Development of a novel prediction method of cis-elements to hypothesize collaborative functions of cis-element pairs in iron-deficient rice

The transcription factor bZIP44 cooperates with MYB10 and MYB72 to regulate the response of Arabidopsis thaliana to iron deficiency stress

Nicotianamine (NA) plays a crucial role in transporting metal ions, including iron (Fe), in plants; therefore, NICOTIANAMINE SYNTHASE (NAS) genes, which control NA synthesis, are tightly regulated at the transcriptional level. However, the transcriptional regulatory mechanisms of NAS genes require further investigations. In this study, we determined the role of bZIP44 in mediating plant response to Fe deficiency stress by conducting transformation experiments and assays. bZIP44 positively regulated the response of Arabidopsis to Fe deficiency stress by interacting with MYB10 and MYB72 to enhance their abilities to bind at NAS2 and NAS4 promoters, thereby increasing NAS2 and NAS4 transcriptional levels and promote NA synthesis. In summary, the transcription activities of bZIP44, MYB10, and MYB72 were induced in response to Fe deficiency stress, which enhanced the interaction between bZIP44 and MYB10 or MYB72 proteins, synergistically activated the transcriptional activity of NAS2 and NAS4, promoted NA synthesis, and improved Fe transport, thereby enhancing plant tolerance to Fe deficiency stress.

Genome-Wide Analyses of Thaumatin-like Protein Family Genes Reveal the Involvement in the Response to Low-Temperature Stress in Ammopiptanthus nanus

Thaumatin-like proteins (TLPs), a family of proteins with high sequence similarity to thaumatin, are shown to be involved in plant defense, and are thus classified into the pathogenesis related protein family 5. Ammopiptanthus nanus is a rare evergreen broad-leaved shrub distributed in the temperate zone of Central Asia, which has a high tolerance to low-temperature stress. To characterize A. nanus TLPs and understand their roles in low-temperature response in A. nanus, a comprehensive analysis of the structure, evolution, and expression of TLP family proteins was performed. A total of 31 TLP genes were detected in the A. nanus genome, and they were divided into four groups based on their phylogenetic positions. The majority of the AnTLPs contained the conserved cysteine residues and were predicted to have the typical three-dimensional structure of plant TLPs. The primary modes of gene duplication of the AnTLP family genes were segmental duplication. The promoter regions of most AnTLP genes contain multiple cis-acting elements related to environmental stress response. Gene expression analysis based on transcriptome data and fluorescence quantitative PCR analysis revealed that several AnTLP genes were involved in cold-stress response. We further showed that a cold-induced AnTLP gene, AnTLP13, was localized in apoplast, and heterologous expression of the AnTLP13 in Escherichia coli and yeast cells and tobacco leaves enhanced low-temperature stress tolerance when compared with the control cells or seedlings. Our study provided important data for understanding the roles of TLPs in plant response to abiotic stress.

The basic leucine zipper transcription factor OsbZIP83 and the glutaredoxins OsGRX6 and OsGRX9 facilitate rice iron utilization under the control of OsHRZ ubiquitin ligases

Under low iron availability, plants induce the expression of various genes for iron uptake and translocation. The rice (Oryza sativa) ubiquitin ligases OsHRZ1 and OsHRZ2 cause overall repression of these iron-related genes at the transcript level, but their protein-level regulation is unclear. We conducted a proteome analysis to identify key regulators whose abundance was regulated by OsHRZs at the protein level. In response to iron deficiency or OsHRZ knockdown, many genes showed differential regulation between the transcript and protein levels, including the TGA-type basic leucine zipper transcription factor OsbZIP83. We also identified two glutaredoxins, OsGRX6 and OsGRX9, as OsHRZ-interacting proteins in yeast and plant cells. OsGRX6 also interacted with OsbZIP83. Our in vitro degradation assay suggested that OsbZIP83, OsGRX6 and OsGRX9 proteins are subjected to 26S proteasome- and OsHRZ-dependent degradation. Proteome analysis and our in vitro degradation assay also suggested that OsbZIP83 protein was preferentially degraded under iron-deficient conditions in rice roots. Transgenic rice lines overexpressing OsGRX9 and OsbZIP83 showed improved tolerance to iron deficiency. Expression of iron-related genes was affected in the OsGRX9 and OsGRX6 knockdown lines, suggesting disturbed iron utilization and signaling. OsbZIP83 overexpression lines showed enhanced expression of OsYSL2 and OsNAS3, which are involved in internal iron translocation, in addition to OsGRX9 and genes related to phytoalexin biosynthesis and the salicylic acid pathway. The results suggest that OsbZIP83, OsGRX6 and OsGRX9 facilitate iron utilization downstream of the OsHRZ pathway.

Elucidation of Novel cis-Regulatory Elements and Promoter Structures Involved in Iron Excess Response Mechanisms in Rice Using a Bioinformatics Approach

Iron (Fe) excess is a major constraint on crop production in flooded acidic soils, particularly in rice cultivation. Under Fe excess, plants activate a complex mechanism and network regulating Fe exclusion by roots and isolation in various tissues. In rice, the transcription factors and cis-regulatory elements (CREs) that regulate Fe excess response mechanisms remain largely elusive. We previously reported comprehensive microarray analyses of several rice tissues in response to various levels of Fe excess stress. In this study, we further explored novel CREs and promoter structures in rice using bioinformatics approaches with this microarray data. We first performed network analyses to predict Fe excess-related CREs through the categorization of the gene expression patterns of Fe excess-responsive transcriptional regulons, and found four major expression clusters: Fe storage type, Fe chelator type, Fe uptake type, and WRKY and other co-expression type. Next, we explored CREs within these four clusters of gene expression types using a machine-learning method called microarray-associated motif analyzer (MAMA), which we previously established. Through a comprehensive bioinformatics approach, we identified a total of 560 CRE candidates extracted by MAMA analyses and 42 important conserved sequences of CREs directly related to the Fe excess response in various rice tissues. We explored several novel cis-elements as candidate Fe excess CREs including GCWGCWGC, CGACACGC, and Myb binding-like motifs. Based on the presence or absence of candidate CREs using MAMA and known PLACE CREs, we found that the Boruta-XGBoost model explained expression patterns with high accuracy of about 83%. Enriched sequences of both novel MAMA CREs and known PLACE CREs led to high accuracy expression patterns. We also found new roles of known CREs in the Fe excess response, including the DCEp2 motif, IDEF1-, Zinc Finger-, WRKY-, Myb-, AP2/ERF-, MADS- box-, bZIP and bHLH- binding sequence-containing motifs among Fe excess-responsive genes. In addition, we built a molecular model and promoter structures regulating Fe excess-responsive genes based on new finding CREs. Together, our findings about Fe excess-related CREs and conserved sequences will provide a comprehensive resource for discovery of genes and transcription factors involved in Fe excess-responsive pathways, clarification of the Fe excess response mechanism in rice, and future application of the promoter sequences to produce genotypes tolerant of Fe excess.

Machine learning: A powerful tool for gene function prediction in plants

Recent advances in sequencing and informatic technologies have led to a deluge of publicly available genomic data. While it is now relatively easy to sequence, assemble, and identify genic regions in diploid plant genomes, functional annotation of these genes is still a challenge. Over the past decade, there has been a steady increase in studies utilizing machine learning algorithms for various aspects of functional prediction, because these algorithms are able to integrate large amounts of heterogeneous data and detect patterns inconspicuous through rule-based approaches. The goal of this review is to introduce experimental plant biologists to machine learning, by describing how it is currently being used in gene function prediction to gain novel biological insights. In this review, we discuss specific applications of machine learning in identifying structural features in sequenced genomes, predicting interactions between different cellular components, and predicting gene function and organismal phenotypes. Finally, we also propose strategies for stimulating functional discovery using machine learning-based approaches in plants.

Putative cis-Regulatory Elements Predict Iron Deficiency Responses in Arabidopsis Roots

Plant iron deficiency (-Fe) activates a complex regulatory network that coordinates root Fe uptake and distribution to sink tissues. In Arabidopsis (Arabidopsis thaliana), FER-LIKE FE DEFICIENCY-INDUCED TRANSCRIPTION FACTOR (FIT), a basic helix-loop-helix (bHLH) transcription factor (TF), regulates root Fe acquisition genes. Many other -Fe-induced genes are FIT independent, and instead regulated by other bHLH TFs and by yet unknown TFs. The cis-regulatory code, that is, the cis-regulatory elements (CREs) and their combinations that regulate plant -Fe-responses, remains largely elusive. Using Arabidopsis root transcriptome data and coexpression clustering, we identified over 100 putative CREs (pCREs) that predicted -Fe-induced gene expression in computational models. To assess pCRE properties and possible functions, we used large-scale in vitro TF binding data, positional bias, and evolutionary conservation. As one example, our approach uncovered pCREs resembling IDE1 (iron deficiency-responsive element 1), a known grass -Fe response CRE. Arabidopsis IDE1-likes were associated with FIT-dependent gene expression, more specifically with biosynthesis of Fe-chelating compounds. Thus, IDE1 seems to be conserved in grass and nongrass species. Our pCREs matched among others in vitro binding sites of B3, NAC, bZIP, and TCP TFs, which might be regulators of -Fe responses. Altogether, our findings provide a comprehensive source of cis-regulatory information for -Fe-responsive genes that advance our mechanistic understanding and inform future efforts in engineering plants with more efficient Fe uptake or transport systems.

Potential of Oryza officinalis to augment the cold tolerance genetic mechanisms of Oryza sativa by network complementation

Oryza officinalis is an accessible alien donor for genetic improvement of rice. Comparison across a representative panel of Oryza species showed that the wild O. officinalis and cultivated O. sativa ssp. japonica have similar cold tolerance potentials. The possibility that either distinct or similar genetic mechanisms are involved in the low temperature responses of each species was addressed by comparing their transcriptional networks. General similarities were supported by shared transcriptomic signatures indicative of equivalent metabolic, hormonal, and defense status. However, O. officinalis has maintained an elaborate cold-responsive brassinosteroid-regulated BES1-network that appeared to have been fragmented in O. sativa. BES1-network is potentially important for integrating growth-related responses with physiological adjustments and defenses through the protection of photosynthetic machinery and maintenance of stomatal aperture, oxidative defenses, and osmotic adjustment. Equivalent physiological processes are functional in O. sativa but their genetic mechanisms are under the direct control of ABA-dependent, DREB-dependent and/or oxidative-mediated networks uncoupled to BES1. While O. officinalis and O. sativa represent long periods of speciation and domestication, their comparable cold tolerance potentials involve equivalent physiological processes but distinct genetic networks. BES1-network represents a novel attribute of O. officinalis with potential applications in diversifying or complementing other mechanisms in the cultivated germplasm.

Iron homeostasis in plants - a brief overview

Iron plays a crucial role in biochemistry and is an essential micronutrient for plants and humans alike. Although plentiful in the Earth's crust it is not usually found in a form readily accessible for plants to use. They must therefore sense and interact with their environment, and have evolved two different molecular strategies to take up iron in the root. Once inside, iron is complexed with chelators and distributed to sink tissues where it is used predominantly in the production of enzyme cofactors or components of electron transport chains. The processes of iron uptake, distribution and metabolism are overseen by tight regulatory mechanisms, at the transcriptional and post-transcriptional level, to avoid iron concentrations building to toxic excess. Iron is also loaded into seeds, where it is stored in vacuoles or in ferritin. This is important for human nutrition as seeds form the edible parts of many crop species. As such, increasing iron in seeds and other tissues is a major goal for biofortification efforts by both traditional breeding and biotechnological approaches.

Rice and chickpea GDPDs are preferentially influenced by low phosphate and CaGDPD1 encodes an active glycerophosphodiester phosphodiesterase enzyme

Rice and chickpea GDPD s are transcriptionally influenced by mineral deficiencies; especially, by phosphate starvation and CaGDP1 encodes an active glycerophosphodiester phosphodiesterase enzyme. Glycerophosphodiester phosphodiesterases (GDPDs) are enzymes involved in the degradation of glycerophosphodiesters into sn-glycerol-3-phosphate and corresponding alcohols. These phospholipid remodeling genes have been suggested to play important roles in phosphate homeostasis. However, comprehensive information about the role of GDPDs under low phosphate (P) and other nutrient deficiencies (N, K, Fe, Zn) in rice and chickpea is missing. Here, we identified 13 OsGDPDs and 6 CaGDPDs in rice and chickpea, respectively, and partly characterized their roles in multiple nutrient stresses. Expression profiling after 7 and 15 days of deficiency treatments revealed unique and overlapping differential expression patterns of OsGDPDs and CaGDPDs under different nutrient stresses. Principal component analysis on the expression patterns of OsGDPDs and CaGDPDs revealed their preferential role in P starvation. Some of the GDPDs were also induced by N, K, Fe and Zn deficiency in temporal manner in both crops suggesting their roles in multiple nutrient stresses. Biochemical characterization of highly responsive chickpea GDPD, CaGDPD1, confirmed its in vitro GDPD activity and revealed its optimal temperature, pH and cofactor requirements. Further, CaGDPD1 showed its accumulation in ER and endomembranes. We hereby propose CaGDPD1 and various OsGDPDs as low P responsive marker genes in chickpea and rice, respectively. Our data uphold role of GDPDs in multinutrient responses and suggest them as candidates for rice and chickpea improvement for tolerance to various nutrient deficiencies.

Jasmonate signaling is activated in the very early stages of iron deficiency responses in rice roots

Under low iron availability, plants induce the expression of various genes involved in iron uptake and translocation at the transcriptional level. This iron deficiency response is affected by various plant hormones, but the roles of jasmonates in this response are not well-known. We investigated the involvement of jasmonates in rice iron deficiency responses. High rates of jasmonate-inducible genes were induced during the very early stages of iron deficiency treatment in rice roots. Many jasmonate-inducible genes were also negatively regulated by the ubiquitin ligases OsHRZ1 and OsHRZ2 and positively regulated by the transcription factor IDEF1. Ten out of 35 genes involved in jasmonate biosynthesis and signaling were rapidly induced at 3 h of iron deficiency treatment, and this induction preceded that of known iron deficiency-inducible genes involved in iron uptake and translocation. Twelve genes involved in jasmonate biosynthesis and signaling were also upregulated in HRZ-knockdown roots. Endogenous concentrations of jasmonic acid and jasmonoyl isoleucine tended to be rapidly increased in roots in response to iron deficiency treatment, whereas these concentrations were higher in HRZ-knockdown roots under iron-sufficient conditions. Analysis of the jasmonate-deficient cpm2 mutant revealed that jasmonates repress the expression of many iron deficiency-inducible genes involved in iron uptake and translocation under iron sufficiency, but this repression is partly canceled under an early stage of iron deficiency. These results indicate that jasmonate signaling is activated during the very early stages of iron deficiency, which is partly regulated by IDEF1 and OsHRZs.

Iron deficiency responses in rice roots

Iron (Fe) is an essential element for most living organisms. To acquire sparingly soluble Fe from the rhizosphere, rice roots rely on two Fe acquisition pathways. The first of these pathways involves Fe(III) chelators specific to graminaceous plants, the mugineic acid family phytosiderophores, and the second involves absorption of Fe(2+). Key components in this response include enzymes involved in the biosynthesis of deoxymugineic acid (OsNAS1, OsNAS2, OsNAAT1, and OsDMAS1), the deoxymugineic acid efflux transporter (TOM1), the Fe(III)-deoxymugineic acid transporter (OsYSL15), and Fe(2+) transporters (OsIRT1, OsIRT2, and OsNRAMP1). In whole roots, these proteins are expressed in a coordinated manner with strong transcriptional induction in response to Fe deficiency. Radial transport of Fe to xylem and phloem is also mediated by the mugineic acid family phytosiderophores, as well as other chelators and their transporters, including Fe(II)-nicotianamine transporter (OsYSL2), phenolics efflux transporters (PEZ1 and PEZ2), and citrate efflux transporter (OsFRDL1). Among these, OsYSL2 is strongly induced under conditions of Fe deficiency. Both transcriptional induction and potential feedback repression mediate the expressional regulation of the genes involved in Fe uptake and translocation in response to Fe deficiency. The transcription factors IDEF1, IDEF2, and OsIRO2 are responsible for transcriptional induction, whereas the ubiquitin ligases OsHRZ1 and OsHRZ2, as well as the transcription factors OsIRO3 and OsbHLH133, are thought to mediate negative regulation. Furthermore, IDEF1 and OsHRZs bind Fe and other metals, and are therefore candidate Fe sensors. The interacting functions of these regulators are thought to fine tune the expression of proteins involved in Fe uptake and translocation.

Iron sensors and signals in response to iron deficiency

The transcription of genes involved in iron acquisition in plants is induced under iron deficiency, but our understanding of iron sensors and signals remains limited. Iron Deficiency-responsive Element-binding Factor 1 (IDEF1) and Hemerythrin motif-containing Really Interesting New Gene- and Zinc-finger proteins (HRZs)/BRUTUS (BTS) have recently emerged as candidate iron sensors because of their functions as potent regulators of iron deficiency responses and their iron-binding properties. IDEF1 is a central transcriptional regulator of graminaceous genes involved in iron uptake and utilization, predominantly during the early stages of iron deficiency. HRZs/BTS are E3 ubiquitin ligases and negative regulators of iron deficiency responses in both graminaceous and non-graminaceous plants. Rice OsHRZ1 and OsHRZ2 are also potent regulators of iron accumulation. Characterizing these putative iron sensors also provides clues to understanding the nature of iron signals, which may involve ionized iron itself, other metals, oxygen, redox status, heme and iron-sulfur clusters, in addition to metabolites affected by iron deficiency. Systemic iron responses may also be regulated by phloem-mobile iron and its chelators such as nicotianamine. Iron sensors and signals will be identified by demonstration of signal transmission by IDEF1, HRZs/BTS, or unknown factors.

Spatial transcriptomes of iron-deficient and cadmium-stressed rice

Although the genes involved in metal homeostasis have been investigated over the past few decades, many genes related to metal homeostasis remain uncharacterized, and a comprehensive analysis of the expression of these genes is required. In the present study, we investigated the spatial gene expression profile of iron (Fe)-deficient and cadmium (Cd)-stressed Oryza sativa (rice) using laser microdissection and microarray analysis. Roots of Fe-deficient and Cd-stressed rice were separated into the vascular bundle, cortex, and epidermis plus exodermis. In addition, vascular bundles from new and old leaves at the lowest node, which are important for metal distribution, were analyzed separately. The spatial expression patterns were distinct in each tissue type. Fe deficiency and Cd stress also had significant effects on the transcriptomes, although these were less pronounced than the spatial effects. Genes encoding transporters involved in metal homeostasis, proteins associated with heavy metal detoxification, and phytohormone-related proteins were comprehensively investigated. Additionally, cis motifs involved in the regulation of these diverse expression changes in various tissue types were predicted. The spatial transcriptomes presented here provide novel insight into the molecular mechanisms of metal homeostasis.