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Summary: Chickpea is the world's fourth largest grown legume crop, which significantly contributes to food security by providing calories and dietary protein globally. However, the increased frequency of drought stress has significantly reduced chickpea production in recent years. Here, we have performed a field experiment with 36 diverse chickpea genotypes to evaluate grain yield, photosynthetic activities and molecular traits related to drought stress. For metabolomics analysis, leaf tissue was collected at three time points representing different pod‐filling stages. We identified L‐threonic acid, fructose and sugar alcohols involved in chickpea adaptive drought response within the mid‐pod‐filling stage. A stress susceptibility index for each genotype was calculated to identify tolerance capacity under drought, distributing the 36 genotypes into four categories from best to worst performance. To understand how biochemical mechanisms control different traits for genetic improvement, we performed a differential Jacobian analysis, which unveiled the interplay between various metabolic pathways across three time points, including higher flux towards inositol interconversions, glycolysis for high‐performing genotypes, fumarate to malate conversion, and carbon and nitrogen metabolism perturbations. Metabolic GWAS (mGWAS) analysis uncovered gene candidates involved in glycolysis and MEP pathway corroborating with the differential biochemical Jacobian results. Accordingly, this proposed data analysis strategy bridges the gap from pure statistical association to causal biochemical relations by exploiting natural variation. Our study offers new perspectives on the genetic and metabolic understanding of drought tolerance‐associated diversity in the chickpea metabolome and led to the identification of metabolic control points that can be also tested in other legume crops. [ABSTRACT FROM AUTHOR]

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How different stressors impact plant health and memory when they are imposed in different generations in wild ecosystems is still scarce. Here, we address how different environments shape heritable memory for the next generation in seeds and seedlings of Pinus radiata, a long‐lived species with economic interest. The performance of the seedlings belonging to two wild clonal subpopulations (optimal fertirrigation vs. slightly stressful conditions) was tested under heat stress through physiological profiling and comparative time‐series chloroplast proteomics. In addition, we explored the seeds conducting a physiological characterization and targeted transcriptomic profiling in both subpopulations. Our results showed differential responses between them, evidencing a cross‐stress transgenerational memory. Seedlings belonging to the stressed subpopulation retained key proteins related to Photosystem II, chloroplast‐to‐nucleus signalling and osmoprotection which helped to overcome the applied heat stress. The seeds also showed a differential gene expression profile for targeted genes and microRNAs, as well as an increased content of starch and secondary metabolites, molecules which showed potential interest as biomarkers for early selection of primed plants. Thus, these finds not only delve into transgenerational cross‐stress memory in trees, but also provide a new biotechnological tool for forest design. Summary statement: These results provide a deep knowledge of transgenerational cross‐stress priming in long‐lived species, revealing potential biomarkers for early selection of primmed seeds as a core strategy for designing climate‐smart forestry. [ABSTRACT FROM AUTHOR]

The recovery and maintenance of plant homeostasis under stressful environments are complex processes involving organelle crosstalk for a coordinated cellular response. Here, we revealed through nuclear and chloroplast subcellular proteomics, biochemical cell profiles and targeted transcriptomics how chloroplasts and nuclei developed their responses under increased temperatures in a long‐lived species (Pinus radiata). Parallel to photosynthetic impairment and reactive oxygen species production in the chloroplast, a DNA damage response was triggered in the nucleus followed by an altered chromatin conformation. In addition, in the nuclei, we found several proteins, such as HEMERA or WHIRLY, which change their locations from the chloroplasts to the nuclei carrying the stress message. Additionally, our data showed a deep rearrangement of RNA metabolism in both organelles, revealing microRNAs and AGO1 as potential regulators of the acclimation mechanisms. Altogether, our study highlights the synchronisation among the different stages required for thermotolerance acquisition in P. radiata, pointing out the role of chromatin conformation and posttranscriptional gene regulation in overcoming heat stress and assuring plant survival for the following years. Summary Statement: Here, we show how nuclei and chloroplasts exchange signals and coordinate their proteomes to overcome heat stress in Pinus radiata. The acclimation process is reflected in a profound physiological rearrangement and a reprogramming of RNA metabolism including an increase in microRNA contents. [ABSTRACT FROM AUTHOR]

Holm oak (Quercus ilex) is the most important and representative species of the Mediterranean forest and of the Spanish agrosilvo-pastoral “dehesa” ecosystem. Despite its environmental and economic interest, Holm oak is an orphan species whose biology is very little known, especially at the molecular level. In order to increase the knowledge on the chemical composition and metabolism of this tree species, the employment of a holistic and multi-omics approach, in the Systems Biology direction would be necessary. However, for orphan and recalcitrant plant species, specific analytical and bioinformatics tools have to be developed in order to obtain adequate quality and data-density before to coping with the study of its biology. By using a plant sample consisting of a pool generated by mixing equal amounts of homogenized tissue from acorn embryo, leaves, and roots, protocols for transcriptome (NGS-Illumina), proteome (shotgun LC-MS/MS), and metabolome (GC-MS) studies have been optimized. These analyses resulted in the identification of around 62629 transcripts, 2380 protein species, and 62 metabolites. Data are compared with those reported for model plant species, whose genome has been sequenced and is well annotated, including Arabidopsis, japonica rice, poplar, and eucalyptus. RNA and protein sequencing favored each other, increasing the number and confidence of the proteins identified and correcting erroneous RNA sequences. The integration of the large amount of data reported using bioinformatics tools allows the Holm oak metabolic network to be partially reconstructed: from the 127 metabolic pathways reported in KEGG pathway database, 123 metabolic pathways can be visualized when using the described methodology. They included: carbohydrate and energy metabolism, amino acid metabolism, lipid metabolism, nucleotide metabolism, and biosynthesis of secondary metabolites. The TCA cycle was the pathway most represented with 5 out of 10 metabolites, 6 out of 8 protein enzymes, and 8 out of 8 enzyme transcripts. On the other hand, gaps, missed pathways, included metabolism of terpenoids and polyketides and lipid metabolism. The multi-omics resource generated in this work will set the basis for ongoing and future studies, bringing the Holm oak closer to model species, to obtain a better understanding of the molecular mechanisms underlying phenotypes of interest (productive, tolerant to environmental cues, nutraceutical value) and to select elite genotypes to be used in restoration and reforestation programs, especially in a future climate change scenario. [ABSTRACT FROM AUTHOR]

In the era of high-throughput biology, it is necessary to develop a simple pipeline for metabolic pathway reconstruction in plant orphan species. However, obtaining a global picture of the plant metabolism may be challenging, especially in nonmodel species. Moreover, the use of bioinformatics tools and statistical analyses is required. This chapter describes how to use different software and online tools for the reconstruction of metabolic pathways of plant species using existing pathway knowledge. In particular, Quercus ilex omics data is employed to develop the present pipeline.