@misc{yaschenko_fenech_mazzoni-putman_alonso_stepanova_2022, title={Deciphering the molecular basis of tissue-specific gene expression in plants: Can synthetic biology help?}, volume={68}, ISSN={["1879-0356"]}, url={https://doi.org/10.1016/j.pbi.2022.102241}, DOI={10.1016/j.pbi.2022.102241}, abstractNote={Gene expression differences between distinct cell types are orchestrated by specific sets of transcription factors and epigenetic regulators acting upon the genome. In plants, the mechanisms underlying tissue-specific gene activity remain largely unexplored. Although transcriptional and epigenetic profiling of individual organs, tissues, and more recently, of single cells can easily detect the molecular signatures of different biological samples, how these unique cell identities are established at the mechanistic level is only beginning to be decoded. Computational methods, including machine learning, used in combination with experimental approaches, enable the identification and validation of candidate cis-regulatory elements driving cell-specific expression. Synthetic biology shows great promise not only as a means of testing candidate DNA motifs but also for establishing the general rules of nature driving promoter architecture and for the rational design of genetic circuits in research and agriculture to confer tissue-specific expression to genes or molecular pathways of interest.}, journal={CURRENT OPINION IN PLANT BIOLOGY}, publisher={Elsevier BV}, author={Yaschenko, Anna E. and Fenech, Mario and Mazzoni-Putman, Serina and Alonso, Jose M. and Stepanova, Anna N.}, year={2022}, month={Aug} }