Pan-transcriptome assembly combined with multiple association analysis provides new insights into the regulatory network of specialized metabolites in the tea plant Camellia sinensis

In-depth exploration of the genomic diversity in tea varieties based on a newly constructed pangenome of Camellia sinensis

Tea, one of the most widely consumed beverages globally, exhibits remarkable genomic diversity in its underlying flavour and health-related compounds. In this study, we present the construction and analysis of a tea pangenome comprising a total of 11 genomes, with a focus on three newly sequenced genomes comprising the purple-leaved assamica cultivar "Zijuan", the temperature-sensitive sinensis cultivar "Anjibaicha" and the wild accession "L618" whose assemblies exhibited excellent quality scores as they profited from latest sequencing technologies. Our analysis incorporates a detailed investigation of transposon complement across the tea pangenome, revealing shared patterns of transposon distribution among the studied genomes and improved transposon resolution with long read technologies, as shown by long terminal repeat (LTR) Assembly Index analysis. Furthermore, our study encompasses a gene-centric exploration of the pangenome, exploring the genomic landscape of the catechin pathway with our study, providing insights on copy number alterations and gene-centric variants, especially for Anthocyanidin synthases. We constructed a gene-centric pangenome by structurally and functionally annotating all available genomes using an identical pipeline, which both increased gene completeness and allowed for a high functional annotation rate. This improved and consistently annotated gene set will allow for a better comparison between tea genomes. We used this improved pangenome to capture the core and dispensable gene repertoire, elucidating the functional diversity present within the tea species. This pangenome resource might serve as a valuable resource for understanding the fundamental genetic basis of traits such as flavour, stress tolerance, and disease resistance, with implications for tea breeding programmes.

Leaf morphology related genes revealed by integrating Pan-transcriptome, GWAS and eQTL analyses in a Liriodendron population

Leaf plays an indispensable role in plant development and growth. Although many known genes related to leaf morphology development have been identified, elucidating the complex genetic basis of leaf morphological traits remains a challenge. Liriodendron plants are common ornamental trees due to their unique leaf shapes, while the molecular mechanism underlying Liriodendron leaf morphogenesis has remained unknown. Herein, we firstly constructed a population-level pan-transcriptome of Liriodendron from 81 accessions to explore the expression presence or absence variations (ePAVs), global expression differences at the population level, as well as differentially expressed genes (DEGs) between the Liriodendron chinense and Liriodendron tulipifera accessions. Subsequently, we integrated a genome-wide association study (GWAS), expression quantitative trait loci (eQTL), and transcriptome-wide association study (TWAS) to identify candidate genes related to leaf morphology. Through GWAS analysis, we identified 18 and 17 significant allelic loci in the leaf size and leaf shape modules, respectively. In addition, we discerned 16 candidate genes in relation to leaf morphological traits via TWAS. Further, integrating the co-localization results of GWAS and eQTL, we determined two regulatory hotspot regions, hot88 and hot758, related to leaf size and leaf shape, respectively. Finally, co-expression analysis, eQTL, and linkage mapping together demonstrated that Lchi_4g10795 regulate their own expression levels through cis-eQTL to affect the expression of downstream genes and cooperatively participate in the development of Liriodendron leaf morphology. These findings will improve our understanding of the molecular regulatory mechanism of Liriodendron leaf morphogenesis and will also accelerate molecular breeding of Liriodendron.

The era of panomics-driven gene discovery in plants

Panomics is an approach to integrate multiple 'omics' datasets, generated using different individuals or natural variations. Considering their diverse phenotypic spectrum, the phenome is inherently associated with panomics-based science, which is further combined with genomics, transcriptomics, metabolomics, and other omics techniques, either independently or collectively. Panomics has been accelerated through recent technological advancements in the field of genomics that enable the detection of population-wide structural variations (SVs) and hence offer unprecedented insights into the genetic variations contributing to important agronomic traits. The present review provides the recent trends of panomics-driven gene discovery toward various traits related to plant development, stress tolerance, accumulation of specialized metabolites, and domestication/dedomestication. In addition, the success stories are highlighted in the broader context of enhancing crop productivity.

DataColor: unveiling biological data relationships through distinctive color mapping

In the era of rapid advancements in high-throughput omics technologies, the visualization of diverse data types with varying orders of magnitude presents a pressing challenge. To bridge this gap, we introduce DataColor, an all-encompassing software solution meticulously crafted to address this challenge. Our aim is to empower users with the ability to handle a wide array of data types through an assortment of tools, while simultaneously streamlining parameter selection for rapid insights and detailed enhancements. DataColor stands as a robust toolkit, encompassing 23 distinct tools coupled with over 600 parameters. The defining characteristic of this toolkit is its adept utilization of the color spectrum, allowing for the representation of data spanning diverse types and magnitudes. Through the integration of advanced algorithms encompassing data clustering, normalization, squarified layouts, and customizable parameters, DataColor unveils an abundance of insights that lay hidden within the intricate relationships embedded in the data. Whether you find yourself navigating the analysis of expansive datasets or embarking on the quest to visualize intricate patterns, DataColor stands as the comprehensive and potent solution. We extend the availability of DataColor to all users at no cost, accessible through the following link: https://github.com/frankgenome/DataColor.

Multiomics Analysis Reveals the Genetic Basis of Volatile Terpenoid Formation in Oolong Tea

Oolong tea has gained great popularity in China due to its pleasant floral and fruity aromas. Although numerous studies have investigated the aroma differences across various tea cultivars, the genetic mechanism is unclear. This study performed multiomics analysis of three varieties suitable for oolong tea and three others with different processing suitability. Our analysis revealed that oolong tea varieties contained higher levels of cadinane sesquiterpenoids. PanTFBS was developed to identify variants of transcription factor binding sites (TFBSs). We found that the CsDCS gene had two TFBS variants in the promoter sequence and a single nucleotide polymorphism (SNP) in the coding sequence. Integrating data on genetic variations, gene expression, and protein-binding sites indicated that CsDCS might be a pivotal gene involved in the biosynthesis of cadinane sesquiterpenoids. These findings advance our understanding of the genetic factors involved in the aroma formation of oolong tea and offer insights into the enhancement of tea aroma.

Analysis of Functional Single-Nucleotide Polymorphisms (SNPs) and Leaf Quality in Tea Collection under Nitrogen-Deficient Conditions

This study discusses the genetic mutations that have a significant association with economically important traits that would benefit tea breeders. The purpose of this study was to analyze the leaf quality and SNPs in quality-related genes in the tea plant collection of 20 mutant genotypes growing without nitrogen fertilizers. Leaf N-content, catechins, L-theanine, and caffeine contents were analyzed in dry leaves via HPLC. Additionally, the photochemical yield, electron transport efficiency, and non-photochemical quenching were analyzed using PAM-fluorimetry. The next generation pooled amplicon-sequencing approach was used for SNPs-calling in 30 key genes related to N metabolism and leaf quality. The leaf N content varied significantly among genotypes (p ≤ 0.05) from 2.3 to 3.7% of dry mass. The caffeine content varied from 0.7 to 11.7 mg g-1, and the L-theanine content varied from 0.2 to 5.8 mg g-1 dry leaf mass. Significant positive correlations were detected between the nitrogen content and biochemical parameters such as theanine, caffeine, and most of the catechins. However, significant negative correlations were observed between the photosynthetic parameters (Y, ETR, Fv/Fm) and several biochemical compounds, including rutin, Quercetin-3-O-glucoside, Kaempferol-3-O-rutinoside, Kaempferol-3-O-glucoside, Theaflavin-3'-gallate, gallic acid. From our SNP-analysis, three SNPs in WRKY57 were detected in all genotypes with a low N content. Moreover, 29 SNPs with a high or moderate effect were specific for #316 (high N-content, high quality) or #507 (low N-content, low quality). The use of a linear regression model revealed 16 significant associations; theaflavin, L-theanine, and ECG were associated with several SNPs of the following genes: ANSa, DFRa, GDH2, 4CL, AlaAT1, MYB4, LHT1, F3'5'Hb, UFGTa. Among them, seven SNPs of moderate effect led to changes in the amino acid contents in the final proteins of the following genes: ANSa, GDH2, 4Cl, F3'5'Hb, UFGTa. These results will be useful for further evaluations of the important SNPs and will help to provide a better understanding of the mechanisms of nitrogen uptake efficiency in tree crops.

5mC DNA methylation modification-mediated regulation in tissue functional differentiation and important flavor substance synthesis of tea plant (Camellia sinensis L.)

In plants, 5mC DNA methylation is an important and conserved epistatic mark involving genomic stability, gene transcriptional regulation, developmental regulation, abiotic stress response, metabolite synthesis, etc. However, the roles of 5mC DNA methylation modification (5mC methylation) in tea plant growth and development (in pre-harvest processing) and flavor substance synthesis in pre- and post-harvest processing are unknown. We therefore conducted a comprehensive methylation analysis of four key pre-harvest tissues (root, leaf, flower, and fruit) and two processed leaves during oolong tea post-harvest processing. We found that differential 5mC methylation among four key tissues is closely related to tissue functional differentiation and that genes expressed tissue-specifically, responsible for tissue-specific functions, maintain relatively low 5mC methylation levels relative to non-tissue-specifically expressed genes. Importantly, hypomethylation modifications of CsAlaDC and TS/GS genes in roots provided the molecular basis for the dominant synthesis of theanine in roots. In addition, integration of 5mC DNA methylationomics, metabolomics, and transcriptomics of post-harvest leaves revealed that content changes in flavor metabolites during oolong tea processing were closely associated with transcription level changes in corresponding metabolite synthesis genes, and changes in transcript levels of these important synthesis genes were strictly regulated by 5mC methylation. We further report that some key genes during processing are regulated by 5mC methylation, which can effectively explain the content changes of important aroma metabolites, including α-farnesene, nerolidol, lipids, and taste substances such as catechins. Our results not only highlight the key roles of 5mC methylation in important flavor substance synthesis in pre- and post-harvest processing, but also provide epimutation-related gene targets for future improvement of tea quality or breeding of whole-tissue high-theanine varieties.

Haplotype-Resolution Transcriptome Analysis Reveals Important Responsive Gene Modules and Allele-Specific Expression Contributions under Continuous Salt and Drought in Camellia sinensis

The tea plant, Camellia sinensis (L.) O. Kuntze, is one of the most important beverage crops with significant economic and cultural value. Global climate change and population growth have led to increased salt and drought stress, negatively affecting tea yield and quality. The response mechanism of tea plants to these stresses remains poorly understood due to the lack of reference genome-based transcriptional descriptions. This study presents a high-quality genome-based transcriptome dynamic analysis of C. sinensis' response to salt and drought stress. A total of 2244 upregulated and 2164 downregulated genes were identified under salt and drought stress compared to the control sample. Most of the differentially expression genes (DEGs) were found to involve divergent regulation processes at different time points under stress. Some shared up- and downregulated DEGs related to secondary metabolic and photosynthetic processes, respectively. Weighted gene co-expression network analysis (WGCNA) revealed six co-expression modules significantly positively correlated with C. sinensis' response to salt or drought stress. The MEpurple module indicated crosstalk between the two stresses related to ubiquitination and the phenylpropanoid metabolic regulation process. We identified 1969 salt-responsive and 1887 drought-responsive allele-specific expression (ASE) genes in C. sinensis. Further comparison between these ASE genes and tea plant heterosis-related genes suggests that heterosis likely contributes to the adversity and stress resistance of C. sinensis. This work offers new insight into the underlying mechanisms of C. sinensis' response to salt and drought stress and supports the improved breeding of tea plants with enhanced salt and drought tolerance.

Molecular markers in tea plant (Camellia sinensis): Applications to evolution, genetic identification, and molecular breeding

Tea plants have a long cultivation history in the world, and the beverage (tea) made from its leaves is well known in the world. Due to the characteristics of self-incompatibility, long-term natural and artificial hybridization, tea plants have a very complex genetic background, which make the classification of tea plants unclear. Molecular marker, one type of genetic markers, has the advantages of stable inheritance, large amount of information, and high reliability. The development of molecular marker has facilitated the understanding of complex tea germplasm resources. So far, molecular markers had played important roles in the study of the origin and evolution, the preservation and identification of tea germplasms, and the excellent cultivars breeding of tea plants. However, the information is scattered, making it difficult to understand the advance of molecular markers in tea plants. In this paper, we summarized the development process and types of molecular markers in tea plants. In addition, the application advance of these molecular markers in tea plants was reviewed. Perspectives of molecular markers in tea plants were also systematically provided and discussed. The elaboration of molecular markers in this paper should help us to renew understanding of its application in tea plants.

Biotechnological Advances to Improve Abiotic Stress Tolerance in Crops

The major challenges that agriculture is facing in the twenty-first century are increasing droughts, water scarcity, flooding, poorer soils, and extreme temperatures due to climate change. However, most crops are not tolerant to extreme climatic environments. The aim in the near future, in a world with hunger and an increasing population, is to breed and/or engineer crops to tolerate abiotic stress with a higher yield. Some crop varieties display a certain degree of tolerance, which has been exploited by plant breeders to develop varieties that thrive under stress conditions. Moreover, a long list of genes involved in abiotic stress tolerance have been identified and characterized by molecular techniques and overexpressed individually in plant transformation experiments. Nevertheless, stress tolerance phenotypes are polygenetic traits, which current genomic tools are dissecting to exploit their use by accelerating genetic introgression using molecular markers or site-directed mutagenesis such as CRISPR-Cas9. In this review, we describe plant mechanisms to sense and tolerate adverse climate conditions and examine and discuss classic and new molecular tools to select and improve abiotic stress tolerance in major crops.