Water-deficit-induced changes in transcription factor expression in maize seedlings.

Plants tolerate water deficits by regulating gene networks controlling cellular and physiological traits to modify growth and development. Transcription factor (TF)-directed regulation of transcription within these gene networks is key to eliciting appropriate responses. In this study, reverse transcription quantitative PCR (RT-qPCR) was used to examine the abundance of 618 transcripts from 536 TF genes in individual root and shoot tissues of maize seedlings grown in vermiculite under well-watered (water potential of -0.02 MPa) and water-deficit conditions (water potentials of -0.3 and -1.6 MPa). A linear mixed model identified 433 TF transcripts representing 392 genes that differed significantly in abundance in at least one treatment, including TFs that intersect growth and development and environmental stress responses. TFs were extensively differentially regulated across stressed maize seedling tissues. Hierarchical clustering revealed TFs with stress-induced increased abundance in primary root tips that likely regulate root growth responses to water deficits, possibly as part of abscisic acid and/or auxin-dependent signaling pathways. Ten of these TFs were selected for validation in nodal root tips of drought-stressed field-grown plants (late V1 to early V2 stage). Changes in abundance of these TF transcripts under a field drought were similar to those observed in the seedling system.

Proteome-wide analysis reveals G protein-coupled receptor-like proteins in rice (Oryza sativa).

G protein-coupled receptors (GPCRs) constitute the largest family of transmembrane proteins in metazoans that mediate the regulation of various physiological responses to discrete ligands through heterotrimeric G protein subunits. The existence of GPCRs in plant is contentious, but their comparable crucial role in various signaling pathways necessitates the identification of novel remote GPCR-like proteins that essentially interact with the plant G protein α subunit and facilitate the transduction of various stimuli. In this study, we identified three putative GPCR-like proteins (OsGPCRLPs) (LOC_Os06g09930.1, LOC_Os04g36630.1, and LOC_Os01g54784.1) in the rice proteome using a stringent bioinformatics workflow. The identified OsGPCRLPs exhibited a canonical GPCR 'type I' 7TM topology, patterns, and biologically significant sites for membrane anchorage and desensitization. Cluster-based interactome mapping revealed that the identified proteins interact with the G protein α subunit which is a characteristic feature of GPCRs. Computational results showing the interaction of identified GPCR-like proteins with G protein α subunit and its further validation by the membrane yeast-two-hybrid assay strongly suggest the presence of GPCR-like 7TM proteins in the rice proteome. The absence of a regulator of G protein signaling (RGS) box in the C- terminal domain, and the presence of signature motifs of canonical GPCR in the identified OsGPCRLPs strongly suggest that the rice proteome contains GPCR-like proteins that might be involved in signal transduction.

Homolog-specific PCR primer design for profiling splice variants.

To study functional diversity of proteins encoded from a single gene, it is important to distinguish the expression levels among the alternatively spliced variants. A variant-specific primer pair is required to amplify each alternatively spliced variant individually. For this purpose, we developed a new feature, homolog-specific primer design (HSPD), in our high-throughput primer and probe design software tool, PRIMEGENS-v2. The algorithm uses a de novo approach to design primers without any prior information of splice variants or close homologs for an input query sequence. It not only designs primer pairs but also finds potential isoforms and homologs of the input sequence. Efficiency of this algorithm was tested for several gene families in soybean. A total of 187 primer pairs were tested under five different abiotic stress conditions with three replications at three time points. Results indicate a high success rate of primer design. Some primer pairs designed were able to amplify all splice variants of a gene. Furthermore, by utilizing combinations within the same multiplex pool, we were able to uniquely amplify a specific variant or duplicate gene. Our method can also be used to design PCR primers to specifically amplify homologs in the same gene family. PRIMEGENS-v2 is available at: http://primegens.org.

Genome-scale probe and primer design with PRIMEGENS.

This chapter introduces the software package PRIMEGENS for designing gene-specific probes and associated PCR primers on a large scale. Such design is especially useful for constructing cDNA or oligo microarray to minimize cross-hybridization. PRIMEGENS can also be used for designing primers to amplify a segment of a unique target gene using reverse-transcriptase (RT)-PCR. The input to PRIMEGENS is a set of sequences, whose primers need to be designed, and a sequence pool containing all the genes in a genome. It provides options to choose various parameters. PRIMEGENS uses a systematic algorithm for designing gene-specific probes and its primer pair. For a given sequence, PRIMEGENS first searches for the longest gene-specific fragment and then designs best PCR product for this fragment. The 2.0 version of PRIMEGENS provides a graphical user interface (GUI) with additional features. The software is freely available for any users and can be downloaded from http://digbio.missouri.edu/primegens/.

PRIMEGENSw3: a web-based tool for high-throughput primer and probe design.

Highly specific and efficient primer and probe design has been a major hurdle in many high-throughput techniques. Successful implementation of any PCR or probe hybridization technique depends on the quality of primers and probes used in terms of their specificity and cross-hybridization. Here we describe PRIMEGENSw3, a set of web-based utilities for high-throughput primer and probe design. These utilities allow users to select genomic regions and to design primer/probe for selected regions in an interactive, user-friendly, and automatic fashion. The system runs the PRIMEGENS algorithm in the back-end on the high-performance server with the stored genomic database or user-provided custom database for cross-hybridization check. Cross-hybridization is checked not only using BLAST but also by checking mismatch positions and energy calculation of potential hybridization hits. The results can be visualized online and also can be downloaded. The average success rate of primer design using PRIMEGENSw3 is ~90 %. The web server also supports primer design for methylated sequences, which is used in epigenetic studies. Stand-alone version of the software is also available for download at the website.

ArrayD: a general purpose software for microarray design.

BACKGROUND: Microarray is a high-throughput technology to study expression of thousands of genes in parallel. A critical aspect of microarray production is the design aimed at space optimization while maximizing the number of gene probes and their replicates to be spotted. RESULTS: We have developed a software called 'ArrayD' that offers various alternative design solutions for an array given a set of user requirements. The user feeds the following inputs: type of source plates to be used, number of gene probes to be printed, number of replicates and number of pins to be used for printing. The solutions are stored in a text file. The choice of a design solution to be used will be governed by the spotting chemistry to be used and the accuracy of the robot. CONCLUSIONS: ArrayD is a software for standard cartesian robots. The software aids users in preparing a judicious and elegant design. ArrayD is universally applicable and is available at http://www.igib.res.in/scientists/arrayd/arrayd.html.

Genome-wide functional annotation by integrating multiple microarray datasets using meta-analysis.

Tremendous amounts of microarray data for various organisms have provided a rich opportunity for computational analyses of gene products. Integrating these data can help inferring biological knowledge effectively. We present a new statistical method of integrating multiple microarray datasets for gene function prediction. We tested the performance of our model using yeast and human datasets. Our results show that combining multiple datasets improves the accuracy over the best function prediction of any single dataset significantly. We also compared performance of the meta p-value and meta correlation methods for function prediction. Supplementary results and code are available at http://digbio.missouri.edu/metaanalyses.

Identification of transcription factor's targets using tissue-specific transcriptomic data in Arabidopsis thaliana.

BACKGROUND: Transcription factors (TFs) regulate downstream genes in response to environmental stresses in plants. Identification of TF target genes can provide insight on molecular mechanisms of stress response systems, which can lead to practical applications such as engineering crops that thrive in challenging environments. Despite various computational techniques that have been developed for identifying TF targets, it remains a challenge to make best use of available experimental data, especially from time-series transcriptome profiling data, for improving TF target identification. RESULTS: In this study, we used a novel approach that combined kinetic modelling of gene expression with a statistical meta-analysis to predict targets of 757 TFs using expression data of 14,905 genes in Arabidopsis exposed to different durations and types of abiotic stresses. Using a kinetic model for the time delay between the expression of a TF gene and its potential targets, we shifted a TF's expression profile to make an interacting pair coherent. We found that partitioning the expression data by tissue and developmental stage improved correlation between TFs and their targets. We identified consensus pairs of correlated profiles between a TF and all other genes among partitioned datasets. We applied this approach to predict novel targets of known TFs. Some of these putative targets were validated from the literature, for E2F's targets in particular, while others provide explicit genes as hypotheses for future studies. CONCLUSION: Our method provides a general framework for TF target prediction with consideration of the time lag between initiation of a TF and activation of its targets. The framework helps make significant inferences by reducing the effects of independent noises in different experiments and by identifying recurring regulatory relationships under various biological conditions. Our TF target predictions may shed some light on common regulatory networks in abiotic stress responses.

Wingless directly represses DPP morphogen expression via an armadillo/TCF/Brinker complex.

BACKGROUND: Spatially restricted morphogen expression drives many patterning and regeneration processes, but how is the pattern of morphogen expression established and maintained? Patterning of Drosophila leg imaginal discs requires expression of the DPP morphogen dorsally and the wingless (WG) morphogen ventrally. We have shown that these mutually exclusive patterns of expression are controlled by a self-organizing system of feedback loops that involve WG and DPP, but whether the feedback is direct or indirect is not known. METHODS/FINDINGS: By analyzing expression patterns of regulatory DNA driving reporter genes in different genetic backgrounds, we identify a key component of this system by showing that WG directly represses transcription of the dpp gene in the ventral leg disc. Repression of dpp requires a tri-partite complex of the WG mediators armadillo (ARM) and dTCF, and the co-repressor Brinker, (BRK), wherein ARM.dTCF and BRK bind to independent sites within the dpp locus. CONCLUSIONS/SIGNIFICANCE: Many examples of dTCF repression in the absence of WNT signaling have been described, but few examples of signal-driven repression requiring both ARM and dTCF binding have been reported. Thus, our findings represent a new mode of WG mediated repression and demonstrate that direct regulation between morphogen signaling pathways can contribute to a robust self-organizing system capable of dynamically maintaining territories of morphogen expression.