Multi-Metabolomics Coupled with Quantitative Descriptive Analysis Revealed Key Alterations in Phytochemical Composition and Sensory Qualities of Decaffeinated Green and Black Tea from the Same Fresh Leaves.

The supercritical CO2-based decaffeination (SCD) method can be used to prepare decaffeinated tea, but its overall effect on the phytochemicals, volatiles, and sensory qualities of green and black teas is still unclear, and its suitability to prepare decaffeinated green and black teas still needs to be compared. This study revealed the effect of SCD on phytochemicals, volatiles, and sensory qualities in black and green tea prepared from the same tea leaves, and compared the suitability of preparing decaffeinated green and black teas using SCD. The results showed that the SCD could remove 98.2 and 97.1% of the caffeine in green and black tea, respectively. However, it can cause further losses of phytochemicals in green and black teas, specifically the loss of epigallocatechin gallate, epigallocatechin, epicatechin gallate, and gallocatechin gallate in green tea and the loss of theanine and arginine in green and black teas. After the decaffeination, both green and black teas lost some volatiles but also generated new volatiles. Especially, the fruit/flower-like aroma, ocimene, linalyl acetate, geranyl acetate, and D-limonene, were generated in the decaffeinated black tea, while herbal/green-like aroma, ß-cyclocitral, 2-ethylhexanol, and safranal, were generated in the decaffeinated green tea. The overall acceptance of decaffeinated green tea decreased due to the substantial reduction in bitterness and astringency, while the overall acceptance of decaffeinated black tea significantly increased. Therefore, SCD is more suitable for the preparation of decaffeinated black tea.

Rapid identification of the green tea geographical origin and processing month based on near-infrared hyperspectral imaging combined with chemometrics.

The geographical origin and processing month of green tea greatly affect its economic value and consumer acceptance. This study investigated the feasibility of combining near-infrared hyperspectral imaging (NIR-HSI) with chemometrics for the identification of green tea. Tea samples produced in three regions of Chongqing (southeastern Chongqing, northeastern Chongqing, and western Chongqing) for four months (from May to August 2020) were collected. Principal component analysis (PCA) was used to reduce data dimensionality and visualize the clustering of samples in different categories. Linear partial least squares-discriminant analysis (PLS-DA) and nonlinear support vector machine (SVM) algorithms were used to develop discriminant models. The PCA-SVM models based on the first four and first five principal components (PCs) achieved the best accuracies of 97.5% and 95% in the prediction set for geographical origin and processing month of green tea, respectively. This study demonstrated the feasibility of HSI in the identification of green tea species, providing a rapid and nondestructive method for the evaluation and control of green tea quality.

The dynamics of vertebrate homeobox gene evolution: gain and loss of genes in mouse and human lineages.

BACKGROUND: Homeobox genes are a large and diverse group of genes, many of which play important roles in transcriptional regulation during embryonic development. Comparison of homeobox genes between species may provide insights into the evolution of developmental mechanisms. RESULTS: Here we report an extensive survey of human and mouse homeobox genes based on their most recent genome assemblies, providing the first comprehensive analysis of mouse homeobox genes and updating an earlier survey of human homeobox genes. In total we recognize 333 human homeobox loci comprising 255 probable genes and 78 probable pseudogenes, and 324 mouse homeobox loci comprising 279 probable genes and 45 probable pseudogenes (accessible at http://homeodb.zoo.ox.ac.uk). Comparison to partial genome sequences from other species allows us to resolve which differences are due to gain of genes and which are due to gene losses. CONCLUSIONS: We find there has been much more homeobox gene loss in the rodent evolutionary lineage than in the primate lineage. While humans have lost only the Msx3 gene, mice have lost Ventx, Argfx, Dprx, Shox, Rax2, LOC647589, Tprx1 and Nanognb. This analysis provides insight into the patterns of homeobox gene evolution in the mammals, and a step towards relating genomic evolution to phenotypic evolution.

HomeoDB2: functional expansion of a comparative homeobox gene database for evolutionary developmental biology.

Homeobox gene database (HomeoDB), a manually curated database of homeobox genes and their classification, has been well received since its release in 2008. Here, we report HomeoDB2, an expansion and improvement of the original database that provides greater functionality for the user. HomeoDB2 includes all homeobox loci from 10 animal genomes (human, mouse, chicken, frog, zebrafish, amphioxus, nematode, fruitfly, beetle, honeybee) plus tools for downloading sequences, comparing between species and BLAST searching. HomeoDB2 provides a resource for studying the dynamics of homeobox gene evolution, and is freely accessible at http://homeodb.zoo.ox.ac.uk.

Comparative genomics of chondrichthyan Hoxa clusters.

BACKGROUND: The chondrichthyan or cartilaginous fish (chimeras, sharks, skates and rays) occupy an important phylogenetic position as the sister group to all other jawed vertebrates and as an early lineage to diverge from the vertebrate lineage following two whole genome duplication events in vertebrate evolution. There have been few comparative genomic analyses incorporating data from chondrichthyan fish and none comparing genomic information from within the group. We have sequenced the complete Hoxa cluster of the Little Skate (Leucoraja erinacea) and compared to the published Hoxa cluster of the Horn Shark (Heterodontus francisci) and to available data from the Elephant Shark (Callorhinchus milii) genome project. RESULTS: A BAC clone containing the full Little Skate Hoxa cluster was fully sequenced and assembled. Analyses of coding sequences and conserved non-coding elements reveal a strikingly high level of conservation across the cartilaginous fish, with twenty ultraconserved elements (100%,100 bp) found between Skate and Horn Shark, compared to three between human and marsupials. We have also identified novel potential non-coding RNAs in the Skate BAC clone, some of which are conserved to other species. CONCLUSION: We find that the Little Skate Hoxa cluster is remarkably similar to the previously published Horn Shark Hoxa cluster with respect to sequence identity, gene size and intergenic distance despite over 180 million years of separation between the two lineages. We suggest that the genomes of cartilaginous fish are more highly conserved than those of tetrapods or teleost fish and so are more likely to have retained ancestral non-coding elements. While useful for isolating homologous DNA, this complicates bioinformatic approaches to identify chondrichthyan-specific non-coding DNA elements.

HomeoDB: a database of homeobox gene diversity.

The homeobox genes are a large and diverse group of genes, many of which play important roles in the embryonic development of animals. Comparative study of homeobox genes, both within and between species, requires an evolutionary-based classification. HomeoDB was designed and implemented as a manually curated database to collect and present homeobox genes in an evolutionarily structured way, allowing genes, gene families and gene classes to be compared between species more readily than was possible previously. In its first release, HomeoDB includes all homeobox genes from human, amphioxus (Branchiostoma floridae) and fruitfly (Drosophila melanogaster); additional species can be added. HomeoDB is freely accessible at (http://homeodb.cbi.pku.edu.cn).

PlantTFDB: a comprehensive plant transcription factor database.

Transcription factors (TFs) play key roles in controlling gene expression. Systematic identification and annotation of TFs, followed by construction of TF databases may serve as useful resources for studying the function and evolution of transcription factors. We developed a comprehensive plant transcription factor database PlantTFDB (http://planttfdb.cbi.pku.edu.cn), which contains 26,402 TFs predicted from 22 species, including five model organisms with available whole genome sequence and 17 plants with available EST sequences. To provide comprehensive information for those putative TFs, we made extensive annotation at both family and gene levels. A brief introduction and key references were presented for each family. Functional domain information and cross-references to various well-known public databases were available for each identified TF. In addition, we predicted putative orthologs of those TFs among the 22 species. PlantTFDB has a simple interface to allow users to search the database by IDs or free texts, to make sequence similarity search against TFs of all or individual species, and to download TF sequences for local analysis.

DPTF: a database of poplar transcription factors.

The database of poplar transcription factors (DPTF) is a plant transcription factor (TF) database containing 2576 putative poplar TFs distributed in 64 families. These TFs were identified from both computational prediction and manual curation. We have provided extensive annotations including sequence features, functional domains, GO assignment and expression evidence for all TFs. In addition, DPTF contains cross-links to the Arabidopsis and rice transcription factor databases making it a unique resource for genome-scale comparative studies of transcriptional regulation in model plants. Availiability: DPTF is available at http://dptf.cbi.pku.edu.cn.

DRTF: a database of rice transcription factors.

SUMMARY: DRTF contains 2025 putative transcription factors (TFs) in Oryza sativa L. ssp. indica and 2384 in ssp. japonica, distributed in 63 families, identified by computational prediction and manual curation. It includes detailed annotations of each TF including sequence features, functional domains, Gene Ontology assignment, chromosomal localization, EST and microarray expression information, as well as multiple sequence alignment of the DNA-binding domains for each TF family. The database can be browsed and searched with a user-friendly web interface. AVAILABILITY: DRTF is available at http://drtf.cbi.pku.edu.cn