Building Transcription Factor Binding Site Models to Understand Gene Regulation in Plants

• Published in: Molecular plant 2019-06, Vol.12 (6), p.743-763
• Main Authors: Lai, Xuelei, Stigliani, Arnaud, Vachon, Gilles, Carles, Cristel, Smaczniak, Cezary, Zubieta, Chloe, Kaufmann, Kerstin, Parcy, François
• Format: Article
• Language: English
• Subjects: Algorithms; Binding Sites; Biochemistry, Molecular Biology; Botanics; Computational Biology - methods; flower development; Flowers - metabolism; Gene Expression Regulation - physiology; Gene regulation; Genomics; Life Sciences; Protein Binding; Transcription factor binding site; Transcription Factors - metabolism; Vegetal Biology
• ISSN: 1674-2052; 1752-9867
• DOI: 10.1016/j.molp.2018.10.010

Transcription factors (TFs) are key cellular components that control gene expression. They recognize specific DNA sequences, the TF binding sites (TFBSs), and thus are targeted to specific regions of the genome where they can recruit transcriptional co-factors and/or chromatin regulators to fine-tune spatiotemporal gene regulation. Therefore, the identification of TFBSs in genomic sequences and their subsequent quantitative modeling is of crucial importance for understanding and predicting gene expression. Here, we review how TFBSs can be determined experimentally, how the TFBS models can be constructed in silico, and how they can be optimized by taking into account features such as position interdependence within TFBSs, DNA shape, and/or by introducing state-of-the-art computational algorithms such as deep learning methods. In addition, we discuss the integration of context variables into the TFBS modeling, including nucleosome positioning, chromatin states, methylation patterns, 3D genome architectures, and TF cooperative binding, in order to better predict TF binding under cellular contexts. Finally, we explore the possibilities of combining the optimized TFBS model with technological advances, such as targeted TFBS perturbation by CRISPR, to better understand gene regulation, evolution, and plant diversity. Transcription factors (TFs) are proteins that recognize specific DNA sequences (Tf binding sites [TFBSs]) to regulate gene expression. In this review, we summarize the most recent experimental methods to identify and model TFBSs. We illustrate how TFBS models, combined with additional information dependent on cellular contexts, can be used to decipher TF binding and gene regulation, with focuses on case studies of TFs involved in floral development.