2017
DOI: 10.1142/s0219720017500056
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The origins and evolutionary history of human non-coding RNA regulatory networks

Abstract: The evolutionary history and origin of the regulatory function of animal non-coding RNAs are not well understood. Lack of conservation of long non-coding RNAs and small sizes of microRNAs has been major obstacles in their phylogenetic analysis. In this study, we tried to shed more light on the evolution of ncRNA regulatory networks by changing our phylogenetic strategy to focus on the evolutionary pattern of their protein coding targets. We used available target databases of miRNAs and lncRNAs to find their pr… Show more

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Cited by 8 publications
(7 citation statements)
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“…The understanding of when, where and to what extent a gene is expressed, can elucidate the regulatory mechanisms and biological pathways that lead to, maintain or reverse multiple drug-resistance in cancer treatment. Almost twenty years ago, the non-coding RNAs (ncRNAs) were discovered [ 2 , 3 ] and provided a breakthrough in our understanding of the functionality of the human genome. To take advantage of the large and rapidly increasing body of genome-scale sequence information, new technologies are required to exploit this information by characterizing biological processes and by studying the synchronous expression of a high number of genes.…”
Section: Introductionmentioning
confidence: 99%
“…The understanding of when, where and to what extent a gene is expressed, can elucidate the regulatory mechanisms and biological pathways that lead to, maintain or reverse multiple drug-resistance in cancer treatment. Almost twenty years ago, the non-coding RNAs (ncRNAs) were discovered [ 2 , 3 ] and provided a breakthrough in our understanding of the functionality of the human genome. To take advantage of the large and rapidly increasing body of genome-scale sequence information, new technologies are required to exploit this information by characterizing biological processes and by studying the synchronous expression of a high number of genes.…”
Section: Introductionmentioning
confidence: 99%
“…Twenty-nine of these downregulated lncRNAs targeted genes encoded ribosomal proteins, indicating the important role of TOR in regulating the cotton ribosome biogenesis. Transposons associate with the origins and transcribed regions of lncRNAs and eventually drive lncRNA expression (Ponting et al, 2009; Kapusta et al, 2013; Xu et al, 2015; Wang et al, 2016a,b; Sherafatian and Mowla, 2017). We analyzed the potential transposons that targeted these ribosome-related lncRNAs (Supplementary Table 4B).…”
Section: Resultsmentioning
confidence: 99%
“…Taken together with the expression patterns of GhTOR genes under different stresses (Figure 5 and Supplementary Figure 1), our results indicated that TOR may directly regulate these potential stress-related lncRNAs and play a vital role in plant stress response. In addition, it is well-known that transposons associate with lncRNA origins and lncRNAs' transcribed regions, eventually driving expression of lncRNAs, and microRNA can also target lncRNAs (Ponting et al, 2009; Kapusta et al, 2013; Xu et al, 2015; Wang et al, 2016a,b; Sherafatian and Mowla, 2017). To confirm the lncRNAs' functions selected in the present study, transposons and miRNAs related with these selected lncRNAs were analyzed (Supplementary Tables 4–6).…”
Section: Discussionmentioning
confidence: 99%
“…The non-coding RNA networks [26,27] are currently under intense investigation, both for evolutionary studies as well as for the elucidation of their multiple roles in the development of disease.…”
Section: Fig 4 (Color Online)mentioning
confidence: 99%
“…Genome studies have revealed an extensive map of genetic variation within the human genome, with changes of all possible kinds, predominantly single nucleotide variants (polymorphisms) (SNP). Additionally, a plethora of non-coding RNA is being reported [27] that form the machinery for the fine tuning of gene expression and affect disease outcome. This wealth of data has been exploited by the use of computer software used to assemble the enormous sequence data in regions of high variability and to produce databases of human mapped variation (e.g.…”
Section: Genome-wide Association Studiesmentioning
confidence: 99%