Shotgun Proteomic Analysis Highlights the Roles of Long-Lived mRNAs and De Novo Transcribed mRNAs in Rice Seeds upon Imbibition

During seed germination, proteins are translated not only from mRNAs newly transcribed upon imbibition but also from long-lived mRNAs that are synthesized during seed maturation and stored in the mature dry seeds. To clarify the distinct roles of proteins translated from long-lived mRNAs and de novo transcribed mRNAs in germinating rice embryos, proteome analysis based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) combining the use of a transcriptional inhibitor was performed. We observed that α-amanitin significantly represses transcription in germinating embryos; nevertheless, the embryos could germinate, albeit slowly. The proteomic analysis revealed that a total of 109 proteins were translated from long-lived mRNAs associated with germination as well as 222 proteins whose expression were dependent on de novo transcription upon imbibition. Transcriptomic datasets available in public databases demonstrated that mRNAs of the 222 proteins notably increased during germination while those of the 109 proteins highly accumulated in dry embryos and constitutively expressed upon imbibition. Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that many of the 109 proteins from long-lived mRNAs are implicated in energy production such as glycolysis or annotated as nucleotide binding proteins, while the 222 proteins are involved in pathways such as pyruvate metabolism and TCA cycle following glycolysis, and momilactones biosynthesis. We propose that long-lived mRNAs support initial energy production and activation of translational machinery upon imbibition whereas de novo transcription accelerates the energy production after glycolysis, which enables rice seeds to germinate vigorously.

IRES-mediated cap-independent translation, a path leading to hidden proteome

Most eukaryotic mRNAs are translated in a cap-dependent fashion; however, under stress conditions, the cap-independent translation driven by internal ribosomal entry sites (IRESs) can serve as an alternative mechanism for protein production. Many IRESs have been discovered from viral or cellular mRNAs to promote ribosome assembly and initiate translation by recruiting different trans-acting factors. Although the mechanisms of translation initiation driven by viral IRESs are relatively well understood, the existence of cellular IRESs is still under debate due to the limitations of translation reporter systems used to assay IRES activities. A recent screen identified > 1000 putative IRESs from viral and human mRNAs, expanding the scope and mechanism for cap-independent translation. Additionally, a large number of circular RNAs lacking free ends were identified in eukaryotic cells, many of which are found to be translated through IRESs. These findings suggest that IRESs may play a previously unappreciated role in driving translation of the new type of mRNA, implying a hidden proteome produced from cap-independent translation.

Investigation and development of maize fused network analysis with multi-omics

Maize is a critically important staple crop in the whole world, which has contributed to both economic security and food in planting areas. The main target for researchers and breeding is the improvement of maize quality and yield. The use of computational biology methods combined with multi-omics for selecting biomolecules of interest for maize breeding has been receiving more attention. Moreover, the rapid growth of high-throughput sequencing data provides the opportunity to explore biomolecules of interest at the molecular level in maize. Furthermore, we constructed weighted networks for each of the omics and then integrated them into a final fused weighted network based on a nonlinear combination method. We also analyzed the final fused network and mined the orphan nodes, some of which were shown to be transcription factors that played a key role in maize development. This study could help to improve maize production via insights at the multi-omics level and provide a new perspective for maize researchers. All related data have been released at http://lab.malab.cn/∼jj/maize.htm.

Improving Silkworm Genome Annotation Using a Proteogenomics Approach

The silkworm genome has been deeply sequenced and assembled, but accurate genome annotation, which is important for modern biological research, remains far from complete. To improve silkworm genome annotation, we carried out a proteogenomics analysis using 9.8 million mass spectra collected from different tissues and developmental stages of the silkworm. The results confirmed the translational products of 4307 existing gene models and identified 1701 novel genome search-specific peptides (GSSPs). Using these GSSPs, 74 novel gene-coding sequences were identified, and 121 existing gene models were corrected. We also identified 1182 novel junction peptides based on an exon-skipping database that resulted in the identification of 973 alternative splicing sites. Furthermore, we performed RNA-seq analysis to improve silkworm genome annotation at the transcriptional level. A total of 1704 new transcripts and 1136 new exons were identified, 2581 untranslated regions (UTRs) were revised, and 1301 alternative splicing (AS) genes were identified. The transcriptomics results were integrated with the proteomics data to further complement and verify the new annotations. In addition, 14 incorrect genes and 10 skipped exons were verified using the two analysis methods. Altogether, we identified 1838 new transcripts and 1593 AS genes and revised 5074 existing genes using proteogenomics and transcriptome analyses. Data are available via ProteomeXchange with identifier PXD009672. The large-scale proteogenomics and transcriptome analyses in this study will greatly improve silkworm genome annotation and contribute to future studies.

The arbuscular mycorrhizal symbiosis regulates aquaporins activity and improves root cell water permeability in maize plants subjected to water stress

Studies have suggested that increased root hydraulic conductivity in mycorrhizal roots could be the result of increased cell-to-cell water flux via aquaporins. This study aimed to elucidate if the key effect of the regulation of maize aquaporins by the arbuscular mycorrhizal (AM) symbiosis is the enhancement of root cell water transport capacity. Thus, water permeability coefficient (P_f ) and cell hydraulic conductivity (L_pc ) were measured in root protoplast and intact cortex cells of AM and non-AM plants subjected or not to water stress. Results showed that cells from droughted-AM roots maintained P_f and L_pc values of nonstressed plants, whereas in non-AM roots, these values declined drastically as a consequence of water deficit. Interestingly, the phosphorylation status of PIP2 aquaporins increased in AM plants subjected to water deficit, and P_f values higher than 12 μm s^-1 were found only in protoplasts from AM roots, revealing the higher water permeability of AM root cells. In parallel, the AM symbiosis increased stomatal conductance, net photosynthesis, and related parameters, showing a higher photosynthetic capacity in these plants. This study demonstrates a better performance of AM root cells in water transport under water deficit, which is connected to the shoot physiological performance in terms of photosynthetic capacity.

On the Impact of the Pangenome and Annotation Discrepancies While Building Protein Sequence Databases for Bacteria Proteogenomics

In proteomics, peptide information within mass spectrometry (MS) data from a specific organism sample is routinely matched against a protein sequence database that best represent such organism. However, if the species/strain in the sample is unknown or genetically poorly characterized, it becomes challenging to determine a database which can represent such sample. Building customized protein sequence databases merging multiple strains for a given species has become a strategy to overcome such restrictions. However, as more genetic information is publicly available and interesting genetic features such as the existence of pan- and core genes within a species are revealed, we questioned how efficient such merging strategies are to report relevant information. To test this assumption, we constructed databases containing conserved and unique sequences for 10 different species. Features that are relevant for probabilistic-based protein identification by proteomics were then monitored. As expected, increase in database complexity correlates with pangenomic complexity. However, Mycobacterium tuberculosis and Bordetella pertussis generated very complex databases even having low pangenomic complexity. We further tested database performance by using MS data from eight clinical strains from M. tuberculosis, and from two published datasets from Staphylococcus aureus. We show that by using an approach where database size is controlled by removing repeated identical tryptic sequences across strains/species, computational time can be reduced drastically as database complexity increases.

Perspective on Alternative Splicing and Proteome Complexity in Plants

Alternative splicing (AS) generates multiple transcripts from the same gene, however, AS contribution to proteome complexity remains elusive in plants. AS is prevalent under stress conditions in plants, but it is counterintuitive why plants would invest in protein synthesis under declining energy supply. We propose that plants employ AS not only to potentially increasing proteomic complexity, but also to buffer against the stress-responsive transcriptome to reduce the metabolic cost of translating all AS transcripts. To maximise efficiency under stress, plants may make fewer proteins with disordered domains via AS to diversify substrate specificity and maintain sufficient regulatory capacity. Furthermore, we suggest that chromatin state-dependent AS engenders short/long-term stress memory to mediate reproducible transcriptional response in the future.

The Scope, Functions, and Dynamics of Posttranslational Protein Modifications

Assessing posttranslational modification (PTM) patterns within protein molecules and reading their functional implications present grand challenges for plant biology. We combine four perspectives on PTMs and their roles by considering five classes of PTMs as examples of the broader context of PTMs. These include modifications of the N terminus, glycosylation, phosphorylation, oxidation, and N-terminal and protein modifiers linked to protein degradation. We consider the spatial distribution of PTMs, the subcellular distribution of modifying enzymes, and their targets throughout the cell, and we outline the complexity of compartmentation in understanding of PTM function. We also consider PTMs temporally in the context of the lifetime of a protein molecule and the need for different PTMs for assembly, localization, function, and degradation. Finally, we consider the combined action of PTMs on the same proteins, their interactions, and the challenge ahead of integrating PTMs into an understanding of protein function in plants.

Directions for research and training in plant omics: Big Questions and Big Data

A key remit of the NSF-funded "Arabidopsis Research and Training for the 21st Century" (ART-21) Research Coordination Network has been to convene a series of workshops with community members to explore issues concerning research and training in plant biology, including the role that research using Arabidopsis thaliana can play in addressing those issues. A first workshop focused on training needs for bioinformatic and computational approaches in plant biology was held in 2016, and recommendations from that workshop have been published (Friesner et al., Plant Physiology, 175, 2017, 1499). In this white paper, we provide a summary of the discussions and insights arising from the second ART-21 workshop. The second workshop focused on experimental aspects of omics data acquisition and analysis and involved a broad spectrum of participants from academics and industry, ranging from graduate students through post-doctorates, early career and established investigators. Our hope is that this article will inspire beginning and established scientists, corporations, and funding agencies to pursue directions in research and training identified by this workshop, capitalizing on the reference species Arabidopsis thaliana and other valuable plant systems.

Rapid and reproducible phosphopeptide enrichment by tandem metal oxide affinity chromatography: application to boron deficiency induced phosphoproteomics

Mass spectrometry has been instrumental in enabling the study of molecular signaling on a cellular scale by way of site-specific quantification of protein post-translational modifications, in particular phosphorylation. Here we describe an updated tandem metal oxide affinity chromatography (MOAC) combined phosphoprotein/phosphopeptide enrichment strategy, a scalable phosphoproteomics approach that allows rapid identification of thousands of phosphopeptides in plant materials. We implemented modifications to several steps of the original tandem MOAC procedure to increase the amount of quantified phosphopeptides and hence site-specific phosphorylation of proteins in a sample beginning with the less amounts of tissue and a substantially smaller amount of extracted protein. We applied this technology to generate time-resolved maps of boron signaling in Arabidopsis roots. We show that the successive enrichment of phosphoproteins in a first and phosphopeptide extraction in a second step using our optimized procedure strongly enriched the root phosphoproteome. Our results reveal that boron deficiency affects over 20% of the measured root phosphoproteome and that many phosphorylation sites with known biological function, and an even larger number of previously undescribed sites, are modified during the time course of boron deficiency. We identify transcription factors as key regulators of hormone signaling pathways that modulate gene expression in boron deprived plants. Furthermore, our phosphorylation kinetics data demonstrate that mitogen-activated protein kinase (MAPK) cascades mediate polarized transport of boron in Arabidopsis roots. Taken together, we establish and validate a robust approach for proteome-wide phosphorylation analysis in plant biology research.

Application of a Sensitive and Reproducible Label-Free Proteomic Approach to Explore the Proteome of Individual Meiotic-Phase Barley Anthers

Meiosis is a highly dynamic and precisely regulated process of cell division, leading to the production of haploid gametes from one diploid parental cell. In the crop plant barley (Hordeum vulgare), male meiosis occurs in anthers, in specialized cells called meiocytes. Barley meiotic tissue is scarce and not easily accessible, making meiosis study a challenging task. We describe here a new micro-proteomics workflow that allows sensitive and reproducible genome-wide label-free proteomic analysis of individual staged barley anthers. This micro-proteomic approach detects more than 4,000 proteins from such small amounts of material as two individual anthers, covering a dynamic range of protein relative abundance levels across five orders of magnitude. We applied our micro-proteomics workflow to investigate the proteome of the developing barley anther containing pollen mother cells in the early stages of meiosis and we successfully identified 57 known and putative meiosis-related proteins. Meiotic proteins identified in our study were found to be key players of many steps and processes in early prophase such as: chromosome condensation, synapsis, DNA double-strand breaks or crossover formation. Considering the small amount of starting material, this work demonstrates an important technological advance in plant proteomics and can be applied for proteomic examination of many size-limited plant specimens. Moreover, it is the first insight into the proteome of individual barley anther at early meiosis. The proteomic data have been deposited to the ProteomeXchange with the accession number PXD010887.

Lineage-Specific Expression Divergence in Grasses Is Associated with Male Reproduction, Host-Pathogen Defense, and Domestication

Poaceae (grasses) is an agriculturally important and widely distributed family of plants with extraordinary phenotypic diversity, much of which was generated under recent lineage-specific evolution. Yet, little is known about the genes and functional modules involved in the lineage-specific divergence of grasses. Here, I address this question on a genome-wide scale by applying a novel branch-based statistic of lineage-specific expression divergence, LED, to RNA-seq data from nine tissues of the wild grass Brachypodium distachyon and its domesticated relatives Oryza sativa japonica (rice) and Sorghum bicolor (sorghum). I find that LED is generally smallest in B. distachyon and largest in O. sativa japonica, which underwent domestication earlier than S. bicolor, supporting the hypothesis that domestication may increase the rate of lineage-specific expression divergence in grasses. Moreover, in all three species, LED is positively correlated with protein-coding sequence divergence and tissue specificity, and negatively correlated with network connectivity. Further analysis reveals that genes with large LED are often primarily expressed in anther, implicating lineage-specific expression divergence in the evolution of male reproductive phenotypes. Gene ontology enrichment analysis also identifies an overrepresentation of terms related to male reproduction in the two domesticated grasses, as well as to those involved in host-pathogen defense in all three species. Last, examinations of genes with the largest LED reveal that their lineage-specific expression divergence may have contributed to antimicrobial functions in B. distachyon, to enhanced adaptation and yield during domestication in O. sativa japonica, and to defense against a widespread and devastating fungal pathogen in S. bicolor. Together, these findings suggest that lineage-specific expression divergence in grasses may increase under domestication and preferentially target rapidly evolving genes involved in male reproduction, host-pathogen defense, and the origin of domesticated phenotypes.

Computational and Experimental Tools to Monitor the Changes in Translation Efficiency of Plant mRNA on a Genome-Wide Scale: Advantages, Limitations, and Solutions

The control of translation in the course of gene expression regulation plays a crucial role in plants' cellular events and, particularly, in responses to environmental factors. The paradox of the great variance between levels of mRNAs and their protein products in eukaryotic cells, including plants, requires thorough investigation of the regulatory mechanisms of translation. A wide and amazingly complex network of mechanisms decoding the plant genome into proteome challenges researchers to design new methods for genome-wide analysis of translational control, develop computational algorithms detecting regulatory mRNA contexts, and to establish rules underlying differential translation. The aims of this review are to (i) describe the experimental approaches for investigation of differential translation in plants on a genome-wide scale; (ii) summarize the current data on computational algorithms for detection of specific structure⁻function features and key determinants in plant mRNAs and their correlation with translation efficiency; (iii) highlight the methods for experimental verification of existed and theoretically predicted features within plant mRNAs important for their differential translation; and finally (iv) to discuss the perspectives of discovering the specific structural features of plant mRNA that mediate differential translation control by the combination of computational and experimental approaches.

Ethylene Receptors, CTRs and EIN2 Target Protein Identification and Quantification Through Parallel Reaction Monitoring During Tomato Fruit Ripening

Ethylene, the plant ripening hormone of climacteric fruit, is perceived by ethylene receptors which is the first step in the complex ethylene signal transduction pathway. Much progress has been made in elucidating the mechanism of this pathway, but there is still a lot to be done in the proteomic quantification of the main proteins involved, particularly during fruit ripening. This work focuses on the mass spectrometry based identification and quantification of the ethylene receptors (ETRs) and the downstream components of the pathway, CTR-like proteins (CTRs) and ETHYLENE INSENSITIVE 2 (EIN2). We used tomato as a model fruit to study changes in protein abundance involved in the ethylene signal transduction during fruit ripening. In order to detect and quantify these low abundant proteins located in the membrane of the endoplasmic reticulum, we developed a workflow comprising sample fractionation and MS analysis using parallel reaction monitoring. This work shows the feasibility of the identification and absolute quantification of all seven ethylene receptors, three out of four CTRs and EIN2 in four ripening stages of tomato. In parallel, gene expression was analyzed through real-time qPCR. Correlation between transcriptomic and proteomic profiles during ripening was only observed for three of the studied proteins, suggesting that the other signaling proteins are likely post-transcriptionally regulated. Based on our quantification results we were able to show that the protein levels of SlETR3 and SlETR4 increased during ripening, probably to control ethylene sensitivity. The other receptors and CTRs showed either stable levels that could sustain, or decreasing levels that could promote fruit ripening.

Deleterious variation shapes the genomic landscape of introgression

While it is appreciated that population size changes can impact patterns of deleterious variation in natural populations, less attention has been paid to how gene flow affects and is affected by the dynamics of deleterious variation. Here we use population genetic simulations to examine how gene flow impacts deleterious variation under a variety of demographic scenarios, mating systems, dominance coefficients, and recombination rates. Our results show that admixture between populations can temporarily reduce the genetic load of smaller populations and cause increases in the frequency of introgressed ancestry, especially if deleterious mutations are recessive. Additionally, when fitness effects of new mutations are recessive, between-population differences in the sites at which deleterious variants exist creates heterosis in hybrid individuals. Together, these factors lead to an increase in introgressed ancestry, particularly when recombination rates are low. Under certain scenarios, introgressed ancestry can increase from an initial frequency of 5% to 30–75% and fix at many loci, even in the absence of beneficial mutations. Further, deleterious variation and admixture can generate correlations between the frequency of introgressed ancestry and recombination rate or exon density, even in the absence of other types of selection. The direction of these correlations is determined by the specific demography and whether mutations are additive or recessive. Therefore, it is essential that null models of admixture include both demography and deleterious variation before invoking other mechanisms to explain unusual patterns of genetic variation.

Individuals from distinct populations sometimes will produce fertile offspring and will exchange genetic material in a process called hybridization. Genomes of hybrid individuals often show non-random patterns of hybrid ancestry across the genome, where some regions have a high frequency of ancestry from the second population and other regions have less. Typically, this pattern has been attributed to adaptive introgression, where beneficial genetic variants are passed from one population to the other, or to genomic incompatibilities between these distinct species. However, other mechanisms could lead to these heterogeneous patterns of ancestry in hybrids. Here we use simulations to investigate whether deleterious mutations affect the patterns of introgressed ancestry across genomes. We show that when ancestry from a larger population is added to a smaller population, the ancestry from the larger population dramatically increases in frequency because it carries fewer deleterious mutations. This occurs even in the absence of beneficial mutations in either population. Additionally, we show that differences in sex chromosome evolution relative to autosomes, or differences in mating system, can affect patterns of introgression in similar ways. Our study argues that deleterious mutations should be included in population genetic models used to identify unusual regions of the genome that appear to be under selection in hybrids.

Biology in Bloom: A Primer on the Arabidopsis thaliana Model System

Arabidopsis thaliana could have easily escaped human scrutiny. Instead, Arabidopsis has become the most widely studied plant in modern biology despite its absence from the dinner table. Pairing diminutive stature and genome with prodigious resources and tools, Arabidopsis offers a window into the molecular, cellular, and developmental mechanisms underlying life as a multicellular photoautotroph. Many basic discoveries made using this plant have spawned new research areas, even beyond the verdant fields of plant biology. With a suite of resources and tools unmatched among plants and rivaling other model systems, Arabidopsis research continues to offer novel insights and deepen our understanding of fundamental biological processes.

Impact of drought and salt stress on the biosynthesis of alkaloids in Chelidonium majus L

When plants are exposed to various stress situations, their alkaloid concentration frequently is enhanced. This well-known phenomenon is presumably due to a passively enhanced rate of biosynthesis, caused by greatly elevated concentrations of NADPH in stressed plants. Here, we used Chelidonium majus L. plants, which accumulate high concentrations of dihydrocoptisine in their leaves, to study the impact of drought and salt stress on the biosynthesis and accumulation of alkaloids. In comparison to well-watered controls, in the transcriptome of the gene encoding the key enzyme in alkaloid biosynthesis, stylopine synthase, is enhanced in stressed C. majus plants. If we presuppose that increased transcript levels correlate with increased enzymatic activity of the gene products, these data indicate, for the first time, that stress-related increases in alkaloid concentration might not only be caused by the well-known stress-related passive shift, but may also be due to an enhancement of enzymatic capacity.

The Use of Proteomic Tools to Address Challenges Faced in Clonal Propagation of Tropical Crops through Somatic Embryogenesis

In many tropical countries with agriculture as the mainstay of the economy, tropical crops are commonly cultivated at the plantation scale. The successful establishment of crop plantations depends on the availability of a large quantity of elite seedling plants. Many plantation companies establish plant tissue culture laboratories to supply planting materials for their plantations and one of the most common applications of plant tissue culture is the mass propagation of true-to-type elite seedlings. However, problems encountered in tissue culture technology prevent its applications being widely adopted. Proteomics can be a powerful tool for use in the analysis of cultures, and to understand the biological processes that takes place at the cellular and molecular levels in order to address these problems. This mini review presents the tissue culture technologies commonly used in the propagation of tropical crops. It provides an outline of some the genes and proteins isolated that are associated with somatic embryogenesis and the use of proteomic technology in analysing tissue culture samples and processes in tropical crops.

Sample Preparation for Analysis of the Plant Mitochondrial Membrane Proteome

Containing plastids and vacuoles in addition to those organelles also found in other (heterotrophic) cells, the plant cell displays an extraordinary level of compartmentalization, largely obtained by the utilization of membranes. These membranes not only confine reaction spaces but must also facilitate cross-talk between organelles and other cell compartments. They also host important components of the plant energy metabolism, i.e., the electron transport chains of mitochondria and chloroplasts. Characterization of the proteomes of these membranes requires isolation of pure and intact organelles from plant tissues followed by subsequent purification of their respective membranes. Membrane fractions are then amenable for further analyses using gel electrophoresis procedures or gel-free proteomic approaches. Here, we describe the preparation of intact mitochondria from Arabidopsis thaliana cell-culture, the isolation of outer and inner mitochondrial membranes and downstream proteomic applications for analyzing their membrane protein content.

Nanobody-Directed Specific Degradation of Proteins by the 26S-Proteasome in Plants

Here, we present data showing the directed degradation of target proteins recognized by a specific nanobody in transgenic plants. Green fluorescent protein was depleted by a chimeric nanobody fused to a distinct F-box domain, which enables protein degradation via the ubiquitin proteasome pathway. This technique could thus be used to knock out other proteins of interest in planta using specific, high-affinity binding proteins.

Unravelling Protein-Protein Interaction Networks Linked to Aliphatic and Indole Glucosinolate Biosynthetic Pathways in Arabidopsis

Within the cell, biosynthetic pathways are embedded in protein-protein interaction networks. In Arabidopsis, the biosynthetic pathways of aliphatic and indole glucosinolate defense compounds are well-characterized. However, little is known about the spatial orchestration of these enzymes and their interplay with the cellular environment. To address these aspects, we applied two complementary, untargeted approaches-split-ubiquitin yeast 2-hybrid and co-immunoprecipitation screens-to identify proteins interacting with CYP83A1 and CYP83B1, two homologous enzymes specific for aliphatic and indole glucosinolate biosynthesis, respectively. Our analyses reveal distinct functional networks with substantial interconnection among the identified interactors for both pathway-specific markers, and add to our knowledge about how biochemical pathways are connected to cellular processes. Specifically, a group of protein interactors involved in cell death and the hypersensitive response provides a potential link between the glucosinolate defense compounds and defense against biotrophic pathogens, mediated by protein-protein interactions.

A code for transcription elongation speed

The two major steps of gene expression are transcription and translation. While hundreds of studies regarding the effect of sequence features on the translation elongation process have been published, very few connect sequence features to the transcription elongation rate. We suggest, for the first time, that short transcript sub-sequences have a typical effect on RNA polymerase (RNAP) speed: we show that nucleotide 5-mers tend to have typical RNAP speed (or transcription rate), which is consistent along different parts of genes and among different groups of genes with high correlation. We also demonstrate that relative RNAP speed correlates with mRNA levels of endogenous and heterologous genes. Furthermore, we show that the estimated transcription and translation elongation rates correlate in endogenous genes. Finally, we demonstrate that our results are consistent for different high resolution experimental measurements of RNAP densities. These results suggest for the first time that transcription elongation is partly encoded in the transcript, affected by the codon-usage, and optimized by evolution with a significant effect on gene expression and organismal fitness.

Proteogenomics from a bioinformatics angle: A growing field

Proteogenomics is a research area that combines areas as proteomics and genomics in a multi-omics setup using both mass spectrometry and high-throughput sequencing technologies. Currently, the main goals of the field are to aid genome annotation or to unravel the proteome complexity. Mass spectrometry based identifications of matching or homologues peptides can further refine gene models. Also, the identification of novel proteoforms is also made possible based on detection of novel translation initiation sites (cognate or near-cognate), novel transcript isoforms, sequence variation or novel (small) open reading frames in intergenic or un-translated genic regions by analyzing high-throughput sequencing data from RNAseq or ribosome profiling experiments. Other proteogenomics studies using a combination of proteomics and genomics techniques focus on antibody sequencing, the identification of immunogenic peptides or venom peptides. Over the years, a growing amount of bioinformatics tools and databases became available to help streamlining these cross-omics studies. Some of these solutions only help in specific steps of the proteogenomics studies, e.g. building custom sequence databases (based on next generation sequencing output) for mass spectrometry fragmentation spectrum matching. Over the last few years a handful integrative tools also became available that can execute complete proteogenomics analyses. Some of these are presented as stand-alone solutions, whereas others are implemented in a web-based framework such as Galaxy. In this review we aimed at sketching a comprehensive overview of all the bioinformatics solutions that are available for this growing research area. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:584-599, 2017.

A Cautionary Tale on the Inclusion of Variable Posttranslational Modifications in Database-Dependent Searches of Mass Spectrometry Data

Mass spectrometry-based proteomics allows in principle the identification of unknown target proteins of posttranslational modifications and the sites of attachment. Including a variety of posttranslational modifications in database-dependent searches of high-throughput mass spectrometry data holds the promise to gain spectrum assignments to modified peptides, thereby increasing the number of assigned spectra, and to identify potentially interesting modification events. However, these potential benefits come for the price of an increased search space, which can lead to reduced scores, increased score thresholds, and erroneous peptide spectrum matches. We have assessed here the advantages and disadvantages of including the variable posttranslational modifications methionine oxidation, protein N-terminal acetylation, cysteine carbamidomethylation, transformation of N-terminal glutamine to pyroglutamic acid (Gln→pyro-Glu), and deamidation of asparagine and glutamine. Based on calculations of local false discovery rates and comparisons to known features of the respective modifications, we recommend for searches of samples that were not enriched for specific posttranslational modifications to only include methionine oxidation, protein N-terminal acetylation, and peptide N-terminal Gln→pyro-Glu as variable modifications. The principle of the validation strategy adopted here can also be applied for assessing the inclusion of posttranslational modifications for differently prepared samples, or for additional modifications. In addition, we have reassessed the special properties of the ubiquitin footprint, which is the remainder of ubiquitin moieties attached to lysines after tryptic digest. We show here that the ubiquitin footprint often breaks off as neutral loss and that it can be distinguished from dicarbamidomethylation events.

Investigating the Role of the Photorespiratory Pathway in Non-photosynthetic Tissues

Whilst photorespiration represents one of the dominant pathway fluxes in photosynthetic tissues there are hints from publically available gene expression data such as that housed in the bioarray resource (BAR; www.bar.utoronto.ca) that several of the constituent enzymes are present in roots and other heterotrophic tissues. Here we describe a protocol based on modification of the gaseous environment surrounding individual tissues of mutant and wild type Arabidopsis and evaluation of the consequences. This method could additionally easily be used for larger plants.

Proteogenomics produces comprehensive and highly accurate protein-coding gene annotation in a complete genome assembly of Malassezia sympodialis

Complete and accurate genome assembly and annotation is a crucial foundation for comparative and functional genomics. Despite this, few complete eukaryotic genomes are available, and genome annotation remains a major challenge. Here, we present a complete genome assembly of the skin commensal yeast Malassezia sympodialis and demonstrate how proteogenomics can substantially improve gene annotation. Through long-read DNA sequencing, we obtained a gap-free genome assembly for M. sympodialis (ATCC 42132), comprising eight nuclear and one mitochondrial chromosome. We also sequenced and assembled four M. sympodialis clinical isolates, and showed their value for understanding Malassezia reproduction by confirming four alternative allele combinations at the two mating-type loci. Importantly, we demonstrated how proteomics data could be readily integrated with transcriptomics data in standard annotation tools. This increased the number of annotated protein-coding genes by 14% (from 3612 to 4113), compared to using transcriptomics evidence alone. Manual curation further increased the number of protein-coding genes by 9% (to 4493). All of these genes have RNA-seq evidence and 87% were confirmed by proteomics. The M. sympodialis genome assembly and annotation presented here is at a quality yet achieved only for a few eukaryotic organisms, and constitutes an important reference for future host-microbe interaction studies.

Shot-gun proteome and transcriptome mapping of the jujube floral organ and identification of a pollen-specific S-locus F-box gene

The flower is a plant reproductive organ that forms part of the fruit produced as the flowering season ends. While the number and identity of proteins expressed in a jujube (Ziziphus jujuba Mill.) flower is currently unknown, integrative proteomic and transcriptomic analyses provide a systematic strategy of characterizing the floral biology of plants. We conducted a shotgun proteomic analysis on jujube flowers by using a filter-aided sample preparation tryptic digestion, followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). In addition, transcriptomics analyses were performed on HiSeq2000 sequencers. In total, 7,853 proteins were identified accounting for nearly 30% of the ‘Junzao’ gene models (27,443). Genes identified in proteome generally showed higher RPKM (reads per kilobase per million mapped reads) values than undetected genes. Gene ontology categories showed that ribosomes and intracellular organelles were the most dominant classes and accounted for 17.0% and 14.0% of the proteome mass, respectively. The top-ranking proteins with iBAQ >10¹⁰ included non-specific lipid transfer proteins, histones, actin-related proteins, fructose-bisphosphate aldolase, Bet v I type allergens, etc. In addition, we identified one pollen-specificity S-locus F-box-like gene located on the same chromosome as the S-RNase gene. Both of these may activate the behaviour of gametophyte self-incompatibility in jujube. These results reflected the protein profile features of jujube flowers and contributes new information important to the jujube breeding system.

Proteomic profile of Piper tuberculatum (Piperaceae)

Abstract Piper tuberculatum (Piperaceae) is a species that accumulates especially amides as secondary metabolites and several biological activities was previously reported. In this article, we report a proteomic study of P. tuberculatum. Bidimensional electrophoresis (2D SDS-PAGE) and mass spectrometry (ESI-Q-TOF) were used in this study. Over a hundred spots and various peptides were identified in this species and the putative functions of these peptides related to defense mechanism as biotic and abiotic stress were assigned. The information presented extend the range of molecular information of P. tuberculatum.

Engineering central metabolism - a grand challenge for plant biologists

The goal of increasing crop productivity and nutrient-use efficiency is being addressed by a number of ambitious research projects seeking to re-engineer photosynthetic biochemistry. Many of these projects will require the engineering of substantial changes in fluxes of central metabolism. However, as has been amply demonstrated in simpler systems such as microbes, central metabolism is extremely difficult to rationally engineer. This is because of multiple layers of regulation that operate to maintain metabolic steady state and because of the highly connected nature of central metabolism. In this review we discuss new approaches for metabolic engineering that have the potential to address these problems and dramatically improve the success with which we can rationally engineer central metabolism in plants. In particular, we advocate the adoption of an iterative 'design-build-test-learn' cycle using fast-to-transform model plants as test beds. This approach can be realised by coupling new molecular tools to incorporate multiple transgenes in nuclear and plastid genomes with computational modelling to design the engineering strategy and to understand the metabolic phenotype of the engineered organism. We also envisage that mutagenesis could be used to fine-tune the balance between the endogenous metabolic network and the introduced enzymes. Finally, we emphasise the importance of considering the plant as a whole system and not isolated organs: the greatest increase in crop productivity will be achieved if both source and sink metabolism are engineered.

Methods, Tools and Current Perspectives in Proteogenomics

With combined technological advancements in high-throughput next-generation sequencing and deep mass spectrometry-based proteomics, proteogenomics, i.e. the integrative analysis of proteomic and genomic data, has emerged as a new research field. Early efforts in the field were focused on improving protein identification using sample-specific genomic and transcriptomic sequencing data. More recently, integrative analysis of quantitative measurements from genomic and proteomic studies have identified novel insights into gene expression regulation, cell signaling, and disease. Many methods and tools have been developed or adapted to enable an array of integrative proteogenomic approaches and in this article, we systematically classify published methods and tools into four major categories, (1) Sequence-centric proteogenomics; (2) Analysis of proteogenomic relationships; (3) Integrative modeling of proteogenomic data; and (4) Data sharing and visualization. We provide a comprehensive review of methods and available tools in each category and highlight their typical applications.

N-terminal Proteomics Assisted Profiling of the Unexplored Translation Initiation Landscape in Arabidopsis thaliana

Proteogenomics is an emerging research field yet lacking a uniform method of analysis. Proteogenomic studies in which N-terminal proteomics and ribosome profiling are combined, suggest that a high number of protein start sites are currently missing in genome annotations. We constructed a proteogenomic pipeline specific for the analysis of N-terminal proteomics data, with the aim of discovering novel translational start sites outside annotated protein coding regions. In summary, unidentified MS/MS spectra were matched to a specific N-terminal peptide library encompassing protein N termini encoded in the Arabidopsis thaliana genome. After a stringent false discovery rate filtering, 117 protein N termini compliant with N-terminal methionine excision specificity and indicative of translation initiation were found. These include N-terminal protein extensions and translation from transposable elements and pseudogenes. Gene prediction provided supporting protein-coding models for approximately half of the protein N termini. Besides the prediction of functional domains (partially) contained within the newly predicted ORFs, further supporting evidence of translation was found in the recently released Araport11 genome re-annotation of Arabidopsis and computational translations of sequences stored in public repositories. Most interestingly, complementary evidence by ribosome profiling was found for 23 protein N termini. Finally, by analyzing protein N-terminal peptides, an in silico analysis demonstrates the applicability of our N-terminal proteogenomics strategy in revealing protein-coding potential in species with well- and poorly-annotated genomes.

Extensive translational regulation during seed germination revealed by polysomal profiling

This work investigates the extent of translational regulation during seed germination. The polysome occupancy of each gene is determined by genome-wide profiling of total mRNA and polysome-associated mRNA. This reveals extensive translational regulation during Arabidopsis thaliana seed germination. The polysome occupancy of thousands of individual mRNAs changes to a large extent during the germination process. Intriguingly, these changes are restricted to two temporal phases (shifts) during germination, seed hydration and germination. Sequence features, such as upstream open reading frame number, transcript length, mRNA stability, secondary structures, and the presence and location of specific motifs correlated with this translational regulation. These features differed significantly between the two shifts, indicating that independent mechanisms regulate translation during seed germination. This study reveals substantial translational dynamics during seed germination and identifies development-dependent sequence features and cis elements that correlate with the translation control, uncovering a novel and important layer of gene regulation during seed germination.

Label-free deep shotgun proteomics reveals protein dynamics during tomato fruit tissues development

Current innovations in mass-spectrometry-based technologies allow deep coverage of protein expression. Despite its immense value and in contrast to transcriptomics, only a handful of studies in crop plants engaged with global proteome assays. Here, we present large-scale shotgun proteomics profiling of tomato fruit across two key tissues and five developmental stages. A total of 7738 individual protein groups were identified and reliably measured at least in one of the analyzed tissues or stages. The depth of our assay enabled identification of 61 differentially expressed transcription factors, including renowned ripening-related regulators and elements of ethylene signaling. Significantly, we measured proteins involved in 83% of all predicted enzymatic reactions in the tomato metabolic network. Hence, proteins representing almost the complete set of reactions in major metabolic pathways were identified, including the cytosolic and plastidic isoprenoid and the phenylpropanoid pathways. Furthermore, the data allowed us to discern between protein isoforms according to expression patterns, which is most significant in light of the weak transcript-protein expression correspondence. Finally, visualization of changes in protein abundance associated with a particular process provided us with a unique view of skin and flesh tissues in developing fruit. This study adds a new dimension to the existing genomic, transcriptomic and metabolomic resources. It is therefore likely to promote translational and post-translational research in tomato and additional species, which is presently focused on transcription.

Didehydrophenylalanine, an abundant modification in the beta subunit of plant polygalacturonases

The structure and the activity of proteins are often regulated by transient or stable post- translational modifications (PTM). Different from well-known, abundant modifications such as phosphorylation and glycosylation some modifications are limited to one or a few proteins across a broad range of related species. Although few examples of the latter type are known, the evolutionary conservation of these modifications and the enzymes responsible for their synthesis suggest an important physiological role. Here, the first observation of a new, fold-directing PTM is described. During the analysis of alfalfa cell wall proteins a -2Da mass shift was observed on phenylalanine residues in the repeated tetrapeptide FxxY of the beta-subunit of polygalacturonase. This modular protein is known to be involved in developmental and stress-responsive processes. The presence of this modification was confirmed using in-house and external datasets acquired by different commonly used techniques in proteome studies. Based on these analyses it was found that all identified phenylalanine residues in the sequence FxxY of this protein were modified to α,β-didehydro-Phe (ΔPhe). Besides showing the reproducible identification of ΔPhe in different species arguments that substantiate the fold-determining role of ΔPhe are given.

Changes in specific protein degradation rates in Arabidopsis thaliana reveal multiple roles of Lon1 in mitochondrial protein homeostasis

Mitochondrial Lon1 loss impairs oxidative phosphorylation complexes and TCA enzymes and causes accumulation of specific mitochondrial proteins. Analysis of over 400 mitochondrial protein degradation rates using ¹⁵ N labelling showed that 205 were significantly different between wild type (WT) and lon1-1. Those proteins included ribosomal proteins, electron transport chain subunits and TCA enzymes. For respiratory complexes I and V, decreased protein abundance correlated with higher degradation rate of subunits in total mitochondrial extracts. After blue native separation, however, the assembled complexes had slow degradation, while smaller subcomplexes displayed rapid degradation in lon1-1. In insoluble fractions, a number of TCA enzymes were more abundant but the proteins degraded slowly in lon1-1. In soluble protein fractions, TCA enzymes were less abundant but degraded more rapidly. These observations are consistent with the reported roles of Lon1 as a chaperone aiding the proper folding of newly synthesized/imported proteins to stabilise them and as a protease to degrade mitochondrial protein aggregates. HSP70, prohibitin and enzymes of photorespiration accumulated in lon1-1 and degraded slowly in all fractions, indicating an important role of Lon1 in their clearance from the proteome.

Resource: Mapping the Triticum aestivum proteome

Yield and quality improvement of bread wheat (Triticum aestivum) is a focus in efforts to meet new demands from population growth and changing human diets. As the complexity of the wheat genome is unravelled, determining how it is used to build the protein machinery of wheat plants is a key next step in explaining detailed aspects of wheat growth and development. The specific functions of wheat organs during vegetative development and the role of metabolism, protein degradation and remobilisation in driving grain production are the foundations of crop performance and have recently become accessible through studies of the wheat proteome. We present a large scale, publicly accessible proteome mapping of wheat consisting of 24 organ and developmental samples. Tissue specific sub-proteomes and ubiquitously expressed markers of the wheat proteome are identified, alongside hierarchical assessment of protein functional classes, their presence in different tissues and correlations between the abundance of functional classes of proteins. Gene-specific identifications and protein family relationships are accounted for in the organisation of the data and 202 new protein-coding transcripts identified by proteogenomic mapping. The interactive database will serve as a vehicle to build, refine and deposit confirmed targeted proteomic assays for wheat proteins and protein families to assess function (www.wheatproteome.org).

An Asymmetrically Balanced Organization of Kinases versus Phosphatases across Eukaryotes Determines Their Distinct Impacts

Protein phosphorylation underlies cellular response pathways across eukaryotes and is governed by the opposing actions of phosphorylating kinases and de-phosphorylating phosphatases. While kinases and phosphatases have been extensively studied, their organization and the mechanisms by which they balance each other are not well understood. To address these questions we performed quantitative analyses of large-scale 'omics' datasets from yeast, fly, plant, mouse and human. We uncovered an asymmetric balance of a previously-hidden scale: Each organism contained many different kinase genes, and these were balanced by a small set of highly abundant phosphatase proteins. Kinases were much more responsive to perturbations at the gene and protein levels. In addition, kinases had diverse scales of phenotypic impact when manipulated. Phosphatases, in contrast, were stable, highly robust and flatly organized, with rather uniform impact downstream. We validated aspects of this organization experimentally in nematode, and supported additional aspects by theoretic analysis of the dynamics of protein phosphorylation. Our analyses explain the empirical bias in the protein phosphorylation field toward characterization and therapeutic targeting of kinases at the expense of phosphatases. We show quantitatively and broadly that this is not only a historical bias, but stems from wide-ranging differences in their organization and impact. The asymmetric balance between these opposing regulators of protein phosphorylation is also common to opposing regulators of two other post-translational modification systems, suggesting its fundamental value.

Protein phosphorylation is a reversible modification that underlies cellular responses to stimuli across organisms. Historically, the study of protein phosphorylation concentrated on the role of kinases, which introduce the phosphate, at the expense of phosphatases, which remove it. Many kinases have been associated with specific phenotypes and considered attractive drug targets, while phosphatases remained far less characterized. It has been unclear whether this discrepancy is due to historical biases or reflects real systemic differences between these enzymes. By analyzing large-scale ‘omics’ datasets across genes, transcripts, proteins, interactions, and organisms, we uncovered an asymmetric architecture of kinases versus phosphatases that balances between them, determines their distinct impact patterns, and affects their therapeutic potential. This architecture is conserved from yeast to human and is partially shared by two other protein modification systems, suggesting it is a general feature of these systems.

Shotgun proteomics of the barley seed proteome

Background

Barley seed proteins are of prime importance to the brewing industry, human and animal nutrition and in plant breeding for cultivar identification. To obtain comprehensive proteomic data from seeds, total protein from a two-rowed (Conrad) and a six-rowed (Lacey) barley cultivar were precipitated in acetone, digested in-solution, and the resulting peptides were analyzed by nano-liquid chromatography coupled with tandem mass spectrometry.

Results

The raw mass spectra data searched against Uniprot’s Barley database using in-house Mascot search engine identified 1168 unique proteins. Gene Ontology (GO) analysis indicated that the majority of the seed proteins were cytosolic, with catalytic activity and associated with carbohydrate metabolism. Spectral counting analysis showed that there are 20 differentially abundant seed proteins between the two-rowed Conrad and six-rowed Lacey cultivars.

Conclusion

This study paves the way for the use of a top-down gel-free proteomics strategy in barley for investigating more complex traits such as malting quality. Differential abundance of hordoindoline proteins impact the seed hardness trait of barley cultivars.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3408-5) contains supplementary material, which is available to authorized users.

Proteogenomic Analysis Greatly Expands the Identification of Proteins Related to Reproduction in the Apogamous Fern Dryopteris affinis ssp. affinis

Performing proteomic studies on non-model organisms with little or no genomic information is still difficult. However, many specific processes and biochemical pathways occur only in species that are poorly characterized at the genomic level. For example, many plants can reproduce both sexually and asexually, the first one allowing the generation of new genotypes and the latter their fixation. Thus, both modes of reproduction are of great agronomic value. However, the molecular basis of asexual reproduction is not well understood in any plant. In ferns, it combines the production of unreduced spores (diplospory) and the formation of sporophytes from somatic cells (apogamy). To set the basis to study these processes, we performed transcriptomics by next-generation sequencing (NGS) and shotgun proteomics by tandem mass spectrometry in the apogamous fern D. affinis ssp. affinis. For protein identification we used the public viridiplantae database (VPDB) to identify orthologous proteins from other plant species and new transcriptomics data to generate a "species-specific transcriptome database" (SSTDB). In total 1,397 protein clusters with 5,865 unique peptide sequences were identified (13 decoy proteins out of 1,410, protFDR 0.93% on protein cluster level). We show that using the SSTDB for protein identification increases the number of identified peptides almost four times compared to using only the publically available VPDB. We identified homologs of proteins involved in reproduction of higher plants, including proteins with a potential role in apogamy. With the increasing availability of genomic data from non-model species, similar proteogenomics approaches will improve the sensitivity in protein identification for species only distantly related to models.

Predictive biophysical modeling and understanding of the dynamics of mRNA translation and its evolution

mRNA translation is the fundamental process of decoding the information encoded in mRNA molecules by the ribosome for the synthesis of proteins. The centrality of this process in various biomedical disciplines such as cell biology, evolution and biotechnology, encouraged the development of dozens of mathematical and computational models of translation in recent years. These models aimed at capturing various biophysical aspects of the process. The objective of this review is to survey these models, focusing on those based and/or validated on real large-scale genomic data. We consider aspects such as the complexity of the models, the biophysical aspects they regard and the predictions they may provide. Furthermore, we survey the central systems biology discoveries reported on their basis. This review demonstrates the fundamental advantages of employing computational biophysical translation models in general, and discusses the relative advantages of the different approaches and the challenges in the field.

The 5'UTR Intron of Arabidopsis GGT1 Aminotransferase Enhances Promoter Activity by Recruiting RNA Polymerase II

Photorespiration is essential for the detoxification of glycolate and recycling of carbon to the Calvin Benson Bassham cycle. Enzymes participating in the pathway have been identified, and investigations now focus on the regulation of photorespiration by transporters and metabolites. However, regulation of photorespiration on the gene level has not been intensively studied. Here, we show that maximum transcript abundance of Glu:glyoxylate aminotransferase 1 (GGT1) is regulated by intron-mediated enhancement (IME) of the 5' leader intron rather than by regulatory elements in the 5' upstream region. The intron is rich in CT-stretches and contains the motif TGTGATTTG that is highly similar to the IME-related motif TTNGATYTG. The GGT1 intron also confers leaf-specific expression of foreign promoters. Quantitative PCR analysis and GUS activity measurements revealed that IME of the GGT1 5'UTR intron is controlled on the transcriptional level. IME by the GGT1 5'UTR intron was at least 2-fold. Chromatin immunoprecipitation experiments showed that the abundance of RNA polymerase II binding to the intron-less construct is reduced.

An Easy Method for Plant Polysome Profiling

Translation of mRNA to protein is a fundamental and highly regulated biological process. Polysome profiling is considered as a gold standard for the analysis of translational regulation. The method described here is an easy and economical way for fractionating polysomes from various plant tissues. A sucrose gradient is made without the need for a gradient maker by sequentially freezing each layer. Cytosolic extracts are then prepared in a buffer containing cycloheximide and chloramphenicol to immobilize the cytosolic and chloroplastic ribosomes to mRNA and are loaded onto the sucrose gradient. After centrifugation, six fractions are directly collected from the bottom to the top of the gradient, without piercing the ultracentrifugation tube. During collection, the absorbance at 260 nm is read continuously to generate a polysome profile that gives a snapshot of global translational activity. Fractions are then pooled to prepare three different mRNA populations: the polysomes, mRNAs bound to several ribosomes; the monosomes, mRNAs bound to one ribosome; and mRNAs that are not bound to ribosomes. mRNAs are then extracted. This protocol has been validated for different plants and tissues including Arabidopsis thaliana seedlings and adult plants, Nicotiana benthamiana, Solanum lycopersicum, and Oryza sativa leaves.

Integration of omic networks in a developmental atlas of maize

Coexpression networks and gene regulatory networks (GRNs) are emerging as important tools for predicting functional roles of individual genes at a system-wide scale. To enable network reconstructions, we built a large-scale gene expression atlas composed of 62,547 messenger RNAs (mRNAs), 17,862 nonmodified proteins, and 6227 phosphoproteins harboring 31,595 phosphorylation sites quantified across maize development. Networks in which nodes are genes connected on the basis of highly correlated expression patterns of mRNAs were very different from networks that were based on coexpression of proteins. Roughly 85% of highly interconnected hubs were not conserved in expression between RNA and protein networks. However, networks from either data type were enriched in similar ontological categories and were effective in predicting known regulatory relationships. Integration of mRNA, protein, and phosphoprotein data sets greatly improved the predictive power of GRNs.

Decoding sORF translation - from small proteins to gene regulation

Translation is best known as the fundamental mechanism by which the ribosome converts a sequence of nucleotides into a string of amino acids. Extensive research over many years has elucidated the key principles of translation, and the majority of translated regions were thought to be known. The recent discovery of wide-spread translation outside of annotated protein-coding open reading frames (ORFs) came therefore as a surprise, raising the intriguing possibility that these newly discovered translated regions might have unrecognized protein-coding or gene-regulatory functions. Here, we highlight recent findings that provide evidence that some of these newly discovered translated short ORFs (sORFs) encode functional, previously missed small proteins, while others have regulatory roles. Based on known examples we will also speculate about putative additional roles and the potentially much wider impact that these translated regions might have on cellular homeostasis and gene regulation.

Maize OXIDATIVE STRESS2 Homologs Enhance Cadmium Tolerance in Arabidopsis through Activation of a Putative SAM-Dependent Methyltransferase Gene

Previously the Arabidopsis (Arabidopsis thaliana) zinc finger protein OXIDATIVE STRESS2 (AtOXS2) and four OXS2-like (AtO2L) family members were described to play a role in stress tolerance and stress escape. For stress escape, SOC1 was a target of AtOXS2. However, for stress tolerance, the downstream targets were not identified. We cloned two OXS2 homolog genes from sweet corn, ZmOXS2b and ZmO2L1 Both genes are transiently inducible by Cd treatment. When expressed in Arabidopsis, each enhances tolerance against cadmium. Further analysis showed that ZmOXS2b and ZmO2L1 proteins enhance Cd tolerance in Arabidopsis by activating at least one target gene, that encoding a putative S-adenosyl-l-Met-dependent methyltransferase superfamily protein (AT5G37990), which we named CIMT1 This activation involves the in vivo interaction with a segment of the CIMT1 promoter that contains a BOXS2 motif previously identified as the binding element for AtOXS2. More importantly, CIMT1 is induced by Cd treatment, and overexpression of this gene alone was sufficient to enhance Cd tolerance in Arabidopsis. The connection of ZmOXS2b and ZmO2L1 to Arabidopsis CIMT1 suggests a similar network may exist in maize (Zea mays) and may provide a clue to possibly using a CIMT1 maize homolog to engineer stress tolerance in a major crop.