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      Effect and mechanism of the long noncoding RNA MALAT1 on retinal neovascularization in retinopathy of prematurity

      , , , ,
      Life Sciences
      Elsevier BV

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            Functional Classification and Experimental Dissection of Long Noncoding RNAs

            Over the last decade, it has been increasingly demonstrated that the genomes of many species are pervasively transcribed, resulting in the production of numerous long noncoding RNAs (lncRNAs). At the same time, it is now appreciated that many types of DNA regulatory elements, such as enhancers and promoters, regularly initiate bidirectional transcription. Thus, discerning functional noncoding transcripts from a vast transcriptome is a paramount priority, and challenge, for the lncRNA field. In this review, we aim to provide a conceptual and experimental framework for classifying and elucidating lncRNA function. We categorize lncRNA loci into those that regulate gene expression in cis versus those that perform functions in trans , and propose an experimental approach to dissect lncRNA activity based on these classifications. These strategies to further understand lncRNAs promise to reveal new and unanticipated biology, with great potential to advance our understanding of normal physiology and disease.
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              The functions and unique features of long intergenic non-coding RNA

              Long intergenic non-coding RNA (lincRNA) genes have diverse features that distinguish them from mRNA-encoding genes and exercise functions such as remodelling chromatin and genome architecture, RNA stabilization and transcription regulation, including enhancer-associated activity. Some genes currently annotated as encoding lincRNAs include small open reading frames (smORFs) and encode functional peptides and thus may be more properly classified as coding RNAs. lincRNAs may broadly serve to fine-tune the expression of neighbouring genes with remarkable tissue specificity through a diversity of mechanisms, highlighting our rapidly evolving understanding of the non-coding genome.
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                Author and article information

                Journal
                Life Sciences
                Life Sciences
                Elsevier BV
                00243205
                November 2020
                November 2020
                : 260
                : 118299
                Article
                10.1016/j.lfs.2020.118299
                32827542
                35169a9f-79f0-423b-8801-cfbd9c9a0167
                © 2020

                https://www.elsevier.com/tdm/userlicense/1.0/

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