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      Cryptic sequence features in the active postmortem transcriptome

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          Our previous study found that more than 500 transcripts significantly increased in abundance in the zebrafish and mouse several hours to days postmortem relative to live controls. The current literature suggests that most mRNAs are post-transcriptionally regulated in stressful conditions. We rationalized that the postmortem transcripts must contain sequence features (3- to 9- mers) that are unique from those in the rest of the transcriptome and that these features putatively serve as binding sites for proteins and/or non-coding RNAs involved in post-transcriptional regulation.


          We identified 5117 and 2245 over-represented sequence features in the mouse and zebrafish, respectively, which represents less than 1.5% of all possible features. Some of these features were disproportionately distributed along the transcripts with high densities in the 3′ untranslated regions of the zebrafish (0.3 mers/nt) and the open reading frames of the mouse (0.6 mers/nt). Yet, the highest density (2.3 mers/nt) occurred in the open reading frames of 11 mouse transcripts that lacked 3′ or 5′ untranslated regions. These results suggest the transcripts with high density of features might serve as ‘molecular sponges’ that sequester RNA binding proteins and/or microRNAs, and thus indirectly increase the stability and gene expression of other transcripts. In addition, some of the features were identified as binding sites for Rbfox and Hud proteins that are also involved in increasing transcript stability and gene expression.


          Our results are consistent with the hypothesis that transcripts involved in responding to extreme stress, such as organismal death, have sequence features that make them different from the rest of the transcriptome. Some of these features serve as putative binding sites for proteins and non-coding RNAs that determine transcript stability and fate. A small number of the transcripts have high density sequence features, which are presumably involved in sequestering RNA binding proteins and microRNAs and thus preventing regulatory interactions among other transcripts. Our results provide baseline data on post-transcriptional regulation in stressful conditions that has implications for regulation in disease, starvation, and cancer.

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          The online version of this article (10.1186/s12864-018-5042-x) contains supplementary material, which is available to authorized users.

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          Most cited references 39

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          A ceRNA hypothesis: the Rosetta Stone of a hidden RNA language?

          Here, we present a unifying hypothesis about how messenger RNAs, transcribed pseudogenes, and long noncoding RNAs "talk" to each other using microRNA response elements (MREs) as letters of a new language. We propose that this "competing endogenous RNA" (ceRNA) activity forms a large-scale regulatory network across the transcriptome, greatly expanding the functional genetic information in the human genome and playing important roles in pathological conditions, such as cancer. Copyright © 2011 Elsevier Inc. All rights reserved.
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            Long noncoding RNAs: functional surprises from the RNA world.

            Most of the eukaryotic genome is transcribed, yielding a complex network of transcripts that includes tens of thousands of long noncoding RNAs with little or no protein-coding capacity. Although the vast majority of long noncoding RNAs have yet to be characterized thoroughly, many of these transcripts are unlikely to represent transcriptional "noise" as a significant number have been shown to exhibit cell type-specific expression, localization to subcellular compartments, and association with human diseases. Here, we highlight recent efforts that have identified a myriad of molecular functions for long noncoding RNAs. In some cases, it appears that simply the act of noncoding RNA transcription is sufficient to positively or negatively affect the expression of nearby genes. However, in many cases, the long noncoding RNAs themselves serve key regulatory roles that were assumed previously to be reserved for proteins, such as regulating the activity or localization of proteins and serving as organizational frameworks of subcellular structures. In addition, many long noncoding RNAs are processed to yield small RNAs or, conversely, modulate how other RNAs are processed. It is thus becoming increasingly clear that long noncoding RNAs can function via numerous paradigms and are key regulatory molecules in the cell.
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              A compendium of RNA-binding motifs for decoding gene regulation.

              RNA-binding proteins are key regulators of gene expression, yet only a small fraction have been functionally characterized. Here we report a systematic analysis of the RNA motifs recognized by RNA-binding proteins, encompassing 205 distinct genes from 24 diverse eukaryotes. The sequence specificities of RNA-binding proteins display deep evolutionary conservation, and the recognition preferences for a large fraction of metazoan RNA-binding proteins can thus be inferred from their RNA-binding domain sequence. The motifs that we identify in vitro correlate well with in vivo RNA-binding data. Moreover, we can associate them with distinct functional roles in diverse types of post-transcriptional regulation, enabling new insights into the functions of RNA-binding proteins both in normal physiology and in human disease. These data provide an unprecedented overview of RNA-binding proteins and their targets, and constitute an invaluable resource for determining post-transcriptional regulatory mechanisms in eukaryotes.

                Author and article information

                206-409-6664 ,
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                14 September 2018
                14 September 2018
                : 19
                [1 ]ISNI 0000000122986657, GRID grid.34477.33, Department of Periodontics, , University of Washington, ; Box 357444, Seattle, WA 98195 USA
                [2 ]ISNI 0000 0004 0421 8357, GRID grid.410425.6, City of Hope, Information Sciences - Beckman Research Institute, ; 4920 Rivergrade Rd., Irwindale, CA 91706 USA
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

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