2016
DOI: 10.1172/jci84419
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Non-coding RNAs in muscle differentiation and musculoskeletal disease

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Cited by 85 publications
(67 citation statements)
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References 128 publications
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“…Through their primary sequence and secondary structure, lncRNAs can bind to other nucleic acids and/or proteins to regulate gene expression programs, in turn controlling a growing number of cellular processes, such as cell division, the stress response, differentiation, survival, and senescence (Audas & Lee, ; Chen, Satpathy, & Chang, ; Grammatikakis, Panda, Abdelmohsen, & Gorospe, ; Li, Tian, Yang, & Gong, ). By affecting these processes, there is increasing appreciation that lncRNAs have a direct impact on the physiology of tissues and organs, and on a growing number of disease processes (e.g., muscle disease, cancer, and cardiovascular pathologies) (Alvarez‐Dominguez & Lodish, ; Ballarino, Morlando, Fatica, & Bozzoni, ; Greco, Gorospe, & Martelli, ; Schmitt & Chang, ; Wang, Xiao, & Wang, ). Despite intense efforts, however, only a small number of lncRNAs have been characterized functionally, while the vast majority of lncRNAs have no known functions at present.…”
Section: Introductionmentioning
confidence: 99%
“…Through their primary sequence and secondary structure, lncRNAs can bind to other nucleic acids and/or proteins to regulate gene expression programs, in turn controlling a growing number of cellular processes, such as cell division, the stress response, differentiation, survival, and senescence (Audas & Lee, ; Chen, Satpathy, & Chang, ; Grammatikakis, Panda, Abdelmohsen, & Gorospe, ; Li, Tian, Yang, & Gong, ). By affecting these processes, there is increasing appreciation that lncRNAs have a direct impact on the physiology of tissues and organs, and on a growing number of disease processes (e.g., muscle disease, cancer, and cardiovascular pathologies) (Alvarez‐Dominguez & Lodish, ; Ballarino, Morlando, Fatica, & Bozzoni, ; Greco, Gorospe, & Martelli, ; Schmitt & Chang, ; Wang, Xiao, & Wang, ). Despite intense efforts, however, only a small number of lncRNAs have been characterized functionally, while the vast majority of lncRNAs have no known functions at present.…”
Section: Introductionmentioning
confidence: 99%
“…lncRNAs, through their ability to interact with nucleic acids as well as with proteins (Guttman & Rinn, ; Rinn & Chang, ; Batista & Chang, ; Cipriano & Ballarino, ), act as scaffolds for the formation of specific functional complexes where different proteins and RNA and even DNA molecules can be tethered together (Wutz et al , ; Clemson et al , ; Tsai et al , ; Ariel et al , ; Hacisuleyman et al , ; Ribeiro et al , ). Nuclear lncRNAs have been described to control the transcriptional myogenic program through diverse modes of action (Ballarino et al , ): as enhancer‐associated transcripts (Mousavi et al , ; Mueller et al , ; Ounzain et al , ), as guides for the recruitment of PRCs and MLL epigenetic regulators or DNA methyltransferases (DNMT; Wang et al , , ), and also as allosteric inhibitors (Han et al , ; Wang et al , ). Important functions have also been ascribed to cytoplasmic lncRNAs through their ability to control mRNA stability and translation (Wang et al , ), to modulate miRNA function acting as competing endogenous RNA (Cesana et al , ; Salmena et al , ; Han et al , ), or to encode for micropeptides (Anderson et al , ; Nelson et al , ).…”
Section: Introductionmentioning
confidence: 99%
“…Numerous tools have been developed to analyze scRNA-seq data, due to its intrinsic features. There are at least 493 tools available on the web [143], covering over 30 categories including quality control, read alignment, normalization, and gene networks analysis. Concluding, scRNA-seq can be performed on full-length RNA or just on its 5 or 3 ends with the consequent necessity of performing the sequencing at a different depth.…”
Section: Rna Sequencing and Bioinformatic Analysismentioning
confidence: 99%
“…In this context, Rizvi and colleagues proposed an algorithm to study transcriptional regulation to identify cell identity over time and therefore cell differentiation in response to specific stimuli. The proposed algorithm, called single-cell topological data analysis (scTDA), does not work as previously developed algorithms that suppose a one or three-like branched structure, but it is based on an unsupervised method that has the advantage of extracting more complex relationships [143]. An interesting feature of this algorithm is that it was able to identify cell states by using lncRNAs supporting the notion of their cell stage-specific expression.…”
Section: Lncrnas In Embryo-derived Cellsmentioning
confidence: 99%