Deutsch
    Chair of Biochemistry and Molecular Biology

    Using functional genomics to unravel transcriptional networks in tumour cells.

    Background:

    Role of the oncoprotein Myc has been well established as a transcription factor (Blackwood and Eisenman 1991). However, the exact mechanism by which Myc brings about this role had been long sought for. The precise binding pattern of Myc on the chromatin and the consequential control of the genes it thereby regulates was recently catalogued in rigorous detail (Walz et al. 2014) using ChIP-Seq and RNA-Seq techniques. Of considerable importance is also the fact that Myc drives the expression of these mentioned genes via an affinity based mechanism which further clarifies how Myc bring about its diverse roles (Lorenzin et al. 2016).One important distinction that must be mentioned here is that these analyses were restricted purely to poly-adenylated mRNA transcribing genes. Even though earlier works (Rahl et al. 2010) have tried to dissect the exact stage of transcription that is regulated by Myc, the quantification of effect of Myc on each stage of transcription remains elusive due to the inherent pitfall of ChIP-Seq technique being a static readout of the protein binding on chromatin. Thus, the effect on Myc on RNA Polymerase II (Pol2), which is a traveling protein during transcription, cannot be studied using ChIP-Seq and a new technique is warranted to study this question.

    Topics:

    One way to study the active transcription in a cell is to read out the nascent mRNA formation in a specific time window. This has been attempted using a variety of analytical techniques like NET-Seq, TT-Seq, GRO-Seq and 4sU Seq (Schwalb et al. 2016)(Churchman and Weissman 2011)(Nojima et al. 2015)(Jonkers, Kwak, and Lis 2014)(Fuchs et al. 2015). To study specifically, the elongation stage of transcription and to read the effect of Myc on elongation rate, we took advantage of 4sU-DRB Seq, which has inherent advantages of being precise as compared to GRO-Seq and offers good enough resolution to study rate of transcriptional elongation with considerable accuracy (Fuchs et al. 2015). In this method, all Pol2 in a cell are synchronized using a reversible elongation inhibitor called DRB. This is followed by washout of DRB concomitant with metabolic labelling of nascent RNA using 4-thiouridine (4sU), which is eventually used to pull down the nascent RNA via biotin label and streptavidin beads. This nascent RNA is then read out using deep sequencing and thus, the exact end of transcriptional wave front can be pin pointed using exhaustive machine learning based bioinformatics algorithms.

    Since all forms of mRNA apart from poly-A mRNA are captured using 4sU-Seq technique, it makes it possible to study transiently expressed and unstable mRNA as well. It has also been postulated that transcriptional control can be fine-tuned with ncRNA and enhancer RNAs (Skalska et al. 2017)(Lai et al. 2015). Hence, an additional output of this work could be an insight into the complete transcriptional landscape of the cell when viewed through the lens of Myc as oncoprotein.

    Objectives:

    1. To gather the quantitative effect of Myc on rate of transcription elongation using DRB-4sU Seq
    2. To elucidate the percentage of control Myc has on individual stages of transcription using spiked-ChIP Seq and 4sU-Seq
    3. To capture the role of ncRNA, eRNA and circRNA in regulation of transcription by Myc.

    References:

    Blackwood, E. M., and R. N. Eisenman. 1991. “Max: A Helix-Loop-Helix Zipper Protein That Forms a Sequence-Specific DNA-Binding Complex with Myc.” Science (New York, N.Y.) 251 (4998): 1211–17.

    Churchman, L. Stirling, and Jonathan S. Weissman. 2011. “Nascent Transcript Sequencing Visualizes Transcription at Nucleotide Resolution.” Nature 469 (7330): 368–73. doi:10.1038/nature09652.

    Fuchs, Gilad, Yoav Voichek, Michal Rabani, Sima Benjamin, Shlomit Gilad, Ido Amit, and Moshe Oren. 2015. “Simultaneous Measurement of Genome-Wide Transcription Elongation Speeds and Rates of RNA Polymerase II Transition into Active Elongation with 4sUDRB-Seq.” Nature Protocols 10 (4): 605–18. doi:10.1038/nprot.2015.035.

    Jonkers, Iris, Hojoong Kwak, and John T. Lis. 2014. “Genome-Wide Dynamics of Pol II Elongation and Its Interplay with Promoter Proximal Pausing, Chromatin, and Exons.” eLife 3 (April): e02407.

    Lai, Fan, Alessandro Gardini, Anda Zhang, and Ramin Shiekhattar. 2015. “Integrator Mediates the Biogenesis of Enhancer RNAs.” Nature 525 (7569): 399–403. doi:10.1038/nature14906.

    Lorenzin, Francesca, Uwe Benary, Apoorva Baluapuri, Susanne Walz, Lisa Anna Jung, Björn von Eyss, Caroline Kisker, Jana Wolf, Martin Eilers, and Elmar Wolf. 2016. “Different Promoter Affinities Account for Specificity in MYC-Dependent Gene Regulation.” eLife 5 (July). doi:10.7554/eLife.15161.

    Nojima, Takayuki, Tomás Gomes, Ana Rita Fialho Grosso, Hiroshi Kimura, Michael J. Dye, Somdutta Dhir, Maria Carmo-Fonseca, and Nicholas J. Proudfoot. 2015. “Mammalian NET-Seq Reveals Genome-Wide Nascent Transcription Coupled to RNA Processing.” Cell 161 (3): 526–40. doi:10.1016/j.cell.2015.03.027.

    Rahl, Peter B., Charles Y. Lin, Amy C. Seila, Ryan A. Flynn, Scott McCuine, Christopher B. Burge, Phillip A. Sharp, and Richard A. Young. 2010. “C-Myc Regulates Transcriptional Pause Release.” Cell 141 (3): 432–45. doi:10.1016/j.cell.2010.03.030.

    Schwalb, Björn, Margaux Michel, Benedikt Zacher, Katja Frühauf, Carina Demel, Achim Tresch, Julien Gagneur, and Patrick Cramer. 2016. “TT-Seq Maps the Human Transient Transcriptome.” Science (New York, N.Y.) 352 (6290): 1225–28. doi:10.1126/science.aad9841.

    Skalska, Lenka, Manuel Beltran-Nebot, Jernej Ule, and Richard G. Jenner. 2017. “Regulatory Feedback from Nascent RNA to Chromatin and Transcription.” Nature Reviews Molecular Cell Biology, March. doi:10.1038/nrm.2017.12.

    Walz, Susanne, Francesca Lorenzin, Jennifer Morton, Katrin E. Wiese, Björn von Eyss, Steffi Herold, Lukas Rycak, et al. 2014. “Activation and Repression by Oncogenic MYC Shape Tumour-Specific Gene Expression Profiles.” Nature 511 (7510): 483–87. doi:10.1038/nature13473.

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