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The existence of dynamic cellular phenotypes in changing environmental conditions is of major interest for cell biologists who aim to understand the mechanism and sequence of regulation of gene expression. In the context of therapeutic protein production by Chinese Hamster Ovary (CHO) cells, a detailed temporal understanding of cell-line behavior and control is necessary to achieve a more predictable and reliable process performance. Of particular interest are data on dynamic, temporally resolved transcriptional regulation of genes in response to altered substrate availability and culture conditions. In this study, the gene transcription dynamics throughout a 9-day batch culture of CHO cells was examined by analyzing histone modifications and gene expression profiles in regular 12- and 24-hr intervals, respectively. Three levels of regulation were observed: (a) the presence or absence of DNA methylation in the promoter region provides an ON/OFF switch; (b) a temporally resolved correlation is observed between the presence of active transcription- and promoter-specific histone marks and the expression level of the respective genes; and (c) a major mechanism of gene regulation is identified by interaction of coding genes with long non-coding RNA (lncRNA), as observed in the regulation of the expression level of both neighboring coding/lnc gene pairs and of gene pairs where the lncRNA is able to form RNA-DNA-DNA triplexes. Such triplex-forming regions were predominantly found in the promoter or enhancer region of the targeted coding gene. Significantly, the coding genes with the highest degree of variation in expression during the batch culture are characterized by a larger number of possible triplex-forming interactions with differentially expressed lncRNAs. This indicates a specific role of lncRNA-triplexes in enabling rapid and large changes in transcription. A more comprehensive understanding of these regulatory mechanisms will provide an opportunity for new tools to control cellular behavior and to engineer enhanced phenotypes. Funding: IHL received support from FWF, the Austrian Science Fund, within the Doctoral Program “BioTechnology of Proteins” W1224, and HD from the “eCHO Systems” ITN PhD program funded by the Marie Sklodowska-Curie grant no. 642663. Additional grants were received from the National Bioinformatics Institute (INB), PRB2-ISCIII (PT13/0001/0044 to JG and AEC) and MINECO (PTA2014-09515 to MD)