The Case for Transcriptional Regulation and Coupling as Relevant Determinants of the Circadian Transcriptome and Proteome in Eukaryotes
My latest paper is out, a commentary, in which together with Luis Larrondo, we evaluate evidence regarding the relative contribution of the different steps of gene expression (transcriptional, post-transcriptional, translational, etc.) in determining daily mRNA and protein rhythms in eukaryotes. We argue that it’s too early to assign a predominant role for one specific stage in this process, as some papers have done, due to a variety of biological and particularly, technical, reasons. We further propose that RNAPII recruitment is rhythmic on a global scale, setting the stage for global nascent transcription, but that tissue-specific mechanisms ultimately locally specify the different processes under clock control.
Here’s the link and info:
Published online before print October 7, 2015, doi: 10.1177/0748730415607321
J Biol Rhythms October 7, 2015 0748730415607321
Circadian clocks drive daily oscillations in a variety of biological processes through the coordinate orchestration of precise gene expression programs. Global expression profiling experiments have suggested that a significant fraction of the transcriptome and proteome is under circadian control, and such output rhythms have historically been assumed to rely on the rhythmic transcription of these genes. Recent genome-wide studies, however, have challenged this long-held view and pointed to a major contribution of posttranscriptional regulation in driving oscillations at the messenger RNA (mRNA) level, while others have highlighted extensive clock translational regulation, regardless of mRNA rhythms. There are various examples of genes that are uniformly transcribed throughout the day but that exhibit rhythmic mRNA levels, and of flat mRNAs, with oscillating protein levels, and such observations have largely been considered to result from independent regulation at each step. These studies have thereby obviated any connections, or coupling, that might exist between the different steps of gene expression and the impact that any of them could have on subsequent ones. Here, we argue that due to both biological and technical reasons, the jury is still out on the determination of the relative contributions of each of the different stages of gene expression in regulating output molecular rhythms. In addition, we propose that through a variety of coupling mechanisms, gene transcription (even when apparently arrhythmic) might play a much relevant role in determining oscillations in gene expression than currently estimated, regulating rhythms at downstream steps. Furthermore, we posit that eukaryotic genomes regulate daily RNA polymerase II (RNAPII) recruitment and histone modifications genome-wide, setting the stage for global nascent transcription, but that tissue-specific mechanisms locally specify the different processes under clock control.
Embracing minimal guidelines for the reporting of RT-qPCR experiments: responsibility lies on both ends
In mid-2012, Stephen A. Bustin, Jo Vandesompele and myself, decided to send a letter to the editor of a glam magazine asking for journals to demand authors to provide at least minimal information for the critical evaluation and reproducibility of published RT-qPCR experiments. The lack of information regarding these experiments is inversely proportional to the IF of the journal: the higher the IF, the lower the amount of information provided for these experiments (See Nat Methods. 2013 Nov;10(11):1063-7). It was no surprise then, considering that they were the ones we targeted in the letter (although not explicitly), that glam journals (you know which…) refused publishing the letter.
I found the letter searching for something else in my computer and decided to share it with you, just as it was written back in 2012. The main theme is as true as it was back then.
Stephen A. Bustinb
Jo Vandesompele c
a Department of Molecular Genetics and Microbiology, Faculty of Biological Sciences, Pontificia Universidad Católica de Chile.
Email: firstname.lastname@example.org. Tel: (+562) 6862348
b Queen Mary University of London, UK
Email: email@example.com. Tel: (+44) 2073777000
c Center for Medical Genetics, Ghent University, Belgium
d Biogazelle, Zwijnaarde, Belgium.
Email: Joke.Vandesompele@UGent.be. Tel: (+32) 479353563.
To the Editor:
Reverse transcription real-time quantitative PCR (RT-qPCR) is currently the most widely used molecular method for the detection and quantification of RNA. RNA integrity and purity, primer sequences and their specificity, assay efficiency and identification of appropriate reference genes are just a few of the essential parameters that must be assessed and reported when using this quantitative technique. Most authors however, fail to include them, either in the methods or the online supplementary sections, with some arguably not even having performed the appropriate controls. As has been previously reported, this can lead to flawed data and wasted efforts in trying to reproduce results that can be, in some cases, artifacts and thus not biologically relevant1.
The MIQE guidelines2,3 were proposed to enhance experimental accuracy and transparency and to enable the research community to assess reported data and reproduce published qPCR experiments. The guidelines should be considered a complete “checklist” to be used as a reference for the reporting of results. While the response to these guidelines has been largely positive, in both commercial and research settings, most currently published articles that include qPCR experiments fail to properly report experimental procedures.
Although it is the authors’ task to embrace minimal guidelines that allow for reproducibility and transparency of their studies, journal editors have a responsibility to demand such information. Even though some publishers have implemented the MIQE guidelines or at least the bulk of the recommendations, many top-tier journals continue to publish research that grossly lacks the required information not only to reproduce the reported experiments, but also to evaluate properly the conclusions derived from them. Given that the number of retractions is on the increase, that the majority of retractions are caused by poor experimental protocols and that once published in the peer-reviewed literature, even a rebuttal does not affect a paper’s frequency of citation, we would like to issue a wakeup call to journal editors and publishers.
We urge journals to demand that all manuscripts include such minimum information, in the form of the MIQE or other guidelines, to ensure the accuracy and reproducibility of the reported results. The use of online supplementary sections makes the often used “space constraint” argument no longer valid.
1. Lanoix, D. et al. Quantitative PCR Pitfalls: The Case of the Human Placenta. Mol Biotechnol (2012).
2. Bustin, S.A. et al. The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin Chem 55, 611-622 (2009).
3. Bustin, S.A. et al. Primer sequence disclosure: a clarification of the MIQE guidelines. Clin Chem 57, 919-921 (2011).
ENCODE Project Consortium et al. 2012. An integrated encyclopedia of DNA elements in the human genome. Nature 489: 57-74.
Graur D, Zheng Y, Price N, Azevedo RB, Zufall RA, Elhaik E. 2013. On the immortality of television sets: “function” in the human genome according to the evolution-free gospel of ENCODE. Genome Biol Evol. 5:578-590.
Eddy S. 2012. The C-value paradox, junk DNA and ENCODE. Curr Biol. 22:R898– R899.
Eddy SR. 2013. The ENCODE project: missteps overshadowing a success. Curr. Biol. 23: R259-61.
Eddy SR. 2013. Is junk DNA bunk? A critique of ENCODE. Proc Natl Acad Sci U S A. 2013 Apr 2;110(14):5294-300.
Kellis M et al. 2014. Defining functional DNA elements in the human genome. Proc Natl Acad Sci U S A. 2014 Apr 29;111(17):6131-8.
Niu D-K, Jiang L. 2013. Can ENCODE tell us how much junk DNA we carry in our genome? Biochem Biophys Res Commun. 430:1340–1343.
Palazzo AF and Gregory TR. 2014. The Case for Junk DNA. PLoS Gentics 10 (5): e1004351
Doolittle, WF, Brunet TDP, Linquist S, Gregory TR (2014). Distinguishing between “function” and “effect” in genome biology. Genome Biol Evol (2014) doi: 10.1093/gbe/evu098
Quick and simple post, considering it is Jan 1st and I’m still tired from last night, and the fact that I just came back from, you guessed it, the lab.
Anyway, I wanted to know what the most recurring topics were on the top two glam journals during 2013, so I obtained the 2013 PubMed-indexed abstracts from Nature and Science using EBOT and then used Wordle to generate a word cloud.
Here are the results:
It’s pretty easy to do it for any other journal or for any other query in PubMed using Ebot. If you want to do something similar for say, your country or institution and you need help, let me know.