consideration include spatial resolution, types of biomolecules, numbers of different biomolecules detected from the same assay, labeled versus label-free approaches, and approximate time required for each assay. Further advancements are still needed for the widespread application of OMICs technologies in performing fast and high throughput spatial mapping of cancer tissues as well as their effective use in research and clinical applications.
Targeting KDM4A-AS1 represses AR/AR-Vs deubiquitination and enhances enzalutamide response in CRPC

Oncogene

2021 Nov 10

Zhang, B;Zhang, M;Yang, Y;Li, Q;Yu, J;Zhu, S;Niu, Y;Shang, Z;
PMID: 34759344 | DOI: 10.1038/s41388-021-02103-x

Castration-resistant prostate cancer (CRPC) is a highly malignant type of advanced cancer resistant to androgen deprivation therapy. One of the important mechanisms for the development of CRPC is the persistent imbalanced regulation of AR and AR splice variants (AR/AR-Vs). In this study, we reported KDM4A-AS1, a recently discovered lncRNA, as a tumor promoter that was significantly increased in CRPC cell lines and cancer tissues. Depletion of KDM4A-AS1 significantly reduced cell viability, proliferation, migration in vitro, and tumor growth in vivo. We found that by binding to the NTD domain, KDM4A-AS1 enhances the stability of USP14-AR/AR-Vs complex, and promoted AR/AR-Vs deubiquitination to protect it from MDM2-mediated ubiquitin-proteasome degradation. Moreover, KDM4A-AS1 was found to enhance CRPC drug resistance to enzalutamide by repressing AR/AR-Vs degradation; antisense oligonucleotide drugs targeting KDM4A-AS1 significantly reduced the growth of tumors with enzalutamide resistance. Taken together, our results indicated that KDM4A-AS1 played an important role in the progression of CRPC and enzalutamide resistance by regulating AR/AR-Vs deubiquitination; targeting KDM4A-AS1 has broad clinical application potential.
Parahippocampal latrophilin-2 (ADGRL2) expression controls topographical presubiculum to entorhinal cortex circuit connectivity

Cell reports

2021 Nov 23

Donohue, JD;Amidon, RF;Murphy, TR;Wong, AJ;Liu, ED;Saab, L;King, AJ;Pae, H;Ajayi, MT;Anderson, GR;
PMID: 34818557 | DOI: 10.1016/j.celrep.2021.110031

Brain circuits are comprised of distinct interconnected neurons that are assembled by synaptic recognition molecules presented by defined pre- and post-synaptic neurons. This cell-cell recognition process is mediated by varying cellular adhesion molecules, including the latrophilin family of adhesion G-protein-coupled receptors. Focusing on parahippocampal circuitry, we find that latrophilin-2 (Lphn2; gene symbol ADGRL2) is specifically enriched in interconnected subregions of the medial entorhinal cortex (MEC), presubiculum (PrS), and parasubiculum (PaS). Retrograde viral tracing from the Lphn2-enriched region of the MEC reveals unique topographical patterning of inputs arising from the PrS and PaS that mirrors Lphn2 expression. Using a Lphn2 conditional knockout mouse model, we find that deletion of MEC Lphn2 expression selectively impairs retrograde viral labeling of inputs arising from the ipsilateral PrS. Combined with analysis of Lphn2 expression within the MEC, this study reveals Lphn2 to be selectively expressed by defined cell types and essential for MEC-PrS circuit connectivity.
Sox6 expression distinguishes dorsally and ventrally biased dopamine neurons in the substantia nigra with distinctive properties and embryonic origins

Cell reports

2021 Nov 09

Pereira Luppi, M;Azcorra, M;Caronia-Brown, G;Poulin, JF;Gaertner, Z;Gatica, S;Moreno-Ramos, OA;Nouri, N;Dubois, M;Ma, YC;Ramakrishnan, C;Fenno, L;Kim, YS;Deisseroth, K;Cicchetti, F;Dombeck, DA;Awatramani, R;
PMID: 34758317 | DOI: 10.1016/j.celrep.2021.109975

Dopamine (DA) neurons in the ventral tier of the substantia nigra pars compacta (SNc) degenerate prominently in Parkinson's disease, while those in the dorsal tier are relatively spared. Defining the molecular, functional, and developmental characteristics of each SNc tier is crucial to understand their distinct susceptibility. We demonstrate that Sox6 expression distinguishes ventrally and dorsally biased DA neuron populations in the SNc. The Sox6+ population in the ventral SNc includes an Aldh1a1+ subset and is enriched in gene pathways that underpin vulnerability. Sox6+ neurons project to the dorsal striatum and show activity correlated with acceleration. Sox6- neurons project to the medial, ventral, and caudal striatum and respond to rewards. Moreover, we show that this adult division is encoded early in development. Overall, our work demonstrates a dual origin of the SNc that results in DA neuron cohorts with distinct molecular profiles, projections, and functions.
Single-cell transcriptomics reveals opposing roles of Shp2 in Myc-driven liver tumor cells and microenvironment

Cell reports

2021 Nov 09

Chen, WS;Liang, Y;Zong, M;Liu, JJ;Kaneko, K;Hanley, KL;Zhang, K;Feng, GS;
PMID: 34758313 | DOI: 10.1016/j.celrep.2021.109974

The mechanisms of Myc-driven liver tumorigenesis are inadequately understood. Herein we show that Myc-driven hepatocellular carcinoma (HCC) is dramatically aggravated in mice with hepatocyte-specific Ptpn11/Shp2 deletion. However, Myc-induced tumors develop selectively from the rare Shp2-positive hepatocytes in Shp2-deficent liver, and Myc-driven oncogenesis depends on an intact Ras-Erk signaling promoted by Shp2 to sustain Myc stability. Despite a stringent requirement of Shp2 cell autonomously, Shp2 deletion induces an immunosuppressive environment, resulting in defective clearance of tumor-initiating cells and aggressive tumor progression. The basal Wnt/β-catenin signaling is upregulated in Shp2-deficient liver, which is further augmented by Myc transfection. Ablating Ctnnb1 suppresses Myc-induced HCC in Shp2-deficient livers, revealing an essential role of β-catenin. Consistently, Myc overexpression and CTNNB1 mutations are frequently co-detected in HCC patients with poor prognosis. These data elucidate complex mechanisms of liver tumorigenesis driven by cell-intrinsic oncogenic signaling in cooperation with a tumor-promoting microenvironment generated by disrupting the specific oncogenic pathway.

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Description
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
EnEmProbe targets exons n and m
En-EmProbe 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

Enabling research, drug development (CDx) and diagnostics

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