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.

Genome-wide association of the metabolic shifts underpinning dark-induced senescence in Arabidopsis.

Dark-induced senescence provokes profound metabolic shifts to recycle nutrients and to guarantee plant survival. To date, research on these processes has largely focused on characterizing mutants deficient in individual pathways. Here, we adopted a time-resolved genome-wide association-based approach to characterize dark-induced senescence by evaluating the photochemical efficiency and content of primary and lipid metabolites at the beginning, or after 3 or 6 days in darkness. We discovered six patterns of metabolic shifts and identified 215 associations with 81 candidate genes being involved in this process. Among these associations, we validated the roles of four genes associated with glycine, galactinol, threonine, and ornithine levels. We also demonstrated the function of threonine and galactinol catabolism during dark-induced senescence. Intriguingly, we determined that the association between tyrosine contents and TYROSINE AMINOTRANSFERASE 1 influences enzyme activity of the encoded protein and transcriptional activity of the gene under normal and dark conditions, respectively. Moreover, the single-nucleotide polymorphisms affecting the expression of THREONINE ALDOLASE 1 and the amino acid transporter gene AVT1B, respectively, only underlie the variation in threonine and glycine levels in the dark. Taken together, these results allow us to present a very detailed model of the metabolic aspects of dark-induced senescence, as well as the process itself.

Going broad and deep: sequencing-driven insights into plant physiology, evolution, and crop domestication.

Deep sequencing is a term that has become embedded in the plant genomic literature in recent years and with good reason. A torrent of (largely) high-quality genomic and transcriptomic data has been collected and most of this has been publicly released. Indeed, almost 1000 plant genomes have been reported (www.plabipd.de) and the 2000 Plant Transcriptomes Project has long been completed. The EarthBioGenome project will dwarf even these milestones. That said, massive progress in understanding plant physiology, evolution, and crop domestication has been made by sequencing broadly (across a species) as well as deeply (within a single individual). We will outline the current state of the art in genome and transcriptome sequencing before we briefly review the most visible of these broad approaches, namely genome-wide association and transcriptome-wide association studies, as well as the compilation of pangenomes. This will include both (i) the most commonly used methods reliant on single nucleotide polymorphisms and short InDels and (ii) more recent examples which consider structural variants. We will subsequently present case studies exemplifying how their application has brought insight into either plant physiology or evolution and crop domestication. Finally, we will provide conclusions and an outlook as to the perspective for the extension of such approaches to different species, tissues, and biological processes.

Mass spectrometry-based metabolomics: a guide for annotation, quantification and best reporting practices.

Mass spectrometry-based metabolomics approaches can enable detection and quantification of many thousands of metabolite features simultaneously. However, compound identification and reliable quantification are greatly complicated owing to the chemical complexity and dynamic range of the metabolome. Simultaneous quantification of many metabolites within complex mixtures can additionally be complicated by ion suppression, fragmentation and the presence of isomers. Here we present guidelines covering sample preparation, replication and randomization, quantification, recovery and recombination, ion suppression and peak misidentification, as a means to enable high-quality reporting of liquid chromatography- and gas chromatography-mass spectrometry-based metabolomics-derived data.

Depicting the genetic and metabolic panorama of chemical diversity in the tea plant.

As a frequently consumed beverage worldwide, tea is rich in naturally important bioactive metabolites. Combining genetic, metabolomic and biochemical methodologies, here, we present a comprehensive study to dissect the chemical diversity in tea plant. A total of 2837 metabolites were identified at high-resolution with 1098 of them being structurally annotated and 63 of them were structurally identified. Metabolite-based genome-wide association mapping identified 6199 and 7823 metabolic quantitative trait loci (mQTL) for 971 and 1254 compounds in young leaves (YL) and the third leaves (TL), respectively. The major mQTL (i.e., P < 1.05 × 10-5, and phenotypic variation explained (PVE) > 25%) were further interrogated. Through extensive annotation of the tea metabolome as well as network-based analysis, this study broadens the understanding of tea metabolism and lays a solid foundation for revealing the natural variations in the chemical composition of the tea plant. Interestingly, we found that galloylations, rather than hydroxylations or glycosylations, were the largest class of conversions within the tea metabolome. The prevalence of galloylations in tea is unusual, as hydroxylations and glycosylations are typically the most prominent conversions of plant specialized metabolism. The biosynthetic pathway of flavonoids, which are one of the most featured metabolites in tea plant, was further refined with the identified metabolites. And we demonstrated the further mining and interpretation of our GWAS results by verifying two identified mQTL (including functional candidate genes CsUGTa, CsUGTb, and CsCCoAOMT) and completing the flavonoid biosynthetic pathway of the tea plant.

Research on the Technological Progress of CZT Array Detectors.

CdZnTe (CZT) is a new type of compound semiconductor that has emerged in recent years. Compared to other semiconductor materials, it possesses an ideal bandgap, high density, and high electron mobility, rendering it an excellent room-temperature composite semiconductor material for X-ray and γ-ray detectors. Due to the exceptional performance of CZT material, detectors manufactured using it exhibit high energy resolution, spatial resolution, and detection efficiency. They also have the advantage of operating at room temperature. CZT array detectors, furthermore, demonstrate outstanding spatial detection and three-dimensional imaging capabilities. Researchers worldwide have conducted extensive studies on this subject. This paper, building upon this foundation, provides a comprehensive analysis of CZT crystals and CZT array detectors and summarizes existing research to offer valuable insights for envisioning new detector methodologies.

Combining novel technologies with interdisciplinary basic research to enhance horticultural crops.

Horticultural crops mainly include fruits, vegetables, ornamental trees and flowers, and tea trees (Melaleuca alternifolia). They produce a variety of nutrients for the daily human diet in addition to the nutrition provided by staple crops, and some of them additionally possess ornamental and medicinal features. As such, horticultural crops make unique and important contributions to both food security and a colorful lifestyle. Under the current climate change scenario, the growing population and limited arable land means that agriculture, and especially horticulture, has been facing unprecedented challenges to meet the diverse demands of human daily life. Breeding horticultural crops with high quality and adaptability and establishing an effective system that combines cultivation, post-harvest handling, and sales becomes increasingly imperative for horticultural production. This review discusses characteristic and recent research highlights in horticultural crops, focusing on the breeding of quality traits and the mechanisms that underpin them. It additionally addresses challenges and potential solutions in horticultural production and post-harvest practices. Finally, we provide a prospective as to how emerging technologies can be implemented alongside interdisciplinary basic research to enhance our understanding and exploitation of horticultural crops.

A phased genome based on single sperm sequencing reveals crossover pattern and complex relatedness in tea plants.

For diploid organisms that are highly heterozygous, a phased haploid genome can greatly aid in functional genomic, population genetic and breeding studies. Based on the genome sequencing of 135 single sperm cells of the elite tea cultivar 'Fudingdabai', we herein phased the genome of Camellia sinensis, one of the most popular beverage crops worldwide. High-resolution genetic and recombination maps of Fudingdabai were constructed, which revealed that crossover (CO) positions were frequently located in the 5' and 3' ends of annotated genes, while CO distributions across the genome were random. The low CO frequency in tea can be explained by strong CO interference, and CO simulation revealed the proportion of interference insensitive CO ranged from 5.2% to 11.7%. We furthermore developed a method to infer the relatedness between tea accessions and detected complex kinship and genetic signatures of 106 tea accessions. Among them, 59 accessions were closely related with Fudingdabai and 31 of them were first-degree relatives. We additionally identified genes displaying allele specific expression patterns between the two haplotypes of Fudingdabai and genes displaying significantly differential expression levels between Fudingdabai and other haplotypes. These results lay the foundation for further investigation of genetic and epigenetic factors underpinning the regulation of gene expression and provide insights into the evolution of tea plants as well as a valuable genetic resource for future breeding efforts.

Population genomics of Zea species identifies selection signatures during maize domestication and adaptation.

BACKGROUND: Maize (Zea mays L. ssp. mays) was domesticated from teosinte (Zea mays ssp. parviglumis) about 9000 years ago in southwestern Mexico and adapted to a range of environments worldwide. Researchers have depicted the maize domestication and adaptation processes over the past two decades, but efforts have been limited either in sample size or genetic diversity. To better understand these processes, we conducted a genome-wide survey of 982 maize inbred lines and 190 teosinte accessions using over 40,000 single-nucleotide polymorphism markers. RESULTS: Population structure, principal component analysis, and phylogenetic trees all confirmed the evolutionary relationship between maize and teosinte, and determined the evolutionary lineage of all species within teosinte. Shared haplotype analysis showed similar levels of ancestral alleles from Zea mays ssp. parviglumis and Zea mays ssp. mexicana in maize. Scans for selection signatures identified 394 domestication sweeps by comparing wild and cultivated maize and 360 adaptation sweeps by comparing tropical and temperate maize. Permutation tests revealed that the public association signals for flowering time were highly enriched in the domestication and adaptation sweeps. Genome-wide association study identified 125 loci significantly associated with flowering-time traits, ten of which identified candidate genes that have undergone selection during maize adaptation. CONCLUSIONS: In this study, we characterized the history of maize domestication and adaptation at the population genomic level and identified hundreds of domestication and adaptation sweeps. This study extends the molecular mechanism of maize domestication and adaptation, and provides resources for basic research and genetic improvement in maize.

Dissection of the domestication-shaped genetic architecture of lettuce primary metabolism.

Lettuce (Lactuca sativa L.) is an important vegetable crop species worldwide. The primary metabolism of this species is essential for its growth, development and reproduction as well as providing a considerable direct source of energy and nutrition for humans. Here, through investigating 77 primary metabolites in 189 accessions including all major horticultural types and wild lettuce L. serriola we showed that the metabolites in L. serriola were different from those in cultivated lettuce. The findings were consistent with the demographic model of lettuce and supported a single domestication event for this species. Selection signals among these metabolic traits were detected. Specifically, galactinol, malate, quinate and threonate were significantly affected by the domestication process and cultivar differentiation of lettuce. Galactinol and raffinose might have been selected during stem lettuce cultivation as an adaption to the local environments in China. Furthermore, we identified 154 loci significantly associated with the level of 51 primary metabolites. Three genes (LG8749721, LG8763094 and LG5482522) responsible for the levels of galactinol, raffinose, quinate and chlorogenic acid were further dissected, which may have been the target of domestication and/or affected by local adaptation. Additionally, our findings strongly suggest that human selection resulted in reduced quinate and chlorogenic acid levels in cultivated lettuce. Our study thus provides beneficial genetic resources for lettuce quality improvement and sheds light on the domestication and evolution of this important leafy green.

Metabolomics analysis reveals differences in evolution between maize and rice.

Metabolites are the intermediate and final products of metabolism, which play essential roles in plant growth, evolution and adaptation to changing climates. However, it is unclear how evolution contributes to metabolic variation in plants. Here, we investigated the metabolomics data from leaf and seed tissues in maize and rice. Using principal components analysis based on leaf metabolites but not seed metabolites, metabolomics data could be clearly separated for rice Indica and Japonica accessions, while two maize subgroups, temperate and tropical, showed more visible admixture. Rice and maize seed exhibited significant interspecific differences in metabolic variation, while within rice, leaf and seed displayed similar metabolic variations. Among 10 metabolic categories, flavonoids had higher variation in maize than rice, indicating flavonoids are a key constituent of interspecific metabolic divergence. Interestingly, metabolic regulation was also found to be reshaped dramatically from positive to negative correlations, indicative of the differential evolutionary processes in maize and rice. Moreover, perhaps due to this divergence significantly more metabolic interactions were identified in rice than maize. Furthermore, in rice, the leaf was found to harbor much more intense metabolic interactions than the seed. Our result suggests that metabolomes are valuable for tracking evolutionary history, thereby complementing and extending genomic insights concerning which features are responsible for interspecific differentiation in maize and rice.

Application and Development of Noncontact Detection Method of α-Particles Based on Radioluminescence.

The detection of α particles is of great significance in military and civil nuclear facility management. At present, the contact method is mainly used to detect α particles, but its shortcomings limit the broad application of this method. In recent years, preliminary research on noncontact α-particle detection methods has been carried out. In this paper, the theory of noncontact α-particles detection methods is introduced and studied. We also review the direct detection and imaging methods of α particles based on the different wavelengths of fluorescence photons, and analyze the application and development of this method, providing an important reference for researchers to carry out related work.

Large-scale metabolite quantitative trait locus analysis provides new insights for high-quality maize improvement.

It is generally recognized that many favorable genes which were lost during domestication, including those related to both nutritional value and stress resistance, remain hidden in wild relatives. To uncover such genes in teosinte, an ancestor of maize, we conducted metabolite profiling in a BC2 F7 population generated from a cross between the maize wild relative (Zea mays ssp. mexicana) and maize inbred line Mo17. In total, 65 primary metabolites were quantified in four tissues (seedling-stage leaf, grouting-stage leaf, young kernel and mature kernel) with clear tissue-specific patterns emerging. Three hundred and fifty quantitative trait loci (QTLs) for these metabolites were obtained, which were distributed unevenly across the genome and included two QTL hotspots. Metabolite concentrations frequently increased in the presence of alleles from the teosinte genome while the opposite was observed for grain yield and shape trait QTLs. Combination of the multi-tissue transcriptome and metabolome data provided considerable insight into the metabolic variations between maize and its wild relatives. This study thus identifies favorable genes hidden in the wild relative which should allow us to balance high yield and quality in future modern crop breeding programs.

A NAC transcription factor and its interaction protein hinder abscisic acid biosynthesis by synergistically repressing NCED5 in Citrus reticulata.

Although abscisic acid (ABA) is a vital regulator of fruit ripening and several transcription factors have been reported to regulate ABA biosynthesis, reports of the effect of ABA on citrus ripening and the regulation of its biosynthesis by a multiple-transcription-factor complex are scarce. In the present study, a systematic metabolic, cytological, and transcriptome analysis of an ABA-deficient mutant (MT) of Citrus reticulata cv. Suavissima confirmed the positive effect of ABA on the citrus ripening process. The analysis of transcriptome profiles indicated that CrNAC036 played an important role in the ABA deficiency of the mutant, most likely due to an effect on the expression of 9-cis-epoxycarotenoid dioxygenase 5 (CrNCED5). Electrophoretic mobility shift assays and dual luciferase assays demonstrated that CrNAC036 can directly bind and negatively regulate CrNCED5 expression. Furthermore, yeast two-hybrid, bimolecular fluorescence complementation, and dual luciferase assays demonstrated that CrNAC036 interacted with CrMYB68, also down-regulating the expression of CrNCED5. Taken together, our results suggest that CrNAC036 and CrMYB68 synergistically inhibit ABA biosynthesis in citrus fruit by regulating the expression of CrNCED5.

Unraveling lipid metabolism in maize with time-resolved multi-omics data.

Maize is the cereal crop with the highest production worldwide, and its oil is a key energy resource. Improving the quantity and quality of maize oil requires a better understanding of lipid metabolism. To predict the function of maize genes involved in lipid biosynthesis, we assembled transcriptomic and lipidomic data sets from leaves of B73 and the high-oil line By804 in two distinct time-series experiments. The integrative analysis based on high-dimensional regularized regression yielded lipid-transcript associations indirectly validated by Gene Ontology and promoter motif enrichment analyses. The co-localization of lipid-transcript associations using the genetic mapping of lipid traits in leaves and seedlings of a B73 × By804 recombinant inbred line population uncovered 323 genes involved in the metabolism of phospholipids, galactolipids, sulfolipids and glycerolipids. The resulting association network further supported the involvement of 50 gene candidates in modulating levels of representatives from multiple acyl-lipid classes. Therefore, the proposed approach provides high-confidence candidates for experimental testing in maize and model plant species.

An integrated multi-layered analysis of the metabolic networks of different tissues uncovers key genetic components of primary metabolism in maize.

Primary metabolism plays a pivotal role in normal plant growth, development and reproduction. As maize is a major crop worldwide, the primary metabolites produced by maize plants are of immense importance from both calorific and nutritional perspectives. Here a genome-wide association study (GWAS) of 61 primary metabolites using a maize association panel containing 513 inbred lines identified 153 significant loci associated with the level of these metabolites in four independent tissues. The genome-wide expression level of 760 genes was also linked with metabolite levels within the same tissue. On average, the genetic variants at each locus or transcriptional variance of each gene identified here were estimated to have a minor effect (4.4-7.8%) on primary metabolic variation. Thirty-six loci or genes were prioritized as being worthy of future investigation, either with regard to functional characterization or for their utility for genetic improvement. This target list includes the well-known opaque 2 (O2) and lkr/sdh genes as well as many less well-characterized genes. During our investigation of these 36 loci, we analyzed the genetic components and variations underlying the trehalose, aspartate and aromatic amino acid pathways, thereby functionally characterizing four genes involved in primary metabolism in maize.

Broadening Our Portfolio in the Genetic Improvement of Maize Chemical Composition.

The adoption of recombinant inbred line and introgression line populations, as well as the study of association mapping panels, has greatly accelerated our ability to identify the genes underlying plant phenotypic variance. In tandem, the development of metabolomics approaches has greatly enhanced our ability to comprehensively define cellular chemical composition. As a consequence, breeding for chemical composition is being extended beyond our traditional targets of oil and protein to include components such as essential amino acids, vitamins, and antioxidant secondary metabolites with considerable purported consequences for human health. Here, we review the above-mentioned developments paying particular attention to the genetic architecture of metabolic traits as well as updating the perspective for utilizing metabolomics in maize improvement.

Risk scores for predicting dysphagia in critically ill patients after cardiac surgery.

BACKGROUND: This study aimed at developing and validating a scoring model to stratify critically ill patients after cardiac surgery based on risk for dysphagia, a common but often neglected complication. METHODS: Data were prospectively collected and analyzed from January 2016 to June 2017 from 395 consecutive post cardiac surgery patients at the cardiac care unit (CCU) at a single center; 103 (26.1%) developed dysphagia. Univariate and multivariate logistic analyses were used to identify independent predictors for dysphagia. The survival nomogram was developed on the basis of a multivariable Cox model, which allowed us to obtain survival probability estimations. The predictive performance of the nomogram was verified for discrimination and calibration. Areas under receiver operating characteristic curve analysis were used to illustrate and evaluate the diagnostic performance of the novel model. RESULTS: The final novel scoring model, named SSG-OD, consists of three independent factors: gastric intubation (OR = 1.024, 95% CI 1.015-1.033), sedative drug use duration (OR = 1.031, 95% CI 1.001-1.063) and stroke or not (OR = 6.182, 95% CI 3.028-12.617). SSG-OD identified patients at risk for dysphagia with sensitivity of 68.5% and specificity of 89.0% (OR = 0.833, 95% CI: 0.782-0.884). The positive and negative likelihood ratios were 6.22 and 0.35. CONCLUSIONS: The novel SSG-OD scoring system to risk stratify CCU patients for dysphagia is an easy-to-use bedside prognostication aid with good predictive performance and the potential to reduce aspiration incidence and accelerate recovery.

Genetic Determinants of the Network of Primary Metabolism and Their Relationships to Plant Performance in a Maize Recombinant Inbred Line Population.

Deciphering the influence of genetics on primary metabolism in plants will provide insights useful for genetic improvement and enhance our fundamental understanding of plant growth and development. Although maize (Zea mays) is a major crop for food and feed worldwide, the genetic architecture of its primary metabolism is largely unknown. Here, we use high-density linkage mapping to dissect large-scale metabolic traits measured in three different tissues (leaf at seedling stage, leaf at reproductive stage, and kernel at 15 d after pollination [DAP]) of a maize recombinant inbred line population. We identify 297 quantitative trait loci (QTLs) with moderate (86.2% of the mapped QTL, R(2) = 2.4 to 15%) to major effects (13.8% of the mapped QTL, R(2) >15%) for 79 primary metabolites across three tissues. Pairwise epistatic interactions between these identified loci are detected for more than 25.9% metabolites explaining 6.6% of the phenotypic variance on average (ranging between 1.7 and 16.6%), which implies that epistasis may play an important role for some metabolites. Key candidate genes are highlighted and mapped to carbohydrate metabolism, the tricarboxylic acid cycle, and several important amino acid biosynthetic and catabolic pathways, with two of them being further validated using candidate gene association and expression profiling analysis. Our results reveal a metabolite-metabolite-agronomic trait network that, together with the genetic determinants of maize primary metabolism identified herein, promotes efficient utilization of metabolites in maize improvement.