Stanford Advisors


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All Publications


  • Analyzing RNA-Protein Interactions by Cross-Link Rates and CLIP-seq Libraries. Current protocols Porter, D. F., Garg, R. M., Meyers, R. M., Miao, W., Ducoli, L., Zarnegar, B. J., Khavari, P. A. 2023; 3 (1): e659

    Abstract

    UV cross-linking-based methods are the most common tool to explore in vivo RNA-protein interactions. UV cross-linking enables the freezing of direct interactions in the cell, which can then be mapped by high-throughput sequencing through a family of methods termed CLIP-seq. CLIP-seq measures the distribution of cross-link events by purifying a protein of interest and sequencing the covalently bound RNA fragments. However, there are disagreements and ambiguities as to which proteins are RNA-binding proteins and what interactions are significant as all proteins contact all RNAs at some frequency. Here we describe a protocol for both determining RNA-protein interactions through a combination of RNA library preparation and the measurement of absolute cross-link rates, which helps determine what proteins are RNA-binding proteins and what interactions are significant. This protocol, comprising an updated form of the easyCLIP protocol, describes guidelines for RNA library preparation, oligo and protein standard construction, and the measurement of cross-link rates. These methods are easily visualizable through their fluorescent labels and can be adapted to study RNA-binding properties of both functional, high affinity RNA-binding proteins, and the accidental RNA interactions of non-RNA-binding proteins. © 2023 Wiley Periodicals LLC. Basic Protocol 1: RNA library construction Basic Protocol 2: Determining UV cross-link rates Support Protocol 1: Cross-linking and lysing cells Support Protocol 2: Adapter preparation Support Protocol 3: Preparation of cross-linked RBP standard.

    View details for DOI 10.1002/cpz1.659

    View details for PubMedID 36705610

  • The p300/CBP Inhibitor A485 Normalizes Psoriatic Fibroblast Gene Expression In Vitro and Reduces Psoriasis-Like Skin Inflammation In Vivo. The Journal of investigative dermatology Kim, J., He, Y., Tormen, S., Kleindienst, P., Ducoli, L., Restivo, G., Drach, M., Levesque, M. P., Navarini, A. A., Tacconi, C., Detmar, M. 2022

    Abstract

    Psoriasis is a chronic inflammatory skin disease that often recurs at the same locations, indicating potential epigenetic changes in lesional skin cells. In this study, we discovered that fibroblasts isolated from psoriatic skin lesions retain an abnormal phenotype even after several passages in culture. Transcriptomic profiling revealed the upregulation of several genes, including the extra domain A splice variant of fibronectin and ITGA4 in psoriatic fibroblasts. A phenotypic library screening of small-molecule epigenetic modifier drugs revealed that selective CBP/p300 inhibitors were able to rescue the psoriatic fibroblast phenotype, reducing the expression levels of extra domain A splice variant of fibronectin and ITGA4. In the imiquimod-induced mouse model of psoriasis-like skin inflammation, systemic treatment with A485, a potent CBP/p300 blocker, significantly reduced skin inflammation, immune cell recruitment, and inflammatory cytokine production. Our findings indicate that epigenetic reprogramming might represent a new approach for the treatment and/or prevention of relapses of psoriasis.

    View details for DOI 10.1016/j.jid.2022.09.004

    View details for PubMedID 36174717

  • Functional annotation of human long noncoding RNAs via molecular phenotyping GENOME RESEARCH Ramilowski, J. A., Yip, C., Agrawal, S., Chang, J., Ciani, Y., Kulakovskiy, I. V., Mendez, M., Ooi, J., Ouyang, J. F., Parkinson, N., Petri, A., Roos, L., Severin, J., Yasuzawa, K., Abugessaisa, I., Akalin, A., Antonov, I. V., Arner, E., Bonetti, A., Bono, H., Borsari, B., Brombacher, F., Cameron, C. F., Cannistraci, C., Cardenas, R., Cardon, M., Chang, H., Dostie, J., Ducoli, L., Favorov, A., Fort, A., Garrido, D., Gil, N., Gimenez, J., Guler, R., Handoko, L., Harshbarger, J., Hasegawa, A., Hasegawa, Y., Hashimoto, K., Hayatsu, N., Heutink, P., Hirose, T., Imada, E. L., Itoh, M., Kaczkowski, B., Kanhere, A., Kawabata, E., Kawaji, H., Kawashima, T., Kelly, S., Kojima, M., Kondo, N., Koseki, H., Kouno, T., Kratz, A., Kurowska-Stolarska, M., Kwon, A., Leek, J., Lennartsson, A., Lizio, M., Lopez-Redondo, F., Luginbuhl, J., Maeda, S., Makeev, V. J., Marchionni, L., Medvedeva, Y. A., Minoda, A., Mueller, F., Munoz-Aguirre, M., Murata, M., Nishiyori, H., Nitta, K. R., Noguchi, S., Noro, Y., Nurtdinov, R., Okazaki, Y., Orlando, V., Paquette, D., Parr, C. C., Rackham, O. L., Rizzu, P., Martinez, D., Sandelin, A., Sanjana, P., Semple, C. M., Shibayama, Y., Sivaraman, D. M., Suzuki, T., Szumowski, S. C., Tagami, M., Taylor, M. S., Terao, C., Thodberg, M., Thongjuea, S., Tripathi, V., Ulitsky, I., Verardo, R., Vorontsov, I. E., Yamamoto, C., Young, R. S., Baillie, J., Forrest, A. R., Guigo, R., Hoffman, M. M., Hon, C., Kasukawa, T., Kauppinen, S., Kere, J., Lenhard, B., Schneider, C., Suzuki, H., Yagi, K., Hoon, M., Shin, J. W., Carninci, P. 2020; 30 (7): 1060–72
  • Functional annotation of human long noncoding RNAs via molecular phenotyping. Genome research Ramilowski, J. A., Yip, C. W., Agrawal, S. n., Chang, J. C., Ciani, Y. n., Kulakovskiy, I. V., Mendez, M. n., Ooi, J. L., Ouyang, J. F., Parkinson, N. n., Petri, A. n., Roos, L. n., Severin, J. n., Yasuzawa, K. n., Abugessaisa, I. n., Akalin, A. n., Antonov, I. V., Arner, E. n., Bonetti, A. n., Bono, H. n., Borsari, B. n., Brombacher, F. n., Cameron, C. J., Cannistraci, C. V., Cardenas, R. n., Cardon, M. n., Chang, H. n., Dostie, J. n., Ducoli, L. n., Favorov, A. n., Fort, A. n., Garrido, D. n., Gil, N. n., Gimenez, J. n., Guler, R. n., Handoko, L. n., Harshbarger, J. n., Hasegawa, A. n., Hasegawa, Y. n., Hashimoto, K. n., Hayatsu, N. n., Heutink, P. n., Hirose, T. n., Imada, E. L., Itoh, M. n., Kaczkowski, B. n., Kanhere, A. n., Kawabata, E. n., Kawaji, H. n., Kawashima, T. n., Kelly, S. T., Kojima, M. n., Kondo, N. n., Koseki, H. n., Kouno, T. n., Kratz, A. n., Kurowska-Stolarska, M. n., Kwon, A. T., Leek, J. n., Lennartsson, A. n., Lizio, M. n., López-Redondo, F. n., Luginbühl, J. n., Maeda, S. n., Makeev, V. J., Marchionni, L. n., Medvedeva, Y. A., Minoda, A. n., Müller, F. n., Muñoz-Aguirre, M. n., Murata, M. n., Nishiyori, H. n., Nitta, K. R., Noguchi, S. n., Noro, Y. n., Nurtdinov, R. n., Okazaki, Y. n., Orlando, V. n., Paquette, D. n., Parr, C. J., Rackham, O. J., Rizzu, P. n., Sánchez Martinez, D. F., Sandelin, A. n., Sanjana, P. n., Semple, C. A., Shibayama, Y. n., Sivaraman, D. M., Suzuki, T. n., Szumowski, S. C., Tagami, M. n., Taylor, M. S., Terao, C. n., Thodberg, M. n., Thongjuea, S. n., Tripathi, V. n., Ulitsky, I. n., Verardo, R. n., Vorontsov, I. E., Yamamoto, C. n., Young, R. S., Baillie, J. K., Forrest, A. R., Guigó, R. n., Hoffman, M. M., Hon, C. C., Kasukawa, T. n., Kauppinen, S. n., Kere, J. n., Lenhard, B. n., Schneider, C. n., Suzuki, H. n., Yagi, K. n., de Hoon, M. J., Shin, J. W., Carninci, P. n. 2020

    Abstract

    Long noncoding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes, and yet, their functions remain largely unknown. As part of the FANTOM6 project, we systematically knocked down the expression of 285 lncRNAs in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNAs exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest-to-date lncRNA knockdown data set with molecular phenotyping (over 1000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2.

    View details for DOI 10.1101/gr.254219.119

    View details for PubMedID 32718982