Integrated multi-omics and genetic analyses reveal molecular determinants underlying Arabidopsis snap33 mutant phenotype

The secretory pathway is essential for plant immunity, delivering diverse antimicrobial molecules into the extracellular space. Arabidopsis thaliana soluble N-ethylmaleimide-sensitive-factor attachment protein receptor SNAP33 is a key actor of this process. The snap33 mutant displays dwarfism and necrotic lesions, however the molecular determinants of its macroscopic phenotypes remain elusive. Here, we isolated several new snap33 mutants that exhibited constitutive cell death and H2O2 accumulation, further defining snap33 as an autoimmune mutant. We then carried out quantitative transcriptomic and proteomic analyses showing that numerous defense transcripts and proteins were up-regulated in the snap33 mutant, among which genes/proteins involved in defense hormone, pattern-triggered immunity, and nucleotide-binding domain leucine-rich-repeat receptor signaling. qRT-PCR analyses and hormone dosages supported these results. Furthermore, genetic analyses elucidated the diverse contributions of the main defense hormones and some nucleotide-binding domain leucine-rich-repeat receptor signaling actors in the establishment of the snap33 phenotype, emphasizing the preponderant role of salicylic acid over other defense phytohormones. Moreover, the accumulation of pattern-triggered immunity and nucleotide-binding domain leucine-rich-repeat receptor signaling proteins in the snap33 mutant was confirmed by immunoblotting analyses and further shown to be salicylic acid-dependent. Collectively, this study unveiled molecular determinants underlying the Arabidopsis snap33 mutant phenotype and brought new insights into autoimmunity signaling.

Impact of high atmospheric carbon dioxide on the biotic stress response of the model cereal species Brachypodium distachyon

Losses due to disease and climate change are among the most important issues currently facing crop production. It is therefore important to establish the impact of climate change, and particularly of high carbon dioxide (hCO2), on plant immunity in cereals, which provide 60% of human calories. The aim of this study was to determine if hCO2 impacts Brachypodium distachyon immunity, a model plant for temperate cereals. Plants were grown in air (430 ppm CO2) and at two high CO2 conditions, one that is relevant to projections within the coming century (1000 ppm) and a concentration sufficient to saturate photosynthesis (3000 ppm). The following measurements were performed: phenotyping and growth, salicylic acid contents, pathogen resistance tests, and RNAseq analysis of the transcriptome. Improved shoot development was observed at both 1000 and 3000 ppm. A transcriptomic analysis pointed to an increase in primary metabolism capacity under hCO2. Alongside this effect, up-regulation of genes associated with secondary metabolism was also observed. This effect was especially evident for the terpenoid and phenylpropanoid pathways, and was accompanied by enhanced expression of immunity-related genes and accumulation of salicylic acid. Pathogen tests using the fungus Magnaporthe oryzae revealed that hCO2 had a complex effect, with enhanced susceptibility to infection but no increase in fungal development. The study reveals that immunity in B. distachyon is modulated by growth at hCO2 and allows identification of pathways that might play a role in this effect.

The Arabidopsis transcription factor NLP2 regulates early nitrate responses and integrates nitrate assimilation with energy and carbon skeleton supply

Nitrate signaling improves plant growth under limited nitrate availability and, hence, optimal resource use for crop production. Whereas several transcriptional regulators of nitrate signaling have been identified, including the Arabidopsis thaliana transcription factor NIN-LIKE PROTEIN7 (NLP7), additional regulators are expected to fine-tune this pivotal physiological response. Here, we characterized Arabidopsis NLP2 as a top-tier transcriptional regulator of the early nitrate response gene regulatory network. NLP2 interacts with NLP7 in vivo and shares key molecular features such as nitrate-dependent nuclear localization, DNA-binding motif, and some target genes with NLP7. Genetic, genomic, and metabolic approaches revealed a specific role for NLP2 in the nitrate-dependent regulation of carbon and energy-related processes that likely influence plant growth under distinct nitrogen environments. Our findings highlight the complementarity and specificity of NLP2 and NLP7 in orchestrating a multitiered nitrate regulatory network that links nitrate assimilation with carbon and energy metabolism for efficient nitrogen use and biomass production.

Genome-Wide Transcriptomic Analysis of the Effects of Infection with the Hemibiotrophic Fungus Colletotrichum lindemuthianum on Common Bean

Bean anthracnose caused by the hemibiotrophic fungus Colletotrichum lindemuthianum is one of the most important diseases of common bean (Phaseolus vulgaris) in the world. In the present study, the whole transcriptome of common bean infected with C. lindemuthianum during compatible and incompatible interactions was characterized at 48 and 72 hpi, corresponding to the biotrophy phase of the infection cycle. Our results highlight the prominent role of pathogenesis-related (PR) genes from the PR10/Bet vI family as well as a complex interplay of different plant hormone pathways including Ethylene, Salicylic acid (SA) and Jasmonic acid pathways. Gene Ontology enrichment analysis reveals that infected common bean seedlings responded by down-regulation of photosynthesis, ubiquitination-mediated proteolysis and cell wall modifications. In infected common bean, SA biosynthesis seems to be based on the PAL pathway instead of the ICS pathway, contrarily to what is described in Arabidopsis. Interestingly, ~30 NLR were up-regulated in both contexts. Overall, our results suggest that the difference between the compatible and incompatible reaction is more a question of timing and strength, than a massive difference in differentially expressed genes between these two contexts. Finally, we used RT-qPCR to validate the expression patterns of several genes, and the results showed an excellent agreement with deep sequencing.

Corrigendum: Genotypic Variation of Nitrogen Use Efficiency and Amino Acid Metabolism in Barley

[This corrects the article DOI: 10.3389/fpls.2021.807798.].

Genotypic Variation of Nitrogen Use Efficiency and Amino Acid Metabolism in Barley

Owing to the large genetic diversity of barley and its resilience under harsh environments, this crop is of great value for agroecological transition and the need for reduction of nitrogen (N) fertilizers inputs. In the present work, we investigated the diversity of a North African barley genotype collection in terms of growth under limiting N (LN) or ample N (HN) supply and in terms of physiological traits including amino acid content in young seedlings. We identified a Moroccan variety, Laanaceur, accumulating five times more lysine in its leaves than the others under both N nutritional regimes. Physiological characterization of the barley collection showed the genetic diversity of barley adaptation strategies to LN and highlighted a genotype x environment interaction. In all genotypes, N limitation resulted in global biomass reduction, an increase in C concentration, and a higher resource allocation to the roots, indicating that this organ undergoes important adaptive metabolic activity. The most important diversity concerned leaf nitrogen use efficiency (LNUE), root nitrogen use efficiency (RNUE), root nitrogen uptake efficiency (RNUpE), and leaf nitrogen uptake efficiency (LNUpE). Using LNUE as a target trait reflecting barley capacity to deal with N limitation, this trait was positively correlated with plant nitrogen uptake efficiency (PNUpE) and RNUpE. Based on the LNUE trait, we determined three classes showing high, moderate, or low tolerance to N limitation. The transcriptomic approach showed that signaling, ionic transport, immunity, and stress response were the major functions affected by N supply. A candidate gene encoding the HvNRT2.10 transporter was commonly up-regulated under LN in the three barley genotypes investigated. Genes encoding key enzymes required for lysine biosynthesis in plants, dihydrodipicolinate synthase (DHPS) and the catabolic enzyme, the bifunctional Lys-ketoglutarate reductase/saccharopine dehydrogenase are up-regulated in Laanaceur and likely account for a hyperaccumulation of lysine in this genotype. Our work provides key physiological markers of North African barley response to low N availability in the early developmental stages.

Retrograde signalling from the mitochondria to the nucleus translates the positive effect of ethylene on dormancy breaking of Arabidopsis thaliana seeds

Ethylene and reactive oxygen species (ROS) regulate seed dormancy alleviation, but the molecular basis of their action and crosstalk remains largely unknown. Here we studied the mechanism of Arabidopsis seed dormancy release by ethylene using cell imaging, and genetic and transcriptomics approaches, in order to tackle its possible interaction with ROS homeostasis. We found that the effect of ethylene on seed germination required ROS production by the mitochondrial electron transport chain. Seed response to ethylene involved a mitochondrial retrograde response (MRR) through nuclear ROS production and upregulation of the MRR components AOX1a and ANAC013, but also required the activation of the ethylene canonical pathway. Together our data allowed deciphering of the mode of action of ethylene on seed germination and the associated dynamics of ROS production. Our findings highlight the occurrence of retrograde signalling in seed germination.

Gene expression predictions and networks in natural populations supports the omnigenic theory

Background

Recent literature on the differential role of genes within networks distinguishes core from peripheral genes. If previous works have shown contrasting features between them, whether such categorization matters for phenotype prediction remains to be studied.

Results

We measured 17 phenotypic traits for 241 cloned genotypes from a Populus nigra collection, covering growth, phenology, chemical and physical properties. We also sequenced RNA for each genotype and built co-expression networks to define core and peripheral genes. We found that cores were more differentiated between populations than peripherals while being less variable, suggesting that they have been constrained through potentially divergent selection. We also showed that while cores were overrepresented in a subset of genes statistically selected for their capacity to predict the phenotypes (by Boruta algorithm), they did not systematically predict better than peripherals or even random genes.

Conclusion

Our work is the first attempt to assess the importance of co-expression network connectivity in phenotype prediction. While highly connected core genes appear to be important, they do not bear enough information to systematically predict better quantitative traits than other gene sets.

DiCoExpress: a tool to process multifactorial RNAseq experiments from quality controls to co-expression analysis through differential analysis based on contrasts inside GLM models

BACKGROUND

RNAseq is nowadays the method of choice for transcriptome analysis. In the last decades, a high number of statistical methods, and associated bioinformatics tools, for RNAseq analysis were developed. More recently, statistical studies realised neutral comparison studies using benchmark datasets, shedding light on the most appropriate approaches for RNAseq data analysis.

RESULTS

DiCoExpress is a script-based tool implemented in R that includes methods chosen based on their performance in neutral comparisons studies. DiCoExpress uses pre-existing R packages including FactoMineR, edgeR and coseq, to perform quality control, differential, and co-expression analysis of RNAseq data. Users can perform the full analysis, providing a mapped read expression data file and a file containing the information on the experimental design. Following the quality control step, the user can move on to the differential expression analysis performed using generalized linear models thanks to the automated contrast writing function. A co-expression analysis is implemented using the coseq package. Lists of differentially expressed genes and identified co-expression clusters are automatically analyzed for enrichment of annotations provided by the user. We used DiCoExpress to analyze a publicly available RNAseq dataset on the transcriptional response of Brassica napus L. to silicon treatment in plant roots and mature leaves. This dataset, including two biological factors and three replicates for each condition, allowed us to demonstrate in a tutorial all the features of DiCoExpress.

CONCLUSIONS

DiCoExpress is an R script-based tool allowing users to perform a full RNAseq analysis from quality controls to co-expression analysis through differential analysis based on contrasts inside generalized linear models. DiCoExpress focuses on the statistical modelling of gene expression according to the experimental design and facilitates the data analysis leading the biological interpretation of the results.

Combining laser-assisted microdissection (LAM) and RNA-seq allows to perform a comprehensive transcriptomic analysis of epidermal cells of Arabidopsis embryo

BACKGROUND

Genome-wide characterization of tissue- or cell-specific gene expression is a recurrent bottleneck in biology. We have developed a sensitive approach based on ultra-low RNA sequencing coupled to laser assisted microdissection for analyzing different tissues of the small Arabidopsis embryo.

METHODS AND RESULTS

We first characterized the number of genes detected according to the quantity of tissue yield and total RNA extracted. Our results revealed that as low as 0.02 mm² of tissue and 50 pg of total RNA can be used without compromising the number of genes detected. The optimised protocol was used to compare the epidermal versus mesophyll cell transcriptomes of cotyledons at the torpedo-shaped stage of embryo development. The approach was validated by the recovery of well-known epidermal genes such AtML1 or AtPDF2 and genes involved in flavonoid and cuticular waxes pathways. Moreover, the interest and sensitivity of this approach were highlighted by the characterization of several transcription factors preferentially expressed in epidermal cells.

CONCLUSION

This technical advance unlocks some current limitations of transcriptomic analyses and allows to investigate further and efficiently new biological questions for which only a very small amounts of cells need to be isolated. For instance, it paves the way to increasing the spatial accuracy of regulatory networks in developing small embryo of Arabidopsis or other plant tissues.