Rice DB: an Oryza Information Portal linking annotation, subcellular location, function, expression, regulation, and evolutionary information for rice and Arabidopsis

Subcellular Proteomics as a Unified Approach of Experimental Localizations and Computed Prediction Data for Arabidopsis and Crop Plants

In eukaryotic organisms, subcellular protein location is critical in defining protein function and understanding sub-functionalization of gene families. Some proteins have defined locations, whereas others have low specificity targeting and complex accumulation patterns. There is no single approach that can be considered entirely adequate for defining the in vivo location of all proteins. By combining evidence from different approaches, the strengths and weaknesses of different technologies can be estimated, and a location consensus can be built. The Subcellular Location of Proteins in Arabidopsis database ( http://suba.live/ ) combines experimental data sets that have been reported in the literature and is analyzing these data to provide useful tools for biologists to interpret their own data. Foremost among these tools is a consensus classifier (SUBAcon) that computes a proposed location for all proteins based on balancing the experimental evidence and predictions. Further tools analyze sets of proteins to define the abundance of cellular structures. Extending these types of resources to plant crop species has been complex due to polyploidy, gene family expansion and contraction, and the movement of pathways and processes within cells across the plant kingdom. The Crop Proteins of Annotated Location database ( http://crop-pal.org/ ) has developed a range of subcellular location resources including a species-specific voting consensus for 12 plant crop species that offers collated evidence and filters for current crop proteomes akin to SUBA. Comprehensive cross-species comparison of these data shows that the sub-cellular proteomes (subcellulomes) depend only to some degree on phylogenetic relationship and are more conserved in major biosynthesis than in metabolic pathways. Together SUBA and cropPAL created reference subcellulomes for plants as well as species-specific subcellulomes for cross-species data mining. These data collections are increasingly used by the research community to provide a subcellular protein location layer, inform models of compartmented cell function and protein-protein interaction network, guide future molecular crop breeding strategies, or simply answer a specific question-where is my protein of interest inside the cell?

CropPAL for discovering divergence in protein subcellular location in crops to support strategies for molecular crop breeding

Agriculture faces increasing demand for yield, higher plant-derived protein content and diversity while facing pressure to achieve sustainability. Although the genomes of many of the important crops have been sequenced, the subcellular locations of most of the encoded proteins remain unknown or are only predicted. Protein subcellular location is crucial in determining protein function and accumulation patterns in plants, and is critical for targeted improvements in yield and resilience. Integrating location data from over 800 studies for 12 major crop species into the cropPAL2020 data collection showed that while >80% of proteins in most species are not localised by experimental data, combining species data or integrating predictions can help bridge gaps at similar accuracy. The collation and integration of over 61 505 experimental localisations and more than 6 million predictions showed that the relative sizes of the protein catalogues located in different subcellular compartments are comparable between crops and Arabidopsis. A comprehensive cross-species comparison showed that between 50% and 80% of the subcellulomes are conserved across species and that conservation only depends to some degree on the phylogenetic relationship of the species. Protein subcellular locations in major biosynthesis pathways are more often conserved than in metabolic pathways. Underlying this conservation is a clear potential for subcellular diversity in protein location between species by means of gene duplication and alternative splicing. Our cropPAL data set and search platform (https://crop-pal.org) provide a comprehensive subcellular proteomics resource to drive compartmentation-based approaches for improving yield, protein composition and resilience in future crop varieties.

Global analysis of threonine metabolism genes unravel key players in rice to improve the abiotic stress tolerance

The diversity in plant metabolites with improved phytonutrients is essential to achieve global food security and sustainable crop yield. Our study using computational metabolomics genome wide association study (cmGWAS) reports on a comprehensive profiling of threonine (Thr) metabolite in rice. Sixteen abiotic stress responsive (AbSR) – Thr metabolite producing genes (ThrMPG), modulate metabolite levels and play a significant role determining both physiological and nutritional importance of rice. These AbSR-ThrMPG were computationally analysed for their protein properties using OryzaCyc through plant metabolic network analyser. A total of 1373 and 1028 SNPs were involved in complex traits and genomic variations. Comparative mapping of AbSR-ThrMPG revealed the chromosomal colinearity with C4 grass species. Further, computational expression pattern of these genes predicted a differential expression profiling in diverse developmental tissues. Protein interaction of protein coding gene sequences revealed that the abiotic stresses (AbS) are multigenic in nature. In silico expression of AbSR-ThrMPG determined the putative involvement in response to individual AbS. This is the first comprehensive genome wide study reporting on AbSR –ThrMPG analysis in rice. The results of this study provide a pivotal resource for further functional investigation of these key genes in the vital areas of manipulating AbS signaling in rice improvement.

Water-stress induced downsizing of light-harvesting antenna complex protects developing rice seedlings from photo-oxidative damage

The impact of water-stress on chloroplast development was studied by applying polyethylene glycol 6000 to the roots of 5-day-old etiolated rice (Oryza sativa) seedlings that were subsequently illuminated up to 72 h. Chloroplast development in drought environment led to down-regulation of light-harvesting Chl-proteins. Photosynthetic proteins of Photosystem II (PSII) and oxygen evolving complex i.e., Cytb559, OEC16, OEC23 and OEC33 as well as those of PSI such as PSI-III, PSI-V, and PSI-VI, decreased in abundance. Consequently, due to reduced light absorption by antennae, the electron transport rates of PSII and PSI decreased by 55% and 25% respectively. Further, seedling development in stress condition led to a decline in the ratio of variable (Fv) to maximum (Fm) Chl a fluorescence, as well in the quantum yield of PSII photochemistry. Addition of Mg²⁺ to the thylakoid membranes suggested that Mg²⁺-induced grana stacking was not affected by water deficit. Proteomic analysis revealed the down-regulation of proteins involved in electron transport and in carbon reduction reactions, and up-regulation of antioxidative enzymes. Our results demonstrate that developing seedlings under water deficit could downsize their light-harvesting capacity and components of photosynthetic apparatus to prevent photo-oxidative stress, excess ROS generation and membrane lipid peroxidation.

Accurate Digitization of the Chlorophyll Distribution of Individual Rice Leaves Using Hyperspectral Imaging and an Integrated Image Analysis Pipeline

Pigments absorb light, transform it into energy, and provide reaction sites for photosynthesis; thus, the quantification of pigment distribution is vital to plant research. Traditional methods for the quantification of pigments are time-consuming and not suitable for the high-throughput digitization of rice pigment distribution. In this study, using a hyperspectral imaging system, we developed an integrated image analysis pipeline for automatically processing enormous amounts of hyperspectral data. We also built models for accurately quantifying 4 pigments (chlorophyll a, chlorophyll b, total chlorophyll and carotenoid) from rice leaves and determined the important bands (700-760 nm) associated with these pigments. At the tillering stage, the R2 values and mean absolute percentage errors of the models were 0.827-0.928 and 6.94-12.84%, respectively. The hyperspectral data and these models can be combined for digitizing the distribution of the chlorophyll with high resolution (0.11 mm/pixel). In summary, the integrated hyperspectral image analysis pipeline and selected models can be used to quantify the chlorophyll distribution in rice leaves. The use of this technique will benefit rice functional genomics and rice breeding.

An integrated hyperspectral imaging and genome-wide association analysis platform provides spectral and genetic insights into the natural variation in rice

With progress of genetic sequencing technology, plant genomics has experienced rapid development and subsequently triggered the progress of plant phenomics. In this study, a high-throughput hyperspectral imaging system (HHIS) was developed to obtain 1,540 hyperspectral indices at whole-plant level during tillering, heading, and ripening stages. These indices were used to quantify traditional agronomic traits and to explore genetic variation. We performed genome-wide association study (GWAS) of these indices and traditional agronomic traits in a global rice collection of 529 accessions. With the genome-level suggestive P-value threshold, 989 loci were identified. Of the 1,540 indices, we detected 502 significant indices (designated as hyper-traits) that exhibited phenotypic and genetic relationship with traditional agronomic traits and had high heritability. Many hyper-trait-associated loci could not be detected using traditional agronomic traits. For example, we identified a candidate gene controlling chlorophyll content (Chl). This gene, which was not identified based on Chl, was significantly associated with a chlorophyll-related hyper-trait in GWAS and was demonstrated to control Chl. Moreover, our study demonstrates that red edge (680-760 nm) is vital for rice research for phenotypic and genetic insights. Thus, combination of HHIS and GWAS provides a novel platform for dissection of complex traits and for crop breeding.

Dynamic and rapid changes in the transcriptome and epigenome during germination and in developing rice (Oryza sativa) coleoptiles under anoxia and re-oxygenation

Detailed molecular profiling of Oryza sativa (rice) was carried out to uncover the features that are essential for germination and early seedling growth under anoxic conditions. Temporal analysis of the transcriptome and methylome from germination to young seedlings under aerobic and anaerobic conditions revealed 82% similarity in the transcriptome and no differences in the epigenome up to 24 h. Following germination, significant changes in the transcriptome and DNA methylation were observed between 4-day aerobically and anaerobically grown coleoptiles. A link between the epigenomic state and cell division versus cell elongation is suggested, as no differences in DNA methylation were observed between 24-h aerobically and anaerobically germinating embryos, when there is little cell division. After that, epigenetic changes appear to correlate with differences between cell elongation (anaerobic conditions) versus cell division (aerobic conditions) in the coleoptiles. Re-oxygenation of 3-day anaerobically grown seedlings resulted in rapid transcriptomic changes in DNA methylation in these coleoptiles. Unlike the transcriptome, changes in DNA methylation upon re-oxygenation did not reflect those seen in aerobic coleoptiles, but instead, reverted to a pattern similar to dry seeds. Reversion to the 'dry seed' state of DNA methylation upon re-oxygenation may act to 'reset the clock' for the rapid molecular changes and cell division that result upon re-oxygenation.

Global Transcriptome Analysis of Combined Abiotic Stress Signaling Genes Unravels Key Players in Oryza sativa L.: An In silico Approach

Combined abiotic stress (CAbS) affects the field grown plants simultaneously. The multigenic and quantitative nature of uncontrollable abiotic stresses complicates the process of understanding the stress response by plants. Considering this, we analyzed the CAbS response of C3 model plant, Oryza sativa by meta-analysis. The datasets of commonly expressed genes by drought, salinity, submergence, metal, natural expression, biotic, and abiotic stresses were data mined through publically accessible transcriptomic abiotic stress (AbS) responsive datasets. Of which 1,175, 12,821, and 42,877 genes were commonly expressed in meta differential, individual differential, and unchanged expressions respectively. Highly regulated 100 differentially expressed AbS genes were derived through integrative meta-analysis of expression data (INMEX). Of this 30 genes were identified from AbS gene families through expression atlas that were computationally analyzed for their physicochemical properties. All AbS genes were physically mapped against O. sativa genome. Comparative mapping of these genes demonstrated the orthologous relationship with related C4 panicoid genome. In silico expression analysis of these genes showed differential expression patterns in different developmental tissues. Protein-protein interaction of these genes, represented the complexity of AbS. Computational expression profiling of candidate genes in response to multiple stresses suggested the putative involvement of OS05G0350900, OS02G0612700, OS05G0104200, OS03G0596200, OS12G0225900, OS07G0152000, OS08G0119500, OS06G0594700, and Os01g0393100 in CAbS. These potential candidate genes need to be studied further to decipher their functional roles in AbS dynamics.

SUBA4: the interactive data analysis centre for Arabidopsis subcellular protein locations

The SUBcellular location database for Arabidopsis proteins (SUBA4, http://suba.live) is a comprehensive collection of manually curated published data sets of large-scale subcellular proteomics, fluorescent protein visualization, protein-protein interaction (PPI) as well as subcellular targeting calls from 22 prediction programs. SUBA4 contains an additional 35 568 localizations totalling more than 60 000 experimental protein location claims as well as 37 new suborganellar localization categories. The experimental PPI data has been expanded to 26 327 PPI pairs including 856 PPI localizations from experimental fluorescent visualizations. The new SUBA4 user interface enables users to choose quickly from the filter categories: ‘subcellular location’, ‘protein properties’, ‘protein–protein interaction’ and ‘affiliations’ to build complex queries. This allows substantial expansion of search parameters into 80 annotation types comprising 1 150 204 new annotations to study metadata associated with subcellular localization. The ‘BLAST’ tab contains a sequence alignment tool to enable a sequence fragment from any species to find the closest match in Arabidopsis and retrieve data on subcellular location. Using the location consensus SUBAcon, the SUBA4 toolbox delivers three novel data services allowing interactive analysis of user data to provide relative compartmental protein abundances and proximity relationship analysis of PPI and coexpression partners from a submitted list of Arabidopsis gene identifiers.

Reannotation of Yersinia pestis Strain 91001 Based on Omics Data

Yersinia pestis is among the most dangerous human pathogens, and systematic research of this pathogen is important in bacterial pathogenomics research. To fully interpret the biological functions, physiological characteristics, and pathogenesis of Y. pestis, a comprehensive annotation of its entire genome is necessary. The emergence of omics-based research has brought new opportunities to better annotate the genome of this pathogen. Here, the complete genome of Y. pestis strain 91001 was reannotated using genomics and proteogenomics data. One hundred and thirty-seven unreliable coding sequences were removed, and 41 homologous genes were relocated with their translational initiation sites, while the functions of seven pseudogenes and 392 hypothetical genes were revised. Moreover, annotations of noncoding RNAs, repeat sequences, and transposable elements have also been incorporated. The reannotated results are freely available at http://tody.bmi.ac.cn.

In vitro and in vivo protein uptake studies in plant mitochondria

The study of protein uptake into mitochondria is an important tool for investigating the subcellular distribution of proteins and the molecular mechanisms that determine location. Here we describe five techniques that allow the quantitative or qualitative monitoring of protein uptake into mitochondria using both in vitro and in vivo approaches.

Databases and informatics resources for analysis of plant mitochondria

As more omics data is generated from various plant species, it is becoming increasingly possible to carry out a range of in silico analyses to gain insight into mitochondrial function in plants. From the use of software tools for DNA motif analyses and transcript expression visualization to proteomic and subcellular localization resources, it is possible to carry out significant in silico analyses that are highly informative to researchers and can help to guide experimental design for further mitochondrial study. Databases specific to plant mitochondrial analyses have been developed in recent years, revealing mitochondria-specific information. This chapter outlines the databases and informatics resources that are useful for plant mitochondrial studies, with specific examples presented to indicate how these resources can be used to gain insight into plant mitochondrial function(s).

Finding the Subcellular Location of Barley, Wheat, Rice and Maize Proteins: The Compendium of Crop Proteins with Annotated Locations (cropPAL)

Barley, wheat, rice and maize provide the bulk of human nutrition and have extensive industrial use as agricultural products. The genomes of these crops each contains >40,000 genes encoding proteins; however, the major genome databases for these species lack annotation information of protein subcellular location for >80% of these gene products. We address this gap, by constructing the compendium of crop protein subcellular locations called crop Proteins with Annotated Locations (cropPAL). Subcellular location is most commonly determined by fluorescent protein tagging of live cells or mass spectrometry detection in subcellular purifications, but can also be predicted from amino acid sequence or protein expression patterns. The cropPAL database collates 556 published studies, from >300 research institutes in >30 countries that have been previously published, as well as compiling eight pre-computed subcellular predictions for all Hordeum vulgare, Triticum aestivum, Oryza sativa and Zea mays protein sequences. The data collection including metadata for proteins and published studies can be accessed through a search portal http://crop-PAL.org. The subcellular localization information housed in cropPAL helps to depict plant cells as compartmentalized protein networks that can be investigated for improving crop yield and quality, and developing new biotechnological solutions to agricultural challenges.

Microarray Analysis of Rice d1 (RGA1) Mutant Reveals the Potential Role of G-Protein Alpha Subunit in Regulating Multiple Abiotic Stresses Such as Drought, Salinity, Heat, and Cold

The genome-wide role of heterotrimeric G-proteins in abiotic stress response in rice has not been examined from a functional genomics perspective, despite the availability of mutants and evidences involving individual genes/processes/stresses. Our rice whole transcriptome microarray analysis (GSE 20925 at NCBI GEO) using the G-alpha subunit (RGA1) null mutant (Daikoku 1 or d1) and its corresponding wild type (Oryza sativa Japonica Nipponbare) identified 2270 unique differentially expressed genes (DEGs). Out of them, we mined for all the potentially abiotic stress-responsive genes using Gene Ontology terms, STIFDB2.0 and Rice DB. The first two approaches produced smaller subsets of the 1886 genes found at Rice DB. The GO approach revealed similar regulation of several families of stress-responsive genes in RGA1 mutant. The Genevestigator analysis of the stress-responsive subset of the RGA1-regulated genes from STIFDB revealed cold and drought-responsive clusters. Meta data analysis at Rice DB revealed large stress-response categories such as cold (878 up/810 down), drought (882 up/837 down), heat (913 up/777 down), and salt stress (889 up/841 down). One thousand four hundred ninety-eight of them are common to all the four abiotic stresses, followed by fewer genes common to smaller groups of stresses. The RGA1-regulated genes that uniquely respond to individual stresses include 111 in heat stress, eight each in cold only and drought only stresses, and two genes in salt stress only. The common DEGs (1498) belong to pathways such as the synthesis of polyamine, glycine-betaine, proline, and trehalose. Some of the common DEGs belong to abiotic stress signaling pathways such as calcium-dependent pathway, ABA independent and dependent pathway, and MAP kinase pathway in the RGA1 mutant. Gene ontology of the common stress responsive DEGs revealed 62 unique molecular functions such as transporters, enzyme regulators, transferases, hydrolases, carbon and protein metabolism, binding to nucleotides, carbohydrates, receptors and lipids, morphogenesis, flower development, and cell homeostasis. We also mined 63 miRNAs that bind to the stress responsive transcripts identified in this study, indicating their post-transcriptional regulation. Overall, these results indicate the potentially extensive role of RGA1 in the regulation of multiple abiotic stresses in rice for further validation.

Elucidation of Complex Nature of PEG Induced Drought-Stress Response in Rice Root Using Comparative Proteomics Approach

Along with many adaptive strategies, dynamic changes in protein abundance seem to be the common strategy to cope up with abiotic stresses which can be best explored through proteomics. Understanding of drought response is the key to decipher regulatory mechanism of better adaptation. Rice (Oryza sativa L.) proteome represents a phenomenal source of proteins that govern traits of agronomic importance, such as drought tolerance. In this study, a comparison of root cytoplasmic proteome was done for a drought tolerant rice (Heena) cultivar in PEG induced drought conditions. A total of 510 protein spots were observed by PDQuest analysis and 125 differentially regulated spots were subjected for MALDI-TOF MS-MS analysis out of which 102 protein spots identified which further led to identification of 78 proteins with a significant score. These 78 differentially expressed proteins appeared to be involved in different biological pathways. The largest percentage of identified proteins was involved in bioenergy and metabolism (29%) and mainly consists of malate dehydrogenase, succinyl-CoA, putative acetyl-CoA synthetase, and pyruvate dehydrogenase etc. This was followed by proteins related to cell defense and rescue (22%) such as monodehydroascorbate reductase and stress-induced protein sti1, then by protein biogenesis and storage class (21%) e.g. putative thiamine biosynthesis protein, putative beta-alanine synthase, and cysteine synthase. Further, cell signaling (9%) proteins like actin and prolyl endopeptidase, and proteins with miscellaneous function (19%) like Sgt1 and some hypothetical proteins were also represented a large contribution toward drought regulatory mechanism in rice. We propose that protein biogenesis, cell defense, and superior homeostasis may render better drought-adaptation. These findings might expedite the functional determination of the drought-responsive proteins and their prioritization as potential molecular targets for perfect adaptation.

Transcriptional Basis of Drought-Induced Susceptibility to the Rice Blast Fungus Magnaporthe oryzae

Plants are often facing several stresses simultaneously. Understanding how they react and the way pathogens adapt to such combinational stresses is poorly documented. Here, we developed an experimental system mimicking field intermittent drought on rice followed by inoculation by the pathogenic fungus Magnaporthe oryzae. This experimental system triggers an enhancement of susceptibility that could be correlated with the dampening of several aspects of plant immunity, namely the oxidative burst and the transcription of several pathogenesis-related genes. Quite strikingly, the analysis of fungal transcription by RNASeq analysis under drought reveals that the fungus is greatly modifying its virulence program: genes coding for small secreted proteins were massively repressed in droughted plants compared to unstressed ones whereas genes coding for enzymes involved in degradation of cell-wall were induced. We also show that drought can lead to the partial breakdown of several major resistance genes by affecting R plant gene and/or pathogen effector expression. We propose a model where a yet unknown plant signal can trigger a change in the virulence program of the pathogen to adapt to a plant host that was affected by drought prior to infection.

Mechanisms of growth and patterns of gene expression in oxygen-deprived rice coleoptiles

Coleoptiles of rice (Oryza sativa) seedlings grown under water commonly elongate by up to 1 mm h(-1) to reach the atmosphere. We initially analysed this highly specialized phenomenon by measuring epidermal cell lengths along the coleoptile axis to determine elongation rates. This revealed a cohort of cells in the basal zone that elongated rapidly following emergence from the embryo, reaching 200 μm within 12 h. After filming coleoptiles in vivo for a day, kinematic analysis was applied. Eight time-sliced 'segments' were defined by their emergence from the embryo at four-hourly intervals, revealing a mathematically simple growth model. Each segment entering the coleoptile from the embryo elongated at a constant velocity, resulting in accelerating growth for the entire organ. Consistent with the epidermal cell lengths, relative rates of elongation (mm mm(-1) h(-1)) were tenfold greater in the small, newly emerged basal segments than the older distal tip segments. This steep axial gradient defined two contrasting growth zones (bases versus tips) in which we measured ATP production and protein, RNA and DNA content, and analysed the global transcriptome under steady-state normoxia, hypoxia (3% O2) and anoxia. Determination of the transcriptome revealed tip-specific induction of genes encoding TCP [Teosinte Branched1 (Tb1) of maize, Cycloidea (Cyc), and Proliferating Cell Factor (Pcf)] transcription factors, RNA helicases, ribosomal proteins and proteins involved in protein folding, whilst expression of F-box domain-containing proteins in the ubiquitin E3-SCF complex (Skp, Cullin, F-box containing complex) was induced specifically in bases under low oxygen conditions. We ascribed the sustained elongation under hypoxia to hypoxia-specific responses such as controlled suppression of photosystem components and induction of RNA binding/splicing functions, indicating preferential allocation of energy to cell extension.

LOTUS-DB: an integrative and interactive database for Nelumbo nucifera study

Besides its important significance in plant taxonomy and phylogeny, sacred lotus (Nelumbo nucifera Gaertn.) might also hold the key to the secrets of aging, which attracts crescent attentions from researchers all over the world. The genetic or molecular studies on this species depend on its genome information. In 2013, two publications reported the sequencing of its full genome, based on which we constructed a database named as LOTUS-DB. It will provide comprehensive information on the annotation, gene function and expression for the sacred lotus. The information will facilitate users to efficiently query and browse genes, graphically visualize genome and download a variety of complex data information on genome DNA, coding sequence (CDS), transcripts or peptide sequences, promoters and markers. It will accelerate researches on gene cloning, functional identification of sacred lotus, and hence promote the studies on this species and plant genomics as well. Database URL: http://lotus-db.wbgcas.cn

MPIC: a mitochondrial protein import components database for plant and non-plant species

In the 2 billion years since the endosymbiotic event that gave rise to mitochondria, variations in mitochondrial protein import have evolved across different species. With the genomes of an increasing number of plant species sequenced, it is possible to gain novel insights into mitochondrial protein import pathways. We have generated the Mitochondrial Protein Import Components (MPIC) Database (DB; http://www.plantenergy.uwa.edu.au/applications/mpic) providing searchable information on the protein import apparatus of plant and non-plant mitochondria. An in silico analysis was carried out, comparing the mitochondrial protein import apparatus from 24 species representing various lineages from Saccharomyces cerevisiae (yeast) and algae to Homo sapiens (human) and higher plants, including Arabidopsis thaliana (Arabidopsis), Oryza sativa (rice) and other more recently sequenced plant species. Each of these species was extensively searched and manually assembled for analysis in the MPIC DB. The database presents an interactive diagram in a user-friendly manner, allowing users to select their import component of interest. The MPIC DB presents an extensive resource facilitating detailed investigation of the mitochondrial protein import machinery and allowing patterns of conservation and divergence to be recognized that would otherwise have been missed. To demonstrate the usefulness of the MPIC DB, we present a comparative analysis of the mitochondrial protein import machinery in plants and non-plant species, revealing plant-specific features that have evolved.

Shredding the signal: targeting peptide degradation in mitochondria and chloroplasts

The biogenesis and functionality of mitochondria and chloroplasts depend on the constant turnover of their proteins. The majority of mitochondrial and chloroplastic proteins are imported as precursors via their N-terminal targeting peptides. After import, the targeting peptides are cleaved off and degraded. Recent work has elucidated a pathway involved in the degradation of targeting peptides in mitochondria and chloroplasts, with two proteolytic components: the presequence protease (PreP) and the organellar oligopeptidase (OOP). PreP and OOP are specialized in degrading peptides of different lengths, with the substrate restriction being dictated by the structure of their proteolytic cavities. The importance of the intraorganellar peptide degradation is highlighted by the fact that elimination of both oligopeptidases affects growth and development of Arabidopsis thaliana.

What happens to plant mitochondria under low oxygen? An omics review of the responses to low oxygen and reoxygenation

Floods can rapidly submerge plants, limiting oxygen to the extent that oxidative phosphorylation no longer generates adequate ATP supplies. Low-oxygen tolerant plants, such as rice, are able to adequately respond to low oxygen by successfully remodelling primary and mitochondrial metabolism to partially counteract the energy crisis that ensues. In this review, we discuss how plants respond to low-oxygen stress at the transcriptomic, proteomic, metabolomic and enzyme activity levels, particularly focusing on mitochondria and interacting pathways. The role of reactive oxygen species and nitrite as an alternative electron acceptor as well as their links to respiratory chain components is discussed. By making intra-kingdom as well as cross-kingdom comparisons, conserved mechanisms of anoxia tolerance are highlighted as well as tolerance mechanisms that are specific to anoxia-tolerant rice during germination and in coleoptiles. We discuss reoxygenation as an often overlooked, yet essential stage of this environmental stress and consider the possibility that changes occurring during low oxygen may also provide benefits upon re-aeration. Finally, we consider what it takes to be low-oxygen tolerant and argue that alternative mechanisms of ATP production, glucose signalling, starch/sucrose signalling as well as reverse metabolism of fermentation end products promote the survival of rice after this debilitating stress.

Spatio-temporal transcript profiling of rice roots and shoots in response to phosphate starvation and recovery

Using rice (Oryza sativa) as a model crop species, we performed an in-depth temporal transcriptome analysis, covering the early and late stages of Pi deprivation as well as Pi recovery in roots and shoots, using next-generation sequencing. Analyses of 126 paired-end RNA sequencing libraries, spanning nine time points, provided a comprehensive overview of the dynamic responses of rice to Pi stress. Differentially expressed genes were grouped into eight sets based on their responses to Pi starvation and recovery, enabling the complex signaling pathways involved in Pi homeostasis to be untangled. A reference annotation-based transcript assembly was also generated, identifying 438 unannotated loci that were differentially expressed under Pi starvation. Several genes also showed induction of unannotated splice isoforms under Pi starvation. Among these, PHOSPHATE2 (PHO2), a key regulator of Pi homeostasis, displayed a Pi starvation-induced isoform, which was associated with increased translation activity. In addition, microRNA (miRNA) expression profiles after long-term Pi starvation in roots and shoots were assessed, identifying 20 miRNA families that were not previously associated with Pi starvation, such as miR6250. In this article, we present a comprehensive spatio-temporal transcriptome analysis of plant responses to Pi stress, revealing a large number of potential key regulators of Pi homeostasis in plants.