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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.

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Genetic mapping studies on crops suggest that agronomic traits can be controlled by gene-distal intergenic loci. Despite the biological importance and the potential agronomic utility of these loci, they remain virtually uncharacterized in all crop species to date. Here, we provide genetic, epigenomic and functional molecular evidence to support the widespread existence of gene-distal (hereafter, distal) loci that act as long-range transcriptional cis-regulatory elements (CREs) in the maize genome. Such loci are enriched for euchromatic features that suggest their regulatory functions. Chromatin loops link together putative CREs with genes and recapitulate genetic interactions. Putative CREs also display elevated transcriptional enhancer activities, as measured by self-transcribing active regulatory region sequencing. These results provide functional support for the widespread existence of CREs that act over large genomic distances to control gene expression.

Background: Only a small percentage of the genome sequence is involved in regulation of gene expression, but to biochemically identify this portion is expensive and laborious. In species like maize, with diverse intergenic regions and lots of repetitive elements, this is an especially challenging problem that limits the use of the data from one line to the other. While regulatory regions are rare, they do have characteristic chromatin contexts and sequence organization (the grammar) with which they can be identified., Results: We developed a computational framework to exploit this sequence arrangement. The models learn to classify regulatory regions based on sequence features - k-mers. To do this, we borrowed two approaches from the field of natural language processing: (1) "bag-of-words" which is commonly used for differentially weighting key words in tasks like sentiment analyses, and (2) a vector-space model using word2vec (vector-k-mers), that captures semantic and linguistic relationships between words. We built "bag-of-k-mers" and "vector-k-mers" models that distinguish between regulatory and non-regulatory regions with an average accuracy above 90%. Our "bag-of-k-mers" achieved higher overall accuracy, while the "vector-k-mers" models were more useful in highlighting key groups of sequences within the regulatory regions., Conclusions: These models now provide powerful tools to annotate regulatory regions in other maize lines beyond the reference, at low cost and with high accuracy.

The translation of the genotype into phenotype, represented for example by the expression of genes encoding enzymes required for the biosynthesis of phytochemicals that are important for interaction of plants with the environment, is largely carried out by transcription factors (TFs) that recognize specific cis-regulatory elements in the genes that they control. TFs and their target genes are organized in gene regulatory networks (GRNs), and thus uncovering GRN architecture presents an important biological challenge necessary to explain gene regulation. Linking TFs to the genes they control, central to understanding GRNs, can be carried out using gene- or TF-centered approaches. In this study, we employed a gene-centered approach utilizing the yeast one-hybrid assay to generate a network of protein-DNA interactions that participate in the transcriptional control of genes involved in the biosynthesis of maize phenolic compounds including general phenylpropanoids, lignins, and flavonoids. We identified 1100 protein-DNA interactions involving 54 phenolic gene promoters and 568 TFs. A set of 11 TFs recognized 10 or more promoters, suggesting a role in coordinating pathway gene expression. The integration of the gene-centered network with information derived from TF-centered approaches provides a foundation for a phenolics GRN characterized by interlaced feed-forward loops that link developmental regulators with biosynthetic genes., (Copyright © 2016 The Author. Published by Elsevier Inc. All rights reserved.)

The century-old maize (Zea mays) salmon silks mutation has been linked to the absence of maysin. Maysin is a C-glycosyl flavone that, when present in silks, confers natural resistance to the maize earworm (Helicoverpa zea), which is one of the most damaging pests of maize in America. Previous genetic analyses predicted Pericarp Color1 (P1; R2R3-MYB transcription factor) to be epistatic to the sm mutation. Subsequent studies identified two loci as being capable of conferring salmon silks phenotypes, salmon silks1 (sm1) and sm2 Benefitting from available sm1 and sm2 mapping information and from knowledge of the genes regulated by P1, we describe here the molecular identification of the Sm1 and Sm2 gene products. Sm2 encodes a rhamnosyl transferase (UGT91L1) that uses isoorientin and UDP-rhamnose as substrates and converts them to rhamnosylisoorientin. Sm1 encodes a multidomain UDP-rhamnose synthase (RHS1) that converts UDP-glucose into UDP-l-rhamnose. Here, we demonstrate that RHS1 shows unexpected substrate plasticity in converting the glucose moiety in rhamnosylisoorientin to 4-keto-6-deoxy glucose, resulting in maysin. Both Sm1 and Sm2 are direct targets of P1, as demonstrated by chromatin immunoprecipitation experiments. The molecular characterization of Sm1 and Sm2 described here completes the maysin biosynthetic pathway, providing powerful tools for engineering tolerance to maize earworm in maize and other plants., (© 2016 American Society of Plant Biologists. All rights reserved.)

Core promoters are crucial for gene regulation, providing blueprints for the assembly of transcriptional machinery at transcription start sites (TSSs). Empirically, TSSs define the coordinates of core promoters and other regulatory sequences. Thus, experimental TSS identification provides an essential step in the characterization of promoters and their features. Here, we describe the application of CAGE (cap analysis of gene expression) to identify genome-wide TSSs used in root and shoot tissues of two maize (Zea mays) inbred lines (B73 and Mo17). Our studies indicate that most TSS clusters are sharp in maize, similar to mice, but distinct from Arabidopsis thaliana, Drosophila melanogaster, or zebra fish, in which a majority of genes have broad-shaped TSS clusters. We established that ∼38% of maize promoters are characterized by a broader TATA-motif consensus, and this motif is significantly enriched in genes with sharp TSSs. A noteworthy plasticity in TSS usage between tissues and inbreds was uncovered, with ∼1500 genes showing significantly different dominant TSSs, sometimes affecting protein sequence by providing alternate translation initiation codons. We experimentally characterized instances in which this differential TSS utilization results in protein isoforms with additional domains or targeted to distinct subcellular compartments. These results provide important insights into TSS selection and gene expression in an agronomically important crop., (© 2015 American Society of Plant Biologists. All rights reserved.)

Establishing the architecture of the gene regulatory networks (GRNs) responsible for controlling the transcription of all genes in an organism is a natural development that follows elucidation of the genome sequence. Reconstruction of the GRN requires the availability of a series of molecular tools and resources that so far have been limited to a few model organisms. One such resource consists of collections of transcription factor (TF) open reading frames (ORFs) cloned into vectors that facilitate easy expression in plants or microorganisms. In this study, we describe the development of a publicly available maize TF ORF collection (TFome) of 2034 clones corresponding to 2017 unique gene models in recombination-ready vectors that make possible the facile mobilization of the TF sequences into a number of different expression vectors. The collection also includes several hundred co-regulators (CoREGs), which we classified into well-defined families, and for which we propose here a standard nomenclature, as we have previously done for TFs. We describe the strategies employed to overcome the limitations associated with cloning ORFs from a genome that remains incompletely annotated, with a partial full-length cDNA set available, and with many TF/CoREG genes lacking experimental support. In many instances this required the combination of genome-wide expression data with gene synthesis approaches. The strategies developed will be valuable for developing similar resources for other agriculturally important plants. Information on all the clones generated is available through the GRASSIUS knowledgebase (http://grassius.org/)., (© 2014 The Authors The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.)

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.

The ionotropic receptor of glutamate activated by N-methyl-D-aspartate (iGluR-NMDA) is a multiheteromeric complex constituted by at least three different types of subunits, encoded by seven different genes. The subunits of iGluR-NMDA have a complex system of regulation of their gene expression. Their expression is specific for each type of neural cell, as well as for the age of the organism. Moreover, there are reports that iGluR-NMDA expression is species-specific. Even though this macromolecular complex is very important in physiology and pathology of the central nervous system, knowledge to date about the regulatory elements controlling expression is scarce. We present the results of an in silico prediction of potential regulatory elements, some of which coincide with the few known experimentally. We also present the important differences regarding the presence and the localization of the regulatory elements among human, rat, and mouse species.