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

Protein research in millets: current status and way forward

MAIN CONCLUSION

Millets' protein studies are lagging behind those of major cereals. Current status and future insights into the investigation of millet proteins are discussed. Millets are important small-seeded cereals majorly grown and consumed by people in Asia and Africa and are considered crops of future food security. Although millets possess excellent climate resilience and nutrient supplementation properties, their research advancements have been lagging behind major cereals. Although considerable genomic resources have been developed in recent years, research on millet proteins and proteomes is currently limited, highlighting a need for further investigation in this area. This review provides the current status of protein research in millets and provides insights to understand protein responses for climate resilience and nutrient supplementation in millets. The reference proteome data is available for sorghum, foxtail millet, and proso millet to date; other millets, such as pearl millet, finger millet, barnyard millet, kodo millet, tef, and browntop millet, do not have any reference proteome data. Many studies were reported on stress-responsive protein identification in foxtail millet, with most studies on the identification of proteins under drought-stress conditions. Pearl millet has a few reports on protein identification under drought and saline stress. Finger millet is the only other millet to have a report on stress-responsive (drought) protein identification in the leaf. For protein localization studies, foxtail millet has a few reports. Sorghum has the highest number of 40 experimentally proven crystal structures, and other millets have fewer or no experimentally proven structures. Further proteomics studies will help dissect the specific proteins involved in climate resilience and nutrient supplementation and aid in breeding better crops to conserve food security.

New insights into molecular features of the genome-wide AOX family and their responses to various stresses in common wheat (Triticum aestivum L.)

Alternative oxidase (AOX) is an important terminal oxidase involved in the alternative oxidation pathway in plants, which is closely related to various biotic and abiotic stress responses. However, a comprehensive research on AOX gene family of wheat is still lacking. In this study, the members of wheat AOX (TaAOX) family were identified, and their molecular characteristics and gene expression patterns were systematically investigated. Seventeen TaAOX genes were identified from Chinese Spring (CS) genome, which were mapped on 7 chromosomes and mainly clustered on the long arm's distal end of the second homologous groups. Phylogenetic analysis showed that TaAOX genes were classified into four subgroups (Ia, Ib, Ic, and Id), and the Ia subgroup possessed the most members. Tandem duplication and segmental duplication events were found during the evolution of TaAOX genes and they were affected by purifying selection demonstrated by Ka/Ks analysis. The exon numbers of this family gene varied greatly from 1 to 9. Except for Ta3BSAOX14, all the proteins encoded by the other 16 TaAOX genes contained the amino acid residues of the key active sites in the AOX domain (cd01053). The expression patterns of TaAOX genes in various tissues and under abiotic and biotic stresses were analyzed using public transcriptome data, furthermore, qRT-PCR analysis was performed for some selected TaAOX genes, and the results suggested that most members of this gene family play an important role in response to different stresses in common wheat. Our results provide basic information and valuable reference for further exploring the gene function of TaAOX family by using gene editing, RNAi, VIGS, and other technologies.

Nitrate-responsive transcriptome analysis of rice RGA1 mutant reveals the role of G-protein alpha subunit in negative regulation of nitrogen-sensitivity and use efficiency

KEY MESSAGE

Nitrate-responsive transcriptomic, phenotypic and physiological analyses of rice RGA1 mutant revealed many novel RGA1-regulated genes/processes/traits related to nitrogen use efficiency, and provided robust genetic evidence of RGA1-regulation of NUE. Nitrogen (N) use efficiency (NUE) is important for sustainable agriculture. G-protein signalling was implicated in N-response/NUE in rice, but needed firm genetic characterization of the role of alpha subunit (RGA1). The knock-out mutant of RGA1 in japonica rice exhibited lesser nitrate-dose sensitivity than the wild type (WT), in yield and NUE. We, therefore, investigated its genomewide nitrate-response relative to WT. It revealed 3416 differentially expressed genes (DEGs), including 719 associated with development, grain yield and phenotypic traits for NUE. The upregulated DEGs were related to photosynthesis, chlorophyll, tetrapyrrole and porphyrin biosynthesis, while the downregulated DEGs belonged to cellular protein metabolism and transport, small GTPase signalling, cell redox homeostasis, etc. We validated 26 nitrate-responsive DEGs across functional categories by RT-qPCR. Physiological validation of nitrate-response in the mutant and the WT at 1.5 and 15 mM doses revealed higher chlorophyll and stomatal length but decreased stomatal density, conductance and transpiration. The consequent increase in photosynthesis and water use efficiency may have contributed to better yield and NUE in the mutant, whereas the WT was N-dose sensitive. The mutant was not as N-dose-responsive as the WT in shoot/root growth, productive tillers and heading date, but equally responsive as WT in total N and protein content. The RGA1 mutant was less impacted by higher N-dose or salt stress in terms of yield, protein content, photosynthetic performance, relative water content, water use efficiency and catalase activity. PPI network analyses revealed known NUE-related proteins as RGA1 interactors. Therefore, RGA1 negatively regulates N-dose sensitivity and NUE in rice.

Coordinated regulation of the mitochondrial retrograde response by circadian clock regulators and ANAC017

Mitochondrial retrograde signaling (MRS) supports photosynthetic function under a variety of conditions. Induction of mitochondrial dysfunction with myxothiazol (a specific inhibitor of the mitochondrial bc₁ complex) or antimycin A (an inhibitor of the mitochondrial bc₁ complex and cyclic electron transport in the chloroplast under light conditions) in the light and dark revealed diurnal control of MRS. This was evidenced by (1) significantly enhanced binding of ANAC017 to promoters in the light compared with the dark in Arabidopsis plants treated with myxothiazol (but not antimycin A), (2) overlap in the experimentally determined binding sites for ANAC017 and circadian clock regulators in the promoters of ANAC013 and AOX1a, (3) a diurnal expression pattern for ANAC017 and transcription factors it regulates, (4) altered expression of ANAC017-regulated genes in circadian clock mutants with and without myxothiazol treatment, and (5) a decrease in the magnitude of LHY and CCA1 expression in an ANAC017-overexpressing line and protein-protein interaction between ANAC017 and PIF4. This study also shows a large difference in transcriptome responses to antimycin A and myxothiazol in the dark: these responses are ANAC017 independent, observed in shoots and roots, similar to biotic challenge and salicylic acid responses, and involve ERF and ZAT transcription factors. This suggests that antimycin A treatment stimulates a second MRS pathway that is mediated or converges with salicylic acid signaling and provides a merging point with chloroplast retrograde signaling.

Correlated retrograde and developmental regulons implicate multiple retrograde signals as coordinators of chloroplast development in maize

Signals emanating from chloroplasts influence nuclear gene expression, but roles of retrograde signals during chloroplast development are unclear. To address this gap, we analyzed transcriptomes of non-photosynthetic maize mutants and compared them to transcriptomes of stages of normal leaf development. The transcriptomes of two albino mutants lacking plastid ribosomes resembled transcriptomes at very early stages of normal leaf development, whereas the transcriptomes of two chlorotic mutants with thylakoid targeting or plastid transcription defects resembled those at a slightly later stage. We identified ∼2,700 differentially expressed genes, which fall into six major categories based on the polarity and mutant-specificity of the change. Downregulated genes were generally expressed late in normal development and were enriched in photosynthesis genes, whereas upregulated genes act early and were enriched for functions in chloroplast biogenesis and cytosolic translation. We showed further that target-of-rapamycin (TOR) signaling was elevated in mutants lacking plastid ribosomes and declined in concert with plastid ribosome buildup during normal leaf development. Our results implicate three plastid signals as coordinators of photosynthetic differentiation. One signal requires plastid ribosomes and activates photosynthesis genes. A second signal reflects attainment of chloroplast maturity and represses chloroplast biogenesis genes. A third signal, the consumption of nutrients by developing chloroplasts, represses TOR, promoting termination of cell proliferation during leaf development.

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?

Protein turnover in the developing Triticum aestivum grain

Protein abundance in cereal grains is determined by the relative rates of protein synthesis and protein degradation during grain development but quantitation of these rates is lacking. Through combining in vivo stable isotope labelling and in-depth quantitative proteomics, we have measured the turnover of 1400 different types of proteins during wheat grain development. We demonstrate that there is a spatiotemporal pattern to protein turnover rates which explain part of the variation in protein abundances that is not attributable to differences in wheat gene expression. We show that c. 20% of total grain adenosine triphosphate (ATP) production is used for grain proteome biogenesis and maintenance, and nearly half of this budget is invested exclusively in storage protein synthesis. We calculate that 25% of newly synthesized storage proteins are turned over during grain development rather than stored. This approach to measure protein turnover rates at proteome scale reveals how different functional categories of grain proteins accumulate, calculates the costs of protein turnover during wheat grain development and identifies the most and the least stable proteins in the developing wheat grain.

Nitrate-responsive transcriptome analysis reveals additional genes/processes and associated traits viz. height, tillering, heading date, stomatal density and yield in japonica rice

Our transcriptomic analysis expanded the repertoire of nitrate-responsive genes/processes in rice and revealed their phenotypic association with root/shoot, stomata, tiller, panicle/flowering and yield, with agronomic implications for nitrogen use efficiency. Nitrogen use efficiency (NUE) is a multigenic quantitative trait, involving many N-responsive genes/processes that are yet to be fully characterized. Microarray analysis of early nitrate response in excised leaves of japonica rice revealed 6688 differentially expressed genes (DEGs), including 2640 hitherto unreported across multiple functional categories. They include transporters, enzymes involved in primary/secondary metabolism, transcription factors (TFs), EF-hand containing calcium binding proteins, hormone metabolism/signaling and methytransferases. Some DEGs belonged to hitherto unreported processes viz. alcohol, lipid and trehalose metabolism, mitochondrial membrane organization, protein targeting and stomatal opening. 1158 DEGs were associated with growth physiology and grain yield or phenotypic traits for NUE. We identified seven DEGs for shoot apical meristem, 66 for leaf/culm/root, 31 for tiller, 70 for heading date/inflorescence/spikelet/panicle, 144 for seed and 78 for yield. RT-qPCR validated nitrate regulation of 31 DEGs belonging to various important functional categories/traits. Physiological validation of N-dose responsive changes in plant development revealed that relative to 1.5 mM, 15 mM nitrate significantly increased stomatal density, stomatal conductance and transpiration rate. Further, root/shoot growth, number of tillers and grain yield declined and panicle emergence/heading date delayed, despite increased photosynthetic rate. We report the binding sites of diverse classes of TFs such as WRKY, MYB, HMG etc., in the 1 kb up-stream regions of 6676 nitrate-responsive DEGs indicating their role in regulating nitrate response/NUE. Together, these findings expand the repertoire of genes and processes involved in genomewide nitrate response in rice and reveal their physiological, phenotypic and agronomic implications for NUE.

Plant Reactome and PubChem: The Plant Pathway and (Bio)Chemical Entity Knowledgebases

Plant Reactome (https://plantreactome.gramene.org) and PubChem ( https://pubchem.ncbi.nlm.nih.gov ) are two reference data portals and resources for curated plant pathways, small molecules, metabolites, gene products, and macromolecular interactions. Plant Reactome knowledgebase, a conceptual plant pathway network, is built by biocuration and integrating (bio)chemical entities, gene products, and macromolecular interactions. It provides manually curated pathways for the reference species Oryza sativa (rice) and gene orthology-based projections that extend pathway knowledge to 106 plant species. Currently, it hosts 320 reference pathways for plant metabolism, hormone signaling, transport, genetic regulation, plant organ development and differentiation, and biotic and abiotic stress responses. In addition to the pathway browsing and search functions, the Plant Reactome provides the analysis tools for pathway comparison between reference and projected species, pathway enrichment in gene expression data, and overlay of gene-gene interaction data on pathways. PubChem, a popular reference database of (bio)chemical entities, provides information on small molecules and other types of chemical entities, such as siRNAs, miRNAs, lipids, carbohydrates, and chemically modified nucleotides. The data in PubChem is collected from hundreds of data sources, including Plant Reactome. This chapter provides a brief overview of the Plant Reactome and the PubChem knowledgebases, their association to other public resources providing accessory information, and how users can readily access the contents.

A hybrid kinetic and constraint-based model of leaf metabolism allows predictions of metabolic fluxes in different environments

While flux balance analysis (FBA) provides a framework for predicting steady-state leaf metabolic network fluxes, it does not readily capture the response to environmental variables without being coupled to other modelling formulations. To address this, we coupled an FBA model of 903 reactions of soybean (Glycine max) leaf metabolism with e-photosynthesis, a dynamic model that captures the kinetics of 126 reactions of photosynthesis and associated chloroplast carbon metabolism. Successful coupling was achieved in an iterative formulation in which fluxes from e-photosynthesis were used to constrain the FBA model and then, in turn, fluxes computed from the FBA model used to update parameters in e-photosynthesis. This process was repeated until common fluxes in the two models converged. Coupling did not hamper the ability of the kinetic module to accurately predict the carbon assimilation rate, photosystem II electron flux, and starch accumulation of field-grown soybean at two CO2 concentrations. The coupled model also allowed accurate predictions of additional parameters such as nocturnal respiration, as well as analysis of the effect of light intensity and elevated CO2 on leaf metabolism. Predictions included an unexpected decrease in the rate of export of sucrose from the leaf at high light, due to altered starch-sucrose partitioning, and altered daytime flux modes in the tricarboxylic acid cycle at elevated CO2 . Mitochondrial fluxes were notably different between growing and mature leaves, with greater anaplerotic, tricarboxylic acid cycle and mitochondrial ATP synthase fluxes predicted in the former, primarily to provide carbon skeletons and energy for protein synthesis.

Identification of plant vacuole proteins by exploiting deep representation learning features

Plant vacuoles are the most important organelles for plant growth, development, and defense, and they play an important role in many types of stress responses. An important function of vacuole proteins is the transport of various classes of amino acids, ions, sugars, and other molecules. Accurate identification of vacuole proteins is crucial for revealing their biological functions. Several automatic and rapid computational tools have been proposed for the subcellular localization of proteins. Regrettably, they are not specific for the identification of plant vacuole proteins. To the best of our knowledge, there is only one computational software specifically trained for plant vacuolar proteins. Although its accuracy is acceptable, the prediction performance and stability of this method in practical applications can still be improved. Hence, in this study, a new predictor named iPVP-DRLF was developed to identify plant vacuole proteins specifically and effectively. This prediction software is designed using the light gradient boosting machine (LGBM) algorithm and hybrid features composed of classic sequence features and deep representation learning features. iPVP-DRLF achieved fivefold cross-validation and independent test accuracy values of 88.25 % and 87.16 %, respectively, both outperforming previous state-of-the-art predictors. Moreover, the blind dataset test results also showed that the performance of iPVP-DRLF was significantly better than the existing tools. The results of comparative experiments confirmed that deep representation learning features have an advantage over other classic sequence features in the identification of plant vacuole proteins. We believe that iPVP-DRLF would serve as an effective computational technique for plant vacuole protein prediction and facilitate related future research. The online server is freely accessible at https://lab.malab.cn/~acy/iPVP-DRLF. In addition, the source code and datasets are also accessible at https://github.com/jiaoshihu/iPVP-DRLF.

Comparative Transcriptomic Analyses of Nitrate-Response in Rice Genotypes With Contrasting Nitrogen Use Efficiency Reveals Common and Genotype-Specific Processes, Molecular Targets and Nitrogen Use Efficiency-Candidates

The genetic basis for nitrogen (N)-response and N use efficiency (NUE) must be found in N-responsive gene expression or protein regulation. Our transcriptomic analysis of nitrate response in two contrasting rice genotypes of Oryza sativa ssp. Indica (Nidhi with low NUE and Panvel1 with high NUE) revealed the processes/functions underlying differential N-response/NUE. The microarray analysis of low nitrate response (1.5 mM) relative to normal nitrate control (15 mM) used potted 21-days old whole plants. It revealed 1,327 differentially expressed genes (DEGs) exclusive to Nidhi and 666 exclusive to Panvel1, apart from 70 common DEGs, of which 10 were either oppositely expressed or regulated to different extents. Gene ontology analyses revealed that photosynthetic processes were among the very few processes common to both the genotypes in low N response. Those unique to Nidhi include cell division, nitrogen utilization, cytoskeleton, etc. in low N-response, whereas those unique to Panvel1 include signal transduction, protein import into the nucleus, and mitochondria. This trend of a few common but mostly unique categories was also true for transporters, transcription factors, microRNAs, and post-translational modifications, indicating their differential involvement in Nidhi and Panvel1. Protein-protein interaction networks constructed using DEG-associated experimentally validated interactors revealed subnetworks involved in cytoskeleton organization, cell wall, etc. in Nidhi, whereas in Panvel1, it was chloroplast development. NUE genes were identified by selecting yield-related genes from N-responsive DEGs and their co-localization on NUE-QTLs revealed the differential distribution of NUE-genes between genotypes but on the same chromosomes 1 and 3. Such hotspots are important for NUE breeders.

The Divergent Roles of the Rice bcl-2 Associated Athanogene (BAG) Genes in Plant Development and Environmental Responses

Bcl-2-associated athanogene (BAG), a group of proteins evolutionarily conserved and functioned as co-chaperones in plants and animals, is involved in various cell activities and diverse physiological processes. However, the biological functions of this gene family in rice are largely unknown. In this study, we identified a total of six BAG members in rice. These genes were classified into two groups, OsBAG1, -2, -3, and -4 are in group I with a conserved ubiquitin-like structure and OsBAG5 and -6 are in group Ⅱ with a calmodulin-binding domain, in addition to a common BAG domain. The BAG genes exhibited diverse expression patterns, with OsBAG4 showing the highest expression level, followed by OsBAG1 and OsBAG3, and OsBAG6 preferentially expressed in the panicle, endosperm, and calli. The co-expression analysis and the hierarchical cluster analysis indicated that the OsBAG1 and OsBAG3 were co-expressed with primary cell wall-biosynthesizing genes, OsBAG4 was co-expressed with phytohormone and transcriptional factors, and OsBAG6 was co-expressed with disease and shock-associated genes. β-glucuronidase (GUS) staining further indicated that OsBAG3 is mainly involved in primary young tissues under both primary and secondary growth. In addition, the expression of the BAG genes under brown planthopper (BPH) feeding, N, P, and K deficiency, heat, drought and plant hormones treatments was investigated. Our results clearly showed that OsBAGs are multifunctional molecules as inferred by their protein structures, subcellular localizations, and expression profiles. BAGs in group I are mainly involved in plant development, whereas BAGs in group II are reactive in gene regulations and stress responses. Our results provide a solid basis for the further elucidation of the biological functions of plant BAG genes.

Sorghum's Whole-Plant Transcriptome and Proteome Responses to Drought Stress: A Review

Sorghum is a cereal crop with key agronomic traits of drought and heat stress tolerance, making it an ideal food and industrial commodity for hotter and more arid climates. These stress tolerances also present a useful scientific resource for studying the molecular basis for environmental resilience. Here we provide an extensive review of current transcriptome and proteome works conducted with laboratory, greenhouse, or field-grown sorghum plants exposed to drought, osmotic stress, or treated with the drought stress-regulatory phytohormone, abscisic acid. Large datasets from these studies reveal changes in gene/protein expression across diverse signaling and metabolic pathways. Together, the emerging patterns from these datasets reveal that the overall functional classes of stress-responsive genes/proteins within sorghum are similar to those observed in equivalent studies of other drought-sensitive model species. This highlights a monumental challenge of distinguishing key regulatory genes/proteins, with a primary role in sorghum adaptation to drought, from genes/proteins that change in expression because of stress. Finally, we discuss possible options for taking the research forward. Successful exploitation of sorghum research for implementation in other crops may be critical in establishing climate-resilient agriculture for future food security.

Identifying protein subcellular localisation in scientific literature using bidirectional deep recurrent neural network

The increased diversity and scale of published biological data has to led to a growing appreciation for the applications of machine learning and statistical methodologies to gain new insights. Key to achieving this aim is solving the Relationship Extraction problem which specifies the semantic interaction between two or more biological entities in a published study. Here, we employed two deep neural network natural language processing (NLP) methods, namely: the continuous bag of words (CBOW), and the bi-directional long short-term memory (bi-LSTM). These methods were employed to predict relations between entities that describe protein subcellular localisation in plants. We applied our system to 1700 published Arabidopsis protein subcellular studies from the SUBA manually curated dataset. The system combines pre-processing of full-text articles in a machine-readable format with relevant sentence extraction for downstream NLP analysis. Using the SUBA corpus, the neural network classifier predicted interactions between protein name, subcellular localisation and experimental methodology with an average precision, recall rate, accuracy and F1 scores of 95.1%, 82.8%, 89.3% and 88.4% respectively (n = 30). Comparable scoring metrics were obtained using the CropPAL database as an independent testing dataset that stores protein subcellular localisation in crop species, demonstrating wide applicability of prediction model. We provide a framework for extracting protein functional features from unstructured text in the literature with high accuracy, improving data dissemination and unlocking the potential of big data text analytics for generating new hypotheses.

Meta-Analysis of Yield-Related and N-Responsive Genes Reveals Chromosomal Hotspots, Key Processes and Candidate Genes for Nitrogen-Use Efficiency in Rice

Nitrogen-use efficiency (NUE) is a function of N-response and yield that is controlled by many genes and phenotypic parameters that are poorly characterized. This study compiled all known yield-related genes in rice and mined them from the N-responsive microarray data to find 1,064 NUE-related genes. Many of them are novel genes hitherto unreported as related to NUE, including 80 transporters, 235 transcription factors (TFs), 44 MicroRNAs (miRNAs), 91 kinases, and 8 phosphatases. They were further shortlisted to 62 NUE-candidate genes following hierarchical methods, including quantitative trait locus (QTL) co-localization, functional evaluation in the literature, and protein-protein interactions (PPIs). They were localized to chromosomes 1, 3, 5, and 9, of which chromosome 1 with 26 genes emerged as a hotspot for NUE spanning 81% of the chromosomes. Further, co-localization of the NUE genes on NUE-QTLs resolved differences in the earlier studies that relied mainly on N-responsive genes regardless of their role in yield. Functional annotations and PPIs for all the 1,064 NUE-related genes and also the shortlisted 62 candidates revealed transcription, redox, phosphorylation, transport, development, metabolism, photosynthesis, water deprivation, and hormonal and stomatal function among the prominent processes. In silico expression analysis confirmed differential expression of the 62 NUE-candidate genes in a tissue/stage-specific manner. Experimental validation in two contrasting genotypes revealed that high NUE rice shows better photosynthetic performance, transpiration efficiency and internal water-use efficiency in comparison to low NUE rice. Feature Selection Analysis independently identified one-third of the common genes at every stage of hierarchical shortlisting, offering 6 priority targets to validate for improving the crop NUE.

Arabidopsis antibody resources for functional studies in plants

Here we report creation of a unique and a very valuable resource for Plant Scientific community worldwide. In this era of post-genomics and modelling of multi-cellular systems using an integrative systems biology approach, better understanding of protein localization at sub-cellular, cellular and tissue levels is likely to result in better understanding of their function and role in cell and tissue dynamics, protein–protein interactions and protein regulatory networks. We have raised 94 antibodies against key Arabidopsis root proteins, using either small peptides or recombinant proteins. The success rate with the peptide antibodies was very low. We show that affinity purification of antibodies massively improved the detection rate. Of 70 protein antibodies, 38 (55%) antibodies could detect a signal with high confidence and 22 of these antibodies are of immunocytochemistry grade. The targets include key proteins involved in hormone synthesis, transport and perception, membrane trafficking related proteins and several sub cellular marker proteins. These antibodies are available from the Nottingham Arabidopsis Stock Centre.

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.

Conserved and Opposite Transcriptome Patterns during Germination in Hordeum vulgare and Arabidopsis thaliana

Seed germination is a critical process for completion of the plant life cycle and for global food production. Comparing the germination transcriptomes of barley (Hordeum vulgare) to Arabidopsis thaliana revealed the overall pattern was conserved in terms of functional gene ontology; however, many oppositely responsive orthologous genes were identified. Conserved processes included a set of approximately 6000 genes that peaked early in germination and were enriched in processes associated with RNA metabolism, e.g., pentatricopeptide repeat (PPR)-containing proteins. Comparison of orthologous genes revealed more than 3000 orthogroups containing almost 4000 genes that displayed similar expression patterns including functions associated with mitochondrial tricarboxylic acid (TCA) cycle, carbohydrate and RNA/DNA metabolism, autophagy, protein modifications, and organellar function. Biochemical and proteomic analyses indicated mitochondrial biogenesis occurred early in germination, but detailed analyses revealed the timing involved in mitochondrial biogenesis may vary between species. More than 1800 orthogroups representing 2000 genes displayed opposite patterns in transcript abundance, representing functions of energy (carbohydrate) metabolism, photosynthesis, protein synthesis and degradation, and gene regulation. Differences in expression of basic-leucine zippers (bZIPs) and Apetala 2 (AP2)/ethylene-responsive element binding proteins (EREBPs) point to differences in regulatory processes at a high level, which provide opportunities to modify processes in order to enhance grain quality, germination, and storage as needed for different uses.

Plastid transit peptides-where do they come from and where do they all belong? Multi-genome and pan-genomic assessment of chloroplast transit peptide evolution

Subcellular relocalization of proteins determines an organism's metabolic repertoire and thereby its survival in unique evolutionary niches. In plants, the plastid and its various morphotypes import a large and varied number of nuclear-encoded proteins to orchestrate vital biochemical reactions in a spatiotemporal context. Recent comparative genomics analysis and high-throughput shotgun proteomics data indicate that there are a large number of plastid-targeted proteins that are either semi-conserved or non-conserved across different lineages. This implies that homologs are differentially targeted across different species, which is feasible only if proteins have gained or lost plastid targeting peptides during evolution. In this study, a broad, multi-genome analysis of 15 phylogenetically diverse genera and in-depth analyses of pangenomes from Arabidopsis and Brachypodium were performed to address the question of how proteins acquire or lose plastid targeting peptides. The analysis revealed that random insertions or deletions were the dominant mechanism by which novel transit peptides are gained by proteins. While gene duplication was not a strict requirement for the acquisition of novel subcellular targeting, 40% of novel plastid-targeted genes were found to be most closely related to a sequence within the same genome, and of these, 30.5% resulted from alternative transcription or translation initiation sites. Interestingly, analysis of the distribution of amino acids in the transit peptides of known and predicted chloroplast-targeted proteins revealed monocot and eudicot-specific preferences in residue distribution.

Genome-Scale Characterization of Predicted Plastid-Targeted Proteomes in Higher Plants

Plastids are morphologically and functionally diverse organelles that are dependent on nuclear-encoded, plastid-targeted proteins for all biochemical and regulatory functions. However, how plastid proteomes vary temporally, spatially, and taxonomically has been historically difficult to analyze at a genome-wide scale using experimental methods. A bioinformatics workflow was developed and evaluated using a combination of fast and user-friendly subcellular prediction programs to maximize performance and accuracy for chloroplast transit peptides and demonstrate this technique on the predicted proteomes of 15 sequenced plant genomes. Gene family grouping was then performed in parallel using modified approaches of reciprocal best BLAST hits (RBH) and UCLUST. A total of 628 protein families were found to have conserved plastid targeting across angiosperm species using RBH, and 828 using UCLUST. However, thousands of clusters were also detected where only one species had predicted plastid targeting, most notably in Panicum virgatum which had 1,458 proteins with species-unique targeting. An average of 45% overlap was found in plastid-targeted protein-coding gene families compared with Arabidopsis, but an additional 20% of proteins matched against the full Arabidopsis proteome, indicating a unique evolution of plastid targeting. Neofunctionalization through subcellular relocalization is known to impart novel biological functions but has not been described before on a genome-wide scale for the plastid proteome. Further work to correlate these predicted novel plastid-targeted proteins to transcript abundance and high-throughput proteomics will uncover unique aspects of plastid biology and shed light on how the plastid proteome has evolved to influence plastid morphology and biochemistry.

Plant Reactome: a knowledgebase and resource for comparative pathway analysis

Plant Reactome (https://plantreactome.gramene.org) is an open-source, comparative plant pathway knowledgebase of the Gramene project. It uses Oryza sativa (rice) as a reference species for manual curation of pathways and extends pathway knowledge to another 82 plant species via gene-orthology projection using the Reactome data model and framework. It currently hosts 298 reference pathways, including metabolic and transport pathways, transcriptional networks, hormone signaling pathways, and plant developmental processes. In addition to browsing plant pathways, users can upload and analyze their omics data, such as the gene-expression data, and overlay curated or experimental gene-gene interaction data to extend pathway knowledge. The curation team actively engages researchers and students on gene and pathway curation by offering workshops and online tutorials. The Plant Reactome supports, implements and collaborates with the wider community to make data and tools related to genes, genomes, and pathways Findable, Accessible, Interoperable and Re-usable (FAIR).

Magnitude of modulation of gene expression in aneuploid maize depends on the extent of genomic imbalance

Aneuploidy has profound effects on an organism, typically more so than polyploidy, and the basis of this contrast is not fully understood. A dosage series of the maize long arm of chromosome 1 (1L) was used to compare relative global gene expression in different types and degrees of aneuploidy to gain insights into how the magnitude of genomic imbalance as well as hypoploidy affects global gene expression. While previously available methods require a selective examination of specific genes, RNA sequencing provides a whole-genome view of gene expression in aneuploids. Most studies of global aneuploidy effects have concentrated on individual types of aneuploids because multiple dose aneuploidies of the same genomic region are difficult to produce in most model genetic organisms. The genetic toolkit of maize allows the examination of multiple ploidies and 1-4 doses of chromosome arms. Thus, a detailed examination of expression changes both on the varied chromosome arms and elsewhere in the genome is possible, in both hypoploids and hyperploids, compared with euploid controls. Previous studies observed the inverse trans effect, in which genes not varied in DNA dosage were expressed in a negative relationship to the varied chromosomal region. This response was also the major type of changes found globally in this study. Many genes varied in dosage showed proportional expression changes, though some were seen to be partly or fully dosage compensated. It was also found that the effects of aneuploidy were progressive, with more severe aneuploids producing effects of greater magnitude.

Barley Root Proteome and Metabolome in Response to Cytokinin and Abiotic Stimuli

Cytokinin is a phytohormone involved in the regulation of diverse developmental and physiological processes in plants. Its potential in biotechnology and for development of higher-yield and more resilient plants has been recognized, yet the molecular mechanisms behind its action are far from understood. In this report, the roots of barley seedlings were explored as a new source to reveal as yet unknown cytokinin-responsive proteins for crop improvement. Here we found significant differences reproducibly observed for 178 proteins, for which some of the revealed cytokinin-responsive pathways were confirmed in metabolome analysis, including alterations phenylpropanoid pathway, amino acid biosynthesis and ROS metabolism. Bioinformatics analysis indicated a significant overlap between cytokinin response and response to abiotic stress. This was confirmed by comparing proteome and metabolome profiles in response to drought, salinity or a period of temperature stress. The results illustrate complex abiotic stress response in the early development of model crop plant and confirm an extensive crosstalk between plant hormone cytokinin and response to temperature stimuli, water availability or salinity stress.

Roles of membrane transporters: connecting the dots from sequence to phenotype

BACKGROUND

Plant membrane transporters are involved in diverse cellular processes underpinning plant physiology, such as nutrient acquisition, hormone movement, resource allocation, exclusion or sequestration of various solutes from cells and tissues, and environmental and developmental signalling. A comprehensive characterization of transporter function is therefore key to understanding and improving plant performance.

SCOPE AND CONCLUSIONS

In this review, we focus on the complexities involved in characterizing transporter function and the impact that this has on current genomic annotations. Specific examples are provided that demonstrate why sequence homology alone cannot be relied upon to annotate and classify transporter function, and to show how even single amino acid residue variations can influence transporter activity and specificity. Misleading nomenclature of transporters is often a source of confusion in transporter characterization, especially for people new to or outside the field. Here, to aid researchers dealing with interpretation of large data sets that include transporter proteins, we provide examples of transporters that have been assigned names that misrepresent their cellular functions. Finally, we discuss the challenges in connecting transporter function at the molecular level with physiological data, and propose a solution through the creation of new databases. Further fundamental in-depth research on specific transport (and other) proteins is still required; without it, significant deficiencies in large-scale data sets and systems biology approaches will persist. Reliable characterization of transporter function requires integration of data at multiple levels, from amino acid residue sequence annotation to more in-depth biochemical, structural and physiological studies.

Cytonuclear Coevolution following Homoploid Hybrid Speciation in Aegilops tauschii

The diploid D-genome lineage of the Triticum/Aegilops complex has an evolutionary history involving genomic contributions from ancient A- and B/S-genome species. We explored here the possible cytonuclear evolutionary responses to this history of hybridization. Phylogenetic analysis of chloroplast DNAs indicates that the D-genome lineage has a maternal origin of the A-genome or some other closely allied lineage. Analyses of the nuclear genome in the D-genome species Aegilops tauschii indicate that accompanying and/or following this ancient hybridization, there has been biased maintenance of maternal A-genome ancestry in nuclear genes encoding cytonuclear enzyme complexes (CECs). Our study provides insights into mechanisms of cytonuclear coevolution accompanying the evolution and eventual stabilization of homoploid hybrid species. We suggest that this coevolutionary process includes likely rapid fixation of A-genome CEC orthologs as well as biased retention of A-genome nucleotides in CEC homologs following population level recombination during the initial generations.

Stress responsive mitochondrial proteins in Arabidopsis thaliana

In the last decade plant mitochondria have emerged as a target, sensor and initiator of signalling cascades to a variety of stress and adverse growth conditions. A combination of various 'omic profiling approaches combined with forward and reverse genetic studies have defined how mitochondria respond to stress and the signalling pathways and regulators of these responses. Reactive oxygen species (ROS)-dependent and -independent pathways, specific metabolites, complex I dysfunction, and the mitochondrial unfolded protein response (UPR) pathway have been proposed to date. These pathways are regulated by kinases (sucrose non-fermenting response like kinase; cyclin dependent protein kinase E 1) and transcription factors from the abscisic acid-related, WRKY and NAC families. A number of independent studies have revealed that these mitochondrial signalling pathways interact with a variety of phytohormone signalling pathways. While this represents significant progress in the last decade there are more pathways to be uncovered. Post-transcriptional/translational regulation is also a likely determinant of the mitochondrial stress response. Unbiased analyses of the expression of genes encoding mitochondrial proteins in a variety of stress conditions reveal a modular network exerting a high degree of anterograde control. As abiotic and biotic stresses have significant impact on the yield of important crops such as rice, wheat and barley we will give an outlook of how knowledge gained in Arabidopsis may help to increase crop production and how emerging technologies may contribute.

Molecular analysis of anthocyanin biosynthesis pathway genes and their differential expression in mango peel

Mango fruit is cherished by masses for its taste and nutrition, contributed by color, flavor, and aroma. Among these, peel color is an important trait contributing to fruit quality and market value. We attempted to elucidate the role of key genes of the anthocyanin biosynthesis pathway related to fruit peel color from the leaf transcriptome of mango cultivar Amrapali. A total of 108 mined transcript sequences were assigned to the phenylpropanoid-flavonoid pathway from which 15 contigs representing anthocyanin biosynthesis genes were annotated. Alternate splice variants were identified by mapping against genes of Citrus clementina and Vitis vinifera (closest relatives) and protein subcellular localization was determined. Phylogenetic analysis of these pathway genes clustered them into distinct groups aligning with homologous genes of Magnifera indica, C. clementina, and V. vinifera. Expression profiling revealed higher relative fold expressions in mature fruit peel of red-colored varieties (Arunika, Ambika, and Tommy Atkins) in comparison with the green-peeled Amrapali. MiCHS, MiCHI, and MiF3H alternate splice variants revealed differential gene expression. Functionally divergent variants indicate availability of an allelic pool programmed to play critical roles in peel color. This study provides insight into the molecular genetic basis of peel color and offers scope for development of biomarkers in varietal improvement programs.

MU-LOC: A Machine-Learning Method for Predicting Mitochondrially Localized Proteins in Plants

Targeting and translocation of proteins to the appropriate subcellular compartments are crucial for cell organization and function. Newly synthesized proteins are transported to mitochondria with the assistance of complex targeting sequences containing either an N-terminal pre-sequence or a multitude of internal signals. Compared with experimental approaches, computational predictions provide an efficient way to infer subcellular localization of a protein. However, it is still challenging to predict plant mitochondrially localized proteins accurately due to various limitations. Consequently, the performance of current tools can be improved with new data and new machine-learning methods. We present MU-LOC, a novel computational approach for large-scale prediction of plant mitochondrial proteins. We collected a comprehensive dataset of plant subcellular localization, extracted features including amino acid composition, protein position weight matrix, and gene co-expression information, and trained predictors using deep neural network and support vector machine. Benchmarked on two independent datasets, MU-LOC achieved substantial improvements over six state-of-the-art tools for plant mitochondrial targeting prediction. In addition, MU-LOC has the advantage of predicting plant mitochondrial proteins either possessing or lacking N-terminal pre-sequences. We applied MU-LOC to predict candidate mitochondrial proteins for the whole proteome of Arabidopsis and potato. MU-LOC is publicly available at http://mu-loc.org.

Multiple marker abundance profiling: combining selected reaction monitoring and data-dependent acquisition for rapid estimation of organelle abundance in subcellular samples

Measuring changes in protein or organelle abundance in the cell is an essential, but challenging aspect of cell biology. Frequently-used methods for determining organelle abundance typically rely on detection of a very few marker proteins, so are unsatisfactory. In silico estimates of protein abundances from publicly available protein spectra can provide useful standard abundance values but contain only data from tissue proteomes, and are not coupled to organelle localization data. A new protein abundance score, the normalized protein abundance scale (NPAS), expands on the number of scored proteins and the scoring accuracy of lower-abundance proteins in Arabidopsis. NPAS was combined with subcellular protein localization data, facilitating quantitative estimations of organelle abundance during routine experimental procedures. A suite of targeted proteomics markers for subcellular compartment markers was developed, enabling independent verification of in silico estimates for relative organelle abundance. Estimation of relative organelle abundance was found to be reproducible and consistent over a range of tissues and growth conditions. In silico abundance estimations and localization data have been combined into an online tool, multiple marker abundance profiling, available in the SUBA4 toolbox (http://suba.live).

LOCALIZER: subcellular localization prediction of both plant and effector proteins in the plant cell

Pathogens secrete effector proteins and many operate inside plant cells to enable infection. Some effectors have been found to enter subcellular compartments by mimicking host targeting sequences. Although many computational methods exist to predict plant protein subcellular localization, they perform poorly for effectors. We introduce LOCALIZER for predicting plant and effector protein localization to chloroplasts, mitochondria, and nuclei. LOCALIZER shows greater prediction accuracy for chloroplast and mitochondrial targeting compared to other methods for 652 plant proteins. For 107 eukaryotic effectors, LOCALIZER outperforms other methods and predicts a previously unrecognized chloroplast transit peptide for the ToxA effector, which we show translocates into tobacco chloroplasts. Secretome-wide predictions and confocal microscopy reveal that rust fungi might have evolved multiple effectors that target chloroplasts or nuclei. LOCALIZER is the first method for predicting effector localisation in plants and is a valuable tool for prioritizing effector candidates for functional investigations. LOCALIZER is available at http://localizer.csiro.au/.

Bioinformatics Analysis of Protein Secretion in Plants

In sessile plants, the dynamic protein secretion pathways orchestrate the cellular responses to internal signals and external environmental changes in almost every aspect of plant developmental events. The cohort of plant proteins, secreted from the plant cells into the extracellular matrix, has been annotated as plant secretome. Therefore, the identification and characterization of secreted proteins will discover novel secretory potentials and establish the functional connection between cellular protein secretion and plant physiological phenomena. Noteworthy, an increasing number of bioinformatics databases and tools have been developed for computational predictions on either secreted proteins or secretory pathways. This chapter summarizes current accessible databases and tools for protein secretion analysis in Arabidopsis thaliana and higher plants, and provides feasible methodologies for bioinformatics analysis of secretome studies for the plant research community.

A Proteomic View on the Role of Legume Symbiotic Interactions

Legume plants are key elements in sustainable agriculture and represent a significant source of plant-based protein for humans and animal feed worldwide. One specific feature of the family is the ability to establish nitrogen-fixing symbiosis with Rhizobium bacteria. Additionally, like most vascular flowering plants, legumes are able to form a mutualistic endosymbiosis with arbuscular mycorrhizal (AM) fungi. These beneficial associations can enhance the plant resistance to biotic and abiotic stresses. Understanding how symbiotic interactions influence and increase plant stress tolerance are relevant questions toward maintaining crop yield and food safety in the scope of climate change. Proteomics offers numerous tools for the identification of proteins involved in such responses, allowing the study of sub-cellular localization and turnover regulation, as well as the discovery of post-translational modifications (PTMs). The current work reviews the progress made during the last decades in the field of proteomics applied to the study of the legume-Rhizobium and -AM symbioses, and highlights their influence on the plant responses to pathogens and abiotic stresses. We further discuss future perspectives and new experimental approaches that are likely to have a significant impact on the field including peptidomics, mass spectrometric imaging, and quantitative proteomics.

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.

OsCHX14 is Involved in the K+ Homeostasis in Rice (Oryza sativa) Flowers

Previously we showed in the osjar1 mutants that the lodicule senescence which controls the closing of rice flowers was delayed. This resulted in florets staying open longer when compared with the wild type. The gene OsJAR1 is silenced in osjar1 mutants and is a key member of the jasmonic acid (JA) signaling pathway. We found that K concentrations in lodicules and flowers of osjar1-2 were significantly elevated compared with the wild type, indicating that K⁺ homeostasis may play a role in regulating the closure of rice flowers. The cation/H⁺ exchanger (CHX) family from rice was screened for potential K⁺ transporters involved as many members of this family in Arabidopsis were exclusively or preferentially expressed in flowers. Expression profiling confirmed that among 17 CHX genes in rice, OsCHX14 was the only member that showed an expression polymorphism, not only in osjar1 mutants but also in RNAi (RNA interference) lines of OsCOI1, another key member of the JA signaling pathway. This suggests that the expression of OsCHX14 is regulated by the JA signaling pathway. Green fluorescent protein (GFP)-tagged OsCHX14 protein was preferentially localized to the endoplasmic reticulum. Promoter-β-glucuronidase (GUS) analysis of transgenic rice revealed that OsCHX14 is mainly expressed in lodicules and the region close by throughout the flowering process. Characterization in yeast and Xenopus laevis oocytes verified that OsCHX14 is able to transport K⁺, Rb⁺ and Cs⁺ in vivo. Our data suggest that OsCHX14 may play an important role in K⁺ homeostasis during flowering in rice.