PEO: Plant Expression Omnibus - a comparative transcriptomic database for 103 Archaeplastida.

The Plant Expression Omnibus (PEO) is a web application that provides biologists with access to gene expression insights across over 100 plant species, ~60 000 manually annotated RNA-seq samples, and more than 4 million genes. The tool allows users to explore the expression patterns of genes across different organs, identify organ-specific genes, and discover top co-expressed genes for any gene of interest. PEO also provides functional annotations for each gene, allowing for the identification of genetic modules and pathways. PEO is designed to facilitate comparative kingdom-wide gene expression analysis and provide a valuable resource for plant biology research. We provide two case studies to demonstrate the utility of PEO in identifying candidate genes in pollen coat biosynthesis in Arabidopsis and investigating the biosynthetic pathway components of capsaicin in Capsicum annuum. The database is freely available at https://expression.plant.tools/.

A method for mining condition-specific co-expressed genes in Camellia sinensis based on k-means clustering.

BACKGROUND: As one of the world's most important beverage crops, tea plants (Camellia sinensis) are renowned for their unique flavors and numerous beneficial secondary metabolites, attracting researchers to investigate the formation of tea quality. With the increasing availability of transcriptome data on tea plants in public databases, conducting large-scale co-expression analyses has become feasible to meet the demand for functional characterization of tea plant genes. However, as the multidimensional noise increases, larger-scale co-expression analyses are not always effective. Analyzing a subset of samples generated by effectively downsampling and reorganizing the global sample set often leads to more accurate results in co-expression analysis. Meanwhile, global-based co-expression analyses are more likely to overlook condition-specific gene interactions, which may be more important and worthy of exploration and research. RESULTS: Here, we employed the k-means clustering method to organize and classify the global samples of tea plants, resulting in clustered samples. Metadata annotations were then performed on these clustered samples to determine the "conditions" represented by each cluster. Subsequently, we conducted gene co-expression network analysis (WGCNA) separately on the global samples and the clustered samples, resulting in global modules and cluster-specific modules. Comparative analyses of global modules and cluster-specific modules have demonstrated that cluster-specific modules exhibit higher accuracy in co-expression analysis. To measure the degree of condition specificity of genes within condition-specific clusters, we introduced the correlation difference value (CDV). By incorporating the CDV into co-expression analyses, we can assess the condition specificity of genes. This approach proved instrumental in identifying a series of high CDV transcription factor encoding genes upregulated during sustained cold treatment in Camellia sinensis leaves and buds, and pinpointing a pair of genes that participate in the antioxidant defense system of tea plants under sustained cold stress. CONCLUSIONS: To summarize, downsampling and reorganizing the sample set improved the accuracy of co-expression analysis. Cluster-specific modules were more accurate in capturing condition-specific gene interactions. The introduction of CDV allowed for the assessment of condition specificity in gene co-expression analyses. Using this approach, we identified a series of high CDV transcription factor encoding genes related to sustained cold stress in Camellia sinensis. This study highlights the importance of considering condition specificity in co-expression analysis and provides insights into the regulation of the cold stress in Camellia sinensis.

LSTrAP-denovo: Automated Generation of Transcriptome Atlases for Eukaryotic Species Without Genomes.

Despite the abundance of species with transcriptomic data, a significant number of species still lack sequenced genomes, making it difficult to study gene function and expression in these organisms. While de novo transcriptome assembly can be used to assemble protein-coding transcripts from RNA-sequencing (RNA-seq) data, the datasets used often only feature samples of arbitrarily selected or similar experimental conditions, which might fail to capture condition-specific transcripts. We developed the Large-Scale Transcriptome Assembly Pipeline for de novo assembled transcripts (LSTrAP-denovo) to automatically generate transcriptome atlases of eukaryotic species. Specifically, given an NCBI TaxID, LSTrAP-denovo can (1) filter undesirable RNA-seq accessions based on read data, (2) select RNA-seq accessions via unsupervised machine learning to construct a sample-balanced dataset for download, (3) assemble transcripts via over-assembly, (4) functionally annotate coding sequences (CDS) from assembled transcripts and (5) generate transcriptome atlases in the form of expression matrices for downstream transcriptomic analyses. LSTrAP-denovo is easy to implement, written in Python, and is freely available at https://github.com/pengkenlim/LSTrAP-denovo/.

The Arabidopsis electron-transfer flavoprotein:ubiquinone oxidoreductase is required during normal seed development and germination.

The importance of the alternative donation of electrons to the ubiquinol pool via the electron-transfer flavoprotein/electron-transfer flavoprotein:ubiquinone oxidoreductase (ETF/ETFQO) complex has been demonstrated. However, the functional significance of this pathway during seed development and germination remains to be elucidated. To assess the function of this pathway, we performed a detailed metabolic and transcriptomic analysis of Arabidopsis mutants to test the molecular consequences of a dysfunctional ETF/ETFQO pathway. We demonstrate that the disruption of this pathway compromises seed germination in the absence of an external carbon source and also impacts seed size and yield. Total protein and storage protein content is reduced in dry seeds, whilst sucrose levels remain invariant. Seeds of ETFQO and related mutants were also characterized by an altered fatty acid composition. During seed development, lower levels of fatty acids and proteins accumulated in the etfqo-1 mutant as well as in mutants in the alternative electron donors isovaleryl-CoA dehydrogenase (ivdh-1) and d-2-hydroxyglutarate dehydrogenase (d2hgdh1-2). Furthermore, the content of several amino acids was increased in etfqo-1 mutants during seed development, indicating that these mutants are not using such amino acids as alternative energy source for respiration. Transcriptome analysis revealed alterations in the expression levels of several genes involved in energy and hormonal metabolism. Our findings demonstrated that the alternative pathway of respiration mediated by the ETF/ETFQO complex affects seed germination and development by directly adjusting carbon storage during seed filling. These results indicate a role for the pathway in the normal plant life cycle to complement its previously defined roles in the response to abiotic stress.

New molecular components that regulates the transcriptional hub in root hairs: coupling environmental signals to endogenous hormones to coordinate growth.

Root hairs (RH) have become an important model system for studying plant growth and how plants modulate their growth in response to cell-intrinsic and environmental stimuli. Here, we will discuss recent advances in our understanding of the molecular mechanisms underlying the growth of Arabidopsis thaliana RH in the interface between responses to environmental cues (e.g. nutrients such as nitrates, phosphate and microorganism) and hormonal stimuli (e.g. auxin). RH growth is under the control of several transcription factors that are also under strong regulation at different levels. In this review we highlight recent new discoveries along these transcriptional pathways that may increase our capacity to enhance nutrient uptake by the roots in the context of abiotic stresses. We used text-mining capacities of the PlantConnectome database to generate the most updated view of RH growth in these complex biological contexts.

Expression Atlas of Selaginella moellendorffii Provides Insights into the Evolution of Vasculature, Secondary Metabolism, and Roots.

Selaginella moellendorffii is a representative of the lycophyte lineage that is studied to understand the evolution of land plant traits such as the vasculature, leaves, stems, roots, and secondary metabolism. However, only a few studies have investigated the expression and transcriptional coordination of Selaginella genes, precluding us from understanding the evolution of the transcriptional programs behind these traits. We present a gene expression atlas comprising all major organs, tissue types, and the diurnal gene expression profiles for S. moellendorffii We show that the transcriptional gene module responsible for the biosynthesis of lignocellulose evolved in the ancestor of vascular plants and pinpoint the duplication and subfunctionalization events that generated multiple gene modules involved in the biosynthesis of various cell wall types. We demonstrate how secondary metabolism is transcriptionally coordinated and integrated with other cellular pathways. Finally, we identify root-specific genes and show that the evolution of roots did not coincide with an increased appearance of gene families, suggesting that the development of new organs does not coincide with increased fixation of new gene functions. Our updated database at conekt.plant.tools represents a valuable resource for studying the evolution of genes, gene families, transcriptomes, and functional gene modules in the Archaeplastida kingdom.

Volatile-Based Diagnosis for Pathogenic Wood-Rot Fungus Fulvifomes siamensis by Electronic Nose (E-Nose) and Solid-Phase Microextraction/Gas Chromatography/Mass Spectrometry.

Wood rot fungus Fulvifomes siamensis infects multiple urban tree species commonly planted in Singapore. A commercial e-nose (Cyranose 320) was used to differentiate some plant and fungi volatiles. The e-nose distinctly clustered the volatiles at 0.25 ppm, and this sensitivity was further increased to 0.05 ppm with the use of nitrogen gas to purge the system and set up the baseline. Nitrogen gas baseline resulted in a higher magnitude of sensor responses and a higher number of responsive sensors. The specificity of the e-nose for F. siamensis was demonstrated by distinctive clustering of its pure culture, fruiting bodies collected from different tree species, and in diseased tissues infected by F. siamensis with a 15-min incubation time. This good specificity was supported by the unique volatile profiles revealed by SPME GC-MS analysis, which also identified the signature volatile for F. siamensis-1,2,4,5-tetrachloro-3,6-dimethoxybenzene. In field conditions, the e-nose successfully identified F. siamensis fruiting bodies on different tree species. The findings of concentration-based clustering and host-tree-specific volatile profiles for fruiting bodies provide further insights into the complexity of volatile-based diagnosis that should be taken into consideration for future studies.

Genomic, transcriptomic, and metabolomic analysis of Oldenlandia corymbosa reveals the biosynthesis and mode of action of anti-cancer metabolites.

Plants accumulate a vast array of secondary metabolites, which constitute a natural resource for pharmaceuticals. Oldenlandia corymbosa belongs to the Rubiaceae family, and has been used in traditional medicine to treat different diseases, including cancer. However, the active metabolites of the plant, their biosynthetic pathway and mode of action in cancer are unknown. To fill these gaps, we exposed this plant to eight different stress conditions and combined different omics data capturing gene expression, metabolic profiles, and anti-cancer activity. Our results show that O. corymbosa extracts are active against breast cancer cell lines and that ursolic acid is responsible for this activity. Moreover, we assembled a high-quality genome and uncovered two genes involved in the biosynthesis of ursolic acid. Finally, we also revealed that ursolic acid causes mitotic catastrophe in cancer cells and identified three high-confidence protein binding targets by Cellular Thermal Shift Assay (CETSA) and reverse docking. Altogether, these results constitute a valuable resource to further characterize the biosynthesis of active metabolites in the Oldenlandia group, while the mode of action of ursolic acid will allow us to further develop this valuable compound.

LSTrAP-Kingdom: an automated pipeline to generate annotated gene expression atlases for kingdoms of life.

MOTIVATION: There are now more than two million RNA sequencing experiments for plants, animals, bacteria and fungi publicly available, allowing us to study gene expression within and across species and kingdoms. However, the tools allowing the download, quality control and annotation of this data for more than one species at a time are currently missing. RESULTS: To remedy this, we present the Large-Scale Transcriptomic Analysis Pipeline in Kingdom of Life (LSTrAP-Kingdom) pipeline, which we used to process 134 521 RNA-seq samples, achieving ∼12 000 processed samples per day. Our pipeline generated quality-controlled, annotated gene expression matrices that rival the manually curated gene expression data in identifying functionally related genes. AVAILABILITY AND IMPLEMENTATION: LSTrAP-Kingdom is available from: https://github.com/wirriamm/plants-pipeline and is fully implemented in Python and Bash. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Malaria.tools-comparative genomic and transcriptomic database for Plasmodium species.

Malaria is a tropical parasitic disease caused by the Plasmodium genus, which resulted in an estimated 219 million cases of malaria and 435 000 malaria-related deaths in 2017. Despite the availability of the Plasmodium falciparum genome since 2002, 74% of the genes remain uncharacterized. To remedy this paucity of functional information, we used transcriptomic data to build gene co-expression networks for two Plasmodium species (P. falciparum and P. berghei), and included genomic data of four other Plasmodium species, P. yoelii, P. knowlesi, P. vivax and P. cynomolgi, as well as two non-Plasmodium species from the Apicomplexa, Toxoplasma gondii and Theileria parva. The genomic and transcriptomic data were incorporated into the resulting database, malaria.tools, which is preloaded with tools that allow the identification and cross-species comparison of co-expressed gene neighbourhoods, clusters and life stage-specific expression, thus providing sophisticated tools to predict gene function. Moreover, we exemplify how the tools can be used to easily identify genes relevant for pathogenicity and various life stages of the malaria parasite. The database is freely available at www.malaria.tools.

The avocado genome informs deep angiosperm phylogeny, highlights introgressive hybridization, and reveals pathogen-influenced gene space adaptation.

The avocado, Persea americana, is a fruit crop of immense importance to Mexican agriculture with an increasing demand worldwide. Avocado lies in the anciently diverged magnoliid clade of angiosperms, which has a controversial phylogenetic position relative to eudicots and monocots. We sequenced the nuclear genomes of the Mexican avocado race, P. americana var. drymifolia, and the most commercially popular hybrid cultivar, Hass, and anchored the latter to chromosomes using a genetic map. Resequencing of Guatemalan and West Indian varieties revealed that ∼39% of the Hass genome represents Guatemalan source regions introgressed into a Mexican race background. Some introgressed blocks are extremely large, consistent with the recent origin of the cultivar. The avocado lineage experienced 2 lineage-specific polyploidy events during its evolutionary history. Although gene-tree/species-tree phylogenomic results are inconclusive, syntenic ortholog distances to other species place avocado as sister to the enormous monocot and eudicot lineages combined. Duplicate genes descending from polyploidy augmented the transcription factor diversity of avocado, while tandem duplicates enhanced the secondary metabolism of the species. Phenylpropanoid biosynthesis, known to be elicited by Colletotrichum (anthracnose) pathogen infection in avocado, is one enriched function among tandems. Furthermore, transcriptome data show that tandem duplicates are significantly up- and down-regulated in response to anthracnose infection, whereas polyploid duplicates are not, supporting the general view that collections of tandem duplicates contribute evolutionarily recent "tuning knobs" in the genome adaptive landscapes of given species.

Structural landscape of the complete genomes of dengue virus serotypes and other viral hemorrhagic fevers.

BACKGROUND: With more than 300 million potentially infected people every year, and with the expanded habitat of mosquitoes due to climate change, Dengue virus (DENV) cannot be considered anymore only a tropical disease. The RNA secondary structure is a functional characteristic of RNA viruses, and together with the accumulated high-throughput sequencing data could provide general insights towards understanding virus biology. Here, we profiled the RNA secondary structure of > 7000 complete viral genomes from 11 different species focusing on viral hemorrhagic fevers, including DENV serotypes, EBOV, and YFV. RESULTS: In our work we demonstrated that the secondary structure and presence of protein-binding domains in the genomes can be used as intrinsic signature to further classify the viruses. With our predictive approach, we achieved high prediction scores of the secondary structure (AUC up to 0.85 with experimental data), and computed consensus secondary structure profiles using hundreds of in silico models. We observed that viruses show different structural patterns, where e.g., DENV-2 and Ebola virus tend to be less structured than the other viruses. Furthermore, we observed virus-specific correlations between secondary structure and the number of interaction sites with human proteins, reaching a correlation of 0.89 in the case of Zika virus. We also identified that helicases-encoding regions are more structured in several flaviviruses, while the regions encoding for the contact proteins exhibit virus-specific clusters in terms of RNA structure and potential protein-RNA interactions. We also used structural data to study the geographical distribution of DENV, finding a significant difference between DENV-3 from Asia and South-America, where the structure is also driving the clustering more than sequence identity, which could imply different evolutionary routes of this subtype. CONCLUSIONS: Our massive computational analysis provided novel results regarding the secondary structure and the interaction with human proteins, not only for DENV serotypes, but also for other flaviviruses and viral hemorrhagic fevers-associated viruses. We showed how the RNA secondary structure can be used to categorise viruses, and even to further classify them based on the interaction with proteins. We envision that these approaches can be used to further classify and characterise these complex viruses.

Transcriptomic and Proteomic Insights into Amborella trichopoda Male Gametophyte Functions.

Flowering plants (angiosperms) are characterized by pollen tubes (PTs; male gametophytes) carrying two immobile sperm cells that grow over long distances through the carpel toward the ovules, where double fertilization is executed. It is not understood how these reproductive structures evolved, which genes occur de novo in male gametophytes of angiosperms, and to which extent PT functions are conserved among angiosperms. To contribute to a deeper understanding of the evolution of gametophyte functions, we generated RNA sequencing data from seven reproductive and two vegetative control tissues of the basal angiosperm Amborella trichopoda and complemented these with proteomic data of pollen grains (PGs) and PTs. The eudicot model plant Arabidopsis (Arabidopsis thaliana) served as a reference organism for data analysis, as more than 200 genes have been associated with male gametophyte functions in this species. We describe methods to collect bicellular A. trichopoda PGs, to induce their germination in vitro, and to monitor PT growth and germ cell division. Transcriptomic and proteomic analyses indicate that A. trichopoda PGs are prepared for germination requiring lipids, energy, but likely also reactive oxygen species, while PTs are especially characterized by catabolic/biosynthetic and transport processes including cell wall biosynthesis and gene regulation. Notably, a number of pollen-specific genes were lacking in Arabidopsis, and the number of genes involved in pollen signaling is significantly reduced in A. trichopoda In conclusion, we provide insight into male gametophyte functions of the most basal angiosperm and establish a valuable resource for future studies on the evolution of flowering plants.

LSTrAP-Crowd: prediction of novel components of bacterial ribosomes with crowd-sourced analysis of RNA sequencing data.

BACKGROUND: Bacterial resistance to antibiotics is a growing health problem that is projected to cause more deaths than cancer by 2050. Consequently, novel antibiotics are urgently needed. Since more than half of the available antibiotics target the structurally conserved bacterial ribosomes, factors involved in protein synthesis are thus prime targets for the development of novel antibiotics. However, experimental identification of these potential antibiotic target proteins can be labor-intensive and challenging, as these proteins are likely to be poorly characterized and specific to few bacteria. Here, we use a bioinformatics approach to identify novel components of protein synthesis. RESULTS: In order to identify these novel proteins, we established a Large-Scale Transcriptomic Analysis Pipeline in Crowd (LSTrAP-Crowd), where 285 individuals processed 26 terabytes of RNA-sequencing data of the 17 most notorious bacterial pathogens. In total, the crowd processed 26,269 RNA-seq experiments and used the data to construct gene co-expression networks, which were used to identify more than a hundred uncharacterized genes that were transcriptionally associated with protein synthesis. We provide the identity of these genes together with the processed gene expression data. CONCLUSIONS: We identified genes related to protein synthesis in common bacterial pathogens and thus provide a resource of potential antibiotic development targets for experimental validation. The data can be used to explore additional vulnerabilities of bacteria, while our approach demonstrates how the processing of gene expression data can be easily crowd-sourced.

Diurnal.plant.tools: Comparative Transcriptomic and Co-expression Analyses of Diurnal Gene Expression of the Archaeplastida Kingdom.

Almost all organisms coordinate some aspects of their biology through the diurnal cycle. Photosynthetic organisms, and plants especially, have established complex programs that coordinate physiological, metabolic and developmental processes with the changing light. The diurnal regulation of the underlying transcriptional processes is observed when groups of functionally related genes (gene modules) are expressed at a specific time of the day. However, studying the diurnal regulation of these gene modules in the plant kingdom was hampered by the large amount of data required for the analyses. To meet this need, we used gene expression data from 17 diurnal studies spanning the whole Archaeplastida kingdom (Plantae kingdom in the broad sense) to make an online diurnal database. We have equipped the database with tools that allow user-friendly cross-species comparisons of gene expression profiles, entire co-expression networks, co-expressed clusters (involved in specific biological processes), time-specific gene expression and others. We exemplify how these tools can be used by studying three important biological questions: (i) the evolution of cell division, (ii) the diurnal control of gene modules in algae and (iii) the conservation of diurnally controlled modules across species. The database is freely available at http://diurnal.plant.tools.

Gene expression analysis of Cyanophora paradoxa reveals conserved abiotic stress responses between basal algae and flowering plants.

The glaucophyte Cyanophora paradoxa represents the most basal member of the kingdom Archaeplastida, but the function and expression of most of its genes are unknown. This information is needed to uncover how functional gene modules, that is groups of genes performing a given function, evolved in the plant kingdom. We have generated a gene expression atlas capturing responses of Cyanophora to various abiotic stresses. The data were included in the CoNekT-Plants database, enabling comparative transcriptomic analyses across two algae and six land plants. We demonstrate how the database can be used to study gene expression, co-expression networks and gene function in Cyanophora, and how conserved transcriptional programs can be identified. We identified gene modules involved in phycobilisome biosynthesis, response to high light and cell division. While we observed no correlation between the number of differentially expressed genes and the impact on growth of Cyanophora, we found that the response to stress involves a conserved, kingdom-wide transcriptional reprogramming, which is activated upon most stresses in algae and land plants. The Cyanophora stress gene expression atlas and the tools found in the https://conekt.plant.tools/ database thus provide a useful resource to reveal functionally related genes and stress responses in the plant kingdom.

Appropriate Thiamin Pyrophosphate Levels Are Required for Acclimation to Changes in Photoperiod.

Thiamin pyrophosphate (TPP) is the active form of vitamin B1 and works as an essential cofactor for enzymes in key metabolic pathways, such as the tricarboxylic acid (TCA) cycle and the pentose phosphate pathway. Although its action as a coenzyme has been well documented, the roles of TPP in plant metabolism are still not fully understood. Here, we investigated the functions of TPP in the regulation of the metabolic networks during photoperiod transition using previously described Arabidopsis (Arabidopsis thaliana) riboswitch mutant plants, which accumulate thiamin vitamers. The results show that photosynthetic and metabolic phenotypes of TPP riboswitch mutants are photoperiod dependent. Additionally, the mutants are more distinct from control plants when plants are transferred from a short-day to a long-day photoperiod, suggesting that TPP also plays a role in metabolic acclimation to the photoperiod. Control plants showed changes in the amplitude of diurnal oscillation in the levels of metabolites, including glycine, maltose, and fumarate, following the photoperiod transition. Interestingly, many of these changes are not present in TPP riboswitch mutant plants, demonstrating their lack of metabolic flexibility. Our results also indicate a close relationship between photorespiration and the TCA cycle, as TPP riboswitch mutants accumulate less photorespiratory intermediates. This study shows the potential role of vitamin B1 in the diurnal regulation of central carbon metabolism in plants and the importance of maintaining appropriate cellular levels of thiamin vitamers for the plant's metabolic flexibility and ability to acclimate to an altered photoperiod.

CoNekT: an open-source framework for comparative genomic and transcriptomic network analyses.

The recent accumulation of gene expression data in the form of RNA sequencing creates unprecedented opportunities to study gene regulation and function. Furthermore, comparative analysis of the expression data from multiple species can elucidate which functional gene modules are conserved across species, allowing the study of the evolution of these modules. However, performing such comparative analyses on raw data is not feasible for many biologists. Here, we present CoNekT (Co-expression Network Toolkit), an open source web server, that contains user-friendly tools and interactive visualizations for comparative analyses of gene expression data and co-expression networks. These tools allow analysis and cross-species comparison of (i) gene expression profiles; (ii) co-expression networks; (iii) co-expressed clusters involved in specific biological processes; (iv) tissue-specific gene expression; and (v) expression profiles of gene families. To demonstrate these features, we constructed CoNekT-Plants for green alga, seed plants and flowering plants (Picea abies, Chlamydomonas reinhardtii, Vitis vinifera, Arabidopsis thaliana, Oryza sativa, Zea mays and Solanum lycopersicum) and thus provide a web-tool with the broadest available collection of plant phyla. CoNekT-Plants is freely available from http://conekt.plant.tools, while the CoNekT source code and documentation can be found at https://github.molgen.mpg.de/proost/CoNekT/.

PhytoNet: comparative co-expression network analyses across phytoplankton and land plants.

Phytoplankton consists of autotrophic, photosynthesizing microorganisms that are a crucial component of freshwater and ocean ecosystems. However, despite being the major primary producers of organic compounds, accounting for half of the photosynthetic activity worldwide and serving as the entry point to the food chain, functions of most of the genes of the model phytoplankton organisms remain unknown. To remedy this, we have gathered publicly available expression data for one chlorophyte, one rhodophyte, one haptophyte, two heterokonts and four cyanobacteria and integrated it into our PlaNet (Plant Networks) database, which now allows mining gene expression profiles and identification of co-expressed genes of 19 species. We exemplify how the co-expressed gene networks can be used to reveal functionally related genes and how the comparative features of PhytoNet allow detection of conserved transcriptional programs between cyanobacteria, green algae, and land plants. Additionally, we illustrate how the database allows detection of duplicated transcriptional programs within an organism, as exemplified by two putative DNA repair programs within Chlamydomonas reinhardtii. PhytoNet is available from www.gene2function.de.

AtRsgA from Arabidopsis thaliana is important for maturation of the small subunit of the chloroplast ribosome.

Plastid ribosomes are very similar in structure and function to the ribosomes of their bacterial ancestors. Since ribosome biogenesis is not thermodynamically favorable under biological conditions it requires the activity of many assembly factors. Here we have characterized a homolog of bacterial RsgA in Arabidopsis thaliana and show that it can complement the bacterial homolog. Functional characterization of a strong mutant in Arabidopsis revealed that the protein is essential for plant viability, while a weak mutant produced dwarf, chlorotic plants that incorporated immature pre-16S ribosomal RNA into translating ribosomes. Physiological analysis of the mutant plants revealed smaller, but more numerous, chloroplasts in the mesophyll cells, reduction of chlorophyll a and b, depletion of proplastids from the rib meristem and decreased photosynthetic electron transport rate and efficiency. Comparative RNA sequencing and proteomic analysis of the weak mutant and wild-type plants revealed that various biotic stress-related, transcriptional regulation and post-transcriptional modification pathways were repressed in the mutant. Intriguingly, while nuclear- and chloroplast-encoded photosynthesis-related proteins were less abundant in the mutant, the corresponding transcripts were increased, suggesting an elaborate compensatory mechanism, potentially via differentially active retrograde signaling pathways. To conclude, this study reveals a chloroplast ribosome assembly factor and outlines the transcriptomic and proteomic responses of the compensatory mechanism activated during decreased chloroplast function.