Transcriptomics integrated with metabolomics reveals the mechanism of CaCl_(2)-HCl electrolyzed water-induced glucosinolate biosynthesis in broccoli sprouts

Glucosinolates are important phytochemicals in Brassicaceae.We investigated the effect of CaCl_(2)-HCl electrolyzed water(CHEW)on glucosinolates biosynthesis in broccoli sprouts.The results showed that CHEW treatment significantly decreased reactive oxygen species(ROS)and malondialdeh yde(MDA)contents in broccoli sprouts.On the the 8^(th)day,compared to tap water treatment,the the total glucosinolate content of broccoli sprouts with CHEW treatment increased by 10.6%and calcium content was dramatically enhanced from 14.4 mg/g DW to 22.7 mg/g DW.Comparative transcriptome and metabolome analyses revealed that CHEW treatment activated ROS and calcium signaling transduction pathways in broccoli sprouts and they interacted through MAPK cascades.Besides,CHEW treatment not only promoted the biosynthesis of amino acids,but also enhanced the expression of structural genes in glucosinolate synthesis through transcription factors(MYBs,bHLHs,WRKYs,etc.).The results of this study provided new insights into the regulatory network of glucosinolates biosynthesis in broccoli sprouts under CHEW treatment.

Progress in oncolytic viruses modified with nanomaterials for intravenous application

In oncolytic virus(OV)therapy,a critical component of tumor immunotherapy,viruses selectively infect,replicate within,and eventually destroy tumor cells.Simultaneously,this therapy activates immune responses and mobilizes immune cells,thereby eliminating residual or distant cancer cells.However,because of OVs’high immunogenicity and immune clearance during circulation,their clinical applications are currently limited to intratumoral injections,and their use is severely restricted.In recent years,numerous studies have used nanomaterials to modify OVs to decrease virulence and increase safety for intravenous injection.The most commonly used nanomaterials for modifying OVs are liposomes,polymers,and albumin,because of their biosafety,practicability,and effectiveness.The aim of this review is to summarize progress in the use of these nanomaterials in preclinical experiments to modify OVs and to discuss the challenges encountered from basic research to clinical application.

2019新型冠状病毒信息库

2019年12月在中国武汉开始爆发的新型肺炎已造成全球25个国家/地区的31516人感染、638人死亡(截止2020年2月7日16时),引起该肺炎的病毒被世界卫生组织命名为2019新型冠状病毒(2019-nCoV)。为促进2019-nCoV数据共享应用并及时向全球公众提供病毒的相关信息,国家生物信息中心(CNCB)/国家基因组科学数据中心(NGDC)建立了2019新型冠状病毒信息库(2019nCoVR,https://bigd.big.ac.cn/ncov)。该信息库整合了来自德国全球流感病毒数据库、美国国家生物技术信息中心、深圳(国家)基因库、国家微生物科学数据中心及CNCB/NGDC等机构公开发布的2019-nCoV核苷酸和蛋白质序列数据、元信息、学术文献、新闻动态、科普文章等信息,开展了不同冠状病毒株的基因组序列变异分析并提供可视化展示。同时,2019nCoVR无缝对接CNCB/NGDC的相关数据库,提供新测序病毒株系的基因组原始测序数据、组装后序列的在线汇交、管理与共享、国际数据库同步发布等数据服务。本文对2019nCoVR数据汇交、管理、发布及使用等进行全面阐述,以方便用户了解该信息库各项功能及数据状况,为加速开展病毒的分类溯源、变异演化、快速检测、药物研发以及新型肺炎的精准预防与治疗等研究提供重要基础。

中国人群参考基因组及基因组变异图谱资源库

随着人类基因组计划和国际千人基因组计划的实施,已公开数百个中国人个体的全基因组数据。建立高精度的中国人群参考基因组序列,发现并解析中国人群特有的序列变异,是我国未来精准医学研究的基础。为满足未来精准医学研究中国人基因组数据持续增长的科学管理和深入研究的需求,中国科学院北京基因组研究所发展并建立了基于中国人群全基因组测序数据的虚拟中国人基因组数据库(Virtual Chinese Genome Database,VCGDB)和中国人群基因组变异数据库(Genome Variation Map, GVM),面向国内外用户提供数据检索、共享、下载和在线分析服务。本文重点介绍了这两个数据库的特点和功能,以及未来发展与应用前景,以期为中国人群参考基因组及基因组变异图谱资源库的推广使用、发展完善提供有益信息。

Establishment of a comprehensive indicator to nondestructively analyze watermelon quality at different ripening stages

Two nondestructive methods based on visible and near-infrared(VIS-NIR)spectroscopy and X-ray image have been used for the evaluation of watermelon quality.The prediction perform-ance based on partial least squares(PLS)by diffuse transmittance measurement(500-1010 nm)was evaluated for_chemical quality attributes SSC(Rc=0.903;RMSEC=0.572%Brix;Rp=0.862;RMSEP=0.717%Brix;RPD=1.83),lycopene(Rc=0.845;RMSEC=0.266 mg/100 gFW;Rp=0.751;RMSEP=0.439 mg/100 gFW;RPD=1.13)and moisture(Rc=0.917;RMSEC=0.280%;Rp=0.937;RMSEP=0.276%;RPD=2.79).The X-ray calibration linearequations developed by extracting the appropriate gray threshold were sufficiently precise forvolume(R?=0.986)and weight(R?=0.993).In order to optimize prediction model of water-melon quality in growth period,multivariate multi-block technique factor analysis enabled in-tegration of these traits:chemical information is related to physical infomation.Applyingprinciple component analysis to extract common factors and varimax with Kaiser normalizationto improve explanatory,the comprehensive indicator based on variances was established satis.factorily with Rc=0.94,RMSEC=0.244,Rp=0.93,RMSEP=0.344 and RPD=2.00.Acomparison of these models indicates that the comprehensive indicator determined only by portable VIS-NIR spectrometer appears as a suitable method for appraising watermelon qualitynondestructively on the plant at diferent ripen stages.This method contributes to infer the picking date of watermelon with higher accuracy and bigger economic benefits than that byexperience.

Nondestructive determination of soluble solids and firmness in mix-cultivar melon using near-infrared CCD spectroscopy

Nondestructive evaluation of melon quality is in great need of comprehensive study.Soluble solids content(SSC)and firmness are the two indicators of melon internal quality that mostly a®ect consumer acceptance.To provide guidance for fruit classification,internal quality standards was preliminarily established through sensory test,as:Melon with SSC over 12
Brix,firmness 4–5.5 kgf·cm^(-2)2 were considered as satisfactory class sample;and SSC over 10
Brix,¯rmness 3.5–6.5 kgf·cm^(-2) as average class sample.The near infrared(NIR)nondestructive detection program was set as spectra collected from the stylar-end,Brix expressed by the average SSC of inner and outer mesocarp,each cultivar of melon was detected with its own optimum integration time,and the second derivative algorithm was used to equalize them.Using wavelength selected by genetic algorithms(GA),a robust SSC model of mix-cultivar melon was established,the root mean standard error of cross-validation(RMSECV)was 0.99 and the ratio performance deviation(RPD)nearly reached 3.0,which almost could meet the accuracy requirement of 1.5
Brix.Firmness model of mix-cultivar melon was acceptable but inferior.

Glucosinolate Variation in Turnip (Brassica rapa L.) at Different Growing Stages

The seed, leaf and root parts of three turnip （ Brassica rapa L.） cultivars were analyzed for glucosinolates. The component and concentration of glucosinolates in the three cultivars were also analyzed at different growing stages. Eight kinds of glucosinolates were tested in turnip. They were PRO, NAP, 4OH, GBN, GBC, NAS, 4ME and NEO, respectively. The contents and kinds of glucosinolates varied at different growing stages. The content of NAS was the highest in the seed, GBC and NEO contents were the highest in the seedling, GBN and NEO contents were the highest in the leaf, while the highest NAS content was in the root.

Plant genomic resources at National Genomics Data Center:assisting in data-driven breeding applications

Genomic data serve as an invaluable resource for unraveling the intricacies of the higher plant systems,including the constituent elements within and among species.Through various efforts in genomic data archiving,integrative analysis and value-added curation,the National Genomics Data Center(NGDC),which is a part of the China National Center for Bioinformation(CNCB),has successfully established and currently maintains a vast amount of database resources.This dedicated initiative of the NGDC facilitates a data-rich ecosystem that greatly strengthens and supports genomic research efforts.Here,we present a comprehensive overview of central repositories dedicated to archiving,presenting,and sharing plant omics data,introduce knowledgebases focused on variants or gene-based functional insights,highlight species-specific multiple omics database resources,and briefly review the online application tools.We intend that this review can be used as a guide map for plant researchers wishing to select effective data resources from the NGDC for their specific areas of study.

SoyOmics:A deeply integrated database on soybean multi-omics

Dear Editor,As one of the most important crops to supply the majority of plant oil and protein for the whole world,soybean is facing an increasing global demand.The reference genome of accession"Williams82"opened the gate of genomics research in soybean(Schmutz et al.,2010).After that,vast multi-omics data were generated,thereby providing valuable resources for functional study and molecular breeding.Parts of these data have been collected in different soybean databases(see details in Supplemental Table 1),such as Soybase(Grant et al.,2010)and SoyKB(Joshi et al.,2012),which made valuable efforts to facilitate the wide utility of these data.Nevertheless,these existing databases poorly tackled multi-omics data integration and interactivity for soybean,provoking tremendous challenges for researchers to deal with these big omics data,particularly considering the unprecedented rate of data growth(Yang et al.,2021).Thus,constructing an integrated multi-omics database for soybean that provides a one-stop solution for big data mining with friendly interactivity is highly desired.

RCoV19:A One-stop Hub for SARS-CoV-2 Genome Data Integration,Variant Monitoring,and Risk Pre-warning

The Resource for Coronavirus 2019(RCoV19)is an open-access information resource dedicated to providing valuable data on the genomes,mutations,and variants of the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).In this updated implementation of RCoV19,we have made significant improvements and advancements over the previous version.Firstly,we have implemented a highly refined genome data curation model.This model now features an automated integration pipeline and optimized curation rules,enabling efficient daily updates of data in RCoV19.Secondly,we have developed a global and regional lineage evolution monitoring platform,alongside an outbreak risk pre-warning system.These additions provide a comprehensive understanding of SARS-CoV-2 evolution and transmission patterns,enabling better preparedness and response strategies.Thirdly,we have developed a powerful interactive mutation spectrum comparison module.This module allows users to compare and analyze mutation patterns,assisting in the detection of potential new lineages.Furthermore,we have incorporated a comprehensive knowledgebase on mutation effects.This knowledgebase serves as a valuable resource for retrieving information on the functional implications of specific mutations.In summary,RCoV19 serves as a vital scientific resource,providing access to valuable data,relevant information,and technical support in the global fight against COVID-19.The complete contents of RCoV19 are available to the public at https://ngdc.cncb.ac.cn/ncov/.

Back to Science in Searching for SARS-CoV-2 Origins

In recent decades,emerging and re-emerging human-infecting pathogens have been represented as huge threats to public health and have become a global concern(1).After outbreaks of two coronaviruses(CoVs),severe acute respiratory syndrome coronavirus(SARS-CoV)and Middle East respiratory syndrome coronavirus(MERS-CoV),severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)became the first-known pandemic hastening CoV with tremendous wrecking to the world(2).The origin tracing of these emerging pathogens is of great significance in infectious disease prevention and control(3–4).The origin of SARS-CoV-2 remains elusive after the more than 3-year pandemic,though scientists around the world are making great efforts.From the experience of studying many other infectious pathogens,origin tracing is systematic and time-consuming work.The supposed origins of many infectious pathogens are still in debate,including SARS-CoV and human immunodeficiency virus,etc(5).

Whole Genome Analyses of Chinese Population and De Novo Assembly of A Northern Han Genome

To unravel the genetic mechanisms of disease and physiological traits,it requires comprehensive sequencing analysis of large sample size in Chinese populations.Here,we report the primary results of the Chinese Academy of Sciences Precision Medicine Initiative(CASPMI)project launched by the Chinese Academy of Sciences,including the de novo assembly of a northern Han reference genome(NH1.0)and whole genome analyses of 597 healthy people coming from most areas in China.Given the two existing reference genomes for Han Chinese(YH and HX1)were both from the south,we constructed NH1.0,a new reference genome from a northern individual,by combining the sequencing strategies of PacBio,10×Genomics,and Bionano mapping.Using this integrated approach,we obtained an N50 scaffold size of 46.63 Mb for the NH1.0 genome and performed a comparative genome analysis of NH1.0 with YH and HX1.In order to generate a genomic variation map of Chinese populations,we performed the whole-genome sequencing of 597 participants and identified 24.85 million(M)single nucleotide variants(SNVs),3.85 M small indels,and 106,382 structural variations.In the association analysis with collected phenotypes,we found that the T allele of rs1549293 in KAT8 significantly correlated with the waist circumference in northern Han males.Moreover,significant genetic diversity in MTHFR,TCN2,FADS1,and FADS2,which associate with circulating folate,vitamin B12,or lipid metabolism,was observed between northerners and southerners.Especially,for the homocysteine-increasing allele of rs1801133(MTHFR 677T),we hypothesize that there exists a “comfort”zone for a high frequency of 677T between latitudes of 35–45 degree North.Taken together,our results provide a high-quality northern Han reference genome and novel population-specific data sets of genetic variants for use in the personalized and precision medicine.

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/.

Population Genetics of SARS-CoV-2: Disentangling Effects of Sampling Bias and Infection Clusters

A novel RNA virus,the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),is responsible for the ongoing outbreak of coronavirus disease 2019(COVID-19).Population genetic analysis could be useful for investigating the origin and evolutionary dynamics of COVID-19.However,due to extensive sampling bias and existence of infection clusters during the epidemic spread,direct applications of existing approaches can lead to biased parameter estimations and data misinterpretation.In this study,we first present robust estimator for the time to the most recent common ancestor(TMRCA)and the mutation rate,and then apply the approach to analyze 12,909 genomic sequences of SARS-CoV-2.The mutation rate is inferred to be 8.69×10^(−4) per site per year with a 95%confidence interval(CI)of[8.61×10^(−4),8.77×10^(−4)],and the TMRCA of the samples inferred to be Nov 28,2019 with a 95%CI of[Oct 20,2019,Dec 9,2019].The results indicate that COVID-19 might originate earlier than and outside of Wuhan Seafood Market.We further demonstrate that genetic polymorphism patterns,including the enrichment of specific haplotypes and the temporal allele frequency trajectories generated from infection clusters,are similar to those caused by evolutionary forces such as natural selection.Our results show that population genetic methods need to be developed to efficiently detangle the effects of sampling bias and infection clusters to gain insights into the evolutionary mechanism of SARS-CoV-2.Software for implementing VirusMuT can be downloaded at https://bigd.big.ac.cn/biocode/tools/BT007081.

SR4R:An Integrative SNP Resource for Genomic Breeding and Population Research in Rice

The information commons for rice(IC4 R)database is a collection of 18 million single nucleotide polymorphisms(SNPs)identified by resequencing of 5152 rice accessions.Although IC4 R offers ultra-high density rice variation map,these raw SNPs are not readily usable for the public.To satisfy different research utilizations of SNPs for population genetics,evolutionary analysis,association studies,and genomic breeding in rice,raw genotypic data of these 18 million SNPs were processed by unified bioinformatics pipelines.The outcomes were used to develop a daughter database of IC4 R-SnpReady for Rice(SR4 R).SR4 R presents four reference SNP panels,including 2,097,405 hapmapSNPs after data filtration and genotype imputation,156,502 tagSNPs selected from linkage disequilibrium-based redundancy removal,1180 fixedSNPs selected from genes exhibiting selective sweep signatures,and 38 barcodeSNPs selected from DNA fingerprinting simulation.SR4 R thus offers a highly efficient rice variation map that combines reduced SNP redundancy with extensive data describing the genetic diversity of rice populations.In addition,SR4 R provides rice researchers with a web interface that enables them to browse all four SNP panels,use online toolkits,as well as retrieve the original data and scripts for a variety of population genetics analyses on local computers.SR4 R is freely available to academic users at http://sr4 r.ic4 r.org/.

On the origin of SARS-CoV-2——The blind watchmaker argument

In the comparison with SARS-CoVof 2003,SARS-CoV-2 is extremely well adapted to the human populations and its adaptive shift from the animal host to humans must have been even more extensive.By the blind watchmaker argument,such an adaptive shift can only happen prior to the onset of the current pandemic and with the aid of step-by-step selection.

Database Resources in BIG Data Center:Submission, Archiving, and Integration of Big Data in Plant Science

With the rapid advancement of sequencing technologies and the growing volume of omics data in plants, there is much anticipation in digging out the treasure from such big data and accordingly refining the current agricultural practice to be applied in the near future. Toward this end, database resources that deliver web services for plant omics data submission, archiving, and integration are urgently needed. As a part of Beijing Institute of Genomics (BIG) of the Chinese Academy of Sciences (CAS), BIG Data Center (http://bigd.big.ac.cn) provides open access to a suite of database resources (Table 1), with the aim of supporting plant research activities for domestic and international users in both academia and industry to translate big data into big discoveries (BIG Data Center Members, 2017;BIG Data Center Members, 2018;BIG Data Center Members, 2019). Here, we give a brief introduction of plant-related database resources in BIG Data Center and appeal to plant research com丒 munities to make full use of these resources for plant data submission, archiving, and integration.

Discovery,Identification and Comparative Analysis of Non-Specific Lipid Transfer Protein (nsLtp) Family in Solanaceae

Plant non-specific lipid transfer proteins （nsLtps） have been reported to be involved in plant defense activity against bacterial and fungal pathogens. In this study, we identified 135 （122 putative and 13 previously identified） Solanaceae nsLtps, which are clustered into 8 different groups. By comparing with Boutrot’s nsLtp classification, we classified these eight groups into five types （I, II, IV, IX and X）. We compared Solanaceae nsLtps with Arabidopsis and Gramineae nsLtps and found that （1） Types I, II and IV are shared by Solanaceae, Gramineae and Arabidopsis; （2） Types III, V, VI and VIII are shared by Gramineae and Arabidopsis but not detected in Solanaceae so far; （3） Type VII is only found in Gramineae whereas type IX is present only in Arabidopsis and Solanaceae; （4） Type X is a new type that accounts for 52.59% Solanaceae nsLtps in our data, and has not been reported in any other plant so far. We further built and compared the three-dimensional structures of the eight groups, and found that the major functional diversification within the nsLtp family could be predated to the monocot/dicot divergence, and many gene duplications and sequence variations had happened in the nsLtp family after the monocot/dicot divergence, especially in Solanaceae.

Rice Genomics: over the Past Two Decades and into the Future

Domestic rice(Oryza sativa L.) is one of the most important cereal crops, feeding a large number of worldwide populations. Along with various high-throughput genome sequencing projects, rice genomics has been making great headway toward direct ?eld applications of basic research advances in understanding the molecular mechanisms of agronomical traits and utilizing diverse germplasm resources. Here, we brie?y review its achievements over the past two decades and present the potential for its bright future.

An RNA-seq-based Gene Expression Profiling of Radiation-induced Tumorigenic Mammary Epithelial Cells

Immortality and tumorigenicity are two distinct characteristics of cancers. Immortalization has been suggested to precede tumorigenesis. To understand the molecular mechanisms of tumorigenicity and cancer progression in mammary epithelium, we established a tumori- genic cell model by means of heavy-ion radiation of an immortal cell model, which was created by overexpressing the human telomerase reverse transcriptase （hTERT） in normal human mammary epithelial cells. We examined the expression profile of this tumorigenic cell line （T hMEC） using the hTERT-overexpressing immortal cell line （IhMEC） as a control. In-depth RNA-seq data was generated by using the next-generation sequencing （NGS） platform （Life Technologies SOLID3）. We found that house-keeping （HK） and tissue-spe- cific （TS） genes were differentially regulated during the tumorigenic process. HK genes tended to be activated while TS genes tended to be repressed. In addition, the HK genes and TS genes tended to contribute differentially to the variation of gene expression at different RPKM （gene expression in reads per exon kilobase per million mapped sequence reads） levels. Based on transcriptome analysis of the two cell lines, we defined 7053 differentially-expressed genes （DEGs） between immortality and tumorigenicity. Differential expression of 20 manually-selected genes was further validated using qRT-PCR. Our observations may help to further our understanding of cellular mechanism（s） in the transition from immortalization to tumorigenesis.