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Truong DJJ, Armbrust N, Geilenkeuser J, Lederer EM, Santl TH, Beyer M, Ittermann S, Steinmaßl E, Dyka M, Raffl G, Phlairaharn T, Greisle T, Živanić M, Grosch M, Drukker M, Westmeyer GG. Intron-encoded cistronic transcripts for minimally invasive monitoring of coding and non-coding RNAs. Nat Cell Biol 2022; 24:1666-1676. [PMID: 36344775 PMCID: PMC9643161 DOI: 10.1038/s41556-022-00998-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Accepted: 08/19/2022] [Indexed: 11/09/2022]
Abstract
Despite their fundamental role in assessing (patho)physiological cell states, conventional gene reporters can follow gene expression but leave scars on the proteins or substantially alter the mature messenger RNA. Multi-time-point measurements of non-coding RNAs are currently impossible without modifying their nucleotide sequence, which can alter their native function, half-life and localization. Thus, we developed the intron-encoded scarless programmable extranuclear cistronic transcript (INSPECT) as a minimally invasive transcriptional reporter embedded within an intron of a gene of interest. Post-transcriptional excision of INSPECT results in the mature endogenous RNA without sequence alterations and an additional engineered transcript that leaves the nucleus by hijacking the nuclear export machinery for subsequent translation into a reporter or effector protein. We showcase its use in monitoring interleukin-2 (IL2) after T cell activation and tracking the transcriptional dynamics of the long non-coding RNA (lncRNA) NEAT1 during CRISPR interference-mediated perturbation. INSPECT is a method for monitoring gene transcription without altering the mature lncRNA or messenger RNA of the target of interest.
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Affiliation(s)
- Dong-Jiunn Jeffery Truong
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Neuherberg, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Niklas Armbrust
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Neuherberg, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Julian Geilenkeuser
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Neuherberg, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Eva-Maria Lederer
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Neuherberg, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Tobias Heinrich Santl
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Neuherberg, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Maren Beyer
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Neuherberg, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Sebastian Ittermann
- grid.4567.00000 0004 0483 2525Institute of Stem Cell Research, Helmholtz Zentrum München, Neuherberg, Germany
| | - Emily Steinmaßl
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Neuherberg, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Mariya Dyka
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Neuherberg, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Gerald Raffl
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Neuherberg, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Teeradon Phlairaharn
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Neuherberg, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Tobias Greisle
- grid.4567.00000 0004 0483 2525Institute of Stem Cell Research, Helmholtz Zentrum München, Neuherberg, Germany
| | - Milica Živanić
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Neuherberg, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Markus Grosch
- grid.4567.00000 0004 0483 2525Institute of Stem Cell Research, Helmholtz Zentrum München, Neuherberg, Germany
| | - Micha Drukker
- grid.4567.00000 0004 0483 2525Institute of Stem Cell Research, Helmholtz Zentrum München, Neuherberg, Germany
| | - Gil Gregor Westmeyer
- grid.4567.00000 0004 0483 2525Institute for Synthetic Biomedicine, Helmholtz Zentrum München, Neuherberg, Germany ,grid.6936.a0000000123222966Department of Chemistry and TUM School of Medicine, Technical University of Munich, Munich, Germany
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Moore JE, Zhang XO, Elhajjajy SI, Fan K, Pratt HE, Reese F, Mortazavi A, Weng Z. Integration of high-resolution promoter profiling assays reveals novel, cell type-specific transcription start sites across 115 human cell and tissue types. Genome Res 2021; 32:389-402. [PMID: 34949670 PMCID: PMC8805725 DOI: 10.1101/gr.275723.121] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 12/19/2021] [Indexed: 12/02/2022]
Abstract
Accurate transcription start site (TSS) annotations are essential for understanding transcriptional regulation and its role in human disease. Gene collections such as GENCODE contain annotations for tens of thousands of TSSs, but not all of these annotations are experimentally validated nor do they contain information on cell type–specific usage. Therefore, we sought to generate a collection of experimentally validated TSSs by integrating RNA Annotation and Mapping of Promoters for the Analysis of Gene Expression (RAMPAGE) data from 115 cell and tissue types, which resulted in a collection of approximately 50 thousand representative RAMPAGE peaks. These peaks are primarily proximal to GENCODE-annotated TSSs and are concordant with other transcription assays. Because RAMPAGE uses paired-end reads, we were then able to connect peaks to transcripts by analyzing the genomic positions of the 3′ ends of read mates. Using this paired-end information, we classified the vast majority (37 thousand) of our RAMPAGE peaks as verified TSSs, updating TSS annotations for 20% of GENCODE genes. We also found that these updated TSS annotations are supported by epigenomic and other transcriptomic data sets. To show the utility of this RAMPAGE rPeak collection, we intersected it with the NHGRI/EBI genome-wide association study (GWAS) catalog and identified new candidate GWAS genes. Overall, our work shows the importance of integrating experimental data to further refine TSS annotations and provides a valuable resource for the biological community.
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Affiliation(s)
| | | | | | - Kaili Fan
- University of Massachusetts Chan Medical School
| | | | | | | | - Zhiping Weng
- University of Massachusetts Chan Medical School;
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53
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Hazan J, Bester AC. CRISPR-Based Approaches for the High-Throughput Characterization of Long Non-Coding RNAs. Noncoding RNA 2021; 7:79. [PMID: 34940760 PMCID: PMC8704461 DOI: 10.3390/ncrna7040079] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 12/06/2021] [Accepted: 12/11/2021] [Indexed: 12/17/2022] Open
Abstract
Over the last decade, tens of thousands of new long non-coding RNAs (lncRNAs) have been identified in the human genome. Nevertheless, except for a handful of genes, the genetic characteristics and functions of most of these lncRNAs remain elusive; this is partially due to their relatively low expression, high tissue specificity, and low conservation across species. A major limitation for determining the function of lncRNAs was the lack of methodologies suitable for studying these genes. The recent development of CRISPR/Cas9 technology has opened unprecedented opportunities to uncover the genetic and functional characteristics of the non-coding genome via targeted and high-throughput approaches. Specific CRISPR/Cas9-based approaches were developed to target lncRNA loci. Some of these approaches involve modifying the sequence, but others were developed to study lncRNAs by inducing transcriptional and epigenetic changes. The discovery of other programable Cas proteins broaden our possibilities to target RNA molecules with greater precision and accuracy. These approaches allow for the knock-down and characterization of lncRNAs. Here, we review how various CRISPR-based strategies have been used to characterize lncRNAs with important functions in different biological contexts and how these approaches can be further utilized to improve our understanding of the non-coding genome.
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Long non-coding RNAs: novel regulators of cellular physiology and function. Pflugers Arch 2021; 474:191-204. [PMID: 34791525 PMCID: PMC8766390 DOI: 10.1007/s00424-021-02641-z] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 10/29/2021] [Accepted: 11/03/2021] [Indexed: 12/19/2022]
Abstract
Long non-coding RNAs were once considered as “junk” RNA produced by aberrant DNA transcription. They are now understood to play central roles in diverse cellular processes from proliferation and migration to differentiation, senescence and DNA damage control. LncRNAs are classed as transcripts longer than 200 nucleotides that do not encode a peptide. They are relevant to many physiological and pathophysiological processes through their control of fundamental molecular functions. This review summarises the recent progress in lncRNA research and highlights the far-reaching physiological relevance of lncRNAs. The main areas of lncRNA research encompassing their characterisation, classification and mechanisms of action will be discussed. In particular, the regulation of gene expression and chromatin landscape through lncRNA control of proteins, DNA and other RNAs will be introduced. This will be exemplified with a selected number of lncRNAs that have been described in numerous physiological contexts and that should be largely representative of the tens-of-thousands of mammalian lncRNAs. To some extent, these lncRNAs have inspired the current thinking on the central dogmas of epigenetics, RNA and DNA mechanisms.
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55
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Huang Y, Li X, Chen W, He Y, Wu S, Li X, Hou B, Wang S, He Y, Jiang H, Lun Y, Zhang J. Analysis of the prognostic significance and potential mechanisms of lncRNAs associated with m6A methylation in papillary thyroid carcinoma. Int Immunopharmacol 2021; 101:108286. [PMID: 34735975 DOI: 10.1016/j.intimp.2021.108286] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 10/04/2021] [Accepted: 10/18/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND m6A methylation-related long non-coding RNAs (lncRNAs) play a significant role in the progression of various tumors and can be used as prognostic markers. However, whether m6A-related lncRNAs also play the same function as prognostic markers in papillary thyroid carcinoma (PTC) remains unclear. METHODS Consensus cluster analysis was performed to divide PTC samples obtained from The Cancer Genome Atlas database into two clusters according to the expression of m6A-related lncRNAs. Then, the least absolute shrinkage and selection operator (LASSO) regression analysis was performed to create and verify a prognostic model. Furthermore, the relationship among risk scores, clusters, programmed death-ligand 1 (PD-L1), tumor microenvironment (TME), clinicopathological characteristics, immune infiltration, immune checkpoint, and tumor mutation burden (TMB) was analyzed. In addition, a nomogram was created, and subsequently, the drug sensitivity of lncRNAs in the prognostic model was analyzed. Finally, the relationship between these lncRNAs and prognosis in pan-cancer was investigated. RESULTS The prognosis, RAS, BRAF, M, and TME were found to be different in two clusters. The prognostic model included three lncRNAs: PSMG3-AS1, BHLHE40-AS1, and AC016747.3. The risk score was associated with clusters, PD-L1, tumor microenvironment, clinicopathological characteristics, immune cell infiltration, immune checkpoint, and TMB, and thus, risk score was confirmed as useful prognostic indicator. Differentially expressed lncRNAs are involved in many malignancies and can be identified as cancer prognostic makers. CONCLUSION According to our research, we can regard m6A-related lncRNAs involved in the procession of PTC as a biomarker of progression-free survival for PTC patients, and pan-cancer.
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Affiliation(s)
- Yinde Huang
- Department of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning 110001, China
| | - Xin Li
- Department of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning 110001, China
| | - Wenbin Chen
- Department of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning 110001, China
| | - Yuzhen He
- Department of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning 110001, China
| | - Song Wu
- Department of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning 110001, China
| | - Xinyang Li
- Department of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning 110001, China
| | - Bingchen Hou
- Department of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning 110001, China
| | - Shiyue Wang
- Department of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning 110001, China
| | - Yuchen He
- Department of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning 110001, China
| | - Han Jiang
- Department of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning 110001, China
| | - Yu Lun
- Department of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning 110001, China
| | - Jian Zhang
- Department of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning 110001, China.
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56
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Identification of sheep lncRNAs related to the immune response to vaccines and aluminium adjuvants. BMC Genomics 2021; 22:770. [PMID: 34706639 PMCID: PMC8554944 DOI: 10.1186/s12864-021-08086-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 10/07/2021] [Indexed: 11/10/2022] Open
Abstract
Background Long non-coding RNAs (lncRNAs) are involved in several immune processes, including the immune response to vaccination, but most of them remain uncharacterised in livestock species. The mechanism of action of aluminium adjuvants as vaccine components is neither not fully understood. Results We built a transcriptome from sheep PBMCs RNA-seq data in order to identify unannotated lncRNAs and analysed their expression patterns along protein coding genes. We found 2284 novel lncRNAs and assessed their conservation in terms of sequence and synteny. Differential expression analysis performed between animals inoculated with commercial vaccines or aluminium adjuvant alone and the co-expression analysis revealed lncRNAs related to the immune response to vaccines and adjuvants. A group of co-expressed genes enriched in cytokine signalling and production highlighted the differences between different treatments. A number of differentially expressed lncRNAs were correlated with a divergently located protein-coding gene, such as the OSM cytokine. Other lncRNAs were predicted to act as sponges of miRNAs involved in immune response regulation. Conclusions This work enlarges the lncRNA catalogue in sheep and puts an accent on their involvement in the immune response to repetitive vaccination, providing a basis for further characterisation of the non-coding sheep transcriptome within different immune cells. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-08086-z.
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57
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Isaev K, Jiang L, Wu S, Lee CA, Watters V, Fort V, Tsai R, Coutinho FJ, Hussein SMI, Zhang J, Wu J, Dirks PB, Schramek D, Reimand J. Pan-cancer analysis of non-coding transcripts reveals the prognostic onco-lncRNA HOXA10-AS in gliomas. Cell Rep 2021; 37:109873. [PMID: 34686327 DOI: 10.1016/j.celrep.2021.109873] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 07/21/2021] [Accepted: 09/29/2021] [Indexed: 12/12/2022] Open
Abstract
Long non-coding RNAs (lncRNAs) are increasingly recognized as functional units in cancer and powerful biomarkers; however, most remain uncharacterized. Here, we analyze 5,592 prognostic lncRNAs in 9,446 cancers of 30 types using machine learning. We identify 166 lncRNAs whose expression correlates with survival and improves the accuracy of common clinical variables, molecular features, and cancer subtypes. Prognostic lncRNAs are often characterized by switch-like expression patterns. In low-grade gliomas, HOXA10-AS activation is a robust marker of poor prognosis that complements IDH1/2 mutations, as validated in another retrospective cohort, and correlates with developmental pathways in tumor transcriptomes. Loss- and gain-of-function studies in patient-derived glioma cells, organoids, and xenograft models identify HOXA10-AS as a potent onco-lncRNA that regulates cell proliferation, contact inhibition, invasion, Hippo signaling, and mitotic and neuro-developmental pathways. Our study underscores the pan-cancer potential of the non-coding transcriptome for identifying biomarkers and regulators of cancer progression.
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Affiliation(s)
- Keren Isaev
- Ontario Institute for Cancer Research, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Lingyan Jiang
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada
| | - Shuai Wu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China; Neurosurgical Institute of Fudan University, Shanghai, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, China
| | - Christian A Lee
- Ontario Institute for Cancer Research, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Valérie Watters
- Cancer Research Center, Université Laval, Quebec City, QC, Canada; CHU of Québec-Université Laval Research Center, Oncology Division, Quebec City, QC, Canada
| | - Victoire Fort
- Cancer Research Center, Université Laval, Quebec City, QC, Canada; CHU of Québec-Université Laval Research Center, Oncology Division, Quebec City, QC, Canada
| | - Ricky Tsai
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada
| | | | - Samer M I Hussein
- Cancer Research Center, Université Laval, Quebec City, QC, Canada; CHU of Québec-Université Laval Research Center, Oncology Division, Quebec City, QC, Canada
| | - Jie Zhang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China; Neurosurgical Institute of Fudan University, Shanghai, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, China
| | - Jinsong Wu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China; Neurosurgical Institute of Fudan University, Shanghai, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, China
| | - Peter B Dirks
- SickKids Research Institute, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Daniel Schramek
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
| | - Jüri Reimand
- Ontario Institute for Cancer Research, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
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58
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Ducoli L, Agrawal S, Hon CC, Ramilowski JA, Sibler E, Tagami M, Itoh M, Kondo N, Abugessaisa I, Hasegawa A, Kasukawa T, Suzuki H, Carninci P, Shin JW, de Hoon MJL, Detmar M. The choice of negative control antisense oligonucleotides dramatically impacts downstream analysis depending on the cellular background. BMC Genom Data 2021; 22:33. [PMID: 34521352 PMCID: PMC8439024 DOI: 10.1186/s12863-021-00992-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 08/29/2021] [Indexed: 11/18/2022] Open
Abstract
Background The lymphatic and the blood vasculature are closely related systems that collaborate to ensure the organism’s physiological function. Despite their common developmental origin, they present distinct functional fates in adulthood that rely on robust lineage-specific regulatory programs. The recent technological boost in sequencing approaches unveiled long noncoding RNAs (lncRNAs) as prominent regulatory players of various gene expression levels in a cell-type-specific manner. Results To investigate the potential roles of lncRNAs in vascular biology, we performed antisense oligonucleotide (ASO) knockdowns of lncRNA candidates specifically expressed either in human lymphatic or blood vascular endothelial cells (LECs or BECs) followed by Cap Analysis of Gene Expression (CAGE-Seq). Here, we describe the quality control steps adopted in our analysis pipeline before determining the knockdown effects of three ASOs per lncRNA target on the LEC or BEC transcriptomes. In this regard, we especially observed that the choice of negative control ASOs can dramatically impact the conclusions drawn from the analysis depending on the cellular background. Conclusion In conclusion, the comparison of negative control ASO effects on the targeted cell type transcriptomes highlights the essential need to select a proper control set of multiple negative control ASO based on the investigated cell types. Supplementary Information The online version contains supplementary material available at 10.1186/s12863-021-00992-1.
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Affiliation(s)
- Luca Ducoli
- Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Vladimir-Prelog-Weg 3, 8093, Zurich, Switzerland.,Molecular Life Sciences PhD Program, Swiss Federal Institute of Technology and University of Zurich, Zurich, Switzerland
| | - Saumya Agrawal
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan.,RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, 230-0045, Japan
| | - Chung-Chau Hon
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan.,RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, 230-0045, Japan
| | - Jordan A Ramilowski
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan.,RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, 230-0045, Japan
| | - Eliane Sibler
- Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Vladimir-Prelog-Weg 3, 8093, Zurich, Switzerland.,Molecular Life Sciences PhD Program, Swiss Federal Institute of Technology and University of Zurich, Zurich, Switzerland
| | - Michihira Tagami
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan.,RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, 230-0045, Japan
| | - Masayoshi Itoh
- RIKEN Preventive Medicine and Diagnosis Innovation Program, RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, 230-0045, Japan
| | - Naoto Kondo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan.,RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, 230-0045, Japan
| | - Imad Abugessaisa
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan.,RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, 230-0045, Japan
| | - Akira Hasegawa
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan.,RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, 230-0045, Japan
| | - Takeya Kasukawa
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan.,RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, 230-0045, Japan
| | - Harukazu Suzuki
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan.,RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, 230-0045, Japan
| | - Piero Carninci
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan.,RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, 230-0045, Japan.,Human Technopole, Via Cristina Belgioioso 171, 20157, Milan, Italy
| | - Jay W Shin
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan.,RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, 230-0045, Japan
| | - Michiel J L de Hoon
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan.,RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, 230-0045, Japan
| | - Michael Detmar
- Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Vladimir-Prelog-Weg 3, 8093, Zurich, Switzerland.
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Douka K, Birds I, Wang D, Kosteletos A, Clayton S, Byford A, Vasconcelos EJR, O'Connell MJ, Deuchars J, Whitehouse A, Aspden JL. Cytoplasmic long noncoding RNAs are differentially regulated and translated during human neuronal differentiation. RNA (NEW YORK, N.Y.) 2021; 27:1082-1101. [PMID: 34193551 PMCID: PMC8370745 DOI: 10.1261/rna.078782.121] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 06/22/2021] [Indexed: 06/10/2023]
Abstract
The expression of long noncoding RNAs is highly enriched in the human nervous system. However, the function of neuronal lncRNAs in the cytoplasm and their potential translation remains poorly understood. Here we performed Poly-Ribo-Seq to understand the interaction of lncRNAs with the translation machinery and the functional consequences during neuronal differentiation of human SH-SY5Y cells. We discovered 237 cytoplasmic lncRNAs up-regulated during early neuronal differentiation, 58%-70% of which are associated with polysome translation complexes. Among these polysome-associated lncRNAs, we find 45 small ORFs to be actively translated, 17 specifically upon differentiation. Fifteen of 45 of the translated lncRNA-smORFs exhibit sequence conservation within Hominidea, suggesting they are under strong selective constraint in this clade. The profiling of publicly available data sets revealed that 8/45 of the translated lncRNAs are dynamically expressed during human brain development, and 22/45 are associated with cancers of the central nervous system. One translated lncRNA we discovered is LINC01116, which is induced upon differentiation and contains an 87 codon smORF exhibiting increased ribosome profiling signal upon differentiation. The resulting LINC01116 peptide localizes to neurites. Knockdown of LINC01116 results in a significant reduction of neurite length in differentiated cells, indicating it contributes to neuronal differentiation. Our findings indicate cytoplasmic lncRNAs interact with translation complexes, are a noncanonical source of novel peptides, and contribute to neuronal function and disease. Specifically, we demonstrate a novel functional role for LINC01116 during human neuronal differentiation.
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Affiliation(s)
- Katerina Douka
- School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom
- LeedsOmics, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Isabel Birds
- School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom
- LeedsOmics, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Dapeng Wang
- LeedsOmics, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Andreas Kosteletos
- School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom
- LeedsOmics, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Sophie Clayton
- School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Abigail Byford
- School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom
| | | | - Mary J O'Connell
- School of Life Sciences, Faculty of Medicine and Health Sciences, The University of Nottingham, Nottingham NG7 2UH, United Kingdom
| | - Jim Deuchars
- LeedsOmics, University of Leeds, Leeds LS2 9JT, United Kingdom
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Adrian Whitehouse
- School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom
- LeedsOmics, University of Leeds, Leeds LS2 9JT, United Kingdom
- Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Julie L Aspden
- School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom
- LeedsOmics, University of Leeds, Leeds LS2 9JT, United Kingdom
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Yuan L, Li F, Wang S, Yi H, Li F, Mao Y. Identification of Tumor Microenvironment-Related Prognostic lncRNAs in Lung Adenocarcinoma. Front Oncol 2021; 11:719812. [PMID: 34408984 PMCID: PMC8366027 DOI: 10.3389/fonc.2021.719812] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 07/06/2021] [Indexed: 12/19/2022] Open
Abstract
Background Lung adenocarcinoma (LUAD) is the most common type of lung cancer and is a severe threat to human health. Although many therapies have been applied to LUAD, the long-term survival rate of patients remains unsatisfactory. We aim to find reliable immune microenvironment-related lncRNA biomarkers to improve LUAD prognosis. Methods ESTIMATE analysis was performed to evaluate the degree of immune infiltration of each patient in TAGA LUAD cohort. Correlation analysis was used to identify the immune microenvironment-related lncRNAs. Univariate cox regression analysis, LASSO analysis, and Kaplan Meier analysis were used to construct and validate the prognostic model based on microenvironment-related lncRNAs. Results We obtained 1,178 immune microenvironment-related lncRNAs after correlation analysis. One hundred and eighty of them are independent prognostic lncRNAs. Sixteen key lncRNAs were selected by LASSO method. This lncRNA-based model successfully predicted patients’ prognosis in validation cohort, and the risk score was related to pathological stage. Besides, we also found that TP53 had the highest frequency mutation in LUAD, and the mutation of TP53 in the high-risk group, which was identified by our survival model, has a poor prognosis. lncRNA-mRNA co-expression network further suggested that these lncRNAs play a vital role in the prognosis of LUAD. Conclusion Here, we filtered 16 key lncRNAs, which could predict the survival of LUAD and may be potential biomarkers and therapeutic targets.
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Affiliation(s)
- Ligong Yuan
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Feng Li
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Shuaibo Wang
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Hang Yi
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Fang Li
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yousheng Mao
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
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Konina D, Sparber P, Viakhireva I, Filatova A, Skoblov M. Investigation of LINC00493/SMIM26 Gene Suggests Its Dual Functioning at mRNA and Protein Level. Int J Mol Sci 2021; 22:ijms22168477. [PMID: 34445188 PMCID: PMC8395196 DOI: 10.3390/ijms22168477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 08/04/2021] [Accepted: 08/05/2021] [Indexed: 11/16/2022] Open
Abstract
The amount of human long noncoding RNA (lncRNA) genes is comparable to protein-coding; however, only a small number of lncRNAs are functionally annotated. Previously, it was shown that lncRNAs can participate in many key cellular processes, including regulation of gene expression at transcriptional and post-transcriptional levels. The lncRNA genes can contain small open reading frames (sORFs), and recent studies demonstrated that some of the resulting short proteins could play an important biological role. In the present study, we investigate the widely expressed lncRNA LINC00493. We determine the structure of the LINC00493 transcript, its cell localization and influence on cell physiology. Our data demonstrate that LINC00493 has an influence on cell viability in a cell-type-specific manner. Furthermore, it was recently shown that LINC00493 has a sORF that is translated into small protein SMIM26. The results of our knockdown and overexpression experiments suggest that both LINC00493/SMIM26 transcript and protein affect cell viability, but in the opposite manner.
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Affiliation(s)
- Daria Konina
- Moscow Institute of Physics and Technology, Phystech School of Biological and Medical Physics, 141701 Dolgoprudny, Russia
- Research Centre of Medical Genetics, Laboratory of Functional Genomics, 115478 Moscow, Russia; (P.S.); (I.V.); (M.S.)
- Correspondence: (D.K.); (A.F.)
| | - Peter Sparber
- Research Centre of Medical Genetics, Laboratory of Functional Genomics, 115478 Moscow, Russia; (P.S.); (I.V.); (M.S.)
| | - Iuliia Viakhireva
- Research Centre of Medical Genetics, Laboratory of Functional Genomics, 115478 Moscow, Russia; (P.S.); (I.V.); (M.S.)
| | - Alexandra Filatova
- Research Centre of Medical Genetics, Laboratory of Functional Genomics, 115478 Moscow, Russia; (P.S.); (I.V.); (M.S.)
- Correspondence: (D.K.); (A.F.)
| | - Mikhail Skoblov
- Research Centre of Medical Genetics, Laboratory of Functional Genomics, 115478 Moscow, Russia; (P.S.); (I.V.); (M.S.)
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Imada EL, Sanchez DF, Dinalankara W, Vidotto T, Ebot EM, Tyekucheva S, Franco GR, Mucci LA, Loda M, Schaeffer EM, Lotan T, Marchionni L. Transcriptional landscape of PTEN loss in primary prostate cancer. BMC Cancer 2021; 21:856. [PMID: 34311724 PMCID: PMC8314517 DOI: 10.1186/s12885-021-08593-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 07/06/2021] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND PTEN is the most frequently lost tumor suppressor in primary prostate cancer (PCa) and its loss is associated with aggressive disease. However, the transcriptional changes associated with PTEN loss in PCa have not been described in detail. In this study, we highlight the transcriptional changes associated with PTEN loss in PCa. METHODS Using a meta-analysis approach, we leveraged two large PCa cohorts with experimentally validated PTEN and ERG status by Immunohistochemistry (IHC), to derive a transcriptomic signature of PTEN loss, while also accounting for potential confounders due to ERG rearrangements. This signature was expanded to lncRNAs using the TCGA quantifications from the FC-R2 expression atlas. RESULTS The signatures indicate a strong activation of both innate and adaptive immune systems upon PTEN loss, as well as an expected activation of cell-cycle genes. Moreover, we made use of our recently developed FC-R2 expression atlas to expand this signature to include many non-coding RNAs recently annotated by the FANTOM consortium. Highlighting potential novel lncRNAs associated with PTEN loss and PCa progression. CONCLUSION We created a PCa specific signature of the transcriptional landscape of PTEN loss that comprises both the coding and an extensive non-coding counterpart, highlighting potential new players in PCa progression. We also show that contrary to what is observed in other cancers, PTEN loss in PCa leads to increased activation of the immune system. These findings can help the development of new biomarkers and help guide therapy choices.
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Affiliation(s)
- Eddie Luidy Imada
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Departamento de Bioquímica e Imunologia, ICB, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil.
| | | | - Wikum Dinalankara
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Thiago Vidotto
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ericka M Ebot
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Svitlana Tyekucheva
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Gloria Regina Franco
- Departamento de Bioquímica e Imunologia, ICB, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - Lorelei Ann Mucci
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Massimo Loda
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | | | - Tamara Lotan
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Luigi Marchionni
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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Zuo Y, Wei D, Zhu C, Naveed O, Hong W, Yang X. Unveiling the Pathogenesis of Psychiatric Disorders Using Network Models. Genes (Basel) 2021; 12:1101. [PMID: 34356117 PMCID: PMC8304351 DOI: 10.3390/genes12071101] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 07/15/2021] [Accepted: 07/16/2021] [Indexed: 01/13/2023] Open
Abstract
Psychiatric disorders are complex brain disorders with a high degree of genetic heterogeneity, affecting millions of people worldwide. Despite advances in psychiatric genetics, the underlying pathogenic mechanisms of psychiatric disorders are still largely elusive, which impedes the development of novel rational therapies. There has been accumulating evidence suggesting that the genetics of complex disorders can be viewed through an omnigenic lens, which involves contextualizing genes in highly interconnected networks. Thus, applying network-based multi-omics integration methods could cast new light on the pathophysiology of psychiatric disorders. In this review, we first provide an overview of the recent advances in psychiatric genetics and highlight gaps in translating molecular associations into mechanistic insights. We then present an overview of network methodologies and review previous applications of network methods in the study of psychiatric disorders. Lastly, we describe the potential of such methodologies within a multi-tissue, multi-omics approach, and summarize the future directions in adopting diverse network approaches.
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Affiliation(s)
- Yanning Zuo
- Department of Biological Chemistry, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA 90095, USA; (Y.Z.); (D.W.); (W.H.)
- Department of Neurobiology, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA 90095, USA
- Department of Integrative Biology and Physiology, University of California at Los Angeles, Los Angeles, CA 90095, USA; (C.Z.); (O.N.)
| | - Don Wei
- Department of Biological Chemistry, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA 90095, USA; (Y.Z.); (D.W.); (W.H.)
- Department of Neurobiology, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, Semel Institute, University of California at Los Angeles, Los Angeles, CA 90095, USA
| | - Carissa Zhu
- Department of Integrative Biology and Physiology, University of California at Los Angeles, Los Angeles, CA 90095, USA; (C.Z.); (O.N.)
| | - Ormina Naveed
- Department of Integrative Biology and Physiology, University of California at Los Angeles, Los Angeles, CA 90095, USA; (C.Z.); (O.N.)
| | - Weizhe Hong
- Department of Biological Chemistry, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA 90095, USA; (Y.Z.); (D.W.); (W.H.)
- Department of Neurobiology, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA 90095, USA
- Brain Research Institute, University of California at Los Angeles, Los Angeles, CA 90095, USA
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California at Los Angeles, Los Angeles, CA 90095, USA; (C.Z.); (O.N.)
- Brain Research Institute, University of California at Los Angeles, Los Angeles, CA 90095, USA
- Institute for Quantitative and Computational Biosciences, University of California at Los Angeles, Los Angeles, CA 90095, USA
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Keihani S, Kluever V, Fornasiero EF. Brain Long Noncoding RNAs: Multitask Regulators of Neuronal Differentiation and Function. Molecules 2021; 26:molecules26133951. [PMID: 34203457 PMCID: PMC8272081 DOI: 10.3390/molecules26133951] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 06/21/2021] [Accepted: 06/24/2021] [Indexed: 02/07/2023] Open
Abstract
The extraordinary cellular diversity and the complex connections established within different cells types render the nervous system of vertebrates one of the most sophisticated tissues found in living organisms. Such complexity is ensured by numerous regulatory mechanisms that provide tight spatiotemporal control, robustness and reliability. While the unusual abundance of long noncoding RNAs (lncRNAs) in nervous tissues was traditionally puzzling, it is becoming clear that these molecules have genuine regulatory functions in the brain and they are essential for neuronal physiology. The canonical view of RNA as predominantly a 'coding molecule' has been largely surpassed, together with the conception that lncRNAs only represent 'waste material' produced by cells as a side effect of pervasive transcription. Here we review a growing body of evidence showing that lncRNAs play key roles in several regulatory mechanisms of neurons and other brain cells. In particular, neuronal lncRNAs are crucial for orchestrating neurogenesis, for tuning neuronal differentiation and for the exact calibration of neuronal excitability. Moreover, their diversity and the association to neurodegenerative diseases render them particularly interesting as putative biomarkers for brain disease. Overall, we foresee that in the future a more systematic scrutiny of lncRNA functions will be instrumental for an exhaustive understanding of neuronal pathophysiology.
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Ping S, Wang S, He J, Chen J. Identification and Validation of Immune-Related lncRNA Signature as a Prognostic Model for Skin Cutaneous Melanoma. PHARMACOGENOMICS & PERSONALIZED MEDICINE 2021; 14:667-681. [PMID: 34113151 PMCID: PMC8184246 DOI: 10.2147/pgpm.s310299] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 05/20/2021] [Indexed: 12/22/2022]
Abstract
Purpose Skin cutaneous melanoma (SKCM) is the most aggressive skin cancer that results in high morbidity and mortality rate worldwide. Immune-related long non-coding RNAs (IRlncRs) play an important role in regulating gene expression in tumors. Therefore, in this study, we aimed to identify IRlncRs signature that could predict prognosis and therapeutic targets for melanoma irrespective of the gene expression levels. Methods RNA-sequencing data were obtained from The Cancer Genome Atlas (TCGA). IRlncRs were identified using co-expression analysis and recognized using univariate analysis. The impact of IRlncRs on survival was analyzed using a modified least absolute shrinkage and selection operator (Lasso) regression model. A 1-year survival receiver operating characteristic curve was constructed, and the area under the curve was calculated to identify the optimal cut-off point to distinguish between high and low-risk groups in patients with SKCM. Furthermore, integrative analysis was performed to identify the impact of clinicopathological features, chemotherapeutic treatment, tumor-infiltrating immune cells, and mutant genes on survival. Results A total of 28 IRlncRs significantly associated with survival were identified. Seventeen IRlncRs pairs were used to build a survival risk model that could be used to distinguish between low and high-risk groups. The high-risk group was negatively associated with tumor-infiltrating immune cells and had a higher half inhibitory centration for chemotherapeutic agents such as cisplatin and vinblastine. Additionally, the high-risk group had a positive correlation with the expression of specific mutant genes such as BRAF and KIT. Conclusion Our findings demonstrate that some IRlncRs have a significant correlation with survival and therapeutic targets for SKCM patients and may provide new insight into the clinical diagnosis and treatment strategies for SKCM patients.
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Affiliation(s)
- Shuai Ping
- Department of Orthopaedics, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430077, People's Republic of China
| | - Siyuan Wang
- Department of Orthopaedics, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430077, People's Republic of China
| | - Jinbing He
- Department of Orthopaedics, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430077, People's Republic of China
| | - Jianghai Chen
- Department of Hand Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China
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Cao H, Xu D, Cai Y, Han X, Tang L, Gao F, Qi Y, Cai D, Wang H, Ri M, Antonets D, Vyatkin Y, Chen Y, You X, Wang F, Nicolas E, Kapranov P. Very long intergenic non-coding (vlinc) RNAs directly regulate multiple genes in cis and trans. BMC Biol 2021; 19:108. [PMID: 34016118 PMCID: PMC8139166 DOI: 10.1186/s12915-021-01044-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 05/01/2021] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The majority of the human genome is transcribed in the form of long non-coding (lnc) RNAs. While these transcripts have attracted considerable interest, their molecular mechanisms of function and biological significance remain controversial. One of the main reasons behind this lies in the significant challenges posed by lncRNAs requiring the development of novel methods and concepts to unravel their functionality. Existing methods often lack cross-validation and independent confirmation by different methodologies and therefore leave significant ambiguity as to the authenticity of the outcomes. Nonetheless, despite all the caveats, it appears that lncRNAs may function, at least in part, by regulating other genes via chromatin interactions. Therefore, the function of a lncRNA could be inferred from the function of genes it regulates. In this work, we present a genome-wide functional annotation strategy for lncRNAs based on identification of their regulatory networks via the integration of three distinct types of approaches: co-expression analysis, mapping of lncRNA-chromatin interactions, and assaying molecular effects of lncRNA knockdowns obtained using an inducible and highly specific CRISPR/Cas13 system. RESULTS We applied the strategy to annotate 407 very long intergenic non-coding (vlinc) RNAs belonging to a novel widespread subclass of lncRNAs. We show that vlincRNAs indeed appear to regulate multiple genes encoding proteins predominantly involved in RNA- and development-related functions, cell cycle, and cellular adhesion via a mechanism involving proximity between vlincRNAs and their targets in the nucleus. A typical vlincRNAs can be both a positive and negative regulator and regulate multiple genes both in trans and cis. Finally, we show vlincRNAs and their regulatory networks potentially represent novel components of DNA damage response and are functionally important for the ability of cancer cells to survive genotoxic stress. CONCLUSIONS This study provides strong evidence for the regulatory role of the vlincRNA class of lncRNAs and a potentially important role played by these transcripts in the hidden layer of RNA-based regulation in complex biological systems.
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Affiliation(s)
- Huifen Cao
- Institute of Genomics, School of Medicine, Huaqiao University, 668 Jimei Road, Xiamen, 361021, China
| | - Dongyang Xu
- Institute of Genomics, School of Medicine, Huaqiao University, 668 Jimei Road, Xiamen, 361021, China
| | - Ye Cai
- Institute of Genomics, School of Medicine, Huaqiao University, 668 Jimei Road, Xiamen, 361021, China
| | - Xueer Han
- Institute of Genomics, School of Medicine, Huaqiao University, 668 Jimei Road, Xiamen, 361021, China
| | - Lu Tang
- Institute of Genomics, School of Medicine, Huaqiao University, 668 Jimei Road, Xiamen, 361021, China
| | - Fan Gao
- Institute of Genomics, School of Medicine, Huaqiao University, 668 Jimei Road, Xiamen, 361021, China
| | - Yao Qi
- Institute of Genomics, School of Medicine, Huaqiao University, 668 Jimei Road, Xiamen, 361021, China
| | - DingDing Cai
- Institute of Genomics, School of Medicine, Huaqiao University, 668 Jimei Road, Xiamen, 361021, China
| | - Huifang Wang
- Institute of Genomics, School of Medicine, Huaqiao University, 668 Jimei Road, Xiamen, 361021, China
| | - Maxim Ri
- AcademGene Ltd., 6, Acad. Lavrentjev ave, Novosibirsk, 630090, Russia
| | - Denis Antonets
- AcademGene Ltd., 6, Acad. Lavrentjev ave, Novosibirsk, 630090, Russia
- SRC VB "Vector" Rospotrebnadzor, Novosibirsk, Koltsovo, 630559, Russia
| | - Yuri Vyatkin
- AcademGene Ltd., 6, Acad. Lavrentjev ave, Novosibirsk, 630090, Russia
| | - Yue Chen
- Institute of Genomics, School of Medicine, Huaqiao University, 668 Jimei Road, Xiamen, 361021, China
| | - Xiang You
- School of Medicine, Xiamen University, Xiang'an Southern Road, Xiamen, 361102, China
| | - Fang Wang
- Institute of Genomics, School of Medicine, Huaqiao University, 668 Jimei Road, Xiamen, 361021, China
| | - Estelle Nicolas
- LBCMCP, Centre de Biologie Intégrative (CBI), Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Philipp Kapranov
- Institute of Genomics, School of Medicine, Huaqiao University, 668 Jimei Road, Xiamen, 361021, China.
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Discovering unknown human and mouse transcription factor binding sites and their characteristics from ChIP-seq data. Proc Natl Acad Sci U S A 2021; 118:2026754118. [PMID: 33975951 DOI: 10.1073/pnas.2026754118] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Transcription factor binding sites (TFBSs) are essential for gene regulation, but the number of known TFBSs remains limited. We aimed to discover and characterize unknown TFBSs by developing a computational pipeline for analyzing ChIP-seq (chromatin immunoprecipitation followed by sequencing) data. Applying it to the latest ENCODE ChIP-seq data for human and mouse, we found that using the irreproducible discovery rate as a quality-control criterion resulted in many experiments being unnecessarily discarded. By contrast, the number of motif occurrences in ChIP-seq peak regions provides a highly effective criterion, which is reliable even if supported by only one experimental replicate. In total, we obtained 2,058 motifs from 1,089 experiments for 354 human TFs and 163 motifs from 101 experiments for 34 mouse TFs. Among these motifs, 487 have not previously been reported. Mapping the canonical motifs to the human genome reveals a high TFBS density ±2 kb around transcription start sites (TSSs) with a peak at -50 bp. On average, a promoter contains 5.7 TFBSs. However, 70% of TFBSs are in introns (41%) and intergenic regions (29%), whereas only 12% are in promoters (-1 kb to +100 bp from TSSs). Notably, some TFs (e.g., CTCF, JUN, JUNB, and NFE2) have motifs enriched in intergenic regions, including enhancers. We inferred 142 cobinding TF pairs and 186 (including 115 completely) tethered binding TF pairs, indicating frequent interactions between TFs and a higher frequency of tethered binding than cobinding. This study provides a large number of previously undocumented motifs and insights into the biological and genomic features of TFBSs.
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Huang S, Lyu S, Gao Z, Zha W, Wang P, Shan Y, He J, Li Y. m6A-Related lncRNAs Are Potential Biomarkers for the Prognosis of Metastatic Skin Cutaneous Melanoma. Front Mol Biosci 2021; 8:687760. [PMID: 34026852 PMCID: PMC8131514 DOI: 10.3389/fmolb.2021.687760] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 04/21/2021] [Indexed: 01/15/2023] Open
Abstract
Background: The incidence of skin cutaneous melanoma (SKCM) has risen more rapidly than any other solid tumor in the past few decades. The median survival for metastatic melanoma is only six to nine months and the 5°years survival rate of patients with conventional therapy is less than 5%. Our aim was to reveal the potential molecular mechanism in m6A modification of lncRNA and provide candidate prognostic biomarkers for metastatic SKCM. Methods: lncRNAs expression level was obtained by re-annotation in TCGA and CCLE datasets. m6A-related lncRNAs were selected though correlation analysis. Univariate cox regression analysis was used to screen out independent prognostic factors. LASSO Cox regression was performed to construct an m6A-related lncRNA model (m6A-LncM). Univariate survival analysis and ROC curve were used to assess the prognostic efficacy of this model and candidate lncRNAs. Enrichment analysis was used to explore the candidate genes’ functions. Results: We obtained 1,086 common m6A-related lncRNAs after Pearson correlation analysis in both two datasets. 130 out of the 1,086 lncRNAs are independent prognostic factors. 24 crucial lncRNAs were filtered after LASSO Cox regression analysis. All the m6A-LncM and the 24 lncRNAs were related to overall survival. Stratified survival analysis of m6A-LncM showed that the model retains its prognostic efficacy in recurrence, radiation therapy and other subgroups. Enrichment analysis also found that these lncRNAs were immune associated. Conclusion: Here, we obtained 24 crucial lncRNAs that may be potential biomarkers to predict survival of metastatic SKCM and may provide a new insight to improve the prognosis of it.
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Affiliation(s)
- Suyang Huang
- Department of Dermatology, The Third People's Hospital of Hangzhou, Hangzhou, China
| | - Shanshan Lyu
- Department of Pathology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Zhe Gao
- Department of Dermatology, The Third People's Hospital of Hangzhou, Hangzhou, China
| | - Weifeng Zha
- Department of Dermatology, The Third People's Hospital of Hangzhou, Hangzhou, China
| | - Ping Wang
- Department of Dermatology, The Third People's Hospital of Hangzhou, Hangzhou, China
| | - Yunyun Shan
- Department of Dermatology, The Third People's Hospital of Hangzhou, Hangzhou, China
| | - Jianzhong He
- Department of Pathology, The Fifth Affiliated Hospital, Sun Yat-Sen University, Zhuhai, China
| | - Yang Li
- Department of Dermatology, The Third People's Hospital of Hangzhou, Hangzhou, China
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Fernandes N, Buchan JR. RNAs as Regulators of Cellular Matchmaking. Front Mol Biosci 2021; 8:634146. [PMID: 33898516 PMCID: PMC8062979 DOI: 10.3389/fmolb.2021.634146] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Accepted: 02/22/2021] [Indexed: 12/30/2022] Open
Abstract
RNA molecules are increasingly being identified as facilitating or impeding the interaction of proteins and nucleic acids, serving as so-called scaffolds or decoys. Long non-coding RNAs have been commonly implicated in such roles, particularly in the regulation of nuclear processes including chromosome topology, regulation of chromatin state and gene transcription, and assembly of nuclear biomolecular condensates such as paraspeckles. Recently, an increased awareness of cytoplasmic RNA scaffolds and decoys has begun to emerge, including the identification of non-coding regions of mRNAs that can also function in a scaffold-like manner to regulate interactions of nascently translated proteins. Collectively, cytoplasmic RNA scaffolds and decoys are now implicated in processes such as mRNA translation, decay, protein localization, protein degradation and assembly of cytoplasmic biomolecular condensates such as P-bodies. Here, we review examples of RNA scaffolds and decoys in both the nucleus and cytoplasm, illustrating common themes, the suitability of RNA to such roles, and future challenges in identifying and better understanding RNA scaffolding and decoy functions.
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Affiliation(s)
| | - J. Ross Buchan
- Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ, United States
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Functional annotation of lncRNA in high-throughput screening. Essays Biochem 2021; 65:761-773. [PMID: 33835127 PMCID: PMC8564734 DOI: 10.1042/ebc20200061] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 02/25/2021] [Accepted: 03/15/2021] [Indexed: 12/17/2022]
Abstract
Recent efforts on the characterization of long non-coding RNAs (lncRNAs) revealed their functional roles in modulating diverse cellular processes. These include pluripotency maintenance, lineage commitment, carcinogenesis, and pathogenesis of various diseases. By interacting with DNA, RNA and protein, lncRNAs mediate multifaceted mechanisms to regulate transcription, RNA processing, RNA interference and translation. Of more than 173000 discovered lncRNAs, the majority remain functionally unknown. The cell type-specific expression and localization of the lncRNA also suggest potential distinct functions of lncRNAs across different cell types. This highlights the niche of identifying functional lncRNAs in different biological processes and diseases through high-throughput (HTP) screening. This review summarizes the current work performed and perspectives on HTP screening of functional lncRNAs where different technologies, platforms, cellular responses and the downstream analyses are discussed. We hope to provide a better picture in applying different technologies to facilitate functional annotation of lncRNA efficiently.
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71
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Ranjan G, Sehgal P, Sharma D, Scaria V, Sivasubbu S. Functional long non-coding and circular RNAs in zebrafish. Brief Funct Genomics 2021:elab014. [PMID: 33755040 DOI: 10.1093/bfgp/elab014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 01/04/2021] [Accepted: 02/19/2021] [Indexed: 02/06/2023] Open
Abstract
The utility of model organisms to understand the function of a novel transcript/genes has allowed us to delineate their molecular mechanisms in maintaining cellular homeostasis. Organisms such as zebrafish have contributed a lot in the field of developmental and disease biology. Attributable to advancement and deep transcriptomics, many new transcript isoforms and non-coding RNAs such as long noncoding RNA (lncRNA) and circular RNAs (circRNAs) have been identified and cataloged in multiple databases and many more are yet to be identified. Various methods and tools have been utilized to identify lncRNAs/circRNAs in zebrafish using deep sequencing of transcriptomes as templates. Functional analysis of a few candidates such as tie1-AS, ECAL1 and CDR1as in zebrafish provides a prospective outline to approach other known or novel lncRNA/circRNA. New genetic alteration tools like TALENS and CRISPRs have helped in probing for the molecular function of lncRNA/circRNA in zebrafish. Further latest improvements in experimental and computational techniques offer the identification of lncRNA/circRNA counterparts in humans and zebrafish thereby allowing easy modeling and analysis of function at cellular level.
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72
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Gusic M, Prokisch H. Genetic basis of mitochondrial diseases. FEBS Lett 2021; 595:1132-1158. [PMID: 33655490 DOI: 10.1002/1873-3468.14068] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 02/17/2021] [Accepted: 02/18/2021] [Indexed: 12/13/2022]
Abstract
Mitochondrial disorders are monogenic disorders characterized by a defect in oxidative phosphorylation and caused by pathogenic variants in one of over 340 different genes. The implementation of whole-exome sequencing has led to a revolution in their diagnosis, duplicated the number of associated disease genes, and significantly increased the diagnosed fraction. However, the genetic etiology of a substantial fraction of patients exhibiting mitochondrial disorders remains unknown, highlighting limitations in variant detection and interpretation, which calls for improved computational and DNA sequencing methods, as well as the addition of OMICS tools. More intriguingly, this also suggests that some pathogenic variants lie outside of the protein-coding genes and that the mechanisms beyond the Mendelian inheritance and the mtDNA are of relevance. This review covers the current status of the genetic basis of mitochondrial diseases, discusses current challenges and perspectives, and explores the contribution of factors beyond the protein-coding regions and monogenic inheritance in the expansion of the genetic spectrum of disease.
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Affiliation(s)
- Mirjana Gusic
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany.,Institute of Human Genetics, Technical University of Munich, Germany.,DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Germany
| | - Holger Prokisch
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany.,Institute of Human Genetics, Technical University of Munich, Germany
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73
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Guiducci G, Stojic L. Long Noncoding RNAs at the Crossroads of Cell Cycle and Genome Integrity. Trends Genet 2021; 37:528-546. [PMID: 33685661 DOI: 10.1016/j.tig.2021.01.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 12/28/2020] [Accepted: 01/18/2021] [Indexed: 12/14/2022]
Abstract
The cell cycle is controlled by guardian proteins that coordinate the process of cell growth and cell division. Alterations in these processes lead to genome instability, which has a causal link to many human diseases. Beyond their well-characterized role of influencing protein-coding genes, an increasing body of evidence has revealed that long noncoding RNAs (lncRNAs) actively participate in regulation of the cell cycle and safeguarding of genome integrity. LncRNAs are versatile molecules that act via a wide array of mechanisms. In this review, we discuss how lncRNAs are implicated in control of the cell cycle and maintenance of genome stability and how changes in lncRNA-regulatory networks lead to proliferative diseases such as cancer.
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Affiliation(s)
- Giulia Guiducci
- Barts Cancer Institute, Centre for Cancer Cell and Molecular Biology, John Vane Science Centre, Charterhouse Square, Queen Mary University of London, London EC1M 6BQ, UK
| | - Lovorka Stojic
- Barts Cancer Institute, Centre for Cancer Cell and Molecular Biology, John Vane Science Centre, Charterhouse Square, Queen Mary University of London, London EC1M 6BQ, UK.
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74
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Ducoli L, Agrawal S, Sibler E, Kouno T, Tacconi C, Hon CC, Berger SD, Müllhaupt D, He Y, Kim J, D'Addio M, Dieterich LC, Carninci P, de Hoon MJL, Shin JW, Detmar M. LETR1 is a lymphatic endothelial-specific lncRNA governing cell proliferation and migration through KLF4 and SEMA3C. Nat Commun 2021; 12:925. [PMID: 33568674 PMCID: PMC7876020 DOI: 10.1038/s41467-021-21217-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 01/20/2021] [Indexed: 01/30/2023] Open
Abstract
Recent studies have revealed the importance of long noncoding RNAs (lncRNAs) as tissue-specific regulators of gene expression. There is ample evidence that distinct types of vasculature undergo tight transcriptional control to preserve their structure, identity, and functions. We determine a comprehensive map of lineage-specific lncRNAs in human dermal lymphatic and blood vascular endothelial cells (LECs and BECs), combining RNA-Seq and CAGE-Seq. Subsequent antisense oligonucleotide-knockdown transcriptomic profiling of two LEC- and two BEC-specific lncRNAs identifies LETR1 as a critical gatekeeper of the global LEC transcriptome. Deep RNA-DNA, RNA-protein interaction studies, and phenotype rescue analyses reveal that LETR1 is a nuclear trans-acting lncRNA modulating, via key epigenetic factors, the expression of essential target genes, including KLF4 and SEMA3C, governing the growth and migratory ability of LECs. Together, our study provides several lines of evidence supporting the intriguing concept that every cell type expresses precise lncRNA signatures to control lineage-specific regulatory programs.
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Affiliation(s)
- Luca Ducoli
- Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland
- Molecular Life Sciences PhD Program, Swiss Federal Institute of Technology and University of Zurich, Zurich, Switzerland
| | - Saumya Agrawal
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
- RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, Japan
| | - Eliane Sibler
- Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland
- Molecular Life Sciences PhD Program, Swiss Federal Institute of Technology and University of Zurich, Zurich, Switzerland
| | - Tsukasa Kouno
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
- RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, Japan
| | - Carlotta Tacconi
- Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland
| | - Chung-Chao Hon
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
- RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, Japan
| | - Simone D Berger
- Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland
| | - Daniela Müllhaupt
- Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland
| | - Yuliang He
- Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland
- Molecular and Translational Biomedicine PhD Program, Swiss Federal Institute of Technology and University of Zurich, Zurich, Switzerland
| | - Jihye Kim
- Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland
| | - Marco D'Addio
- Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland
| | - Lothar C Dieterich
- Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland
| | - Piero Carninci
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
- RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, Japan
| | - Michiel J L de Hoon
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
- RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, Japan
| | - Jay W Shin
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.
- RIKEN Center for Life Science Technologies, Yokohama, Kanagawa, Japan.
| | - Michael Detmar
- Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland.
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75
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Abugessaisa I, Ramilowski JA, Lizio M, Severin J, Hasegawa A, Harshbarger J, Kondo A, Noguchi S, Yip CW, Ooi J, Tagami M, Hori F, Agrawal S, Hon C, Cardon M, Ikeda S, Ono H, Bono H, Kato M, Hashimoto K, Bonetti A, Kato M, Kobayashi N, Shin J, de Hoon M, Hayashizaki Y, Carninci P, Kawaji H, Kasukawa T. FANTOM enters 20th year: expansion of transcriptomic atlases and functional annotation of non-coding RNAs. Nucleic Acids Res 2021; 49:D892-D898. [PMID: 33211864 PMCID: PMC7779024 DOI: 10.1093/nar/gkaa1054] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 10/16/2020] [Accepted: 10/21/2020] [Indexed: 11/15/2022] Open
Abstract
The Functional ANnoTation Of the Mammalian genome (FANTOM) Consortium has continued to provide extensive resources in the pursuit of understanding the transcriptome, and transcriptional regulation, of mammalian genomes for the last 20 years. To share these resources with the research community, the FANTOM web-interfaces and databases are being regularly updated, enhanced and expanded with new data types. In recent years, the FANTOM Consortium's efforts have been mainly focused on creating new non-coding RNA datasets and resources. The existing FANTOM5 human and mouse miRNA atlas was supplemented with rat, dog, and chicken datasets. The sixth (latest) edition of the FANTOM project was launched to assess the function of human long non-coding RNAs (lncRNAs). From its creation until 2020, FANTOM6 has contributed to the research community a large dataset generated from the knock-down of 285 lncRNAs in human dermal fibroblasts; this is followed with extensive expression profiling and cellular phenotyping. Other updates to the FANTOM resource includes the reprocessing of the miRNA and promoter atlases of human, mouse and chicken with the latest reference genome assemblies. To facilitate the use and accessibility of all above resources we further enhanced FANTOM data viewers and web interfaces. The updated FANTOM web resource is publicly available at https://fantom.gsc.riken.jp/.
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Affiliation(s)
- Imad Abugessaisa
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Jordan A Ramilowski
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
- Advanced Medical Research Center, Yokohama City University, Kanagawa, Japan
| | - Marina Lizio
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Jesicca Severin
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Akira Hasegawa
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Jayson Harshbarger
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Atsushi Kondo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Shuhei Noguchi
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Chi Wai Yip
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | | | - Michihira Tagami
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Fumi Hori
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Saumya Agrawal
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Chung Chau Hon
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Melissa Cardon
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Shuya Ikeda
- Database Center for Life Science, Research Organization of Information and Systems, Mishima, Shizuoka, Japan
| | - Hiromasa Ono
- Database Center for Life Science, Research Organization of Information and Systems, Mishima, Shizuoka, Japan
| | - Hidemasa Bono
- Database Center for Life Science, Research Organization of Information and Systems, Mishima, Shizuoka, Japan
- Program of Biomedical Science, Graduate School of Integrated Sciences for Life, Hiroshima University
| | - Masaki Kato
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Kosuke Hashimoto
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Alessandro Bonetti
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
- Karolinska Institutet, Stockholm, Sweden
| | - Masaki Kato
- RIKEN Head Office for Information Systems and Cybersecurity, Wako, Saitama, Japan
| | - Norio Kobayashi
- RIKEN Head Office for Information Systems and Cybersecurity, Wako, Saitama, Japan
| | - Jay Shin
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Michiel de Hoon
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | | | - Piero Carninci
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Hideya Kawaji
- Correspondence may also be addressed to Hideya Kawaji.
| | - Takeya Kasukawa
- To whom correspondence should be addressed. Tel: +81 45 503 9222; Fax: +81 45 503 9219;
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76
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Chen Z, Wu A. Progress and challenge for computational quantification of tissue immune cells. Brief Bioinform 2021; 22:6065002. [PMID: 33401306 DOI: 10.1093/bib/bbaa358] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 10/23/2020] [Accepted: 11/07/2020] [Indexed: 12/28/2022] Open
Abstract
Tissue immune cells have long been recognized as important regulators for the maintenance of balance in the body system. Quantification of the abundance of different immune cells will provide enhanced understanding of the correlation between immune cells and normal or abnormal situations. Currently, computational methods to predict tissue immune cell compositions from bulk transcriptomes have been largely developed. Therefore, summarizing the advantages and disadvantages is appropriate. In addition, an examination of the challenges and possible solutions for these computational models will assist the development of this field. The common hypothesis of these models is that the expression of signature genes for immune cell types might represent the proportion of immune cells that contribute to the tissue transcriptome. In general, we grouped all reported tools into three groups, including reference-free, reference-based scoring and reference-based deconvolution methods. In this review, a summary of all the currently reported computational immune cell quantification tools and their applications, limitations, and perspectives are presented. Furthermore, some critical problems are found that have limited the performance and application of these models, including inadequate immune cell type, the collinearity problem, the impact of the tissue environment on the immune cell expression level, and the deficiency of standard datasets for model validation. To address these issues, tissue specific training datasets that include all known immune cells, a hierarchical computational framework, and benchmark datasets including both tissue expression profiles and the abundances of all the immune cells are proposed to further promote the development of this field.
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Affiliation(s)
- Ziyi Chen
- Suzhou Institute of Systems Medicine, Center for Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Jiangsu, Suzhou, China
| | - Aiping Wu
- Suzhou Institute of Systems Medicine, Center for Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Jiangsu, Suzhou, China
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77
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Takahashi H, Nishiyori-Sueki H, Ramilowski JA, Itoh M, Carninci P. Low Quantity Single Strand CAGE (LQ-ssCAGE) Maps Regulatory Enhancers and Promoters. Methods Mol Biol 2021; 2351:67-90. [PMID: 34382184 DOI: 10.1007/978-1-0716-1597-3_4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The Cap Analysis of Gene Expression (CAGE) is a powerful method to identify Transcription Start Sites (TSSs) of capped RNAs while simultaneously measuring transcripts expression level. CAGE allows mapping at single nucleotide resolution at all active promoters and enhancers. Large CAGE datasets have been produced over the years from individual laboratories and consortia, including the Encyclopedia of DNA Elements (ENCODE) and Functional Annotation of the Mammalian Genome (FANTOM) consortia. These datasets constitute open resource for TSS annotations and gene expression analysis. Here, we provide an experimental protocol for the most recent CAGE method called Low Quantity (LQ) single strand (ss) CAGE "LQ-ssCAGE", which enables cost-effective profiling of low quantity RNA samples. LQ-ssCAGE is especially useful for samples derived from cells cultured in small volumes, cellular compartments such as nuclear RNAs or for samples from developmental stages. We demonstrate the reproducibility and effectiveness of the method by constructing 240 LQ-ssCAGE libraries from 50 ng of THP-1 cell extracted RNAs and discover lowly expressed novel enhancer and promoter-derived lncRNAs.
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Affiliation(s)
- Hazuki Takahashi
- RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Kanagawa, Japan.
| | | | - Jordan A Ramilowski
- RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Kanagawa, Japan.
- Advanced Medical Research Center, Yokohama City University, Yokohama, Kanagawa, Japan.
| | - Masayoshi Itoh
- RIKEN Preventive Medicine and Diagnosis Innovation Program (PMI), Saitama, Japan
| | - Piero Carninci
- RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Kanagawa, Japan.
- Human Technopole, Milano, Italy.
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78
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Zhang J, Liu H, Zhang W, Li Y, Fan Z, Jiang H, Luo J. Identification of lncRNA-mRNA Regulatory Module to Explore the Pathogenesis and Prognosis of Melanoma. Front Cell Dev Biol 2020; 8:615671. [PMID: 33392203 PMCID: PMC7773644 DOI: 10.3389/fcell.2020.615671] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 11/24/2020] [Indexed: 12/21/2022] Open
Abstract
Skin cutaneous melanoma (SKCM) is an aggressive form of skin cancer that results in high mortality rate worldwide. It is vital to discover effective prognostic biomarkers and therapeutic targets for the treatment of melanoma. Long non-coding RNA (lncRNA) has been verified to play an essential role in the regulation of gene expression in diseases and tumors. Therefore, it is significant to explore the function of lncRNAs in the development and progression of SKCM. In this paper, a set of differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) were first screened out using 471 cutaneous melanoma samples and 813 normal skin samples. Gene Ontology and KEGG pathway enrichment analysis were performed to obtain the significant function annotations and pathways of DEmRNAs. We also ran survival analysis on both DElncRNAs and DEmRNAs to identify prognostic-related lncRNAs and mRNAs. Next, a set of hub genes derived from protein-protein interaction (PPI) network analysis and lncRNA target genes screened from starbase-ENCORI database were integrated to construct a lncRNA-mRNA regulatory module, which includes 6 lncRNAs 4 target mRNAs. We further checked the capacity of these lncRNA and mRNA in the diagnosis of melanoma, and found that single lncRNA can effectively distinguish tumor and normal tissue. Moreover, we ran CMap analysis to select a list of small molecule drugs for SKCM, such as EGFR inhibitor AG-490, growth factor receptor inhibitor GW-441756 and apoptosis stimulant betulinic-acid, which have shown therapeutic effect in the treatment of melanoma.
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Affiliation(s)
- Jiaqi Zhang
- Department of Radiotherapy, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, China.,Department of Dermatology, Graduate School of Dalian Medical University, Dalian, China
| | - Hui Liu
- Aliyun School of Big Data, Changzhou University, Changzhou, China
| | - Wenhao Zhang
- Aliyun School of Big Data, Changzhou University, Changzhou, China
| | - Yinfang Li
- Aliyun School of Big Data, Changzhou University, Changzhou, China
| | - Zhigang Fan
- Department of Oncology, Affiliated 3201 Hospital of Xi'an Jiaotong University, Hanzhong, China
| | - Hua Jiang
- Department of Oncology, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou, China
| | - Judong Luo
- Department of Radiotherapy, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, China
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79
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Antonov I, Medvedeva Y. Direct Interactions with Nascent Transcripts Is Potentially a Common Targeting Mechanism of Long Non-Coding RNAs. Genes (Basel) 2020; 11:genes11121483. [PMID: 33321875 PMCID: PMC7764144 DOI: 10.3390/genes11121483] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Revised: 12/03/2020] [Accepted: 12/04/2020] [Indexed: 11/16/2022] Open
Abstract
Although thousands of mammalian long non-coding RNAs (lncRNAs) have been reported in the last decade, their functional annotation remains limited. A wet-lab approach to detect functions of a novel lncRNA usually includes its knockdown followed by RNA sequencing and identification of the deferentially expressed genes. However, identification of the molecular mechanism(s) used by the lncRNA to regulate its targets frequently becomes a challenge. Previously, we developed the ASSA algorithm that detects statistically significant inter-molecular RNA-RNA interactions. Here we designed a workflow that uses ASSA predictions to estimate the ability of an lncRNA to function via direct base pairing with the target transcripts (co- or post-transcriptionally). The workflow was applied to 300+ lncRNA knockdown experiments from the FANTOM6 pilot project producing statistically significant predictions for 71 unique lncRNAs (104 knockdowns). Surprisingly, the majority of these lncRNAs were likely to function co-transcriptionally, i.e., hybridize with the nascent transcripts of the target genes. Moreover, a number of the obtained predictions were supported by independent iMARGI experimental data on co-localization of lncRNA and chromatin. We detected an evolutionarily conserved lncRNA CHASERR (AC013394.2 or LINC01578) that could regulate target genes co-transcriptionally via interaction with a nascent transcript by directing CHD2 helicase. The obtained results suggested that this nuclear lncRNA may be able to activate expression of the target genes in trans by base-pairing with the nascent transcripts and directing the CHD2 helicase to the regulated promoters leading to open the chromatin and active transcription. Our study highlights the possible importance of base-pairing between nuclear lncRNAs and nascent transcripts for the regulation of gene expression.
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Affiliation(s)
- Ivan Antonov
- Research Center of Biotechnology, Institute of Bioengineering, Russian Academy of Science, 119071 Moscow, Russia;
- Department of Biological and Medical Physics, Moscow Institute of Physics and Technology, Dolgoprudny, 141701 Moscow Region, Russia
| | - Yulia Medvedeva
- Research Center of Biotechnology, Institute of Bioengineering, Russian Academy of Science, 119071 Moscow, Russia;
- Department of Biological and Medical Physics, Moscow Institute of Physics and Technology, Dolgoprudny, 141701 Moscow Region, Russia
- Correspondence:
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80
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Functional Screening Techniques to Identify Long Non-Coding RNAs as Therapeutic Targets in Cancer. Cancers (Basel) 2020; 12:cancers12123695. [PMID: 33317042 PMCID: PMC7763270 DOI: 10.3390/cancers12123695] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 12/06/2020] [Accepted: 12/07/2020] [Indexed: 12/16/2022] Open
Abstract
Simple Summary Long non-coding RNAs (lncRNAs) are a recently discovered class of molecules in the cell, with potential to be utilized as therapeutic targets in cancer. A number of lncRNAs have been described to play important roles in tumor progression and drive molecular processes involved in cell proliferation, apoptosis or invasion. However, the vast majority of lncRNAs have not been studied in the context of cancer thus far. With the advent of CRISPR/Cas genome editing, high-throughput functional screening approaches to identify lncRNAs that impact cancer growth are becoming more accessible. Here, we review currently available methods to study hundreds to thousands of lncRNAs in parallel to elucidate their role in tumorigenesis and cancer progression. Abstract Recent technological advancements such as CRISPR/Cas-based systems enable multiplexed, high-throughput screening for new therapeutic targets in cancer. While numerous functional screens have been performed on protein-coding genes to date, long non-coding RNAs (lncRNAs) represent an emerging class of potential oncogenes and tumor suppressors, with only a handful of large-scale screens performed thus far. Here, we review in detail currently available screening approaches to identify new lncRNA drivers of tumorigenesis and tumor progression. We discuss the various approaches of genomic and transcriptional targeting using CRISPR/Cas9, as well as methods to post-transcriptionally target lncRNAs via RNA interference (RNAi), antisense oligonucleotides (ASOs) and CRISPR/Cas13. We discuss potential advantages, caveats and future applications of each method to provide an overview and guide on investigating lncRNAs as new therapeutic targets in cancer.
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81
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Hao Q, Zong X, Sun Q, Lin YC, Song YJ, Hashemikhabir S, Hsu RY, Kamran M, Chaudhary R, Tripathi V, Singh DK, Chakraborty A, Li XL, Kim YJ, Orjalo AV, Polycarpou-Schwarz M, Moriarity BS, Jenkins LM, Johansson HE, Zhu YJ, Diederichs S, Bagchi A, Kim TH, Janga SC, Lal A, Prasanth SG, Prasanth KV. The S-phase-induced lncRNA SUNO1 promotes cell proliferation by controlling YAP1/Hippo signaling pathway. eLife 2020; 9:55102. [PMID: 33108271 PMCID: PMC7591261 DOI: 10.7554/elife.55102] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 10/12/2020] [Indexed: 12/13/2022] Open
Abstract
Cell cycle is a cellular process that is subject to stringent control. In contrast to the wealth of knowledge of proteins controlling the cell cycle, very little is known about the molecular role of lncRNAs (long noncoding RNAs) in cell-cycle progression. By performing genome-wide transcriptome analyses in cell-cycle-synchronized cells, we observed cell-cycle phase-specific induction of >2000 lncRNAs. Further, we demonstrate that an S-phase-upregulated lncRNA, SUNO1, facilitates cell-cycle progression by promoting YAP1-mediated gene expression. SUNO1 facilitates the cell-cycle-specific transcription of WTIP, a positive regulator of YAP1, by promoting the co-activator, DDX5-mediated stabilization of RNA polymerase II on chromatin. Finally, elevated SUNO1 levels are associated with poor cancer prognosis and tumorigenicity, implying its pro-survival role. Thus, we demonstrate the role of a S-phase up-regulated lncRNA in cell-cycle progression via modulating the expression of genes controlling cell proliferation.
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Affiliation(s)
- Qinyu Hao
- Department of Cell and Developmental Biology, Cancer center at Illinois, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Xinying Zong
- Department of Cell and Developmental Biology, Cancer center at Illinois, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Qinyu Sun
- Department of Cell and Developmental Biology, Cancer center at Illinois, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Yo-Chuen Lin
- Department of Cell and Developmental Biology, Cancer center at Illinois, University of Illinois at Urbana-Champaign, Urbana, United States
| | - You Jin Song
- Department of Cell and Developmental Biology, Cancer center at Illinois, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Seyedsasan Hashemikhabir
- Department of BioHealth Informatics, School of Informatics and Computing, IUPUI, Indianapolis, United States
| | - Rosaline Yc Hsu
- Department of Cell and Developmental Biology, Cancer center at Illinois, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Mohammad Kamran
- Department of Cell and Developmental Biology, Cancer center at Illinois, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Ritu Chaudhary
- Regulatory RNAs and Cancer Section, Genetics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, United States
| | - Vidisha Tripathi
- Department of Cell and Developmental Biology, Cancer center at Illinois, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Deepak Kumar Singh
- Department of Cell and Developmental Biology, Cancer center at Illinois, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Arindam Chakraborty
- Department of Cell and Developmental Biology, Cancer center at Illinois, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Xiao Ling Li
- Regulatory RNAs and Cancer Section, Genetics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, United States
| | - Yoon Jung Kim
- Department of Biological Sciences and Center for Systems Biology, The University of Texas at Dallas, Richardson, United States
| | | | | | - Branden S Moriarity
- Department of Pediatrics, University of Minnesota, Minneapolis, United States
| | - Lisa M Jenkins
- Center for Cancer Research National Cancer Institute, Bethesda, United States
| | | | - Yuelin J Zhu
- Molecular Genetics Section, Genetics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, United States
| | - Sven Diederichs
- Division of RNA Biology and Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Division of Cancer University of Freiburg, German Cancer Consortium (DKTK), Freiburg, Germany
| | - Anindya Bagchi
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, United States
| | - Tae Hoon Kim
- Department of Biological Sciences and Center for Systems Biology, The University of Texas at Dallas, Richardson, United States
| | - Sarath C Janga
- Department of BioHealth Informatics, School of Informatics and Computing, IUPUI, Indianapolis, United States
| | - Ashish Lal
- Regulatory RNAs and Cancer Section, Genetics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, United States
| | - Supriya G Prasanth
- Department of Cell and Developmental Biology, Cancer center at Illinois, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Kannanganattu V Prasanth
- Department of Cell and Developmental Biology, Cancer center at Illinois, University of Illinois at Urbana-Champaign, Urbana, United States
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82
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Towards a comprehensive pipeline to identify and functionally annotate long noncoding RNA (lncRNA). Comput Biol Med 2020; 127:104028. [PMID: 33126123 DOI: 10.1016/j.compbiomed.2020.104028] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Revised: 09/28/2020] [Accepted: 09/29/2020] [Indexed: 12/20/2022]
Abstract
Long noncoding RNAs (lncRNAs) are implicated in various genetic diseases and cancer, attributed to their critical role in gene regulation. They are a divergent group of RNAs and are easily differentiated from other types with unique characteristics, functions, and mechanisms of action. In this review, we provide a list of some of the prominent data repositories containing lncRNAs, their interactome, and predicted and validated disease associations. Next, we discuss various wet-lab experiments formulated to obtain the data for these repositories. We also provide a critical review of in silico methods available for the identification purpose and suggest techniques to further improve their performance. The bulk of the methods currently focus on distinguishing lncRNA transcripts from the coding ones. Functional annotation of these transcripts still remains a grey area and more efforts are needed in that space. Finally, we provide details of current progress, discuss impediments, and illustrate a roadmap for developing a generalized computational pipeline for comprehensive annotation of lncRNAs, which is essential to accelerate research in this area.
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83
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Long Non-Coding RNAs in Liver Cancer and Nonalcoholic Steatohepatitis. Noncoding RNA 2020; 6:ncrna6030034. [PMID: 32872482 PMCID: PMC7549373 DOI: 10.3390/ncrna6030034] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 08/25/2020] [Accepted: 08/27/2020] [Indexed: 12/12/2022] Open
Abstract
This review aims to highlight the recent findings of long non-coding RNAs (lncRNAs) in liver disease. In particular, we focus on the functions of lncRNAs in hepatocellular carcinoma (HCC) and non-alcoholic steatohepatitis (NASH). We summarize the current research trend in lncRNAs and their potential as biomarkers and therapeutic targets for the treatment of HCC and NASH.
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84
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Imada EL, Sanchez DF, Collado-Torres L, Wilks C, Matam T, Dinalankara W, Stupnikov A, Lobo-Pereira F, Yip CW, Yasuzawa K, Kondo N, Itoh M, Suzuki H, Kasukawa T, Hon CC, de Hoon MJL, Shin JW, Carninci P, Jaffe AE, Leek JT, Favorov A, Franco GR, Langmead B, Marchionni L. Recounting the FANTOM CAGE-Associated Transcriptome. Genome Res 2020; 30:1073-1081. [PMID: 32079618 PMCID: PMC7397872 DOI: 10.1101/gr.254656.119] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Accepted: 02/11/2020] [Indexed: 02/02/2023]
Abstract
Long noncoding RNAs (lncRNAs) have emerged as key coordinators of biological and cellular processes. Characterizing lncRNA expression across cells and tissues is key to understanding their role in determining phenotypes, including human diseases. We present here FC-R2, a comprehensive expression atlas across a broadly defined human transcriptome, inclusive of over 109,000 coding and noncoding genes, as described in the FANTOM CAGE-Associated Transcriptome (FANTOM-CAT) study. This atlas greatly extends the gene annotation used in the original recount2 resource. We demonstrate the utility of the FC-R2 atlas by reproducing key findings from published large studies and by generating new results across normal and diseased human samples. In particular, we (a) identify tissue-specific transcription profiles for distinct classes of coding and noncoding genes, (b) perform differential expression analysis across thirteen cancer types, identifying novel noncoding genes potentially involved in tumor pathogenesis and progression, and (c) confirm the prognostic value for several enhancer lncRNAs expression in cancer. Our resource is instrumental for the systematic molecular characterization of lncRNA by the FANTOM6 Consortium. In conclusion, comprised of over 70,000 samples, the FC-R2 atlas will empower other researchers to investigate functions and biological roles of both known coding genes and novel lncRNAs.
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Affiliation(s)
- Eddie Luidy Imada
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21827, USA.,Departamento de Bioqúımica e Imunologia, ICB, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, 31270-901, Brazil
| | - Diego Fernando Sanchez
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21827, USA
| | | | - Christopher Wilks
- Department of Computer Science, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Tejasvi Matam
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21827, USA
| | - Wikum Dinalankara
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21827, USA
| | - Aleksey Stupnikov
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21827, USA
| | - Francisco Lobo-Pereira
- Departamento de Biologia General, ICB, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, 31270-901, Brazil
| | - Chi-Wai Yip
- RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | - Kayoko Yasuzawa
- RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | - Naoto Kondo
- RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | - Masayoshi Itoh
- RIKEN, Preventive Medicine and Diagnostic Innovation Program, Yokohama, 351-0198, Japan
| | - Harukazu Suzuki
- RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | - Takeya Kasukawa
- RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | - Chung-Chau Hon
- RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | | | - Jay W Shin
- RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | - Piero Carninci
- RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | - Andrew E Jaffe
- Lieber Institute for Brain Development, Baltimore, Maryland 21205, USA.,Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA.,Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA
| | - Jeffrey T Leek
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA
| | - Alexander Favorov
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21827, USA.,Laboratory of Systems Biology and Computational Genetics, VIGG RAS, 117971 Moscow, Russia
| | - Gloria R Franco
- Departamento de Bioqúımica e Imunologia, ICB, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, 31270-901, Brazil
| | - Ben Langmead
- Department of Computer Science, Johns Hopkins University, Baltimore, Maryland 21218, USA.,Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA
| | - Luigi Marchionni
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21827, USA
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