Over the last several decades, increased agricultural production has been driven by improved agronomic practices and a dramatic increase in the use of nitrogen-containing fertilizers to maximize the yield potential of crops. To reduce input costs and to minimize the potential environmental impacts of nitrogen fertilizer that has been used to optimize yield, an increased understanding of the molecular responses to nitrogen under field conditions is critical for our ability to further improve agricultural sustainability. Using maize (Zea mays) as a model, we have characterized the transcriptional response of plants grown under limiting and sufficient nitrogen conditions and during the recovery of nitrogen-starved plants. We show that a large percentage (approximately 7%) of the maize transcriptome is nitrogen responsive, similar to previous observations in other plant species. Furthermore, we have used statistical approaches to identify a small set of genes whose expression profiles can quantitatively assess the response of plants to varying nitrogen conditions. Using a composite gene expression scoring system, this single set of biomarker genes can accurately assess nitrogen responses independently of genotype, developmental stage, tissue type, or environment, including in plants grown under controlled environments or in the field. Importantly, the biomarker composite expression response is much more rapid and quantitative than phenotypic observations. Consequently, we have successfully used these biomarkers to monitor nitrogen status in real-time assays of field-grown maize plants under typical production conditions. Our results suggest that biomarkers have the potential to be used as agronomic tools to monitor and optimize nitrogen fertilizer usage to help achieve maximal crop yields.
Eukaryotic organisms possess a complex RNA-directed gene expression regulatory network allowing the production of unique gene expression patterns. A recent addition to the repertoire of RNA-based gene regulation is miRNA target decoys, endogenous RNA that can negatively regulate miRNA activity. miRNA decoys have been shown to be a valuable tool for understanding the function of several miRNA families in plants and invertebrates. Engineering and precise manipulation of an endogenous RNA regulatory network through modification of miRNA activity also affords a significant opportunity to achieve a desired outcome of enhanced plant development or response to environmental stresses. Here we report that expression of miRNA decoys as single or heteromeric non-cleavable microRNA (miRNA) sites embedded in either non-protein-coding or within the 3′ untranslated region of protein-coding transcripts can regulate the expression of one or more miRNA targets. By altering the sequence of the miRNA decoy sites, we were able to attenuate miRNA inactivation, which allowed for fine regulation of native miRNA targets and the production of a desirable range of plant phenotypes. Thus, our results demonstrate miRNA decoys are a flexible and robust tool, not only for studying miRNA function, but also for targeted engineering of gene expression in plants. Computational analysis of the Arabidopsis transcriptome revealed a number of potential miRNA decoys, suggesting that endogenous decoys may have an important role in natural modulation of expression in plants.
Crop yield is a highly complex quantitative trait. Historically, successful breeding for improved grain yield has led to crop plants with improved source capacity, altered plant architecture, and increased resistance to abiotic and biotic stresses. To date, transgenic approaches towards improving crop grain yield have primarily focused on protecting plants from herbicide, insects, or disease. In contrast, we have focused on identifying genes that, when expressed in soybean, improve the intrinsic ability of the plant to yield more. Through the large scale screening of candidate genes in transgenic soybean, we identified an Arabidopsis thaliana B-box domain gene (AtBBX32) that significantly increases soybean grain yield year after year in multiple transgenic events in multi-location field trials. In order to understand the underlying physiological changes that are associated with increased yield in transgenic soybean, we examined phenotypic differences in two AtBBX32-expressing lines and found increases in plant height and node, flower, pod, and seed number. We propose that these phenotypic changes are likely the result of changes in the timing of reproductive development in transgenic soybean that lead to the increased duration of the pod and seed development period. Consistent with the role of BBX32 in A. thaliana in regulating light signaling, we show that the constitutive expression of AtBBX32 in soybean alters the abundance of a subset of gene transcripts in the early morning hours. In particular, AtBBX32 alters transcript levels of the soybean clock genes GmTOC1 and LHY-CCA1-like2 (GmLCL2). We propose that through the expression of AtBBX32 and modulation of the abundance of circadian clock genes during the transition from dark to light, the timing of critical phases of reproductive development are altered. These findings demonstrate a specific role for AtBBX32 in modulating soybean development, and demonstrate the validity of expressing single genes in crops to deliver increased agricultural productivity.
ATHB17 (AT2G01430) is an Arabidopsis gene encoding a member of the α-subclass of the homeodomain leucine zipper class II (HD-Zip II) family of transcription factors. The ATHB17 monomer contains four domains common to all class II HD-Zip proteins: a putative repression domain adjacent to a homeodomain, leucine zipper, and carboxy terminal domain. However, it also possesses a unique N-terminus not present in other members of the family. In this study we demonstrate that the unique 73 amino acid N-terminus is involved in regulation of cellular localization of ATHB17. The ATHB17 protein is shown to function as a transcriptional repressor and an EAR-like motif is identified within the putative repression domain of ATHB17. Transformation of maize with an ATHB17 expression construct leads to the expression of ATHB17Δ113, a truncated protein lacking the first 113 amino acids which encodes a significant portion of the repression domain. Because ATHB17Δ113 lacks the repression domain, the protein cannot directly affect the transcription of its target genes. ATHB17Δ113 can homodimerize, form heterodimers with maize endogenous HD-Zip II proteins, and bind to target DNA sequences; thus, ATHB17Δ113 may interfere with HD-Zip II mediated transcriptional activity via a dominant negative mechanism. We provide evidence that maize HD-Zip II proteins function as transcriptional repressors and that ATHB17Δ113 relieves this HD-Zip II mediated transcriptional repression activity. Expression of ATHB17Δ113 in maize leads to increased ear size at silking and, therefore, may enhance sink potential. We hypothesize that this phenotype could be a result of modulation of endogenous HD-Zip II pathways in maize.
The expanding use of RNA interference (RNAi) in agricultural biotechnology necessitates tools for characterizing and quantifying double-stranded RNA (dsRNA)-containing transcripts that are expressed in transgenic plants. We sought to detect and quantify such transcripts in transgenic maize lines engineered to control western corn rootworm (Diabrotica virgifera virgifera LeConte) via overexpression of an inverted repeat sequence bearing a portion of the putative corn rootworm orthologue of yeast Snf7 (DvSnf7), an essential component of insect cell receptor sorting. A quantitative assay was developed to detect DvSnf7 sense strand-containing dsRNA transcripts that is based on the QuantiGene Plex 2.0 RNA assay platform from Affymetrix. The QuantiGene assay utilizes cooperative binding of multiple oligonucleotide probes with specificity for the target sequence resulting in exceptionally high assay specificity. Successful implementation of this assay required heat denaturation in the presence of the oligonucleotide probes prior to hybridization, presumably to dissociate primary transcripts carrying the duplex dsRNA structure. The dsRNA assay was validated using a strategy analogous to the rigorous enzyme-linked immunosorbent assay evaluations that are typically performed for foreign proteins expressed in transgenic plants. Validation studies indicated that the assay is sensitive (to 10 pg of dsRNA/g of fresh tissue), highly reproducible, and linear over ∼2.5 logs. The assay was validated using purified RNA from multiple maize tissue types, and studies indicate that the assay is also quantitative in crude tissue lysates. To the best of our knowledge, this is the first report of a non-polymerase chain reaction-based quantitative assay for dsRNA-containing transcripts, based on the use of the QuantiGene technology platform, and will broadly facilitate characterization of dsRNA in biological and environmental samples.
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