The volatile organic compounds generated from the Maillard reaction between l-ascorbic acid and l-cysteine in hot compressed water.

BACKGROUND: Hot compressed water (HCW), also known as subcritical water (SCW), refers to high-temperature compressed water in a special physical and chemical state. It is an emerging technology for natural product extraction. The volatile organic compounds (VOCs) generated from the Maillard reaction between l-ascorbic acid (ASA) and l-cysteine (Cys) have attracted significant interest in the flavor and fragrance industry. This study aimed to explore the formation mechanism of VOCs from ASA and Cys and examine the effects of reaction parameters such as temperature, time, and pH in HCW. RESULTS: The identified VOCs were predominantly thiophene derivatives, polysulfides, and pyrazine derivatives in HCW. The findings indicated that thiophene derivatives were formed under various pH conditions, with polysulfide formation favored under acidic conditions and pyrazine derivative formation preferred under weak alkaline conditions, specifically at pH 8.0. CONCLUSION: The Maillard reaction between ASA and Cys mainly produced thiophene derivatives, polysulfides, and pyrazine derivatives in HCW. The generation mechanism was significantly dependent on the surrounding pH conditions. © 2024 Society of Chemical Industry.

The P10K database: a data portal for the protist 10 000 genomes project.

Protists, a highly diverse group of microscopic eukaryotic organisms distinct from fungi, animals and plants, exert crucial roles within the earth's biosphere. However, the genomes of only a small fraction of known protist species have been published and made publicly accessible. To address this constraint, the Protist 10 000 Genomes Project (P10K) was initiated, implementing a specialized pipeline for single-cell genome/transcriptome assembly, decontamination and annotation of protists. The resultant P10K database (https://ngdc.cncb.ac.cn/p10k/) serves as a comprehensive platform, collating and disseminating genome sequences and annotations from diverse protist groups. Currently, the P10K database has incorporated 2959 genomes and transcriptomes, including 1101 newly sequenced datasets by P10K and 1858 publicly available datasets. Notably, it covers 45% of the protist orders, with a significant representation (53% coverage) of ciliates, featuring nearly a thousand genomes/transcriptomes. Intriguingly, analysis of the unique codon table usage among ciliates has revealed differences compared to the NCBI taxonomy system, suggesting a need to revise the codon tables used for these species. Collectively, the P10K database serves as a valuable repository of genetic resources for protist research and aims to expand its collection by incorporating more sequenced data and advanced analysis tools to benefit protist studies worldwide.

PPGR: a comprehensive perennial plant genomes and regulation database.

Perennial woody plants hold vital ecological significance, distinguished by their unique traits. While significant progress has been made in their genomic and functional studies, a major challenge persists: the absence of a comprehensive reference platform for collection, integration and in-depth analysis of the vast amount of data. Here, we present PPGR (Resource for Perennial Plant Genomes and Regulation; https://ngdc.cncb.ac.cn/ppgr/) to address this critical gap, by collecting, integrating, analyzing and visualizing genomic, gene regulation and functional data of perennial plants. PPGR currently includes 60 species, 847 million protein-protein/TF (transcription factor)-target interactions, 9016 transcriptome samples under various environmental conditions and genetic backgrounds. Noteworthy is the focus on genes that regulate wood production, seasonal dormancy, terpene biosynthesis and leaf senescence representing a wealth of information derived from experimental data, literature mining, public databases and genomic predictions. Furthermore, PPGR incorporates a range of multi-omics search and analysis tools to facilitate browsing and application of these extensive datasets. PPGR represents a comprehensive and high-quality resource for perennial plants, substantiated by an illustrative case study that demonstrates its capacity in unraveling gene functions and shedding light on potential regulatory processes.

Autoinducer-2 promotes adherence of Aeromonas veronii through facilitating the expression of MSHA type IV pili genes mediated by c-di-GMP.

IMPORTANCE: Aeromonas veronii can adhere to host cells through different adherence factors including outer-membrane proteins (OMPs), lipopolysaccharide (LPS), and pili, but its adherence mechanisms are still unclear. Here, we evaluated the effect of autoinducer-2 (AI-2) on adherence of A. veronii and its regulation mechanism. After determination of the promotion effect of AI-2 on adherence, we investigated which adherence factor was regulated by AI-2, and the results show that AI-2 only limits the formation of pili. Among the four distinct pili systems, only the mannose-sensitive hemagglutinin (MSHA) type IV pili genes were significantly downregulated after deficiency of AI-2. MshE, an ATPase belonged to MSHA type IV pilin, was confirmed as c-di-GMP receptor, that can bind with c-di-GMP which is positively regulated by AI-2, and the increase of c-di-GMP can promote the expression of MSHA type IV pili genes and adherence of A. veronii. Therefore, this study confirms that c-di-GMP positively regulated by AI-2 binds with MshE, then increases the expression of MSHA pili genes, finally promoting adherence of A. veronii, suggesting a multilevel positive regulatory adhesion mechanism that is responsible for A. veronii adherence.

MethBank 4.0: an updated database of DNA methylation across a variety of species.

DNA methylation, as the most intensively studied epigenetic mark, regulates gene expression in numerous biological processes including development, aging, and disease. With the rapid accumulation of whole-genome bisulfite sequencing data, integrating, archiving, analyzing, and visualizing those data becomes critical. Since its first publication in 2015, MethBank has been continuously updated to include more DNA methylomes across more diverse species. Here, we present MethBank 4.0 (https://ngdc.cncb.ac.cn/methbank/), which reports an increase of 309% in data volume, with 1449 single-base resolution methylomes of 23 species, covering 236 tissues/cell lines and 15 biological contexts. Value-added information, such as more rigorous quality evaluation, more standardized metadata, and comprehensive downstream annotations have been integrated in the new version. Moreover, expert-curated knowledge modules of featured differentially methylated genes associated with biological contexts and methylation analysis tools have been incorporated as new components of MethBank. In addition, MethBank 4.0 is equipped with a series of new web interfaces to browse, search, and visualize DNA methylation profiles and related information. With all these improvements, we believe the updated MethBank 4.0 will serve as a fundamental resource to provide a wide range of data services for the global research community.

CCAS: One-stop and comprehensive annotation system for individual cancer genome at multi-omics level.

Due to the explosion of cancer genome data and the urgent needs for cancer treatment, it is becoming increasingly important and necessary to easily and timely analyze and annotate cancer genomes. However, tumor heterogeneity is recognized as a serious barrier to annotate cancer genomes at the individual patient level. In addition, the interpretation and analysis of cancer multi-omics data rely heavily on existing database resources that are often located in different data centers or research institutions, which poses a huge challenge for data parsing. Here we present CCAS (Cancer genome Consensus Annotation System, https://ngdc.cncb.ac.cn/ccas/#/home), a one-stop and comprehensive annotation system for the individual patient at multi-omics level. CCAS integrates 20 widely recognized resources in the field to support data annotation of 10 categories of cancers covering 395 subtypes. Data from each resource are manually curated and standardized by using ontology frameworks. CCAS accepts data on single nucleotide variant/insertion or deletion, expression, copy number variation, and methylation level as input files to build a consensus annotation. Outputs are arranged in the forms of tables or figures and can be searched, sorted, and downloaded. Expanded panels with additional information are used for conciseness, and most figures are interactive to show additional information. Moreover, CCAS offers multidimensional annotation information, including mutation signature pattern, gene set enrichment analysis, pathways and clinical trial related information. These are helpful for intuitively understanding the molecular mechanisms of tumors and discovering key functional genes.

scMethBank: a database for single-cell whole genome DNA methylation maps.

Single-cell bisulfite sequencing methods are widely used to assess epigenomic heterogeneity in cell states. Over the past few years, large amounts of data have been generated and facilitated deeper understanding of the epigenetic regulation of many key biological processes including early embryonic development, cell differentiation and tumor progression. It is an urgent need to build a functional resource platform with the massive amount of data. Here, we present scMethBank, the first open access and comprehensive database dedicated to the collection, integration, analysis and visualization of single-cell DNA methylation data and metadata. Current release of scMethBank includes processed single-cell bisulfite sequencing data and curated metadata of 8328 samples derived from 15 public single-cell datasets, involving two species (human and mouse), 29 cell types and two diseases. In summary, scMethBank aims to assist researchers who are interested in cell heterogeneity to explore and utilize whole genome methylation data at single-cell level by providing browse, search, visualization, download functions and user-friendly online tools. The database is accessible at: https://ngdc.cncb.ac.cn/methbank/scm/.

EWAS Open Platform: integrated data, knowledge and toolkit for epigenome-wide association study.

Epigenome-Wide Association Study (EWAS) has become a standard strategy to discover DNA methylation variation of different phenotypes. Since 2018, we have developed EWAS Atlas and EWAS Data Hub to integrate a growing volume of EWAS knowledge and data, respectively. Here, we present EWAS Open Platform (https://ngdc.cncb.ac.cn/ewas) that includes EWAS Atlas, EWAS Data Hub and the newly developed EWAS Toolkit. In the current implementation, EWAS Open Platform integrates 617 018 high-quality EWAS associations from 910 publications, covering 51 phenotypes, 275 diseases and 104 environmental factors. It also provides well-normalized DNA methylation array data and the corresponding metadata from 115 852 samples, which involve 707 tissues, 218 cell lines and 528 diseases. Taking advantage of integrated knowledge and data in EWAS Atlas and EWAS Data Hub, EWAS Open Platform equips with EWAS Toolkit, a powerful one-stop site for EWAS enrichment, annotation, and knowledge network construction and visualization. Collectively, EWAS Open Platform provides open access to EWAS knowledge, data and toolkit and thus bears great utility for a broader range of relevant research.

Genome Warehouse: A Public Repository Housing Genome-scale Data.

The Genome Warehouse (GWH) is a public repository housing genome assembly data for a wide range of species and delivering a series of web services for genome data submission, storage, release, and sharing. As one of the core resources in the National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB; https://ngdc.cncb.ac.cn), GWH accepts both full and partial (chloroplast, mitochondrion, and plasmid) genome sequences with different assembly levels, as well as an update of existing genome assemblies. For each assembly, GWH collects detailed genome-related metadata of biological project, biological sample, and genome assembly, in addition to genome sequence and annotation. To archive high-quality genome sequences and annotations, GWH is equipped with a uniform and standardized procedure for quality control. Besides basic browse and search functionalities, all released genome sequences and annotations can be visualized with JBrowse. By May 21, 2021, GWH has received 19,124 direct submissions covering a diversity of 1108 species and has released 8772 of them. Collectively, GWH serves as an important resource for genome-scale data management and provides free and publicly accessible data to support research activities throughout the world. GWH is publicly accessible at https://ngdc.cncb.ac.cn/gwh.

GMQN: A Reference-Based Method for Correcting Batch Effects and Probe Bias in HumanMethylation BeadChip.

The Illumina HumanMethylation BeadChip is one of the most cost-effective methods to quantify DNA methylation levels at single-base resolution across the human genome, which makes it a routine platform for epigenome-wide association studies. It has accumulated tens of thousands of DNA methylation array samples in public databases, providing great support for data integration and further analysis. However, the majority of public DNA methylation data are deposited as processed data without background probes which are widely used in data normalization. Here, we present Gaussian mixture quantile normalization (GMQN), a reference based method for correcting batch effects as well as probe bias in the HumanMethylation BeadChip. Availability and implementation: https://github.com/MengweiLi-project/gmqn.

The 2019 novel coronavirus resource.

An ongoing outbreak of a novel coronavirus infection in Wuhan, China since December 2019 has led to 31,516 infected persons and 638 deaths across 25 countries (till 16:00 on February 7, 2020). The virus causing this pneumonia was then named as the 2019 novel coronavirus (2019-nCoV) by the World Health Organization. To promote the data sharing and make all relevant information of 2019-nCoV publicly available, we construct the 2019 Novel Coronavirus Resource (2019nCoVR, https://bigd.big.ac.cn/ncov). 2019nCoVR features comprehensive integration of genomic and proteomic sequences as well as their metadata information from the Global Initiative on Sharing All Influenza Data, National Center for Biotechnology Information, China National GeneBank, National Microbiology Data Center and China National Center for Bioinformation (CNCB)/National Genomics Data Center (NGDC). It also incorporates a wide range of relevant information including scientific literatures, news, and popular articles for science dissemination, and provides visualization functionalities for genome variation analysis results based on all collected 2019-nCoV strains. Moreover, by linking seamlessly with related databases in CNCB/NGDC, 2019nCoVR offers virus data submission and sharing services for raw sequence reads and assembled sequences. In this report, we provide comprehensive descriptions on data deposition, management, release and utility in 2019nCoVR, laying important foundations in aid of studies on virus classification and origin, genome variation and evolution, fast detection, drug development and pneumonia precision prevention and therapy.

The Global Landscape of SARS-CoV-2 Genomes, Variants, and Haplotypes in 2019nCoVR.

On January 22, 2020, China National Center for Bioinformation (CNCB) released the 2019 Novel Coronavirus Resource (2019nCoVR), an open-access information resource for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). 2019nCoVR features a comprehensive integration of sequence and clinical information for all publicly available SARS-CoV-2 isolates, which are manually curated with value-added annotations and quality evaluated by an automated in-house pipeline. Of particular note, 2019nCoVR offers systematic analyses to generate a dynamic landscape of SARS-CoV-2 genomic variations at a global scale. It provides all identified variants and their detailed statistics for each virus isolate, and congregates the quality score, functional annotation, and population frequency for each variant. Spatiotemporal change for each variant can be visualized and historical viral haplotype network maps for the course of the outbreak are also generated based on all complete and high-quality genomes available. Moreover, 2019nCoVR provides a full collection of SARS-CoV-2 relevant literature on the coronavirus disease 2019 (COVID-19), including published papers from PubMed as well as preprints from services such as bioRxiv and medRxiv through Europe PMC. Furthermore, by linking with relevant databases in CNCB, 2019nCoVR offers data submission services for raw sequence reads and assembled genomes, and data sharing with NCBI. Collectively, SARS-CoV-2 is updated daily to collect the latest information on genome sequences, variants, haplotypes, and literature for a timely reflection, making 2019nCoVR a valuable resource for the global research community. 2019nCoVR is accessible at https://bigd.big.ac.cn/ncov/.

EWAS Data Hub: a resource of DNA methylation array data and metadata.

Epigenome-Wide Association Study (EWAS) has become an effective strategy to explore epigenetic basis of complex traits. Over the past decade, a large amount of epigenetic data, especially those sourced from DNA methylation array, has been accumulated as the result of numerous EWAS projects. We present EWAS Data Hub (https://bigd.big.ac.cn/ewas/datahub), a resource for collecting and normalizing DNA methylation array data as well as archiving associated metadata. The current release of EWAS Data Hub integrates a comprehensive collection of DNA methylation array data from 75 344 samples and employs an effective normalization method to remove batch effects among different datasets. Accordingly, taking advantages of both massive high-quality DNA methylation data and standardized metadata, EWAS Data Hub provides reference DNA methylation profiles under different contexts, involving 81 tissues/cell types (that contain 25 brain parts and 25 blood cell types), six ancestry categories, and 67 diseases (including 39 cancers). In summary, EWAS Data Hub bears great promise to aid the retrieval and discovery of methylation-based biomarkers for phenotype characterization, clinical treatment and health care.

IDP-denovo: de novo transcriptome assembly and isoform annotation by hybrid sequencing.

Motivation: In the past years, the long read (LR) sequencing technologies, such as Pacific Biosciences and Oxford Nanopore Technologies, have been demonstrated to substantially improve the quality of genome assembly and transcriptome characterization. Compared to the high cost of genome assembly by LR sequencing, it is more affordable to generate LRs for transcriptome characterization. That is, when informative transcriptome LR data are available without a high-quality genome, a method for de novo transcriptome assembly and annotation is of high demand. Results: Without a reference genome, IDP-denovo performs de novo transcriptome assembly, isoform annotation and quantification by integrating the strengths of LRs and short reads. Using the GM12878 human data as a gold standard, we demonstrated that IDP-denovo had superior sensitivity of transcript assembly and high accuracy of isoform annotation. In addition, IDP-denovo outputs two abundance indices to provide a comprehensive expression profile of genes/isoforms. IDP-denovo represents a robust approach for transcriptome assembly, isoform annotation and quantification for non-model organism studies. Applying IDP-denovo to a non-model organism, Dendrobium officinale, we discovered a number of novel genes and novel isoforms that were not reported by the existing annotation library. These results reveal the high diversity of gene isoforms in D.officinale, which was not reported in the existing annotation library. Availability and implementation: The dataset of Dendrobium officinale used/analyzed during the current study has been deposited in SRA, with accession code SRP094520. IDP-denovo is available for download at www.healthcare.uiowa.edu/labs/au/IDP-denovo/. Supplementary information: Supplementary data are available at Bioinformatics online.

Single-cell transcriptome analysis reveals widespread monoallelic gene expression in individual rice mesophyll cells.

Monoallelic gene expression refers to the phenomenon that all transcripts of a gene in a cell are expressed from only one of the two alleles in a diploid organism. Although monoallelic gene expression has been occasionally reported with bulk transcriptome analysis in plants, how prevalent it is in individual plant cells remains unknown. Here, we developed a single-cell RNA-seq protocol in rice and investigated allelic expression patterns in mesophyll cells of indica (93-11) and japonica (Nipponbare) inbred lines, as well as their F1 reciprocal hybrids. We observed pervasive monoallelic gene expression in individual mesophyll cells, which could be largely explained by stochastic and independent transcription of two alleles. By contrast, two mechanisms that were proposed previously based on bulk transcriptome analyses, parent-of-origin effects and allelic repression, were not well supported by our data. Furthermore, monoallelically expressed genes exhibited a number of characteristics, such as lower expression levels, narrower H3K4me3/H3K9ac/H3K27me3 peaks, and larger expression divergences between 93-11 and Nipponbare. Taken together, the development of a single-cell RNA-seq protocol in this study offers us an excellent opportunity to investigate the origins and prevalence of monoallelic gene expression in plant cells.

ISRNA: an integrative online toolkit for short reads from high-throughput sequencing data.

UNLABELLED: Integrative Short Reads NAvigator (ISRNA) is an online toolkit for analyzing high-throughput small RNA sequencing data. Besides the high-speed genome mapping function, ISRNA provides statistics for genomic location, length distribution and nucleotide composition bias analysis of sequence reads. Number of reads mapped to known microRNAs and other classes of short non-coding RNAs, coverage of short reads on genes, expression abundance of sequence reads as well as some other analysis functions are also supported. The versatile search functions enable users to select sequence reads according to their sub-sequences, expression abundance, genomic location, relationship to genes, etc. A specialized genome browser is integrated to visualize the genomic distribution of short reads. ISRNA also supports management and comparison among multiple datasets. AVAILABILITY: ISRNA is implemented in Java/C++/Perl/MySQL and can be freely accessed at http://omicslab.genetics.ac.cn/ISRNA/.

PsRobot: a web-based plant small RNA meta-analysis toolbox.

Small RNAs (smRNAs) in plants, mainly microRNAs and small interfering RNAs, play important roles in both transcriptional and post-transcriptional gene regulation. The broad application of high-throughput sequencing technology has made routinely generation of bulk smRNA sequences in laboratories possible, thus has significantly increased the need for batch analysis tools. PsRobot is a web-based easy-to-use tool dedicated to the identification of smRNAs with stem-loop shaped precursors (such as microRNAs and short hairpin RNAs) and their target genes/transcripts. It performs fast analysis to identify smRNAs with stem-loop shaped precursors among batch input data and predicts their targets using a modified Smith-Waterman algorithm. PsRobot integrates the expression data of smRNAs in major plant smRNA biogenesis gene mutants and smRNA-associated protein complexes to give clues to the smRNA generation and functional processes. Besides improved specificity, the reliability of smRNA target prediction results can also be evaluated by mRNA cleavage (degradome) data. The cross species conservation statuses and the multiplicity of smRNA target sites are also provided. PsRobot is freely accessible at http://omicslab.genetics.ac.cn/psRobot/.