The Arabidopsis Gene Regulatory Information Server (AGRIS; http://arabidopsis.med.ohio-state.edu/ ) provides a comprehensive resource for gene regulatory studies in the model plant Arabidopsis thaliana . Three interlinked databases, AtTFDB, AtcisDB and AtRegNet, furnish comprehensive and updated information on transcription factors (TFs), predicted and experimentally verified cis -regulatory elements (CREs) and their interactions, respectively. In addition to significant contributions in the identification of the entire set of TF–DNA interactions, which are the key to understand the gene regulatory networks that govern Arabidopsis gene expression, tools recently incorporated into AGRIS include the complete set of words length 5–15 present in the Arabidopsis genome and the integration of AtRegNet with visualization tools, such as the recently developed ReIN application. All the information in AGRIS is publicly available and downloadable upon registration.

KNOTTED1 (KN1)-like homeobox (KNOX) transcription factors function in plant meristems, self-renewing structures consisting of stem cells and their immediate daughters. We defined the KN1 cistrome in maize inflorescences and found that KN1 binds to several thousand loci, including 643 genes that are modulated in one or multiple tissues. These KN1 direct targets are strongly enriched for transcription factors (including other homeobox genes) and genes participating in hormonal pathways, most significantly auxin, demonstrating that KN1 plays a key role in orchestrating the upper levels of a hierarchical gene regulatory network that impacts plant meristem identity and function.

The transcription regulatory network inside a eukaryotic cell is defined by the combinatorial actions of transcription factors (TFs). However, TF binding studies in plants are too few in number to produce a general picture of this complex network. In this study, we use large-scale ChIP-seq to reconstruct it in the maize leaf, and train machine-learning models to predict TF binding and co-localization. The resulting network covers 77% of the expressed genes, and shows a scale-free topology and functional modularity like a real-world network. TF binding sequence preferences are conserved within family, while co-binding could be key for their binding specificity. Cross-species comparison shows that core network nodes at the top of the transmission of information being more conserved than those at the bottom. This study reveals the complex and redundant nature of the plant transcription regulatory network, and sheds light on its architecture, organizing principle and evolutionary trajectory.

Deep learning methodologies have revolutionized prediction in many fields and show potential to do the same in molecular biology and genetics. However, applying these methods in their current forms ignores evolutionary dependencies within biological systems and can result in false positives and spurious conclusions. We developed two approaches that account for evolutionary relatedness in machine learning models: ( i ) gene-family–guided splitting and ( ii ) ortholog contrasts. The first approach accounts for evolution by constraining model training and testing sets to include different gene families. The second approach uses evolutionarily informed comparisons between orthologous genes to both control for and leverage evolutionary divergence during the training process. The two approaches were explored and validated within the context of mRNA expression level prediction and have the area under the ROC curve (auROC) values ranging from 0.75 to 0.94. Model weight inspections showed biologically interpretable patterns, resulting in the hypothesis that the 3′ UTR is more important for fine-tuning mRNA abundance levels while the 5′ UTR is more important for large-scale changes.

Pericarp Color1 (P1) encodes an R2R3-MYB transcription factor responsible for the accumulation of insecticidal flavones in maize (Zea mays) silks and red phlobaphene pigments in pericarps and other floral tissues, which makes P1 an important visual marker. Using genome-wide expression analyses (RNA sequencing) in pericarps and silks of plants with contrasting P1 alleles combined with chromatin immunoprecipitation coupled with high-throughput sequencing, we show here that the regulatory functions of P1 are much broader than the activation of genes corresponding to enzymes in a branch of flavonoid biosynthesis. P1 modulates the expression of several thousand genes, and ∼1500 of them were identified as putative direct targets of P1. Among them, we identified F2H1, corresponding to a P450 enzyme that converts naringenin into 2-hydroxynaringenin, a key branch point in the P1-controlled pathway and the first step in the formation of insecticidal C-glycosyl flavones. Unexpectedly, the binding of P1 to gene regulatory regions can result in both gene activation and repression. Our results indicate that P1 is the major regulator for a set of genes involved in flavonoid biosynthesis and a minor modulator of the expression of a much larger gene set that includes genes involved in primary metabolism and production of other specialized compounds.