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4. Long non-coding RNAs: definitions, functions, challenges and recommendations

Author

Mattick, John S., Amaral, Paulo P., Carninci, Piero, Carpenter, Susan, Chang, Howard Y., Chen, Ling-Ling, Chen, Runsheng, Dean, Caroline, Dinger, Marcel E., Fitzgerald, Katherine A., Gingeras, Thomas R., Guttman, Mitchell, Hirose, Tetsuro, Huarte, Maite, Johnson, Rory, Kanduri, Chandrasekhar, Kapranov, Philipp, Lawrence, Jeanne B., Lee, Jeannie T., Mendell, Joshua T., Mercer, Timothy R., Moore, Kathryn J., Nakagawa, Shinichi, Rinn, John L., Spector, David L., Ulitsky, Igor, Wan, Yue, Wilusz, Jeremy E., and Wu, Mian

Published
2023
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5. Natural history of Ebola virus disease in rhesus monkeys shows viral variant emergence dynamics and tissue-specific host responses

Author

Normandin, Erica, Triana, Sergio, Raju, Siddharth S., Lan, Tammy C.T., Lagerborg, Kim, Rudy, Melissa, Adams, Gordon C., DeRuff, Katherine C., Logue, James, Liu, David, Strebinger, Daniel, Rao, Arya, Messer, Katelyn S., Sacks, Molly, Adams, Ricky D., Janosko, Krisztina, Kotliar, Dylan, Shah, Rickey, Crozier, Ian, Rinn, John L., Melé, Marta, Honko, Anna N., Zhang, Feng, Babadi, Mehrtash, Luban, Jeremy, Bennett, Richard S., Shalek, Alex K., Barkas, Nikolaos, Lin, Aaron E., Hensley, Lisa E., Sabeti, Pardis C., and Siddle, Katherine J.

Published
2023
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7. Genetic Models Reveal cis and trans Immune-Regulatory Activities for lincRNA-Cox2

Author

Elling, Roland, Robinson, Elektra K, Shapleigh, Barbara, Liapis, Stephen C, Covarrubias, Sergio, Katzman, Sol, Groff, Abigail F, Jiang, Zhaozhao, Agarwal, Shiuli, Motwani, Mona, Chan, Jennie, Sharma, Shruti, Hennessy, Elizabeth J, FitzGerald, Garret A, McManus, Michael T, Rinn, John L, Fitzgerald, Katherine A, and Carpenter, Susan

Subjects
Biological Sciences, Genetics, 2.1 Biological and endogenous factors, Aetiology, Inflammatory and immune system, Animals, Cyclooxygenase 2, Enhancer Elements, Genetic, Gene Deletion, Gene Expression Regulation, HEK293 Cells, Humans, Immunity, Lipopolysaccharides, Lung, Macrophages, Mice, Inbred C57BL, Mice, Knockout, Models, Genetic, Mutation, RNA, RNA Splicing, RNA, Long Noncoding, RNA, Messenger, Spleen, Transcription, Genetic, CRISPR/Cas9, CRISPRi, Ptgs2, inflammation, innate immunity, lincRNA-Cox2, Biochemistry and Cell Biology, Medical Physiology, Biological sciences
Abstract

An inducible gene expression program is a hallmark of the host inflammatory response. Recently, long intergenic non-coding RNAs (lincRNAs) have been shown to regulate the magnitude, duration, and resolution of these responses. Among these is lincRNA-Cox2, a dynamically regulated gene that broadly controls immune gene expression. To evaluate the in vivo functions of this lincRNA, we characterized multiple models of lincRNA-Cox2-deficient mice. LincRNA-Cox2-deficient macrophages and murine tissues had altered expression of inflammatory genes. Transcriptomic studies from various tissues revealed that deletion of the lincRNA-Cox2 locus also strongly impaired the basal and inducible expression of the neighboring gene prostaglandin-endoperoxide synthase (Ptgs2), encoding cyclooxygenase-2, a key enzyme in the prostaglandin biosynthesis pathway. By utilizing different genetic manipulations in vitro and in vivo, we found that lincRNA-Cox2 functions through an enhancer RNA mechanism to regulate Ptgs2. More importantly, lincRNA-Cox2 also functions in trans, independently of Ptgs2, to regulate critical innate immune genes in vivo.

Published
2018

20. Improving RNA-Seq expression estimates by correcting for fragment bias

Author

Roberts, Adam, Trapnell, Cole, Donaghey, Julie, Rinn, John L, and Pachter, Lior

Abstract

Abstract The biochemistry of RNA-Seq library preparation results in cDNA fragments that are not uniformly distributed within the transcripts they represent. This non-uniformity must be accounted for when estimating expression levels, and we show how to perform the needed corrections using a likelihood based approach. We find improvements in expression estimates as measured by correlation with independently performed qRT-PCR and show that correction of bias leads to improved replicability of results across libraries and sequencing technologies.

Published
2011

22. HOXA3 modulates injury-induced mobilization and recruitment of bone marrow-derived cells.

Author

Mace, Kimberly A, Restivo, Terry E, Rinn, John L, Paquet, Agnes C, Chang, Howard Y, Young, David M, and Boudreau, Nancy J

Subjects
Leukocytes, Bone Marrow Cells, Cells, Cultured, Animals, Mice, Mice, Mutant Strains, Diabetes Mellitus, Disease Models, Animal, Homeodomain Proteins, Oligonucleotide Array Sequence Analysis, Flow Cytometry, Immunohistochemistry, Random Allocation, Reverse Transcriptase Polymerase Chain Reaction, Wound Healing, Cell Movement, Female, Male, Wound repair, HOXA3, Bone marrow-derived cells, Endothelial progenitor cells, Inflammation, Angiogenesis, Vasculogenesis, GFP chimeras, Cells, Cultured, Mutant Strains, Disease Models, Animal, Immunology, Biological Sciences, Technology, Medical and Health Sciences
Abstract

The regulated recruitment and differentiation of multipotent bone marrow-derived cells (BMDCs) to sites of injury are critical for efficient wound healing. Previously we demonstrated that sustained expression of HOXA3 both accelerated wound healing and promoted angiogenesis in diabetic mice. In this study, we have used green fluorescent protein-positive bone marrow chimeras to investigate the effect of HOXA3 expression on recruitment of BMDCs to wounds. We hypothesized that the enhanced neovascularization induced by HOXA3 is due to enhanced mobilization, recruitment, and/or differentiation of BMDCs. Here we show that diabetic mice treated with HOXA3 displayed a significant increase in both mobilization and recruitment of endothelial progenitor cells compared with control mice. Importantly, we also found that HOXA3-treated mice had significantly fewer inflammatory cells recruited to the wound compared with control mice. Microarray analyses of HOXA3-treated wounds revealed that indeed HOXA3 locally increased expression of genes that selectively promote stem/progenitor cell mobilization and recruitment while also suppressing expression of numerous members of the proinflammatory nuclear factor kappaB pathway, including myeloid differentiation primary response gene 88 and toll-interacting protein. Thus HOXA3 accelerates wound repair by mobilizing endothelial progenitor cells and attenuating the excessive inflammatory response of chronic wounds.

Published
2009

24. The Tug1 lncRNA locus is essential for male fertility

Author

Lewandowski, Jordan P., Dumbović, Gabrijela, Watson, Audrey R., Hwang, Taeyoung, Jacobs-Palmer, Emily, Chang, Nydia, Much, Christian, Turner, Kyle M., Kirby, Christopher, Rubinstein, Nimrod D., Groff, Abigail F., Liapis, Steve C., Gerhardinger, Chiara, Bester, Assaf, Pandolfi, Pier Paolo, Clohessy, John G., Hoekstra, Hopi E., Sauvageau, Martin, and Rinn, John L.

Published
2020
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31. Identification of human long noncoding RNAs associated with nonalcoholic fatty liver disease and metabolic homeostasis

Author

Ruan, Xiangbo, Li, Ping, Ma, Yonghe, Jiang, Cheng-fei, Chen, Yi, Shi, Yu, Gupta, Nikhil, Seifuddin, Fayaz, Pirooznia, Mehdi, Ohnishi, Yasuyuki, Yoneda, Nao, Nishiwaki, Megumi, Dumbovic, Gabrijela, Rinn, John L., Higuchi, Yuichiro, Kawai, Kenji, Suemizu, Hiroshi, and Cao, Haiming

Subjects
Metabolic regulation -- Genetic aspects -- Health aspects, Fatty liver -- Genetic aspects -- Risk factors, RNA -- Identification and classification -- Physiological aspects -- Health aspects, Health care industry
Abstract

A growing number of long noncoding RNAs (lncRNAs) have emerged as vital metabolic regulators. However, most human lncRNAs are nonconserved and highly tissue specific, vastly limiting our ability to identify human lncRNA metabolic regulators (hLMRs). In this study, we established a pipeline to identify putative hLMRs that are metabolically sensitive, disease relevant, and population applicable. We first progressively processed multilevel human transcriptome data to select liver lncRNAs that exhibit highly dynamic expression in the general population, show differential expression in a nonalcoholic fatty liver disease (NAFLD) population, and respond to dietary intervention in a small NAFLD cohort. We then experimentally demonstrated the responsiveness of selected hepatic lncRNAs to defined metabolic milieus in a liver-specific humanized mouse model. Furthermore, by extracting a concise list of protein-coding genes that are persistently correlated with lncRNAs in general and NAFLD populations, we predicted the specific function for each hLMR. Using gain- and loss-offunction approaches in humanized mice as well as ectopic expression in conventional mice, we validated the regulatory role of one nonconserved hLMR in cholesterol metabolism by coordinating with an RNA-binding protein, PTBP1, to modulate the transcription of cholesterol synthesis genes. Our work overcame the heterogeneity intrinsic to human data to enable the efficient identification and functional definition of disease-relevant human lncRNAs in metabolic homeostasis., Introduction In the past 2 decades, metabolic diseases have reached epidemic proportions globally (1, 2), underscoring the urgent need for a better understanding of metabolism regulation in humans. Although significant [...]

Published
2021
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32. T-REX17 is a transiently expressed non-coding RNA essential for human endoderm formation

Author

Landshammer, Alexandro, primary, Bolondi, Adriano, primary, Kretzmer, Helene, additional, Much, Christian, additional, Buschow, René, additional, Rose, Alina, additional, Wu, Hua-Jun, additional, Mackowiak, Sebastian D, additional, Braendl, Bjoern, additional, Giesselmann, Pay, additional, Tornisiello, Rosaria, additional, Parsi, Krishna Mohan, additional, Huey, Jack, additional, Mielke, Thorsten, additional, Meierhofer, David, additional, Maehr, René, additional, Hnisz, Denes, additional, Michor, Franziska, additional, Rinn, John L, additional, and Meissner, Alexander, additional

Published
2023
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33. DNMT1 inhibition by pUG-fold quadruplex RNA

Author

Jansson-Fritzberg, Linnea I, primary, Sousa, Camila I, additional, Smallegan, Michael J, additional, Song, Jessica J, additional, Gooding, Anne R, additional, Kasinath, Vignesh, additional, Rinn, John L, additional, and Cech, Thomas R, additional

Published
2022
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34. Author response: T-REX17 is a transiently expressed non-coding RNA essential for human endoderm formation

Author

Landshammer, Alexandro, primary, Bolondi, Adriano, primary, Kretzmer, Helene, additional, Much, Christian, additional, Buschow, René, additional, Rose, Alina, additional, Wu, Hua-Jun, additional, Mackowiak, Sebastian D, additional, Braendl, Bjoern, additional, Giesselmann, Pay, additional, Tornisiello, Rosaria, additional, Parsi, Krishna Mohan, additional, Huey, Jack, additional, Mielke, Thorsten, additional, Meierhofer, David, additional, Maehr, René, additional, Hnisz, Denes, additional, Michor, Franziska, additional, Rinn, John L, additional, and Meissner, Alexander, additional

Published
2022
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37. DNMT1 inhibition by pUG-fold quadruplex RNA

Author

Jansson-Fritzberg, Linnea I., primary, Sousa, Camila I., additional, Smallegan, Michael J., additional, Song, Jessica J., additional, Gooding, Anne R., additional, Kasinath, Vignesh, additional, Rinn, John L., additional, and Cech, Thomas R., additional

Published
2022
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39. Discovery and characterization of LNCSOX17 as an essential regulator in human endoderm formation

Author

Landshammer, Alexandro, primary, Bolondi, Adriano, additional, Kretzmer, Helene, additional, Much, Christian, additional, Buschow, René, additional, Rose, Alina, additional, Wu, Hua-Jun, additional, Mackowiak, Sebastian, additional, Braendl, Bjoern, additional, Giesselmann, Pay, additional, Tornisiello, Rosaria, additional, Parsi, Krishna Mohan, additional, Huey, Jack, additional, Mielke, Thorsten, additional, Meierhofer, David, additional, Maehr, René, additional, Hnisz, Denes, additional, Michor, Franziska, additional, Rinn, John L., additional, and Meissner, Alexander, additional

Published
2022
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40. The long non-coding RNA Morrbid regulates Bim and short-lived myeloid cell lifespan

Author

Kotzin, Jonathan J., Spencer, Sean P., McCright, Sam J., Kumar, Dinesh B. Uthaya, Collet, Magalie A., Mowel, Walter K., Elliott, Ellen N., Uyar, Asli, Makiya, Michelle A., Dunagin, Margaret C., Harman, Christian C. D., Virtue, Anthony T., Zhu, Stella, Bailis, Will, Stein, Judith, Hughes, Cynthia, Raj, Arjun, Wherry, E. John, Goff, Loyal A., Klion, Amy D., Rinn, John L., Williams, Adam, Flavell, Richard A., and Henao-Mejia, Jorge

Subjects
Cell regulation -- Methods, Granulocytes -- Physiological aspects, RNA -- Physiological aspects, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Author(s): Jonathan J. Kotzin [1, 2]; Sean P. Spencer [1, 2]; Sam J. McCright [1, 2]; Dinesh B. Uthaya Kumar [3, 4]; Magalie A. Collet [3]; Walter K. Mowel [1, [...]

Published
2016
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42. Long noncoding RNAs regulate adipogenesis

Author

Sun, Lei, Goff, Loyal A., Trapnell, Cole, Alexander, Ryan, Lo, Kinyui Alice, Hacisuleyman, Ezgi, Sauvageau, Martin, Tazon-Vega, Barbara, Kelley, David R., Hendrickson, David G., Yuan, Bingbing, Kellis, Manolis, Lodish, Harvey F., and Rinn, John L.

Published
2013

43. Single-Cell Profiling of Ebola Virus Disease In Vivo Reveals Viral and Host Dynamics

Author

Harvard University--MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology. Department of Chemistry, Massachusetts Institute of Technology. Institute for Medical Engineering & Science, Koch Institute for Integrative Cancer Research at MIT, Ragon Institute of MGH, MIT and Harvard, Kotliar, Dylan, Lin, Aaron E, Logue, James, Hughes, Travis K, Khoury, Nadine M, Raju, Siddharth S, Wadsworth, Marc H, Chen, Han, Kurtz, Jonathan R, Dighero-Kemp, Bonnie, Bjornson, Zach B, Mukherjee, Nilanjan, Sellers, Brian A, Tran, Nancy, Bauer, Matthew R, Adams, Gordon C, Adams, Ricky, Rinn, John L, Melé, Marta, Schaffner, Stephen F, Nolan, Garry P, Barnes, Kayla G, Hensley, Lisa E, McIlwain, David R, Shalek, Alex K, Sabeti, Pardis C, Bennett, Richard S, Harvard University--MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology. Department of Chemistry, Massachusetts Institute of Technology. Institute for Medical Engineering & Science, Koch Institute for Integrative Cancer Research at MIT, Ragon Institute of MGH, MIT and Harvard, Kotliar, Dylan, Lin, Aaron E, Logue, James, Hughes, Travis K, Khoury, Nadine M, Raju, Siddharth S, Wadsworth, Marc H, Chen, Han, Kurtz, Jonathan R, Dighero-Kemp, Bonnie, Bjornson, Zach B, Mukherjee, Nilanjan, Sellers, Brian A, Tran, Nancy, Bauer, Matthew R, Adams, Gordon C, Adams, Ricky, Rinn, John L, Melé, Marta, Schaffner, Stephen F, Nolan, Garry P, Barnes, Kayla G, Hensley, Lisa E, McIlwain, David R, Shalek, Alex K, Sabeti, Pardis C, and Bennett, Richard S

Abstract

© 2020 The Author(s) Single-cell profiling of circulating immune cells during Ebola virus (EBOV) infection in non-human primates resolves molecular correlates of viral tropism, characterizes replication dynamics within infected cells, and distinguishes expression changes that are mediated by viral infection from those due to cytokine signaling.

Published
2022

44. Dissecting neural differentiation regulatory networks through epigenetic footprinting

Author

Ziller, Michael J., Edri, Reuven, Yaffe, Yakey, Donaghey, Julie, Pop, Ramona, Mallard, William, Issner, Robbyn, Gifford, Casey A., Goren, Alon, Xing, Jeffrey, Gu, Hongcang, Cacchiarelli, Davide, Tsankov, Alexander M., Epstein, Charles, Rinn, John L., Mikkelsen, Tarjei S., Kohlbacher, Oliver, Gnirke, Andreas, Bernstein, Bradley E., Elkabetz, Yechiel, and Meissner, Alexander

Subjects
Neural circuitry -- Research, Genetic research, Stem cells -- Genetic aspects, Neurological research, Cell differentiation -- Research, Epigenetic inheritance -- Research, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Models derived from human pluripotent stem cells that accurately recapitulate neural development in vitro and allow for the generation of specific neuronal subtypes are of major interest to the stem cell and biomedical community. Notch signalling, particularly through the Notch effector HES5, is a major pathway critical for the onset and maintenance of neural progenitor cells in the embryonic and adult nervous system (1-3). Here we report the transcriptional and epigenomic analysis of six consecutive neural progenitor cell stages derived from a HES5::eGFP reporter human embryonic stem cell line (4). Using this system, we aimed to model cell-fate decisions including specification, expansion and patterning during the ontogeny of cortical neural stem and progenitor cells. In order to dissect regulatory mechanisms that orchestrate the stage-specific differentiation process, we developed a computational framework to infer key regulators of each cell-state transition based on the progressive remodelling of the epigenetic landscape and then validated these through a pooled short hairpin RNA screen. We were also able to refine our previous observations on epigenetic priming at transcription factor binding sites and suggest here that they are mediated by combinations of core and stage-specific factors. Taken together, we demonstrate the utility of our system and outline a general framework, not limited to the context of the neural lineage, to dissect regulatory circuits of differentiation., We used the human embryonic stem (ES) cell line WA9 (also known as H9) expressing GFP under the HES5 promoter (4) to isolate defined neural progenitor populations of neuroepithelial (NE), [...]

Published
2015

48. Additional file 1 of Prolonged FOS activity disrupts a global myogenic transcriptional program by altering 3D chromatin architecture in primary muscle progenitor cells

Author

Barutcu, A. Rasim, Elizalde, Gabriel, Gonzalez, Alfredo E., Soni, Kartik, Rinn, John L., Wagers, Amy J., and Almada, Albert E.

Abstract

Additional file 1: Supplementary Figure S1. Related to Figure 1. Validation and characterizing of our DOX-Inducible system for manipulating FOS expression in Muscle Progenitor Cells Ex Vivo. (A) Representative images of cultured muscle progenitor cells in GM supplemented with increasing amounts of Doxycycline (0, 0.005 μg/ml, 0.01 μg/ml, 0.05 μg/ml, 0.1 μg/ml, 0.5 μg/ml, 1 μg/ml, 2.5 μg/ml, 5 μg/ml) for 48 hours in culture. Scale bars represent 50 microns. (B) Quantification of the total number of Hoechst+ cells after 48 hours in GM supplemented with the indicated concentration of DOX (n=cells from 3mice). (C) Experimental Flowchart for detecting FOS protein (sc-7292) using ProteinSimple WES platform and analysis using the COMPASS software. (D) Virtual bands showing gradual increase of FOS protein with increasing amounts of DOX. Raw area of signal is shown for loading control (GAPDH) and FOS. FOS signal normalized to GAPDH is displayed, highlighting that 1 ug/ml of DOX was the lowest concentration that gave the maximal induction of FOS protein. (E) 20X images of two-week cultured muscle progenitor cells grown in GM for 48 hours or differentiated in DM for 72 hours and stained for PAX7 and MyoG. Nuclei stained with DAPI. Scale bar represents 50 microns. (F) Corrected total cell fluorescence (CTCF) for PAX7 (left) and MYOG (right) quantified in (E). n= 98-4184 cells (PAX7) and n= 2169-46118 cells (MYOG). (G) Corrected total cell fluorescence (CTCF) for PAX7 (left) and MYOG (right) in two-week cultured pSLIK-Fos and pSLIK-Gfp muscle progenitor cells. n=2295-2816 (PAX7) and n=1432-3779 (MYOG). Mean comparisons using One-way ANOVA with post-hoc Tukey test (B) and Mann Whitney U-test (F, G). Supplementary Figure S2. Related to Figure 3. FOS-dependent suppression of myogenic genes in muscle progenitor cells is reversible upon DOX removal. pSLIK-Fos cells were treated with 1 ug/ml DOX for 72-hours and then chased with media devoid of DOX for 3 and 5 days followed by RT-qPCR. Mean relative mRNA expression (+/-SD) and normalized (to Gapdh) for Fos, MyoD, MyoG, Tcap, and Ttn. Data shows that upon removal of DOX, mRNA expression for MyoD, MyoG, Tcap, and Ttn are de-repressed concomitant with FOS returning to basal levels. Mean comparisons were performed with a one-way ANOVA with post hoc Tukey test. N= 5-6 replicate cultures from cells pooled from 4 mice. Supplementary Figure S3. Related to Figure 3. Chromatin Immunoprecipitation (ChIP)-qPCR analysis for H3K27Me3 occupancy at the promoter region of Bmp6, an intergenic region, MyoD, and Ttn in pSLIK-Fos and pSLIK-Gfp cultured muscle progenitor cells. (A) Experimental design: Primary satellite cells were infected with virus expressing pSLIK-Fos or pSLIK-Gfp constructs, selected with 100 μg/mL of hygromycin for 6 days, and expanded for approximately 3 weeks to generate enough cells for ChIP-qPCR. Once at the desired cell density, pSLIK-Fos and pSLIK-Gfp cells were cultured in GM-supplemented with 1μg/mL doxycycline (DOX) for 48 hours. Chromatin was IP’d using an H3K27Me3- or immunoglobulin G (IgG)-specific antibodies followed by qPCR. Plot shows mean percent of input (+/- SD) for each amplicon targeting the first 500bps upstream of the TSS for Bmp6 and an intergenic region (left) and MyoD and Ttn (right). Location of primers relative to gene TSS is shown in schematic above each plot. Statistical comparisons were performed with two-way ANOVA with post hoc Holm-Sidak test. N= 8-9 replicate IPs were performed on cells pooled from 4 mice. Supplementary Figure S4. Related to Figure 4. Quality Metrics of Hi-C Datasets. (A) Pairwise comparison of all Hi-C heatmaps for each replicate of pSLIK-Gfp and pSLIK-Fos datasets showing all the chromosomes and the inter-chromosomal interactions. (B) Scaling plot showing the interaction frequency as a function of genomic distance, demonstrating that pSLIK-Fos and pSLIK-Gfp muscle progenitor cells have similar rates of decay of interaction frequency. (C) Representative higher resolution images of Hi-C datasets of pSLIK-Gfp and pSLIK-Fos muscle progenitor cells. Supplementary Figure S5. Related to Figure 5. Compartment Analysis of Hi-C Data. (A-B) Heatmap for the pSLIK-Fos and pSLIK-Gfp cells showing the compartment strength, quantified by plotting interaction frequencies in 250kb bins arranged by their values along the first eigenvector (PC1/EV1) to obtain compartmentalization saddle plots. The average interaction frequencies of the observed / expected interactions between pairs of loci (250kb bins) were calculated and arranged by their compartment signal (1st eigenvector value) for pSLIK-Fos and pSLIK-Gfp muscle progenitor cells. In these plots the upper left quadrant represents B-B interactions, and the lower right corner represents A-A interactions. (C) Comparison of the intra- and inter-compartmental interaction frequencies indicates that FOS induction (i.e., pSLIK-Fos cells) results in significantly higher interactions within the A-type and B-type compartments (p < 2.2 x 10-16, Wilcoxon rank-sum test). In contrast, the inter-compartmental (between the A-type and B-type compartments) interactions were significantly decreased (p < 2.2 x 10-16, Wilcoxon rank-sum test) in pSLIK-Fos cells when compared to pSLIK-Gfp cells. (D) Gene ontology terms of differentially expressed transcripts whose coding regions have switched from open (A-type) to closed (B-type) compartmentalization. (E). Gene ontology terms of differentially expressed transcripts whose coding regions have switched from closed (B-type) to open (A-type) compartmentalization. Supplementary Figure S6. Related to Figure 6. Analysis of TAD boundaries. (A) A representative Hi-C heatmap at 40kb resolution for a 10 megabase genomic region (chr1:186,000,000-196,000,000) with insulation plots depicted on the bottom showing that most TADs are stable in pSLIK-Fos cells relative to pSLIK-Gfp cells. (B) Violin plot demonstrating similar TAD boundary strengths between pSLIK-Gfp and pSLIK-Fos datasets (p-value: Wilcoxon rank-sum test). Supplementary Figure S7. Related to Figure 6. Analysis of looping events. (A) Hi-C heatmap of pSLIK-Gfp and pSLIK-Fos datasets showing a reduction of a loop formation at the Myl1 gene locus, which is associated with a decrease in Myl1 gene expression (pSLIK-Fos vs. pSLIK-Gfp log2FC = -1.7). The z-scores of the looping interaction are depicted on the figure. (B) Overlap in MyoD-specific looping events in [38] that overlaps with FOS-specific looping events identified in this study.

Published
2022
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49. Unbiased Reconstruction of a Mammalian Transcriptional Network Mediating Pathogen Responses

Author

Amit, Ido, Garber, Manuel, Chevrier, Nicolas, Leite, Ana Paula, Donner, Yoni, Eisenhaure, Thomas, Guttman, Mitchell, Grenier, Jennifer K., Li, Weibo, Zuk, Or, Schubert, Lisa A., Birditt, Brian, Shay, Tal, Goren, Alon, Zhang, Xiaolan, Smith, Zachary, Deering, Raquel, McDonald, Rebecca C., Cabili, Moran, Bernstein, Bradley E., Rinn, John L., Meissner, Alex, Root, David E., Hacohen, Nir, and Regev, Aviv

Published
2009
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