Abstract
There is extensive evidence that posttranscriptional mechanisms of gene regulation, such as mRNA turnover, critically affect the patterns of expressed mRNAs. Conventional microarray analysis measures steady-state messenger RNA (mRNA) levels, which represents the dynamic balance between new transcription and mRNA degradation. Accordingly, only de novo transcription can accurately reflect the temporal and spatial events of transcriptional regulation. In this chapter, we describe a recently reported method to study transcription systematically. It involves the genome-wide labeling of nascent transcripts using nonradioactive modified nucleotides, their isolation for amplification, and their hybridization and analysis using commercial microarrays.
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References
Raghavan A, Ogilvie RL, Reilly C, Abelson ML, Raghavan S, Vasdewani J, Krathwohl M, Bohjanen PR (2002) Genome-wide analysis of mRNA decay in resting and activated primary human T lymphocytes. Nucleic Acid Res 30: 5529–5538
Wang Y, Liu CL, Storey JD, Tibshirani RJ, Herschlag D, Brown PO (2002) Precision and Functional Specificity in mRNA Decay. Proc Natl Acad Sci USA 99: 5860–5865
Fan J, Yang X, Wang W, Wood WH III, Becker KG, Gorospe M (2002) Global Analysis of Stress-regulated mRNA Turnover Using cDNA Arrays. Proc Natl Acad Sci USA 99: 10611–10616
Cheadle C, Fan J, Cho-Chung YS, et al. (2005) Control of gene expression during T cell activation: alternate regulation of mRNA transcription and mRNA stability. BMC Genomics 6: 75
Wei CL, Wu Q, Vega VB, et al. (2006) A global map of p53 transcription-factor binding sites in the human genome. Cell 124: 207–219
Hallikas O, Palin K, Sinjushina N, Rautiainen R, Partanen J, Ukkonen E, Taipale J (2006) Genome-wide prediction of mammalian enhancers based on analysis of transcription-factor binding affinity. Cell 124: 47–59
Weinmann AS (2004) Novel ChIP-based strategies to uncover transcription factor target genes in the immune system. Nature Rev Immunol 4: 381–386
Zeller KI, Zhao X, Lee CW, et al. (2006) Global mapping of c-Myc binding sites and target gene networks in human B cells. Proc Natl Acad Sci USA 103: 17834–17839
Kim J, Chu J, Shen X, Wang J, Orkin SH (2008). An extended transcriptional network for pluripotency of embryonic stem cells. Cell 132: 1049–1061
Fan J, Zhan M, Shen J, Martindale JL, Yang X, Kawai T, Gorospe M (2006) En masse nascent transcription analysis to elucidate regulatory transcription factors. Nucleic Acids Res 34: 1492–1500
Fan J, Zeller K, Chen YC, Watkins T, Barnes KC, Becker KG, Dang CV, Cheadle C (2010) Time-Dependent c-Myc Transactomes Mapped by Array-Based Nuclear Run-On Reveal Transcriptional Modules in Human B Cells. PLoS ONE 5: e9691
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Fan, J., Chen, YC., Watkins, T., Dang, C.V., Gorospe, M., Cheadle, C. (2012). Array-Based Nuclear Run-On Analysis. In: Vancura, A. (eds) Transcriptional Regulation. Methods in Molecular Biology, vol 809. Springer, New York, NY. https://doi.org/10.1007/978-1-61779-376-9_33
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DOI: https://doi.org/10.1007/978-1-61779-376-9_33
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