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。

An online coronavirus analysis platform from the National Genomics Data Center

DEAR EDITOR,Since the first reported severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection in December 2019,coronavirus disease 2019(COVID-19)has become a global pandemic,spreading to more than 200 countries and regions worldwide.With continued research progress and virus detection,SARS-CoV-2 genomes and sequencing data have been reported and accumulated at an unprecedented rate.

Database Commons:A Catalog of Worldwide Biological Databases

Biological databases serve as a global fundamental infrastructure for the worldwide scientific community,which dramatically aid the transformation of big data into knowledge discovery and drive significant innovations in a wide range of research fields.Given the rapid data production,biological databases continue to increase in size and importance.To build a catalog of worldwide biological databases,we curate a total of 5825 biological databases from 8931 publications,which are geographically distributed in 72 countries/regions and developed by 1975 institutions(as of September 20,2022).We further devise a z-index,a novel index to characterize the scientific impact of a database,and rank all these biological databases as well as their hosting institutions and countries in terms of citation and z-index.Consequently,we present a series of statistics and trends of worldwide biological databases,yielding a global perspective to better understand their status and impact for life and health sciences.An up-to-date catalog of worldwide biological databases,as well as their curated meta-information and derived statistics,is publicly available at Database Commons(https://ngdc.cncb.ac.cn/databasecommons/).

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/.

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.

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/.

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/.

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.

Review of pantograph and catenary interaction

The application of electrified railway directly promotes relevant studies on pantograph-catenary interac- tion. With the increase of train running speed, the operating conditions for pantograph and catenary have become increasingly complex. This paper reviews the related achievements contributed by groups and institutions around the world. This article specifically focuses on three aspects： The dynamic characteristics of the panto- graph and catenary components, the systems＇ dynamic properties, and the environmental influences on the pantograph-catenary interaction. In accordance with the existing studies, future research may prioritize the task of identifying the mechanism of contact force variation. This kind of study can be carried out by simplifying the pantograph-catenary interaction into a moving load problem and utilizing the theory of matching mechanical impedance. In addition, developing a computational platform that accommodates environmental interferences and multi-field coupling effects is necessary in order to further explore applications based on fundamental studies.

IC4R-2.0:Rice Genome Reannotation Using Massive RNA-seq Data

Genome reannotation aims for complete and accurate characterization of gene models and thus is of critical significance for in-depth exploration of gene function.Although the availability of massive RNA-seq data provides great opportunities for gene model refinement,few efforts have been made to adopt these precious data in rice genome reannotation.Here we reannotate the rice(Oryza sativa L.ssp.japonica)genome based on integration of large-scale RNA-seq data and release a new annotation system IC4 R-2.0.In general,IC4 R-2.0 significantly improves the completeness of gene structure,identifies a number of novel genes,and integrates a variety of functional annotations.Furthermore,long non-coding RNAs(lncRNAs)and circular RNAs(circRNAs)are systematically characterized in the rice genome.Performance evaluation shows that compared to previous annotation systems,IC4 R-2.0 achieves higher integrity and quality,primarily attributable to massive RNA-seq data applied in genome annotation.Consequently,we incorporate the improved annotations into the Information Commons for Rice(IC4 R),a database integrating multiple omics data of rice,and accordingly update IC4 R by providing more user-friendly web interfaces and implementing a series of practical online tools.Together,the updated IC4 R,which is equipped with the improved annotations,bears great promise for comparative and functional genomic studies in rice and other monocotyledonous species.The IC4 R-2.0 annotation system and related resources are freely accessible at http://ic4 r.org/.

Rice Expression Database(RED)：An integrated RNA-Seq-derived gene expression database for rice

Rice is one of the most important stable food as well as a monocotyledonous model organism for the plant research community.Here,we present RED（Rice Expression Database;http：//expression.ic4r.org）,an integrated database of rice gene expression profiles derived entirely from RNA-Seq data.RED features a comprehensive collection of 284 high-quality RNA-Seq experiments,integrates a large number of gene expression profiles and covers a wide range of rice growth stages as well as various treatments.Based on massive expression profiles,RED provides a list of housekeeping and tissue-specific genes and dynamically constructs co-expression networks for gene（s） of interest.Besides,it provides user-friendly web interfaces for querying,browsing and visualizing expression profiles of concerned genes.Together,as a core resource in BIG Data Center,RED bears great utility for characterizing the function of rice genes and better understanding important biological processes and mechanisms underlying complex agronomic traits in rice.

Biological Databases for Human Research

The completion of the Human Genome Project lays a foundation for systematically studying the human genome from evolutionary history to precision medicine against diseases.With the explosive growth of biological data, there is an increasing number of biological databases that have been developed in aid of human-related research. Here we present a collection of humanrelated biological databases and provide a mini-review by classifying them into different categories according to their data types. As human-related databases continue to grow not only in count but also in volume, challenges are ahead in big data storage, processing, exchange and curation.