New BAR tools for mining expression data and exploring Cis-elements in Arabidopsis thaliana

Specificity landscapes of 40 R2R3-MYBs reveal how paralogs target different cis-elements by homodimeric binding

Paralogous transcription factors (TFs) frequently recognize highly similar DNA motifs. Homodimerization can help distinguish them according to their different dimeric configurations. Here, by studying R2R3-MYB TFs, we show that homodimerization can also directly change the recognized DNA motifs to distinguish between similar TFs. By high-throughput SELEX, we profiled the specificity landscape for 40 R2R3-MYBs of subfamily VIII and curated 833 motif models. The dimeric models show that homodimeric binding has evoked specificity changes for AtMYBs. Focusing on AtMYB2 as an example, we show that homodimerization has modified its specificity and allowed it to recognize additional cis-regulatory sequences that are different from the closely related CCWAA-box AtMYBs and are unique among all AtMYBs. Genomic sites described by the modified dimeric specificities of AtMYB2 are conserved in evolution and involved in AtMYB2-specific transcriptional activation. Collectively, this study provides rich data on sequence preferences of VIII R2R3-MYBs and suggests an alternative mechanism that guides closely related TFs to respective cis-regulatory sites.

20 years of the Bio-Analytic Resource for Plant Biology

The Bio-Analytic Resource for Plant Biology ('the BAR', at https://bar.utoronto.ca) is celebrating its 20th year in operation in 2025. The BAR encompasses and provides visualization tools for large 'omics data sets from plants. The BAR covers data from Arabidopsis, tomato, wheat, barley and 29 other plant species (with data for 2 others to be released soon). These data include nucleotide and protein sequence data, gene expression data, protein-protein and protein-DNA interactions, protein structures, subcellular localizations, and polymorphisms. The data are stored in more than 200 relational databases holding 186 GB of data and are presented to the researchers via web apps. These web apps provide data analysis and visualization tools. Some of the most popular tools are eFP ('electronic fluorescent pictograph') Browsers, ePlants and ThaleMine (an Arabidopsis-specific instance of InterMine). The BAR was designated a Global Core Biodata Resource in 2023. Like other GCBRs, the BAR has excellent operational stability, provides access without login requirement, and provides an API for researchers to be able to access BAR data programmatically. We present in this update a new overarching search tool called Gaia that permits easy access to all BAR data, powered by machine learning and artificial intelligence.

Genome-wide association mapping of biochemical traits and its correlation with MYMIV resistance in mungbean (Vigna radiata L. Wilczek)

The mungbean yellow mosaic India virus (MYMIV, Begomovirus vignaradiataindiaense) causes Yellow Mosaic Disease (YMD) in mungbean (Vigna radiata L.). The biochemical assays including total phenol content (TPC), total flavonoid content (TFC), ascorbic acid (AA), DPPH (2,2-diphenyl-1-picrylhydrazyl), and FRAP (Ferric Reducing Antioxidant Power) were used to study the mungbean plants defense response to MYMIV infection. A wide range was recorded for the Area Under Disease Progress Curve (AUDPC; 1.75-1266.98) and coefficient of infection (CI; 0.33-45.53). In YMD susceptible genotypes, significant variations were observed for TPC [2001.27-2834.13 mgGAE/100 g dry weight (DW)], TFC (252.65-341.30 mg/100 g DW), AA (40.33-64.69 mg/100 g DW), DPPH (32.11-53.47% scavenging effect DW), and FRAP (48.99-101.22 µmol Fe2+/g DW). Similarly, in resistant genotypes also wide range was recorded for TPC (1788.50-2286.38 mgGAE/100 g DW), TFC (206.12-337.32 mg/100 gDAS samples varied from 384.6.46-47.64% scavenging effect DW), and FRAP (53.68-114.24 µmol Fe2+/g DW). Except for FRAP, other studied parameters were in the lower range in the resistant genotypes than the susceptible genotypes. Genome-wide association studies (GWAS) of 132 genotypes have identified 31,953 single nucleotide polymorphism (SNPs). MLM (Mixed Linear Model) and BLINK (Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway) models have identified 119 shared SNPs for various biochemical traits and MYMIV resistance. The key candidate genes include VRADI09G06940 (YMD resistance, TIR-NBS-LRR class, chr. 9), VRADI01G05030 [flavonoid biosynthesis; MYB65 transcription factor (TF); chr. 1], VRADI03G07600 (phenol biosynthesis; GATA TF 16; chr. 3), VRADI04G08470 (ascorbic acid; heat shock protein 70 kDa protein; chr. 4), VRADI04G07510 (FRAP; subtilisin-like protease SBT1.9; chr. 4), and VRADI05G02870 (DPPH; vacuolar protein sorting-associated protein 2; chr. 5). The identified genomic resources will enhance mungbean genomics and facilitate the advancement of genomic-assisted breeding in mungbean.

Confronting the data deluge: How artificial intelligence can be used in the study of plant stress

The advent of the genomics era enabled the generation of high-throughput data and computational methods that serve as powerful hypothesis-generating tools to understand the genomic and gene functional basis of plant stress resilience. The proliferation of experimental and analytical methods used in biology has resulted in a situation where plentiful data exists, but the volume and heterogeneity of this data has made analysis a significant challenge. Current advanced deep-learning models have displayed an unprecedented level of comprehension and problem-solving ability, and have been used to predict gene structure, function and expression based on DNA or protein sequence, and prominently also their use in high-throughput phenomics in agriculture. However, the application of deep-learning models to understand gene regulatory and signalling behaviour is still in its infancy. We discuss in this review the availability of data resources and bioinformatic tools, and several applications of these advanced ML/AI models in the context of plant stress response, and demonstrate the use of a publicly available LLM (ChatGPT) to derive a knowledge graph of various experimental and computational methods used in the study of plant stress. We hope this will stimulate further interest in collaboration between computer scientists, computational biologists and plant scientists to distil the deluge of genomic, transcriptomic, proteomic, metabolomic and phenomic data into meaningful knowledge that can be used for the benefit of humanity.

Rapidly Evolved Genes in Three Reaumuria Transcriptomes and Potential Roles of Pentatricopeptide Repeat Superfamily Proteins in Endangerment of R. trigyna

Reaumuria genus (Tamaricaceae) is widely distributed across the desert and semi-desert regions of Northern China, playing a crucial role in the restoration and protection of desert ecosystems. Previous studies mainly focused on the physiological responses to environmental stresses; however, due to the limited availability of genomic information, the underlying mechanism of morphological and ecological differences among the Reaumuria species remains poorly understood. In this study, we presented the first catalog of expressed transcripts for R. kaschgarica, a sympatric species of xerophyte R. soongorica. We further performed the pair-wise transcriptome comparison to determine the conserved and divergent genes among R. soongorica, R. kaschgarica, and the relict recretohalophyte R. trigyna. Annotation of the 600 relatively conserved genes revealed that some common genetic modules are employed by the Reaumuria species to confront with salt and drought stresses in arid environment. Among the 250 genes showing strong signs of positive selection, eight pentatricopeptide repeat (PPR) superfamily protein genes were specifically identified, including seven PPR genes in the R. soongorica vs. R. trigyna comparison and one PPR gene in the R. kaschgarica vs. R. trigyna comparison, while the cyclin D3 gene was found in the R. soongorica vs. R. trigyna comparison. These findings suggest that genetic variations in PPR genes may affect the fertility system or compromise the extent of organelle RNA editing in R. trigyna. The present study provides valuable genomic information for R. kaschgarica and preliminarily reveals the conserved genetic bases for the abiotic stress adaptation and interspecific divergent selection in the Reaumuria species. The rapidly evolved PPR and cyclin D3 genes provide new insights on the endangerment of R. trigyna and the leaf length difference among the Reaumuria species.

Multi-GWAS reveals significant genomic regions for Mungbean yellow mosaic India virus resistance in urdbean (Vigna mungo (L.) across multiple environments

KEY MESSAGE

Unraveling genetic markers for MYMIV resistance in urdbean, with 8 high-confidence marker-trait associations identified across diverse environments, provides crucial insights for combating MYMIV disease, informing future breeding strategies. Globally, yellow mosaic disease (YMD) causes significant yield losses, reaching up to 100% in favorable environments within major urdbean cultivating regions. The introgression of genomic regions conferring resistance into urdbean cultivars is crucial for combating YMD, including resistance against mungbean yellow mosaic India virus (MYMIV). To uncover the genetic basis of MYMIV resistance, we conducted a genome-wide association study (GWAS) using three multi-locus models in 100 diverse urdbean genotypes cultivated across six individual and two combined environments. Leveraging 4538 high-quality single nucleotide polymorphism (SNP) markers, we identified 28 unique significant marker-trait associations (MTAs) for MYMIV resistance, with 8 MTAs considered of high confidence due to detection across multiple GWAS models and/or environments. Notably, 4 out of 28 MTAs were found in proximity to previously reported genomic regions associated with MYMIV resistance in urdbean and mungbean, strengthening our findings and indicating consistent genomic regions for MYMIV resistance. Among the eight highly significant MTAs, one localized on chromosome 6 adjacent to previously identified quantitative trait loci for MYMIV resistance, while the remaining seven were novel. These MTAs contain several genes implicated in disease resistance, including four common ones consistently found across all eight MTAs: receptor-like serine-threonine kinases, E3 ubiquitin-protein ligase, pentatricopeptide repeat, and ankyrin repeats. Previous studies have linked these genes to defense against viral infections across different crops, suggesting their potential for further basic research involving cloning and utilization in breeding programs. This study represents the first GWAS investigation aimed at identifying resistance against MYMIV in urdbean germplasm.

Genome-wide discovery of InDels and validation of PCR-Based InDel markers for earliness in a RIL population and genotypes of lentil (Lens culinaris Medik.)

The systematic identification of insertion/deletion (InDel) length polymorphisms from the entire lentil genome can be used to map the quantitative trait loci (QTL) and also for the marker-assisted selection (MAS) for various linked traits. The InDels were identified by comparing the whole-genome resequencing (WGRS) data of two extreme bulks (early- and late-flowering bulk) and a parental genotype (Globe Mutant) of lentil. The bulks were made by pooling 20 extreme recombinant inbred lines (RILs) each, derived by crossing Globe Mutant (late flowering parent) with L4775 (early flowering parent). Finally, 734,716 novel InDels were identified, which is nearly one InDel per 5,096 bp of lentil genome. Furthermore, 74.94% of InDels were within the intergenic region and 99.45% displayed modifier effects. Of these, 15,732 had insertions or deletions of 20 bp or more, making them amenable to the development of PCR-based markers. An InDel marker I-SP-356.6 (chr. 3; position 356,687,623; positioned 174.5 Kb from the LcFRI gene) was identified as having a phenotypic variance explained (PVE) value of 47.7% for earliness when validated in a RIL population. Thus, I-SP-356.6 marker can be deployed in MAS to facilitate the transfer of the earliness trait to other elite late-maturing cultivars. Two InDel markers viz., I-SP-356.6 and I-SP-383.9 (chr. 3; linked to LcELF3a gene) when tested in 9 lentil genotypes differing for maturity duration, clearly distinguished three early (L4775, ILL7663, Precoz) and four late genotypes (Globe Mutant, MFX, L4602, L830). However, these InDels could not be validated in two genotypes (L4717, L4727), suggesting either absence of polymorphism and/or presence of other loci causing earliness. The identified InDel markers can act as valuable tools for MAS for the development of early maturing lentil varieties.

Genomic analysis of a spontaneous unifoliate mutant reveals gene candidates associated with compound leaf development in Vigna unguiculata [L] Walp

Molecular mechanisms which underpin compound leaf development in some legumes have been reported, but there is no previous study on the molecular genetic control of compound leaf formation in Vigna unguiculata (cowpea), an important dryland legume of African origin. In most studied species with compound leaves, class 1 KNOTTED-LIKE HOMEOBOX genes expressed in developing leaf primordia sustain morphogenetic activity, allowing leaf dissection and the development of leaflets. Other genes, such as, SINGLE LEAFLET1 in Medicago truncatula and Trifoliate in Solanum lycopersicum, are also implicated in regulating compound leaf patterning. To set the pace for an in-depth understanding of the genetics of compound leaf development in cowpea, we applied RNA-seq and whole genome shotgun sequence datasets of a spontaneous cowpea unifoliate mutant and its trifoliate wild-type cultivar to conduct comparative reference-based gene expression, de novo genome-wide isoform switch, and genome variant analyses between the two genotypes. Our results suggest that genomic variants upstream of LATE ELONGATED HYPOCOTYL and down-stream of REVEILLE4, BRASSINOSTERIOD INSENSITIVE1 and LATERAL ORGAN BOUNDARIES result in down-regulation of key components of cowpea circadian rhythm central oscillator and brassinosteroid signaling, resulting in unifoliate leaves and brassinosteroid-deficient-like phenotypes. We have stated hypotheses that will guide follow-up studies expected to provide more insights.

Identification of quantitative trait loci (QTLs) regulating leaf SPAD value and trichome density in mungbean (Vigna radiata L.) using genotyping-by-sequencing (GBS) approach

Quantitative trait loci (QTL) mapping is used for the precise localization of genomic regions regulating various traits in plants. Two major QTLs regulating Soil Plant Analysis Development (SPAD) value (qSPAD-7-1) and trichome density (qTric-7-2) in mungbean were identified using recombinant inbred line (RIL) populations (PMR-1×Pusa Baisakhi) on chromosome 7. Functional analysis of QTL region identified 35 candidate genes for SPAD value (16 No) and trichome (19 No) traits. The candidate genes regulating trichome density on the dorsal leaf surface of the mungbean include VRADI07G24840, VRADI07G17780, and VRADI07G15650, which encodes for ZFP6, TFs bHLH DNA-binding superfamily protein, and MYB102, respectively. Also, candidate genes having vital roles in chlorophyll biosynthesis are VRADIO7G29860, VRADIO7G29450, and VRADIO7G28520, which encodes for s-adenosyl-L-methionine, FTSHI1 protein, and CRS2-associated factor, respectively. The findings unfolded the opportunity for the development of customized genotypes having high SPAD value and high trichome density having a possible role in yield and mungbean yellow vein mosaic India virus (MYMIV) resistance in mungbean.

Genome-wide association studies for earliness, MYMIV resistance, and other associated traits in mungbean (Vigna radiata L. Wilczek) using genotyping by sequencing approach

Yellow mosaic disease (YMD) remains a major constraint in mungbean (Vigna radiata (L.)) production; while short-duration genotypes offer multiple crop cycles per year and help in escaping terminal heat stress, especially during summer cultivation. A comprehensive genotyping by sequencing (GBS)-based genome-wide association studies (GWAS) analysis was conducted using 132 diverse mungbean genotypes for traits like flowering time, YMD resistance, soil plant analysis development (SPAD) value, trichome density, and leaf area. The frequency distribution revealed a wide range of values for all the traits. GBS studies identified 31,953 high-quality single nucleotide polymorphism (SNPs) across all 11 mungbean chromosomes and were used for GWAS. Structure analysis revealed the presence of two genetically distinct populations based on ΔK. The linkage disequilibrium (LD) varied throughout the chromosomes and at r2 = 0.2, the mean LD decay was estimated as 39.59 kb. Two statistical models, mixed linear model (MLM) and Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) identified 44 shared SNPs linked with various candidate genes. Notable candidate genes identified include FPA for flowering time (VRADI10G01470; chr. 10), TIR-NBS-LRR for mungbean yellow mosaic India virus (MYMIV) resistance (VRADI09G06940; chr. 9), E3 ubiquitin-protein ligase RIE1 for SPAD value (VRADI07G28100; chr. 11), WRKY family transcription factor for leaf area (VRADI03G06560; chr. 3), and LOB domain-containing protein 21 for trichomes (VRADI06G04290; chr. 6). In-silico validation of candidate genes was done through digital gene expression analysis using Arabidopsis orthologous (compared with Vigna radiata genome). The findings provided valuable insight for marker-assisted breeding aiming for the development of YMD-resistant and early-maturing mungbean varieties.

Genome-wide association studies for phenological and agronomic traits in mungbean (Vigna radiata L. Wilczek)

Mungbean (Vigna radiata L. Wilczek) is one of the important warm-season food legumes, contributing substantially to nutritional security and environmental sustainability. The genetic complexity of yield-associated agronomic traits in mungbean is not well understood. To dissect the genetic basis of phenological and agronomic traits, we evaluated 153 diverse mungbean genotypes for two phenological (days to heading and days to maturity) and eight agronomic traits (leaf nitrogen status using SPAD, plant height, number of primary branches, pod length, number of pods per plant, seeds per pod, 100-seed weight, and yield per plant) under two environmental conditions. A wide array of phenotypic variability was apparent among the studied genotypes for all the studied traits. The broad sense of heritability of traits ranged from 0.31 to 0.95 and 0.21 to 0.94 at the Delhi and Ludhiana locations, respectively. A total of 55,634 genome-wide single nucleotide polymorphisms (SNPs) were obtained by the genotyping-by-sequencing method, of which 15,926 SNPs were retained for genome-wide association studies (GWAS). GWAS with Bayesian information and linkage-disequilibrium iteratively nested keyway (BLINK) model identified 50 SNPs significantly associated with phenological and agronomic traits. In total, 12 SNPs were found to be significantly associated with phenological traits across environments, explaining 7%-18.5% of phenotypic variability, and 38 SNPs were significantly associated with agronomic traits, explaining 4.7%-27.6% of the phenotypic variability. The maximum number of SNPs (15) were located on chromosome 1, followed by seven SNPs each on chromosomes 2 and 8. The BLAST search identified 19 putative candidate genes that were involved in light signaling, nitrogen responses, phosphorus (P) transport and remobilization, photosynthesis, respiration, metabolic pathways, and regulating growth and development. Digital expression analysis of 19 genes revealed significantly higher expression of 12 genes, viz. VRADI01G08170, VRADI11G09170, VRADI02G00450, VRADI01G00700, VRADI07G14240, VRADI03G06030, VRADI02G14230, VRADI08G01540, VRADI09G02590, VRADI08G00110, VRADI02G14240, and VRADI02G00430 in the roots, cotyledons, seeds, leaves, shoot apical meristems, and flowers. The identified SNPs and putative candidate genes provide valuable genetic information for fostering genomic studies and marker-assisted breeding programs that improve yield and agronomic traits in mungbean.

Discovery of a cis-regulatory element SaeM involved in dynamic regulation of synergid-specific MYB98

MYB98 is a key regulator of the genetic network behind pollen tube attraction toward the female gametophyte. MYB98 is specifically expressed in the synergid cells (SCs), a female gametophyte component cells specialized for pollen tube attraction. However, it had not been clear how exactly MYB98 achieves this specific expression pattern. In the current study, we have determined that a normal SC-specific expression of MYB98 is dependent on a 16-bp-long cis-regulatory element, CATTTACACATTAAAA, freshly named as the "S ynergid-specific A ctivation E lement of M YB98" (SaeM). An 84 bp fragment harboring SaeM in the middle was sufficient to drive exclusively SC-specific expression. The element was present in a significantly large proportion of SC-specific gene promoters and in the promoter of MYB98 homologous genes in the Brassicaceae (pMYB98s). Significance of such family-wide SaeM-like element conservation in exclusive SC-specific expression was confirmed by the Arabidopsis-like activation feature of Brassica oleracea-derived pMYB98 and absence of such feature of pMYB98 derived from a non-Brassicaceae member Prunus persica. Additionally, the yeast-one-hybrid assay showed that the SaeM can be recognized by ANTHOCYANINLESS2 (ANL2) and DAP-seq data further suggested for additional three ANL2 homologs targeting the similar cis-element. Overall, our study has concluded that SaeM plays a crucial role in driving exclusively SC-specific expression of MYB98 and strongly suggests for the involvement of ANL2 and its homologs in its dynamic regulation in planta. Future study on the transcription factors is expected to shed more light on the mechanism behind the process.

Deciphering Macromolecular Interactions Involved in Abiotic Stress Signaling: A Review of Bioinformatics Analysis

Plant functioning and responses to abiotic stresses largely involve regulations at the transcriptomic level via complex interactions of signal molecules, signaling cascades, and regulators. Nevertheless, all the signaling networks involved in responses to abiotic stresses have not yet been fully established. The in-depth analysis of transcriptomes in stressed plants has become a relevant state-of-the-art methodology to study these regulations and signaling pathways that allow plants to cope with or attempt to survive abiotic stresses. The plant science and molecular biology community has developed databases about genes, proteins, protein-protein interactions, protein-DNA interactions and ontologies, which are valuable sources of knowledge for deciphering such regulatory and signaling networks. The use of these data and the development of bioinformatics tools help to make sense of transcriptomic data in specific contexts, such as that of abiotic stress signaling, using functional biological approaches. The aim of this chapter is to present and assess some of the essential online tools and resources that will allow novices in bioinformatics to decipher transcriptomic data in order to characterize the cellular processes and functions involved in abiotic stress responses and signaling. The analysis of case studies further describes how these tools can be used to conceive signaling networks on the basis of transcriptomic data. In these case studies, particular attention was paid to the characterization of abiotic stress responses and signaling related to chemical and xenobiotic stressors.

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 Coexpression Tool: a tool for gene coexpression analysis in Arabidopsis thaliana

Gene coexpression analysis refers to the discovery of sets of genes which exhibit similar expression patterns across multiple transcriptomic data sets, such as microarray experiment data of public repositories. Arabidopsis Coexpression Tool (ACT), a gene coexpression analysis web tool for Arabidopsis thaliana, identifies genes which are correlated to a driver gene. Primary microarray data from ATH1 Affymetrix platform were processed with Single-Channel Array Normalization algorithm and combined to produce a coexpression tree which contains ∼21,000 A. thaliana genes. ACT was developed to present subclades of coexpressed genes, as well as to perform gene set enrichment analysis, being unique in revealing enriched transcription factors targeting coexpressed genes. ACT offers a simple and user-friendly interface producing working hypotheses which can be experimentally verified for the discovery of gene partnership, pathway membership, and transcriptional regulation. ACT analyses have been successful in identifying not only genes with coordinated ubiquitous expressions but also genes with tissue-specific expressions.

A prion-like protein regulator of seed germination undergoes hydration-dependent phase separation

Many organisms evolved strategies to survive desiccation. Plant seeds protect dehydrated embryos from various stressors and can lay dormant for millennia. Hydration is the key trigger to initiate germination, but the mechanism by which seeds sense water remains unresolved. We identified an uncharacterized Arabidopsis thaliana prion-like protein we named FLOE1, which phase separates upon hydration and allows the embryo to sense water stress. We demonstrate that biophysical states of FLOE1 condensates modulate its biological function in vivo in suppressing seed germination under unfavorable environments. We find intragenic, intraspecific, and interspecific natural variation in FLOE1 expression and phase separation and show that intragenic variation is associated with adaptive germination strategies in natural populations. This combination of molecular, organismal, and ecological studies uncovers FLOE1 as a tunable environmental sensor with direct implications for the design of drought-resistant crops, in the face of climate change.

Discovering novel cancer bio-markers in acquired lapatinib resistance using Bayesian methods

Signalling transduction pathways (STPs) are commonly hijacked by many cancers for their growth and malignancy, but demystifying their underlying mechanisms is difficult. Here, we developed methodologies with a fully Bayesian approach in discovering novel driver bio-markers in aberrant STPs given high-throughput gene expression (GE) data. This project, namely 'PathTurbEr' (Pathway Perturbation Driver) uses the GE dataset derived from the lapatinib (an EGFR/HER dual inhibitor) sensitive and resistant samples from breast cancer cell lines (SKBR3). Differential expression analysis revealed 512 differentially expressed genes (DEGs) and their pathway enrichment revealed 13 highly perturbed singalling pathways in lapatinib resistance, including PI3K-AKT, Chemokine, Hippo and TGF-$\beta $ singalling pathways. Next, the aberration in TGF-$\beta $ STP was modelled as a causal Bayesian network (BN) using three MCMC sampling methods, i.e. Neighbourhood sampler (NS) and Hit-and-Run (HAR) sampler that potentially yield robust inference with lower chances of getting stuck at local optima and faster convergence compared to other state-of-art methods. Next, we examined the structural features of the optimal BN as a statistical process that generates the global structure using $p_1$-model, a special class of Exponential Random Graph Models (ERGMs), and MCMC methods for their hyper-parameter sampling. This step enabled key drivers identification that drive the aberration within the perturbed BN structure of STP, and yielded 34, 34 and 23 perturbation driver genes out of 80 constituent genes of three perturbed STP models of TGF-$\beta $ signalling inferred by NS, HAR and MH sampling methods, respectively. Functional-relevance and disease-relevance analyses suggested their significant associations with breast cancer progression/resistance.

ASCORBATE PEROXIDASE6 delays the onset of age-dependent leaf senescence

Age-dependent changes in reactive oxygen species (ROS) levels are critical in leaf senescence. While H2O2-reducing enzymes such as catalases and cytosolic ASCORBATE PEROXIDASE1 (APX1) tightly control the oxidative load during senescence, their regulation and function are not specific to senescence. Previously, we identified the role of ASCORBATE PEROXIDASE6 (APX6) during seed maturation in Arabidopsis (Arabidopsis thaliana). Here, we show that APX6 is a bona fide senescence-associated gene. APX6 expression is specifically induced in aging leaves and in response to senescence-promoting stimuli such as abscisic acid (ABA), extended darkness, and osmotic stress. apx6 mutants showed early developmental senescence and increased sensitivity to dark stress. Reduced APX activity, increased H2O2 level, and altered redox state of the ascorbate pool in mature pre-senescing green leaves of the apx6 mutants correlated with the early onset of senescence. Using transient expression assays in Nicotiana benthamiana leaves, we unraveled the age-dependent post-transcriptional regulation of APX6. We then identified the coding sequence of APX6 as a potential target of miR398, which is a key regulator of copper redistribution. Furthermore, we showed that mutants of SQUAMOSA PROMOTER BINDING PROTEIN-LIKE7 (SPL7), the master regulator of copper homeostasis and miR398 expression, have a higher APX6 level compared with the wild type, which further increased under copper deficiency. Our study suggests that APX6 is a modulator of ROS/redox homeostasis and signaling in aging leaves that plays an important role in developmental- and stress-induced senescence programs.

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.

Classification and Computational Analysis of Arabidopsis thaliana Sperm Cell-Specific F-Box Protein Gene 3p.AtFBP113

In plants, F-box proteins (FBPs) constitute one of the largest superfamilies of regulatory proteins. Most F-box proteins are shown to be an integral part of SCF complexes, which carry out the degradation of proteins and regulate diverse important biological processes. Anthers and pollen development have a huge importance in crop breeding. Despite the vast diversity of FBPs in Arabidopsis male reproductive organs, their role in anther and pollen development is not much explored. Moreover, a standard nomenclature for naming FBPs is also lacking. Here, we propose a standard nomenclature for naming the FBPs of Arabidopsis thaliana uniformly and carry out a systematic analysis of sperm cell-specific FBP gene, i.e., 3p.AtFBP113 due to its reported high and preferential expression, for detailed functional annotation. The results revealed that 3p.AtFBP113 is located on the small arm of chromosome and encodes 397 amino acid long soluble, stable, and hydrophilic protein with the possibility of localization in various cellular compartments. The presence of the C-terminal F-box associated domain (FBA) with immunoglobulin-like fold anticipated its role in protein binding. Gene ontology based functional annotation and tissue-specific gene co-expression analysis further strengthened its role in protein binding and ubiquitination. Moreover, various potential post/co-translational modifications were anticipated and the predicted tertiary structure also showed the presence of characteristic domains and fold. Thus, the outcomes of the study will be useful in developing a better understating of the function of 3p.AtFBP113 during the process of pollen development, which will be helpful for targeting the gene for manipulation of male fertility that has immense importance in hybrid breeding.

Genome-Wide Association Analysis for Phosphorus Use Efficiency Traits in Mungbean (Vigna radiata L. Wilczek) Using Genotyping by Sequencing Approach

Mungbean (Vigna radiata L. Wilczek) is an annual grain legume crop affected by low availability of phosphorus. Phosphorus deficiency mainly affects the growth and development of plants along with changes in root morphology and increase in root-to-shoot ratio. Deciphering the genetic basis of phosphorus use efficiency (PUE) traits can benefit our understanding of mungbean tolerance to low-phosphorus condition. To address this issue, 144 diverse mungbean genotypes were evaluated for 12 PUE traits under hydroponics with optimum- and low-phosphorus levels. The broad sense heritability of traits ranged from 0.63 to 0.92 and 0.58 to 0.92 under optimum- and low-phosphorus conditions, respectively. This study, reports for the first time such a large number of genome wide Single nucleotide polymorphisms (SNPs) (76,160) in mungbean. Further, genome wide association study was conducted using 55,634 SNPs obtained by genotyping-by-sequencing method. The results indicated that total 136 SNPs shared by both GLM and MLM models were associated with tested PUE traits under different phosphorus regimes. We have identified SNPs with highest p value (-log10(p)) for some traits like, TLA and RDW with p value (-log10(p)) of more than 6.0 at LP/OP and OP condition. We have identified nine SNPs (three for TLA and six for RDW trait) which was found to be present in chromosomes 8, 4, and 7. One SNP present in Vradi07g06230 gene contains zinc finger CCCH domain. In total, 71 protein coding genes were identified, of which 13 genes were found to be putative candidate genes controlling PUE by regulating nutrient uptake and root architectural development pathways in mungbean. Moreover, we identified three potential candidate genes VRADI11G08340, VRADI01G05520, and VRADI04G10750 with missense SNPs in coding sequence region, which results in significant variation in protein structure at tertiary level. The identified SNPs and candidate genes provide the essential information for genetic studies and marker-assisted breeding program for improving low-phosphorus tolerance in mungbean.

Phosphorylation of the Pseudomonas Effector AvrPtoB by Arabidopsis SnRK2.8 Is Required for Bacterial Virulence

A critical component controlling bacterial virulence is the delivery of pathogen effectors into plant cells during infection. Effectors alter host metabolism and immunity for the benefit of pathogens. Multiple effectors are phosphorylated by host kinases, and this posttranslational modification is important for their activity. We sought to identify host kinases involved in effector phosphorylation. Multiple phosphorylated effector residues matched the proposed consensus motif for the plant calcium-dependent protein kinase (CDPK) and Snf1-related kinase (SnRK) superfamily. The conserved Pseudomonas effector AvrPtoB acts as an E3 ubiquitin ligase and promotes bacterial virulence. In this study, we identified a member of the Arabidopsis SnRK family, SnRK2.8, which interacts with AvrPtoB in yeast and in planta. We showed that SnRK2.8 was required for AvrPtoB virulence functions, including facilitating bacterial colonization, suppression of callose deposition, and targeting the plant defense regulator NPR1 and analyses receptor FLS2. Mass spectrometry analysis revealed that AvrPtoB phosphorylation occurs at multiple serine residues in planta, with S258 phosphorylation significantly reduced in the snrk2.8 knockout. AvrPtoB phospho-null mutants exhibited compromised virulence functions and were unable to suppress NPR1 accumulation, FLS2 accumulation, or inhibit FLS2-BAK1 complex formation upon flagellin perception. Taken together, these data identify a conserved plant kinase utilized by a pathogen effector to promote disease.

Network-based approaches for understanding gene regulation and function in plants

Expression reprogramming directed by transcription factors is a primary gene regulation underlying most aspects of the biology of any organism. Our views of how gene regulation is coordinated are dramatically changing thanks to the advent and constant improvement of high-throughput profiling and transcriptional network inference methods: from activities of individual genes to functional interactions across genes. These technical and analytical advances can reveal the topology of transcriptional networks in which hundreds of genes are hierarchically regulated by multiple transcription factors at systems level. Here we review the state of the art of experimental and computational methods used in plant biology research to obtain large-scale datasets and model transcriptional networks. Examples of direct use of these network models and perspectives on their limitations and future directions are also discussed.

Cell type-specific genome scans of DNA methylation divergence indicate an important role for transposable elements

In population genomics, genetic diversity measures play an important role in genome scans for divergent sites. In population epigenomics, comparable tools are rare although the epigenome can vary at several levels of organization. We propose a model-free, information-theoretic approach, the Jensen-Shannon divergence (JSD), as a flexible diversity index for epigenomic diversity. Here, we demonstrate how JSD uncovers the relationship between genomic features and cell type-specific methylome diversity in Arabidopsis thaliana. However, JSD is applicable to any epigenetic mark and any collection of individuals, tissues, or cells, for example to assess the heterogeneity in healthy organs and tumors.

AtMYB92 enhances fatty acid synthesis and suberin deposition in leaves of Nicotiana benthamiana

Acyl lipids are important constituents of the plant cell. Depending on the cell type, requirements in acyl lipids vary greatly, implying a tight regulation of fatty acid and lipid metabolism. The discovery of the WRINKLED1 (WRI1) transcription factors, members of the AP2-EREBP (APETALA2-ethylene-responsive element binding protein) family, has emphasized the importance of transcriptional regulation for adapting the rate of acyl chain production to cell requirements. Here, we describe the identification of another activator of the fatty acid biosynthetic pathway, the Arabidopsis MYB92 transcription factor. This MYB and all the members of the subgroups S10 and S24 of MYB transcription factors can directly activate the promoter of BCCP2 that encodes a component of the fatty acid biosynthetic pathway. Two adjacent MYB cis-regulatory elements are essential for the binding and activation of the BCCP2 promoter by MYB92. Overexpression of MYB92 or WRI1 in Nicotiana benthamiana induces the expression of fatty acid biosynthetic genes but results in the accumulation of different types of acyl lipids. In the presence of WRI1, triacylglycerol biosynthetic enzymes coded by constitutively expressed genes efficiently channel the excess fatty acids toward reserve lipid accumulation. By contrast, MYB92 activates both fatty acid and suberin biosynthetic genes; hence, the remarkable increase in suberin monomers measured in leaves expressing MYB92. These results provide additional insight into the molecular mechanisms that control the biosynthesis of an important cell wall-associated acylglycerol polymer playing critical roles in plants.

Prediction of condition-specific regulatory genes using machine learning

Recent advances in genomic technologies have generated data on large-scale protein-DNA interactions and open chromatin regions for many eukaryotic species. How to identify condition-specific functions of transcription factors using these data has become a major challenge in genomic research. To solve this problem, we have developed a method called ConSReg, which provides a novel approach to integrate regulatory genomic data into predictive machine learning models of key regulatory genes. Using Arabidopsis as a model system, we tested our approach to identify regulatory genes in data sets from single cell gene expression and from abiotic stress treatments. Our results showed that ConSReg accurately predicted transcription factors that regulate differentially expressed genes with an average auROC of 0.84, which is 23.5-25% better than enrichment-based approaches. To further validate the performance of ConSReg, we analyzed an independent data set related to plant nitrogen responses. ConSReg provided better rankings of the correct transcription factors in 61.7% of cases, which is three times better than other plant tools. We applied ConSReg to Arabidopsis single cell RNA-seq data, successfully identifying candidate regulatory genes that control cell wall formation. Our methods provide a new approach to define candidate regulatory genes using integrated genomic data in plants.

COPI complex isoforms are required for the early acceptance of compatible pollen grains in Arabidopsis thaliana

The Coat Protein I (COPI) complex is a seven-subunit coatomer complex consisting of the α, β, β', γ, δ, ε, and ζ proteins. In Arabidopsis thaliana, COPI is required for retrograde transport from the Golgi to the endoplasmic reticulum, Golgi maintenance, and cell plate formation. During compatible pollination, vesicle recruitment to the pollen contact point is required for pollen hydration and pollen tube penetration. Here, to identify other aspects of trafficking involved in the acceptance of compatible pollen by stigmatic papillae and to determine their roles in compatible pollination, we characterized knockout lines of several isoforms of the COPI complex, including α1-COP, γ-COP, and ε-COP. Specifically, we characterized pollen grain adherence, pollen tube penetration, and seed set in the mutants. Of the mutant lines examined, α1-cop had the most severe phenotypes, including altered compatible pollen grain adherence and tube germination and reduced seed set, whereas the other lines had milder phenotypes but visibly retarded compatible pollen acceptance. This is the first study demonstrating that COPI complex subunits are required for the acceptance of compatible pollen.

Hierarchical and Dynamic Regulation of Defense-Responsive Specialized Metabolism by WRKY and MYB Transcription Factors

The plant kingdom produces hundreds of thousands of specialized bioactive metabolites, some with pharmaceutical and biotechnological importance. Their biosynthesis and function have been studied for decades, but comparatively less is known about how transcription factors with overlapping functions and contrasting regulatory activities coordinately control the dynamics and output of plant specialized metabolism. Here, we performed temporal studies on pathogen-infected intact host plants with perturbed transcription factors. We identified WRKY33 as the condition-dependent master regulator and MYB51 as the dual functional regulator in a hierarchical gene network likely responsible for the gene expression dynamics and metabolic fluxes in the camalexin and 4-hydroxy-indole-3-carbonylnitrile (4OH-ICN) pathways. This network may have also facilitated the regulatory capture of the newly evolved 4OH-ICN pathway in Arabidopsis thaliana by the more-conserved transcription factor MYB51. It has long been held that the plasticity of plant specialized metabolism and the canalization of development should be differently regulated; our findings imply a common hierarchical regulatory architecture orchestrated by transcription factors for specialized metabolism and development, making it an attractive target for metabolic engineering.

Test of Arabidopsis Space Transcriptome: A Discovery Environment to Explore Multiple Plant Biology Spaceflight Experiments

Recent advances in the routine access to space along with increasing opportunities to perform plant growth experiments on board the International Space Station have led to an ever-increasing body of transcriptomic, proteomic, and epigenomic data from plants experiencing spaceflight. These datasets hold great promise to help understand how plant biology reacts to this unique environment. However, analyses that mine across such expanses of data are often complex to implement, being impeded by the sheer number of potential comparisons that are possible. Complexities in how the output of these multiple parallel analyses can be presented to the researcher in an accessible and intuitive form provides further barriers to such research. Recent developments in computational systems biology have led to rapid advances in interactive data visualization environments designed to perform just such tasks. However, to date none of these tools have been tailored to the analysis of the broad-ranging plant biology spaceflight data. We have therefore developed the Test Of Arabidopsis Space Transcriptome (TOAST) database (https://astrobiology.botany.wisc.edu/astrobotany-toast) to address this gap in our capabilities. TOAST is a relational database that uses the Qlik database management software to link plant biology, spaceflight-related omics datasets, and their associated metadata. This environment helps visualize relationships across multiple levels of experiments in an easy to use gene-centric platform. TOAST draws on data from The US National Aeronautics and Space Administration's (NASA's) GeneLab and other data repositories and also connects results to a suite of web-based analytical tools to facilitate further investigation of responses to spaceflight and related stresses. The TOAST graphical user interface allows for quick comparisons between plant spaceflight experiments using real-time, gene-specific queries, or by using functional gene ontology, Kyoto Encyclopedia of Genes and Genomes pathway, or other filtering systems to explore genetic networks of interest. Testing of the database shows that TOAST confirms patterns of gene expression already highlighted in the literature, such as revealing the modulation of oxidative stress-related responses across multiple plant spaceflight experiments. However, this data exploration environment can also drive new insights into patterns of spaceflight responsive gene expression. For example, TOAST analyses highlight changes to mitochondrial function as likely shared responses in many plant spaceflight experiments.

In-Silico Evaluation of a New Gene From Wheat Reveals the Divergent Evolution of the CAP160 Homologous Genes Into Monocots

This study reports the evolutionary history and in-silico functional characterization of a novel water-deficit and ABA-responsive gene in wheat. This gene has remote sequence similarity to known abiotic stress-related genes in different plants, including CAP160 in Spinacia oleracea, RD29B in Arabidopsis thaliana, and CDeT11-24 in Craterostigma plantagineum. The study investigated if these genes form a close homologous relationship or if they are a result of convergent evolutionary processes. The results indicated a closely shared homologous relationship between these genes. Bayesian phylogenetic analysis of the protein sequences of the remotely related CAP160 proteins from various plant species indicated the presence of three distinct clades. Further analyses indicated that CAP160 homologous genes have predominantly evolved through neutral processes, with multiple regions experiencing signatures of purifying selection, while others were indicated to be the result of episodic diversifying selection events. Functional predictions revealed that these genes might share at least two functions related to abiotic stress conditions: one similar to the cryoprotective function of LEA protein, and the other a signalling molecule with phosphatidic acid binding specificity. Studies focused on the identification of cold-responsive genes are essential for the development of cold-tolerant crop plants, if we are to increase agricultural productivity throughout temperate regions.

Inference of plant gene regulatory networks using data-driven methods: A practical overview

Transcriptional regulation is a complex and dynamic process that plays a vital role in plant growth and development. A key component in the regulation of genes is transcription factors (TFs), which coordinate the transcriptional control of gene activity. A gene regulatory network (GRN) is a collection of regulatory interactions between TFs and their target genes. The accurate delineation of GRNs offers a significant contribution to our understanding about how plant cells are organized and function, and how individual genes are regulated in various conditions, organs or cell types. During the past decade, important progress has been made in the identification of GRNs using experimental and computational approaches. However, a detailed overview of available platforms supporting the analysis of GRNs in plants is missing. Here, we review current databases, platforms and tools that perform data-driven analyses of gene regulation in Arabidopsis. The platforms are categorized into two sections, 1) promoter motif analysis tools that use motif mapping approaches to find TF motifs in the regulatory sequences of genes of interest and 2) network analysis tools that identify potential regulators for a set of input genes using a range of data types in order to generate GRNs. We discuss the diverse datasets integrated and highlight the strengths and caveats of different platforms. Finally, we shed light on the limitations of the above approaches and discuss future perspectives, including the need for integrative approaches to unravel complex GRNs in plants.

Genome-Wide Computational Identification of Biologically Significant Cis-Regulatory Elements and Associated Transcription Factors from Rice

The interactions between transcription factors (TFs) and cis-acting regulatory elements (CREs) provide crucial information on the regulation of gene expression. The determination of TF-binding sites and CREs experimentally is costly and time intensive. An in silico identification and annotation of TFs, and the prediction of CREs from rice are made possible by the availability of whole genome sequence and transcriptome data. In this study, we tested the applicability of two algorithms developed for other model systems for the identification of biologically significant CREs of co-expressed genes from rice. CREs were identified from the DNA sequences located upstream from the transcription start sites, untranslated regions (UTRs), and introns, and downstream from the translational stop codons of co-expressed genes. The biologically significance of each CRE was determined by correlating their absence and presence in each gene with that gene's expression profile using a meta-database constructed from 50 rice microarray data sets. The reliability of these methods in the predictions of CREs and their corresponding TFs was supported by previous wet lab experimental data and a literature review. New CREs corresponding to abiotic stresses, biotic stresses, specific tissues, and developmental stages were identified from rice, revealing new pieces of information for future experimental testing. The effectiveness of some-but not all-CREs was found to be affected by copy number, position, and orientation. The corresponding TFs that were most likely correlated with each CRE were also identified. These findings not only contribute to the prioritization of candidates for further analysis, the information also contributes to the understanding of the gene regulatory network.

TF2Network: predicting transcription factor regulators and gene regulatory networks in Arabidopsis using publicly available binding site information

A gene regulatory network (GRN) is a collection of regulatory interactions between transcription factors (TFs) and their target genes. GRNs control different biological processes and have been instrumental to understand the organization and complexity of gene regulation. Although various experimental methods have been used to map GRNs in Arabidopsis thaliana, their limited throughput combined with the large number of TFs makes that for many genes our knowledge about regulating TFs is incomplete. We introduce TF2Network, a tool that exploits the vast amount of TF binding site information and enables the delineation of GRNs by detecting potential regulators for a set of co-expressed or functionally related genes. Validation using two experimental benchmarks reveals that TF2Network predicts the correct regulator in 75–92% of the test sets. Furthermore, our tool is robust to noise in the input gene sets, has a low false discovery rate, and shows a better performance to recover correct regulators compared to other plant tools. TF2Network is accessible through a web interface where GRNs are interactively visualized and annotated with various types of experimental functional information. TF2Network was used to perform systematic functional and regulatory gene annotations, identifying new TFs involved in circadian rhythm and stress response.

Building Transcription Factor Binding Site Models to Understand Gene Regulation in Plants

Transcription factors (TFs) are key cellular components that control gene expression. They recognize specific DNA sequences, the TF binding sites (TFBSs), and thus are targeted to specific regions of the genome where they can recruit transcriptional co-factors and/or chromatin regulators to fine-tune spatiotemporal gene regulation. Therefore, the identification of TFBSs in genomic sequences and their subsequent quantitative modeling is of crucial importance for understanding and predicting gene expression. Here, we review how TFBSs can be determined experimentally, how the TFBS models can be constructed in silico, and how they can be optimized by taking into account features such as position interdependence within TFBSs, DNA shape, and/or by introducing state-of-the-art computational algorithms such as deep learning methods. In addition, we discuss the integration of context variables into the TFBS modeling, including nucleosome positioning, chromatin states, methylation patterns, 3D genome architectures, and TF cooperative binding, in order to better predict TF binding under cellular contexts. Finally, we explore the possibilities of combining the optimized TFBS model with technological advances, such as targeted TFBS perturbation by CRISPR, to better understand gene regulation, evolution, and plant diversity.

Insights into ABA-mediated regulation of guard cell primary metabolism revealed by systems biology approaches

Despite the fact that guard cell abscisic acid (ABA) signalling pathway is well documented, our understanding concerning how and to which extent ABA regulates guard cell metabolism remains fragmentary. Here we have adopted different systems approaches to investigate how ABA modulates guard cell central metabolism by providing genes that are possibly ABA-regulated. By using previous published Arabidopsis guard cell transcript profiling data, we carried out an extensive co-expression network analysis using ABA-related genes and those related to the metabolism and transport of sugars, starch and organic acids. Next, we investigated the presence of ABA responsive elements (ABRE) in the promoter of genes that are highly expressed in guard cells, responsive to ABA and co-expressed with ABA-related genes. Together, these analyses indicated that 44 genes are likely regulated by ABA and 8 of them are highly expressed in guard cells in both the presence and absence of ABA, including genes of the tricarboxylic acid cycle and those related to sucrose and hexose transport and metabolism. It seems likely that ABA may modulate both sucrose transport through guard cell plasma membrane and sucrose metabolism within guard cells. In this context, genes associated with sucrose synthase, sucrose phosphate synthase, trehalose-6-phosphate, invertase, UDP-glucose epimerase/pyrophosphorylase and different sugar transporters contain ABRE in their promoter and are thus possibly ABA regulated. Although validation experiments are required, our study highlights the importance of systems biology approaches to drive new hypothesis and to unravel genes and pathways that are regulated by ABA in guard cells.

The Bio-Analytic Resource for Plant Biology

Bioinformatic tools have become part of the way plant researchers undertake investigations. Large data sets encompassing genomes, transcriptomes, proteomes, epigenomes, and other "-omes" that have been generated in the past decade may be easily accessed with such tools, such that hypotheses may be generated at the click of a mouse. In this chapter, we'll cover the use of bioinformatic tools available at the Bio-Analytic Resource for Plant Biology at http://bar.utoronto.ca for exploring gene expression and coexpression patterns, undertaking promoter analyses, performing functional classification enrichment analyses for sets of genes, and examining protein-protein interactions. We also touch on some newer bioinformatic tools that allow integration of data from several sources for improved hypothesis generation, both for Arabidopsis and translationally. Most of the data sets come from Arabidopsis, but useful BAR tools for other species will be mentioned where appropriate.

Heterodimerization of Arabidopsis calcium/proton exchangers contributes to regulation of guard cell dynamics and plant defense responses

Arabidopsis thaliana cation exchangers (CAX1 and CAX3) are closely related tonoplast-localized calcium/proton (Ca2+/H+) antiporters that contribute to cellular Ca2+ homeostasis. CAX1 and CAX3 were previously shown to interact in yeast; however, the function of this complex in plants has remained elusive. Here, we demonstrate that expression of CAX1 and CAX3 occurs in guard cells. Additionally, CAX1 and CAX3 are co-expressed in mesophyll tissue in response to wounding or flg22 treatment, due to the induction of CAX3 expression. Having shown that the transporters can be co-expressed in the same cells, we demonstrate that CAX1 and CAX3 can form homomeric and heteromeric complexes in plants. Consistent with the formation of a functional CAX1-CAX3 complex, CAX1 and CAX3 integrated into the yeast genome suppressed a Ca2+-hypersensitive phenotype of mutants defective in vacuolar Ca2+ transport, and demonstrated enzyme kinetics different from those of either CAX protein expressed by itself. We demonstrate that the interactions between CAX proteins contribute to the functioning of stomata, because stomata were more closed in cax1-1, cax3-1, and cax1-1/cax3-1 loss-of-function mutants due to an inability to buffer Ca2+ effectively. We hypothesize that the formation of CAX1-CAX3 complexes may occur in the mesophyll to affect intracellular Ca2+ signaling during defense responses.

SeqEnrich: A tool to predict transcription factor networks from co-expressed Arabidopsis and Brassica napus gene sets

Transcription factors and their associated DNA binding sites are key regulatory elements of cellular differentiation, development, and environmental response. New tools that predict transcriptional regulation of biological processes are valuable to researchers studying both model and emerging-model plant systems. SeqEnrich predicts transcription factor networks from co-expressed Arabidopsis or Brassica napus gene sets. The networks produced by SeqEnrich are supported by existing literature and predicted transcription factor–DNA interactions that can be functionally validated at the laboratory bench. The program functions with gene sets of varying sizes and derived from diverse tissues and environmental treatments. SeqEnrich presents as a powerful predictive framework for the analysis of Arabidopsis and Brassica napus co-expression data, and is designed so that researchers at all levels can easily access and interpret predicted transcriptional circuits. The program outperformed its ancestral program ChipEnrich, and produced detailed transcription factor networks from Arabidopsis and Brassica napus gene expression data. The SeqEnrich program is ideal for generating new hypotheses and distilling biological information from large-scale expression data.