AtCAST3.0 update: a web-based tool for analysis of transcriptome data by searching similarities in gene expression profiles

Arabidopsis bioinformatics: tools and strategies

The sequencing of the Arabidopsis thaliana genome 21 years ago ushered in the genomics era for plant research. Since then, an incredible variety of bioinformatic tools permit easy access to large repositories of genomic, transcriptomic, proteomic, epigenomic and other '-omic' data. In this review, we cover some more recent tools (and highlight the 'classics') for exploring such data in order to help formulate quality, testable hypotheses, often without having to generate new experimental data. We cover tools for examining gene expression and co-expression patterns, undertaking promoter analyses and gene set enrichment analyses, and exploring protein-protein and protein-DNA interactions. We will touch on tools that integrate different data sets at the end of the article.

Arabidopsis ACINUS is O-glycosylated and regulates transcription and alternative splicing of regulators of reproductive transitions

O-GlcNAc modification plays important roles in metabolic regulation of cellular status. Two homologs of O-GlcNAc transferase, SECRET AGENT (SEC) and SPINDLY (SPY), which have O-GlcNAc and O-fucosyl transferase activities, respectively, are essential in Arabidopsis but have largely unknown cellular targets. Here we show that AtACINUS is O-GlcNAcylated and O-fucosylated and mediates regulation of transcription, alternative splicing (AS), and developmental transitions. Knocking-out both AtACINUS and its distant paralog AtPININ causes severe growth defects including dwarfism, delayed seed germination and flowering, and abscisic acid (ABA) hypersensitivity. Transcriptomic and protein-DNA/RNA interaction analyses demonstrate that AtACINUS represses transcription of the flowering repressor FLC and mediates AS of ABH1 and HAB1, two negative regulators of ABA signaling. Proteomic analyses show AtACINUS's O-GlcNAcylation, O-fucosylation, and association with splicing factors, chromatin remodelers, and transcriptional regulators. Some AtACINUS/AtPININ-dependent AS events are altered in the sec and spy mutants, demonstrating a function of O-glycosylation in regulating alternative RNA splicing.

Bioinformatic Tools in Arabidopsis Research

Bioinformatic tools are now an everyday part of a plant researcher's collection of protocols. They allow almost instantaneous access to large data sets encompassing genomes, transcriptomes, proteomes, epigenomes, and other "-omes," which are now being generated with increasing speed and decreasing cost. With the appropriate queries, such tools can generate quality hypotheses, sometimes without the need for new experimental data. In this chapter, we will investigate some of the tools used for examining gene expression and coexpression patterns, performing promoter analyses and functional classification enrichment for sets of genes, and exploring protein-protein and protein-DNA interactions in Arabidopsis. We will also cover additional tools that allow integration of data from several sources for improved hypothesis generation.

Plant Regulomics: a data-driven interface for retrieving upstream regulators from plant multi-omics data

High-throughput technology has become a powerful approach for routine plant research. Interpreting the biological significance of high-throughput data has largely focused on the functional characterization of a large gene list or genomic loci that involves the following two aspects: the functions of the genes or loci and how they are regulated as a whole, i.e. searching for the upstream regulators. Traditional platforms for functional annotation largely help resolving the first issue. Addressing the second issue is essential for a global understanding of the regulatory mechanism, but is more challenging, and requires additional high-throughput experimental evidence and a unified statistical framework for data-mining. The rapid accumulation of 'omics data provides a large amount of experimental data. We here present Plant Regulomics, an interface that integrates 19 925 transcriptomic and epigenomic data sets and diverse sources of functional evidence (58 112 terms and 695 414 protein-protein interactions) from six plant species along with the orthologous genes from 56 whole-genome sequenced plant species. All pair-wise transcriptomic comparisons with biological significance within the same study were performed, and all epigenomic data were processed to genomic loci targeted by various factors. These data were well organized to gene modules and loci lists, which were further implemented into the same statistical framework. For any input gene list or genomic loci, Plant Regulomics retrieves the upstream factors, treatments, and experimental/environmental conditions regulating the input from the integrated 'omics data. Additionally, multiple tools and an interactive visualization are available through a user-friendly web interface. Plant Regulomics is available at http://bioinfo.sibs.ac.cn/plant-regulomics.

Nitric oxide deficiency decreases C-repeat binding factor-dependent and -independent induction of cold acclimation

Plant tolerance to freezing temperatures is governed by endogenous components and environmental factors. Exposure to low non-freezing temperatures is a key factor in the induction of freezing tolerance in the process called cold acclimation. The role of nitric oxide (NO) in cold acclimation was explored in Arabidopsis using triple nia1nia2noa1-2 mutants that are impaired in the nitrate-dependent and nitrate-independent pathways of NO production, and are thus NO deficient. Here, we demonstrate that cold-induced NO accumulation is required to promote the full cold acclimation response through C-repeat Binding Factor (CBF)-dependent gene expression, as well as the CBF-independent expression of other cold-responsive genes such as Oxidation-Related Zinc Finger 2 (ZF/OZF2). NO deficiency also altered abscisic acid perception and signaling and the cold-induced production of anthocyanins, which are additional factors involved in cold acclimation.

Nitric oxide responses in Arabidopsis hypocotyls are mediated by diverse phytohormone pathways

Plants are often exposed to high levels of nitric oxide (NO) that affects development and stress-triggered responses. However, the way in which plants sense NO is still largely unknown. Here we combine the analysis of early changes in the transcriptome of plants exposed to a short acute pulse of exogenous NO with the identification of transcription factors (TFs) involved in NO sensing. The NO-responsive transcriptome was enriched in hormone homeostasis- and signaling-related genes. To assess events involved in NO sensing in hypocotyls, we used a functional sensing assay based on the NO-induced inhibition of hypocotyl elongation in etiolated seedlings. Hormone-related mutants and the TRANSPLANTA collection of transgenic lines conditionally expressing Arabidopsis TFs were screened for NO-triggered hypocotyl shortening. These approaches allowed the identification of hormone-related TFs, ethylene perception and signaling, strigolactone biosynthesis and signaling, and salicylate production and accumulation that are essential for or modulate hypocotyl NO sensing. Moreover, NO inhibits hypocotyl elongation through the positive and negative regulation of some abscisic acid (ABA) receptors and transcripts encoding brassinosteroid signaling components thereby also implicating these hormones in NO sensing.

PlantExpress: A Database Integrating OryzaExpress and ArthaExpress for Single-species and Cross-species Gene Expression Network Analyses with Microarray-Based Transcriptome Data

Publicly available microarray-based transcriptome data on plants are remarkably valuable in terms of abundance and variation of samples, particularly for Oryza sativa (rice) and Arabidopsis thaliana (Arabidopsis). Here, we introduce the web database PlantExpress (http://plantomics.mind.meiji.ac.jp/PlantExpress/) as a platform for gene expression network (GEN) analysis with the public microarray data of rice and Arabidopsis. PlantExpress has two functional modes. The single-species mode is specialized for GEN analysis within one of the species, while the cross-species mode is optimized for comparative GEN analysis between the species. The single-species mode for rice is the new version of OryzaExpress, which we have maintained since 2006. The single-species mode for Arabidopsis, named ArthaExpress, was newly developed. PlantExpress stores data obtained from three microarrays, the Affymetrix Rice Genome Array, the Agilent Rice Gene Expression 4x44K Microarray, and the Affymetrix Arabidopsis ATH1 Genome Array, with respective totals of 2,678, 1,206, and 10,940 samples. This database employs a ‘MyList’ function with which users may save lists of arbitrary genes and samples (experimental conditions) to use in analyses. In cross-species mode, the MyList function allows performing comparative GEN analysis between rice and Arabidopsis. In addition, the gene lists saved in MyList can be directly exported to the PODC database, which provides information and a platform for comparative GEN analysis based on RNA-seq data and knowledge-based functional annotation of plant genes. PlantExpress will facilitate understanding the biological functions of plant genes.

Brassinosteroids participate in the control of basal and acquired freezing tolerance of plants

Brassinosteroids (BRs) are growth-promoting plant hormones that play a role in abiotic stress responses, but molecular modes that enable this activity remain largely unknown. Here we show that BRs participate in the regulation of freezing tolerance. BR signaling-defective mutants of Arabidopsis thaliana were hypersensitive to freezing before and after cold acclimation. The constitutive activation of BR signaling, in contrast, enhanced freezing resistance. Evidence is provided that the BR-controlled basic helix-loop-helix transcription factor CESTA (CES) can contribute to the constitutive expression of the C-REPEAT/DEHYDRATION-RESPONSIVE ELEMENT BINDING FACTOR (CBF) transcriptional regulators that control cold responsive (COR) gene expression. In addition, CBF-independent classes of BR-regulated COR genes are identified that are regulated in a BR- and CES-dependent manner during cold acclimation. A model is presented in which BRs govern different cold-responsive transcriptional cascades through the posttranslational modification of CES and redundantly acting factors. This contributes to the basal resistance against freezing stress, but also to the further improvement of this resistance through cold acclimation.

Transcriptome analysis of hormone-induced gene expression in Brachypodium distachyon

Brachypodium distachyon is a new model plant closely related to wheat and other cereals. In this study, we performed a comprehensive analysis of hormone-regulated genes in Brachypodium distachyon using RNA sequencing technology. Brachypodium distachyon seedlings were treated with eight phytohormones (auxin, cytokinine, brassinosteroid, gibberelline, abscisic acid, ethylene, jasmonate and salicylic acid) and two inhibitors, Brz220 (brassinosteroid biosynthesis inhibitor) and prohexadione (gibberelline biosynthesis inhibitor). The expressions of 1807 genes were regulated in a phytohormone-dependent manner. We compared the data with the phytohormone responses that have reported in rice. Transcriptional responses to hormones are conserved between Bracypodium and rice. Transcriptional regulation by brassinosteroid, gibberellin and ethylene was relatively weaker than those by other hormones. This is consistent with the data obtained from comprehensive analysis of hormone responses reported in Arabidopsis. Brachypodium and Arabidopsis also shared some common transcriptional responses to phytohormones. Alternatively, unique transcriptional responses to phytohormones were observed in Brachypodium. For example, the expressions of ACC synthase genes were up-regulated by auxin treatment in rice and Arabidopsis, but no orthologous ACC synthase gene was up-regulated in Brachypodium. Our results provide information useful to understand the diversity and similarity of hormone-regulated transcriptional responses between eudicots and monocots.

PhenoMeter: A Metabolome Database Search Tool Using Statistical Similarity Matching of Metabolic Phenotypes for High-Confidence Detection of Functional Links

This article describes PhenoMeter (PM), a new type of metabolomics database search that accepts metabolite response patterns as queries and searches the MetaPhen database of reference patterns for responses that are statistically significantly similar or inverse for the purposes of detecting functional links. To identify a similarity measure that would detect functional links as reliably as possible, we compared the performance of four statistics in correctly top-matching metabolic phenotypes of Arabidopsis thaliana metabolism mutants affected in different steps of the photorespiration metabolic pathway to reference phenotypes of mutants affected in the same enzymes by independent mutations. The best performing statistic, the PM score, was a function of both Pearson correlation and Fisher's Exact Test of directional overlap. This statistic outperformed Pearson correlation, biweight midcorrelation and Fisher's Exact Test used alone. To demonstrate general applicability, we show that the PM reliably retrieved the most closely functionally linked response in the database when queried with responses to a wide variety of environmental and genetic perturbations. Attempts to match metabolic phenotypes between independent studies were met with varying success and possible reasons for this are discussed. Overall, our results suggest that integration of pattern-based search tools into metabolomics databases will aid functional annotation of newly recorded metabolic phenotypes analogously to the way sequence similarity search algorithms have aided the functional annotation of genes and proteins. PM is freely available at MetabolomeExpress (https://www.metabolome-express.org/phenometer.php).