Molecular investigation of Tuscan sweet cherries sampled over three years: gene expression analysis coupled to metabolomics and proteomics

Literature Review of Proteomics Approach Associated with Coffee

As a significant crop growing all across the world, coffee is mostly produced in the bean belt of our global atlas. Worldwide variations in environmental conditions are causing a decline in the yield and quality of coffee varieties. Coffee production is the main emphasis of several traditional breeding techniques. But conventional breeding methods are not sufficient to tackle the problems related to coffee. The field of genomics, which includes transcriptomics, proteomics, and metabolomics, has made great paces in the last ten years. Proteomics is a well-known technique used to enhance the growth, yield, breeding, and quality of different plants under stable and shifting environments. The regulation of specific enzymes, genes, protein expression, modification, translation, and other features played an important role in the enhancement of important plants. However, relatively less research on the proteomics approach for coffee has been published in the last few years. For this reason, some of the most important aspects of proteome profiling for coffee plants have been covered in this review, including growth, the somatic embryo technique, altitude, environmental adoption, drought, and the role that proteins and important enzymes play in the flavor and taste of coffee. This review can aid in the breeding of new cultivars and improve coffee attributes. Furthermore, the present literature can pave the way for proteomics research on coffee.

Integrating Metabolomics and Proteomics Technologies Provides Insights into the Flavor Precursor Changes at Different Maturity Stages of Arabica Coffee Cherries

The metabolic modulation of major flavor precursors during coffee cherry ripening is critical for the characteristic coffee flavor formation. However, the formation mechanism of flavor precursors during coffee cherry ripening remains unknown. In the present study, a colorimeter was employed to distinguish different maturity stages of coffee cherry based on the coffee cherry skin colors, and proteomics and metabolomics profiles were integrated to comprehensively investigate the flavor precursor dynamics involved in Arabica coffee cherry ripening. The data obtained in the present study provide an integral view of the critical pathways involved in flavor precursor changes during coffee cherry ripening. Moreover, the contributions of critical events in regulating the development of flavor precursors during the four ripening stages of coffee cherries, including the biosynthesis and metabolism pathways of organic acids, amino acids, flavonoids, and sugars, are discussed. Overall, a total of 456 difference express metabolites were selected, and they were identified as being concentrated in the four maturity stages of coffee cherries; furthermore, 76 crucial enzymes from the biosynthesis and metabolism of sugars, organic acids, amino acids, and flavonoids contributed to flavor precursor formation. Among these enzymes, 45 difference express proteins that could regulate 40 primary amino acids and organic acids flavor precursors were confirmed. This confirmation indicates that the metabolic pathways of amino acids and organic acids played a significant role in the flavor formation of Arabica coffee cherries during ripening. These results provide new insights into the protease modulation of flavor precursor changes in Arabica coffee cherry ripening.

Genome-wide identification of the TIFY family reveals JAZ subfamily function in response to hormone treatment in Betula platyphylla

BACKGROUND

The TIFY family is a plant-specific gene family and plays an important role in plant growth and development. But few reports have been reported on the phylogenetic analysis and gene expression profiling of TIFY family genes in birch (Betula platyphylla).

RESULTS

In this study, we characterized TIFY family and identified 12 TIFY genes and using phylogeny and chromosome mapping analysis in birch. TIFY family members were divided into JAZ, ZML, PPD and TIFY subfamilies. Phylogenetic analysis revealed that 12 TIFY genes were clustered into six evolutionary branches. The chromosome distribution showed that 12 TIFY genes were unevenly distributed on 5 chromosomes. Some TIFY family members were derived from gene duplication in birch. We found that six JAZ genes from JAZ subfamily played essential roles in response to Methyl jasmonate (MeJA), the JAZ genes were correlated with COI1 under MeJA. Co-expression and GO enrichment analysis further revealed that JAZ genes were related to hormone. JAZ proteins involved in the ABA and SA pathways. Subcellular localization experiments confirmed that the JAZ proteins were localized in the nucleus. Yeast two-hybrid assay showed that the JAZ proteins may form homologous or heterodimers to regulate hormones.

CONCLUSION

Our results provided novel insights into biological function of TIFY family and JAZ subfamily in birch. It provides the theoretical reference for in-depth analysis of plant hormone and molecular breeding design for resistance.

A molecular study of Italian ryegrass grown on Martian regolith simulant

In the last decade, the exploration of deep space has become the objective of the national space programs of many countries. The International Space Exploration Coordination Group has set a roadmap whose long-range strategy envisions the expansion of human presence in the solar system to progress with exploration and knowledge and to accelerate innovation. Crewed missions to Mars could be envisaged by 2040. In this scenario, finding ways to use the local resources for the provision of food, construction materials, propellants, pharmaceuticals is needed. Plants are important resources for deep space manned missions because they produce phytochemicals of pharmaceutical relevance, are sources of food and provide oxygen which is crucial in bioregenerative life support systems. Growth analysis and plant biomass yield have been previously evaluated on Martian regolith simulants; however, molecular approaches employing gene expression analysis and proteomics are still missing. The present work aims at filling this gap by providing molecular data on a representative member of the Poaceae, Lolium multiflorum Lam., grown on potting soil and a Martian regolith simulant (MMS-1). The molecular data were complemented with optical microscopy of root/leaf tissues and physico-chemical analyses. The results show that the plants grew for 2 weeks on regolith simulants. The leaves were bent downwards and chlorotic, the roots developed a lacunar aerenchyma and small brownish deposits containing Fe were observed. Gene expression analysis and proteomics revealed changes in transcripts related to the phenylpropanoid pathway, stress response, primary metabolism and proteins involved in translation and DNA methylation. Additionally, the growth of plants slightly but significantly modified the pH of the regolith simulants. The results here presented constitute a useful resource to get a comprehensive understanding of the major factors impacting the growth of plants on MMS-1.

Flavonoid Metabolic Profiles and Gene Mapping of Rice (Oryza sativa L.) Purple Gradient Grain Hulls

Rice (Oryza sativa L.) grain hull color is an easily observable trait and regarded as a crucial morphological marker in rice breeding. Here, a purple gradient grain hull mutant (pg) was found from natural mutations of a straw-white grain hull rice variety IARI 6184B (Orzya sativa L. subsp. indica). The color of the mutant grain hulls changed from straw-white to pink, then purple, and finally brownish-yellow. Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) identified 217 flavonoids, including 18 anthocyanins, among which cyanidin O-syringic acid had the highest concentration in pink (66.2 × 10⁶) and purple (68.0 × 10⁶) grain hulls. The relative contents of hesperetin O-malonyl-hexoside, apigenin derivatives, genistein derivatives, and kaempferol 3-O derivatives were consistently downregulated during pg grain hull development. Conversely, 12 anthocyanins were upregulated in colored hulls, and cyanidin 3-O-malonylhexoside was abundant only in pink and purple grain hulls. Moreover, the candidate gene was mapped into a 1.38 Mb region on chromosome 4 through bulked segregant analysis based on deep sequencing (BSA-seq) and gene mapping approaches. These results increased our understanding of anthocyanin biosynthesis in rice grains, helping rice breeders to select new rice varieties with desirable grain traits.

Research Progress and Trends in Metabolomics of Fruit Trees

Metabolomics is an indispensable part of modern systems biotechnology, applied in the diseases' diagnosis, pharmacological mechanism, and quality monitoring of crops, vegetables, fruits, etc. Metabolomics of fruit trees has developed rapidly in recent years, and many important research results have been achieved in combination with transcriptomics, genomics, proteomics, quantitative trait locus (QTL), and genome-wide association study (GWAS). These research results mainly focus on the mechanism of fruit quality formation, metabolite markers of special quality or physiological period, the mechanism of fruit tree's response to biotic/abiotic stress and environment, and the genetics mechanism of fruit trait. According to different experimental purposes, different metabolomic strategies could be selected, such as targeted metabolomics, non-targeted metabolomics, pseudo-targeted metabolomics, and widely targeted metabolomics. This article presents metabolomics strategies, key techniques in metabolomics, main applications in fruit trees, and prospects for the future. With the improvement of instruments, analysis platforms, and metabolite databases and decrease in the cost of the experiment, metabolomics will prompt the fruit tree research to achieve more breakthrough results.

The perennial fruit tree proteogenomics atlas: a spatial map of the sweet cherry proteome and transcriptome

Genome-wide transcriptome analysis provides systems-level insights into plant biology. Due to the limited depth of quantitative proteomics our understanding of gene-protein-complex stoichiometry is largely unknown in plants. Recently, the complexity of the proteome and its cell-/tissue-specific distribution have boosted the research community to the integration of transcriptomics and proteomics landscapes in a proteogenomic approach. Herein, we generated a quantitative proteome and transcriptome abundance atlas of 15 major sweet cherry (Prunus avium L., cv 'Tragana Edessis') tissues represented by 29 247 genes and 7584 proteins. Additionally, 199 984 alternative splicing events, particularly exon skipping and alternative 3' splicing, were identified in 23 383 transcribed regions of the analyzed tissues. Common signatures as well as differences between mRNA and protein quantities, including genes encoding transcription factors and allergens, within and across the different tissues are reported. Using our integrated dataset, we identified key putative regulators of fruit development, notably genes involved in the biosynthesis of anthocyanins and flavonoids. We also provide proteogenomic-based evidence for the involvement of ethylene signaling and pectin degradation in cherry fruit ripening. Moreover, clusters of genes and proteins with similar and different expression and suppression trends across diverse tissues and developmental stages revealed a relatively low RNA abundance-to-protein correlation. The present proteogenomic analysis allows us to identify 17 novel sweet cherry proteins without prior protein-level annotation evidenced in the currently available databases. To facilitate use by the community, we also developed the Sweet Cherry Atlas Database (https://grcherrydb.com/) for viewing and data mining these resources. This work provides new insights into the proteogenomics workflow in plants and a rich knowledge resource for future investigation of gene and protein functions in Prunus species.

Could Causal Discovery in Proteogenomics Assist in Understanding Gene-Protein Relations? A Perennial Fruit Tree Case Study Using Sweet Cherry as a Model

Genome-wide transcriptome analysis is a method that produces important data on plant biology at a systemic level. The lack of understanding of the relationships between proteins and genes in plants necessitates a further thorough analysis at the proteogenomic level. Recently, our group generated a quantitative proteogenomic atlas of 15 sweet cherry (Prunus avium L.) cv. ‘Tragana Edessis’ tissues represented by 29,247 genes and 7584 proteins. The aim of the current study was to perform a targeted analysis at the gene/protein level to assess the structure of their relation, and the biological implications. Weighted correlation network analysis and causal modeling were employed to, respectively, cluster the gene/protein pairs, and reveal their cause–effect relations, aiming to assess the associated biological functions. To the best of our knowledge, this is the first time that causal modeling has been employed within the proteogenomics concept in plants. The analysis revealed the complex nature of causal relations among genes/proteins that are important for traits of interest in perennial fruit trees, particularly regarding the fruit softening and ripening process in sweet cherry. Causal discovery could be used to highlight persistent relations at the gene/protein level, stimulating biological interpretation and facilitating further study of the proteogenomic atlas in plants.