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,int...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.展开更多
DEAR EDITOR,The COVID-19 pandemic caused by SARS-CoV-2 continues to pose a tremendous threat to human society. SARS-CoV-2is airborne and transmits primarily through social contact;however, whether cold chain-related t...DEAR EDITOR,The COVID-19 pandemic caused by SARS-CoV-2 continues to pose a tremendous threat to human society. SARS-CoV-2is airborne and transmits primarily through social contact;however, whether cold chain-related transmission has occurred remains highly debated(Han & Liu, 2022;Lewis,2021;Ma et al., 2021;Mallapaty et al., 2021;Pang et al.,2020;Wu et al., 2021). Here, we present a novel method and identify two transmission routes based on lineage-specific reductions in the SARS-CoV-2 evolutionary rate.展开更多
Urea is a major end product of nitrogen catabolism,serving as an osmolyte to regulate osmotic stress in fish exposed to varying water environments.It has been well known that urea transporters(UTs)facilitate the rapid...Urea is a major end product of nitrogen catabolism,serving as an osmolyte to regulate osmotic stress in fish exposed to varying water environments.It has been well known that urea transporters(UTs)facilitate the rapid movement of urea across cell membranes.However,researches on ut genes were predominantly focused on elasmobranchs and early developmental stages of fish.In this investigation,a total of three ut genes were identified in spotted sea bass.Phylogenetic,homology,and syntenic analyses were conducted to validate the annotation and assess the evolutionary relationships among ut genes.Both ut-a and ut-b genes have retained their evolutionary stability,demonstrating a significant level of homology between them.To gain deeper insights into the evolution of ut genes in spotted sea bass,we performed selective pressure analysis using site,branch,and branch-site models.The results suggested that positive selection likely played a significant role in shaping the evolution of the ut gene family.Furthermore,tissue-specific expression analyses revealed high expression levels of ut genes in osmoregulatory tissues such as the gill and kidney.Additionally,all three ut genes exhibited salinity-related expression patterns in gill and kidney tissues during both seawater-to-freshwater(SF)and freshwater-to-seawater(FS)adaptation.In situ hybridization results demonstrated the localization of both ut-a and ut-c mRNAs on the gill lamellae and adjacent gill filament epithelium.In summary,our study establishes a solid foundation for future research elucidating the evolutionary relationships and functional significance of ut genes during salinity acclimation in spotted sea bass and other teleost species.展开更多
Background Big data challenges In the late 1980s and early 1990s,three major international biological data centers were created:the DNA Database of Japan(DDBJ)[1],the European Bioinformatics Institute(EMBL-EBI)in the ...Background Big data challenges In the late 1980s and early 1990s,three major international biological data centers were created:the DNA Database of Japan(DDBJ)[1],the European Bioinformatics Institute(EMBL-EBI)in the United Kingdom(UK)[2],and the National Center for Biotechnology Information(NCBI)in the United States(US)[3].展开更多
Cell migration plays a significant role in physiological and pathological processes.Understanding the characteristics of cell movement is crucial for comprehending biological processes such as cell functionality,cell ...Cell migration plays a significant role in physiological and pathological processes.Understanding the characteristics of cell movement is crucial for comprehending biological processes such as cell functionality,cell migration,and cell–cell interactions.One of the fundamental characteristics of cell movement is the specific distribution of cell speed,containing valuable information that still requires comprehensive understanding.This article investigates the distribution of mean velocities along cell trajectories,with a focus on optimizing the efficiency of cell food search in the context of the entire colony.We confirm that the specific velocity distribution in the experiments corresponds to an optimal search efficiency when spatial weighting is considered.The simulation results indicate that the distribution of average velocity does not align with the optimal search efficiency when employing average spatial weighting.However,when considering the distribution of central spatial weighting,the specific velocity distribution in the experiment is shown to correspond to the optimal search efficiency.Our simulations reveal that for any given distribution of average velocity,a specific central spatial weighting can be identified among the possible central spatial weighting that aligns with the optimal search strategy.Additionally,our work presents a method for determining the spatial weights embedded in the velocity distribution of cell movement.Our results have provided new avenues for further investigation of significant topics,such as relationship between cell behavior and environmental conditions throughout their evolutionary history,and how cells achieve collective cooperation through cell-cell communication.展开更多
Quantitative examination of cellular motion and intercellullar interactions possesses substantial relevance for both biology and medicine.However,the effects of intercellular interactions during cellular locomotion re...Quantitative examination of cellular motion and intercellullar interactions possesses substantial relevance for both biology and medicine.However,the effects of intercellular interactions during cellular locomotion remain under-explored in experimental research.As such,this study seeks to bridge this research gap,adopting Dictyostelium discoideum(Dicty)cells as a paradigm to investigate variations in cellular motion during reciprocal collisions.We aim to attain a comprehensive understanding of how cell interactions influence cell motion.By observing and processing the motion trajectories of colliding cells under diverse chemical environments,we calculated the diffusion coefficient(D)and the persistence time(τ),using mean square displacement.Our analysis of the relationship dynamics between D andτprior to the collisions reveals intricate and non-monotonic alterations in cell movements during collisions.By quantitatively scrutinizing theτtrend,we were able to categorize the cellular responses to interactions under different conditions.Importantly,we ascertained that the effect of cell interactions during collisions in Dicty cells emulates a classical sigmoid function.This discovery suggests that cellular responses might comply with a pattern akin to the Weber–Fechner law.展开更多
BACKGROUND Preoperative risk stratification is significant for the management of endometrial cancer(EC)patients.Radiomics based on magnetic resonance imaging(MRI)in combination with clinical features may be useful to ...BACKGROUND Preoperative risk stratification is significant for the management of endometrial cancer(EC)patients.Radiomics based on magnetic resonance imaging(MRI)in combination with clinical features may be useful to predict the risk grade of EC.AIM To construct machine learning models to predict preoperative risk stratification of patients with EC based on radiomics features extracted from MRI.METHODS The study comprised 112 EC patients.The participants were randomly separated into training and validation groups with a 7:3 ratio.Logistic regression analysis was applied to uncover independent clinical predictors.These predictors were then used to create a clinical nomogram.Extracted radiomics features from the T2-weighted imaging and diffusion weighted imaging sequences of MRI images,the Mann-Whitney U test,Pearson test,and least absolute shrinkage and selection operator analysis were employed to evaluate the relevant radiomic features,which were subsequently utilized to generate a radiomic signature.Seven machine learning strategies were used to construct radiomic models that relied on the screening features.The logistic regression method was used to construct a composite nomogram that incorporated both the radiomic signature and clinical independent risk indicators.RESULTS Having an accuracy of 0.82 along with an area under the curve(AUC)of 0.915[95%confidence interval(CI):0.806-0.986],the random forest method trained on radiomics characteristics performed better than expected.The predictive accuracy of radiomics prediction models surpassed that of both the clinical nomogram(AUC:0.75,95%CI:0.611-0.899)and the combined nomogram(AUC:0.869,95%CI:0.702-0.986)that integrated clinical parameters and radiomic signature.CONCLUSION The MRI-based radiomics model may be an effective tool for preoperative risk grade prediction in EC patients.展开更多
Glutamine metabolism(GM)plays an important role in tumor growth and proliferation.Skin cutaneous melanoma(SKCM)is a glutamine-dependent cancer.However,the molecular characteristics and action mechanism of GM on SKCM r...Glutamine metabolism(GM)plays an important role in tumor growth and proliferation.Skin cutaneous melanoma(SKCM)is a glutamine-dependent cancer.However,the molecular characteristics and action mechanism of GM on SKCM remain unclear.Therefore,we aimed to explore the effects of GM-related genes on survival,clinicopathological characteristics,and the tumor microenvironment in SKCM.In this study,682 SKCM samples were obtained from the Cancer Genome Atlas(TCGA)and Gene Expression Omnibus(GEO)databases.Consensus clustering was used to classify SKCM samples into distinct subtypes based on 41 GM-related genes.Differences in survival,immune infiltration,clinical characteristics,and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways as well as differentially expressed genes(DEGs)between subgroups were evaluated.A prognostic model was constructed according to prognostic DEGs.Differential analyses in survival,immune infiltration,tumor microenvironment(TME),tumor mutation burden(TMB),stemness,and drug sensitivity between risk groups were conducted.We identified two distinct GM-related subtypes on SKCM and found that GM-related gene alterations were associated with survival probability,clinical features,biological function,and immune infiltration.Then a risk model based on six DEGs(IL18,SEMA6A,PAEP,TNFRSF17,AIM2,and CXCL10)was constructed and validated for predicting overall survival in SKCM patients.The results showed that the risk score was negatively correlated with CD8+T cells,activated CD4+memory T cells,M1 macrophages,andγδT cells.The group with a low-risk score was accompanied by a better survival rate with higher TME scores and lower stemness index.Moreover,the group with high-and low-risk score had a significant difference with the sensitivity of 75 drugs(p<0.001).Overall,distinct subtypes in SKCM patients based on GM-related genes were identified and the risk model was constructed,which might contribute to prognosis prediction,guide clinical therapy,and develop novel therapeutic strategies.展开更多
The Genome Warehouse(GWH),accessible at https://ngdc.cncb.ac.cn/gwh,is an extensively-utilized public repository dedicated to the deposition,management,and sharing of genome assembly sequences,annotations,and metadata...The Genome Warehouse(GWH),accessible at https://ngdc.cncb.ac.cn/gwh,is an extensively-utilized public repository dedicated to the deposition,management,and sharing of genome assembly sequences,annotations,and metadata.This paper highlights noteworthy enhancements to the GWH since the 2021 version,emphasizing substantial advancements in web interfaces for data submission,database functionality updates,and re-source integration.Key updates include the reannotation of released prokaryotic genomes,mirroring of genome resources from National Center for Biotechnology Information(NCBl)GenBank and Reference Sequence Database(RefSeq),integration of Poxviridae sequences,implementation of an online batch submission system,enhancements to the quality control system,advanced search capabilities,and the introduction of a controlled-access mechanism for human genome data.These improvements collectively enhance the ease and security of data submission and access as well as genome data value,thereby improving convenience and utility for researchers in the genomics field.展开更多
Tumorigenesis is usually accompanied by changes in metabolic patterns,known as metabolic reprogramming[1].To meet the overall metabolic needs for tumor growth and development,tumors regulate the metabolic processes of...Tumorigenesis is usually accompanied by changes in metabolic patterns,known as metabolic reprogramming[1].To meet the overall metabolic needs for tumor growth and development,tumors regulate the metabolic processes of different cell types by exploiting various environmental and nutritional conditions[2].The metabolic reprogramming of various human tumors is largely conservative[3].However,substantial heterogeneity complicates the identification of their internal causes and mechanisms.Transcriptomics can comprehensively measure tumor metabolism indirectly[4-6].Metabolic reprogramming studies of single cells in various cancer types based on scRNA-seq can reveal their internal networks with other cancer determinants.展开更多
Erythropoiesis is a finely regulated and complex process that involves multiple transformations from hematopoietic stem cells to mature red blood cells at hematopoietic sites from the embryonic to adult stages.Investi...Erythropoiesis is a finely regulated and complex process that involves multiple transformations from hematopoietic stem cells to mature red blood cells at hematopoietic sites from the embryonic to adult stages.Investigations into its molecular mechanisms have generated a wealth of expression data,including bulk and single-cell RNA sequencing data.A comprehensively integrated and well-curated erythropoiesis-specific database will greatly facilitate the mining of gene expression data and enable large-scale research of erythropoiesis and erythroid-related diseases.Here,we present EryDB,an open-access and comprehensive database dedicated to the collection,integration,analysis,and visualization of transcriptomic data for erythropoiesis and erythroid-related diseases.Currently,the database includes expertly curated quality-assured data of 3803 samples and 1,187,119 single cells derived from 107 public studies of three species(Homo sapiens,Mus musculus,and Danio rerio),nine tissue types,and five diseases.EryDB provides users with the ability to not only browse the molecular features of erythropoiesis between tissues and species,but also perform computational analyses of single-cell and bulk RNA sequencing data,thus serving as a convenient platform for customized queries and analyses.EryDB v1.0 is freely accessible at https://ngdc.cncb.ac.cn/EryDB/home.展开更多
Advancements in high-throughput omics technologies have facilitated a systematic exploration of crucial hematopoietic organs across diverse species.A thorough understanding of hematopoiesis in vivo and facilitation of...Advancements in high-throughput omics technologies have facilitated a systematic exploration of crucial hematopoietic organs across diverse species.A thorough understanding of hematopoiesis in vivo and facilitation of generating functional hematopoietic stem and progenitor cells(HSPCs)in vitro necessitate a comprehensive hematopoietic cross-stage developmental landscape across species.To address this need,we developed HemAtlas,a platform designed for the systematic mapping of hematopoiesis both in vivo and in vitro.HemAtlas features detailed analyses of multi-omics datasets from humans,mice,zebrafish,and HSPC in vitro culture systems.Utilizing literature curation and data normalization,HemAtlas integrates various functional modules,allowing interactive exploration and visualization of any collected omics data based on user-specific interests.Moreover,by applying a systematic and uniform integration method,we constructed organ-wide hematopoietic references for each species with manually curated cell annotations,enabling a comprehensive decoding of cross-stage developmental hematopoiesis at the organ level.Of particular significance are three distinctive functions-single-cell cross-stage,cross-species,and cross-model analyses-that HemAtlas employs to elucidate the hematopoietic development in zebrafish,mice,and humans,and to offer guidance on the generation of HSPCs in vitro.Simultaneously,HemAtlas incorporates a comprehensive map of HSPC cross-stage development to reveal HSPC stage-specific properties.Taken together,HemAtlas serves as a crucial resource to advance our understanding of hematopoiesis and is available at https://ngdc.cncb.ac.cn/hematlas/.展开更多
The Genome Sequence Archive(GSA)is a data repository for archiving raw sequence data,which provides data storage and sharing services for worldwide scientific communities.Considering explosive data growth with diverse...The Genome Sequence Archive(GSA)is a data repository for archiving raw sequence data,which provides data storage and sharing services for worldwide scientific communities.Considering explosive data growth with diverse data types,here we present the GSA family by expanding into a set of resources for raw data archive with different purposes,namely,GSA(https://ngdc.cncb.ac.cn/gsa/),GSA for Human(GSA-Human,https://ngdc.cncb.ac.cn/gsa-human/),and Open Archive for Miscellaneous Data(OMIX,https://ngdc.cncb.ac.cn/omix/).Compared with the 2017 version,GSA has been significantly updated in data model,online functionalities,and web interfaces.GSA-Human,as a new partner of GSA,is a data repository specialized in human genetics-related data with controlled access and security.OMIX,as a critical complement to the two resources mentioned above,is an open archive for miscellaneous data.Together,all these resources form a family of resources dedicated to archiving explosive data with diverse types,accepting data submissions from all over the world,and providing free open access to all publicly available data in support of worldwide research activities.展开更多
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 cor...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 genomescale 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.展开更多
The rapid advancement of sequencing technologies poses challenges in managing the large volume and exponential growth of sequence data efficiently and on time.To address this issue,we present GenBase(https://ngdc.cncb...The rapid advancement of sequencing technologies poses challenges in managing the large volume and exponential growth of sequence data efficiently and on time.To address this issue,we present GenBase(https://ngdc.cncb.ac.cn/genbase),an open-access data repository that follows the International Nucleotide Sequence Database Collaboration(INSDC)data standards and structures,for efficient nucleotide sequence archiving,searching,and sharing.As a core resource within the National Genomics Data Center(NGDC)of the China National Center for Bioinformation(CNCB;https://ngdc.cncb.ac.cn),GenBase offers bilingual submission pipeline and services,as well as local submission assistance in China.GenBase also provides a unique Excel format for metadata description and feature annotation of nucleotide sequences,along with a real-time data validation system to streamline sequence submissions.As of April 23,2024,GenBase received 68,251 nucleotide sequences and 689,574 annotated protein sequences across 414 species from 2319 submissions.Out of these,63,614(93%)nucleotide sequences and 620,640(90%)annotated protein sequences have been released and are publicly accessible through GenBase’s web search system,File Transfer Protocol(FTP),and Application Programming Interface(API).Additionally,in collaboration with INSDC,GenBase has constructed an effective data exchange mechanism with GenBank and started sharing released nucleotide sequences.Furthermore,GenBase integrates all sequences from GenBank with daily updates,demonstrating its commitment to actively contributing to global sequence data management and sharing.展开更多
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 provi...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/.展开更多
Data and their tailored characteristics are inheritable and longlived,surpassing their analyzed results and conclusions regardless if they are produced by their generators or users.Aside from designing experiments for...Data and their tailored characteristics are inheritable and longlived,surpassing their analyzed results and conclusions regardless if they are produced by their generators or users.Aside from designing experiments for the new acquisition,scientific researchers always begin with a thorough synthesis of the existing data,especially those that have been demonstrated authentic and timely.展开更多
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-Co...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/.展开更多
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...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/).展开更多
Leaf senescence is the final stage of leaf development and involves the active degradation and dynamic transfer of its cellular components to newly growing and storage tissues,which contributes to plant fitness(Gan an...Leaf senescence is the final stage of leaf development and involves the active degradation and dynamic transfer of its cellular components to newly growing and storage tissues,which contributes to plant fitness(Gan and Amasino,1997;Lim et al.,2007).The genetic modification of leaf senescence has emerged as a promising strategy for improving nutritional traits and stress tolerance in plants(Rivero et al.,2007).Efforts to dissect the molecular mechanisms underpinning leaf senescence reveal that it is a highly coordinated process regulated by a large number of senescence-associated genes(SAGs)(Guo and Gan,2005;Lim et al.,2007).Functional studies of these SAG genes through reverse genetics strategies and identification of senescence-altered mutants through forward genetic screening have deepened the understanding of leaf senescence(Guo et al.,2021).展开更多
基金supported by Technological Innovation 2030 (2022ZD0401701)National Natural Science Foundation of China (32000475,32030021)+1 种基金Strategic Priority Research Program of the Chinese Academy of Sciences (XDA24040201)Youth Innovation Promotion Association of the Chinese Academy of Sciences (Y2021038).
文摘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.
基金supported by the National Key Research and Development Project (2020YFC0847000,2021YFC0863300, 2020YFC0845900)the Strategic Priority Research Program of the Chinese Academy of Sciences (XDPB17)+1 种基金the National Natural Science Foundation of China (31100273, 91731304,31172073)Shandong Academician Workstation Program#170401 (to G.P.Z.)。
文摘DEAR EDITOR,The COVID-19 pandemic caused by SARS-CoV-2 continues to pose a tremendous threat to human society. SARS-CoV-2is airborne and transmits primarily through social contact;however, whether cold chain-related transmission has occurred remains highly debated(Han & Liu, 2022;Lewis,2021;Ma et al., 2021;Mallapaty et al., 2021;Pang et al.,2020;Wu et al., 2021). Here, we present a novel method and identify two transmission routes based on lineage-specific reductions in the SARS-CoV-2 evolutionary rate.
基金supported by the National Natural Science Foundation of China(No.32072947)the China Agriculture Research System(No.CARS-47)。
文摘Urea is a major end product of nitrogen catabolism,serving as an osmolyte to regulate osmotic stress in fish exposed to varying water environments.It has been well known that urea transporters(UTs)facilitate the rapid movement of urea across cell membranes.However,researches on ut genes were predominantly focused on elasmobranchs and early developmental stages of fish.In this investigation,a total of three ut genes were identified in spotted sea bass.Phylogenetic,homology,and syntenic analyses were conducted to validate the annotation and assess the evolutionary relationships among ut genes.Both ut-a and ut-b genes have retained their evolutionary stability,demonstrating a significant level of homology between them.To gain deeper insights into the evolution of ut genes in spotted sea bass,we performed selective pressure analysis using site,branch,and branch-site models.The results suggested that positive selection likely played a significant role in shaping the evolution of the ut gene family.Furthermore,tissue-specific expression analyses revealed high expression levels of ut genes in osmoregulatory tissues such as the gill and kidney.Additionally,all three ut genes exhibited salinity-related expression patterns in gill and kidney tissues during both seawater-to-freshwater(SF)and freshwater-to-seawater(FS)adaptation.In situ hybridization results demonstrated the localization of both ut-a and ut-c mRNAs on the gill lamellae and adjacent gill filament epithelium.In summary,our study establishes a solid foundation for future research elucidating the evolutionary relationships and functional significance of ut genes during salinity acclimation in spotted sea bass and other teleost species.
基金funded by the“Strategic Priority Research Program”of CAS(Grant No.XDB38030200)the Open Biodiversity and Health Big Data Programme of International Union of Biological Sciences awarded to YB.
文摘Background Big data challenges In the late 1980s and early 1990s,three major international biological data centers were created:the DNA Database of Japan(DDBJ)[1],the European Bioinformatics Institute(EMBL-EBI)in the United Kingdom(UK)[2],and the National Center for Biotechnology Information(NCBI)in the United States(US)[3].
基金Project supported by the National Natural Science Foundation of China(Grant No.31971183).
文摘Cell migration plays a significant role in physiological and pathological processes.Understanding the characteristics of cell movement is crucial for comprehending biological processes such as cell functionality,cell migration,and cell–cell interactions.One of the fundamental characteristics of cell movement is the specific distribution of cell speed,containing valuable information that still requires comprehensive understanding.This article investigates the distribution of mean velocities along cell trajectories,with a focus on optimizing the efficiency of cell food search in the context of the entire colony.We confirm that the specific velocity distribution in the experiments corresponds to an optimal search efficiency when spatial weighting is considered.The simulation results indicate that the distribution of average velocity does not align with the optimal search efficiency when employing average spatial weighting.However,when considering the distribution of central spatial weighting,the specific velocity distribution in the experiment is shown to correspond to the optimal search efficiency.Our simulations reveal that for any given distribution of average velocity,a specific central spatial weighting can be identified among the possible central spatial weighting that aligns with the optimal search strategy.Additionally,our work presents a method for determining the spatial weights embedded in the velocity distribution of cell movement.Our results have provided new avenues for further investigation of significant topics,such as relationship between cell behavior and environmental conditions throughout their evolutionary history,and how cells achieve collective cooperation through cell-cell communication.
基金Project supported by the National Natural Science Foundation of China(Grant No.31971183)。
文摘Quantitative examination of cellular motion and intercellullar interactions possesses substantial relevance for both biology and medicine.However,the effects of intercellular interactions during cellular locomotion remain under-explored in experimental research.As such,this study seeks to bridge this research gap,adopting Dictyostelium discoideum(Dicty)cells as a paradigm to investigate variations in cellular motion during reciprocal collisions.We aim to attain a comprehensive understanding of how cell interactions influence cell motion.By observing and processing the motion trajectories of colliding cells under diverse chemical environments,we calculated the diffusion coefficient(D)and the persistence time(τ),using mean square displacement.Our analysis of the relationship dynamics between D andτprior to the collisions reveals intricate and non-monotonic alterations in cell movements during collisions.By quantitatively scrutinizing theτtrend,we were able to categorize the cellular responses to interactions under different conditions.Importantly,we ascertained that the effect of cell interactions during collisions in Dicty cells emulates a classical sigmoid function.This discovery suggests that cellular responses might comply with a pattern akin to the Weber–Fechner law.
文摘BACKGROUND Preoperative risk stratification is significant for the management of endometrial cancer(EC)patients.Radiomics based on magnetic resonance imaging(MRI)in combination with clinical features may be useful to predict the risk grade of EC.AIM To construct machine learning models to predict preoperative risk stratification of patients with EC based on radiomics features extracted from MRI.METHODS The study comprised 112 EC patients.The participants were randomly separated into training and validation groups with a 7:3 ratio.Logistic regression analysis was applied to uncover independent clinical predictors.These predictors were then used to create a clinical nomogram.Extracted radiomics features from the T2-weighted imaging and diffusion weighted imaging sequences of MRI images,the Mann-Whitney U test,Pearson test,and least absolute shrinkage and selection operator analysis were employed to evaluate the relevant radiomic features,which were subsequently utilized to generate a radiomic signature.Seven machine learning strategies were used to construct radiomic models that relied on the screening features.The logistic regression method was used to construct a composite nomogram that incorporated both the radiomic signature and clinical independent risk indicators.RESULTS Having an accuracy of 0.82 along with an area under the curve(AUC)of 0.915[95%confidence interval(CI):0.806-0.986],the random forest method trained on radiomics characteristics performed better than expected.The predictive accuracy of radiomics prediction models surpassed that of both the clinical nomogram(AUC:0.75,95%CI:0.611-0.899)and the combined nomogram(AUC:0.869,95%CI:0.702-0.986)that integrated clinical parameters and radiomic signature.CONCLUSION The MRI-based radiomics model may be an effective tool for preoperative risk grade prediction in EC patients.
基金supported by the National Natural Science Foundation of China(Grant Number[No.82071956])and the Clinical Research Plan of Shanghai Hospital Development Center(Grant Number[No.2020CR4065]).
文摘Glutamine metabolism(GM)plays an important role in tumor growth and proliferation.Skin cutaneous melanoma(SKCM)is a glutamine-dependent cancer.However,the molecular characteristics and action mechanism of GM on SKCM remain unclear.Therefore,we aimed to explore the effects of GM-related genes on survival,clinicopathological characteristics,and the tumor microenvironment in SKCM.In this study,682 SKCM samples were obtained from the Cancer Genome Atlas(TCGA)and Gene Expression Omnibus(GEO)databases.Consensus clustering was used to classify SKCM samples into distinct subtypes based on 41 GM-related genes.Differences in survival,immune infiltration,clinical characteristics,and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways as well as differentially expressed genes(DEGs)between subgroups were evaluated.A prognostic model was constructed according to prognostic DEGs.Differential analyses in survival,immune infiltration,tumor microenvironment(TME),tumor mutation burden(TMB),stemness,and drug sensitivity between risk groups were conducted.We identified two distinct GM-related subtypes on SKCM and found that GM-related gene alterations were associated with survival probability,clinical features,biological function,and immune infiltration.Then a risk model based on six DEGs(IL18,SEMA6A,PAEP,TNFRSF17,AIM2,and CXCL10)was constructed and validated for predicting overall survival in SKCM patients.The results showed that the risk score was negatively correlated with CD8+T cells,activated CD4+memory T cells,M1 macrophages,andγδT cells.The group with a low-risk score was accompanied by a better survival rate with higher TME scores and lower stemness index.Moreover,the group with high-and low-risk score had a significant difference with the sensitivity of 75 drugs(p<0.001).Overall,distinct subtypes in SKCM patients based on GM-related genes were identified and the risk model was constructed,which might contribute to prognosis prediction,guide clinical therapy,and develop novel therapeutic strategies.
基金supported by the Science&Technology Fundamental Resources Investigation Program(Grant No.2022FY101203 to Xuetong Zhao)the International Partnership Program of the Chinese Academy of Sciences(Grant No.161GJHZ2022002MI to Yiming Bao)+2 种基金the Professional Association of the Alliance of International Science Organizations(Grant No.ANSO-PA-2023-07 to Yiming Bao)the CAS Key Technology Talent Program to Meili Chen,the Open Biodiversity and Health Big Data Programme of IUBS to Yiming Bao,the National Key R&D Program of China(Grant No.2023YFC2605700 to Wenming Zhao)the National Natural Science Foundation of China(Grant Nos.32170678 to Wenming Zhao,32170669 to Jingfa Xiao,and 32030021 to Zhang Zhang).
文摘The Genome Warehouse(GWH),accessible at https://ngdc.cncb.ac.cn/gwh,is an extensively-utilized public repository dedicated to the deposition,management,and sharing of genome assembly sequences,annotations,and metadata.This paper highlights noteworthy enhancements to the GWH since the 2021 version,emphasizing substantial advancements in web interfaces for data submission,database functionality updates,and re-source integration.Key updates include the reannotation of released prokaryotic genomes,mirroring of genome resources from National Center for Biotechnology Information(NCBl)GenBank and Reference Sequence Database(RefSeq),integration of Poxviridae sequences,implementation of an online batch submission system,enhancements to the quality control system,advanced search capabilities,and the introduction of a controlled-access mechanism for human genome data.These improvements collectively enhance the ease and security of data submission and access as well as genome data value,thereby improving convenience and utility for researchers in the genomics field.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB38030400)the National Natural Science Foundation of China(32170669 and 32300542)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(2022098).
文摘Tumorigenesis is usually accompanied by changes in metabolic patterns,known as metabolic reprogramming[1].To meet the overall metabolic needs for tumor growth and development,tumors regulate the metabolic processes of different cell types by exploiting various environmental and nutritional conditions[2].The metabolic reprogramming of various human tumors is largely conservative[3].However,substantial heterogeneity complicates the identification of their internal causes and mechanisms.Transcriptomics can comprehensively measure tumor metabolism indirectly[4-6].Metabolic reprogramming studies of single cells in various cancer types based on scRNA-seq can reveal their internal networks with other cancer determinants.
基金supported by the National Key R&D Program of China(Grant No.2022YFC2406803)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA16010602)the National Natural Science Foundation of China(Grant Nos.81870097,82070114,and 82270126).
文摘Erythropoiesis is a finely regulated and complex process that involves multiple transformations from hematopoietic stem cells to mature red blood cells at hematopoietic sites from the embryonic to adult stages.Investigations into its molecular mechanisms have generated a wealth of expression data,including bulk and single-cell RNA sequencing data.A comprehensively integrated and well-curated erythropoiesis-specific database will greatly facilitate the mining of gene expression data and enable large-scale research of erythropoiesis and erythroid-related diseases.Here,we present EryDB,an open-access and comprehensive database dedicated to the collection,integration,analysis,and visualization of transcriptomic data for erythropoiesis and erythroid-related diseases.Currently,the database includes expertly curated quality-assured data of 3803 samples and 1,187,119 single cells derived from 107 public studies of three species(Homo sapiens,Mus musculus,and Danio rerio),nine tissue types,and five diseases.EryDB provides users with the ability to not only browse the molecular features of erythropoiesis between tissues and species,but also perform computational analyses of single-cell and bulk RNA sequencing data,thus serving as a convenient platform for customized queries and analyses.EryDB v1.0 is freely accessible at https://ngdc.cncb.ac.cn/EryDB/home.
基金supported by grants from the National Natural Science Foundation of China(Grant No.32030032 to Feng LiuGrant Nos.T2425005 and 32030021 to Zhang Zhang)+1 种基金the Initiative Scientific Research Program,Institute of Zoology,Chinese Academy of Sciences(Grant Nos.2023IOZ0305 and 2023IOZ0102 to Feng Liu)the International Partnership Program of the Chinese Academy of Sciences(Grant No.153F11KYSB20160008 to Zhang Zhang).
文摘Advancements in high-throughput omics technologies have facilitated a systematic exploration of crucial hematopoietic organs across diverse species.A thorough understanding of hematopoiesis in vivo and facilitation of generating functional hematopoietic stem and progenitor cells(HSPCs)in vitro necessitate a comprehensive hematopoietic cross-stage developmental landscape across species.To address this need,we developed HemAtlas,a platform designed for the systematic mapping of hematopoiesis both in vivo and in vitro.HemAtlas features detailed analyses of multi-omics datasets from humans,mice,zebrafish,and HSPC in vitro culture systems.Utilizing literature curation and data normalization,HemAtlas integrates various functional modules,allowing interactive exploration and visualization of any collected omics data based on user-specific interests.Moreover,by applying a systematic and uniform integration method,we constructed organ-wide hematopoietic references for each species with manually curated cell annotations,enabling a comprehensive decoding of cross-stage developmental hematopoiesis at the organ level.Of particular significance are three distinctive functions-single-cell cross-stage,cross-species,and cross-model analyses-that HemAtlas employs to elucidate the hematopoietic development in zebrafish,mice,and humans,and to offer guidance on the generation of HSPCs in vitro.Simultaneously,HemAtlas incorporates a comprehensive map of HSPC cross-stage development to reveal HSPC stage-specific properties.Taken together,HemAtlas serves as a crucial resource to advance our understanding of hematopoiesis and is available at https://ngdc.cncb.ac.cn/hematlas/.
基金supported by grants from National Key R&D Program of China(Grant No.2017YFC0907502 to ZZ)Strategic Priority Research Program of Chinese Academy of Sciences(Grant Nos.XDB38060100 and XDB38030200 to YB+13 种基金XDB38050300 to WZXDB38030400 to JXXDA19050302 to ZZ)National Key R&D Program of China(Grant Nos.2016YFC0901603 to WZ2017YFC1201202 to YW2020YFC0847000 and 2018YFD1000505 to WZ2016YFE0206600 to YB)The 13th Five-year Informatization Plan of Chinese Academy of Sciences(Grant No.XXH13505-05 to YB)Genomics Data Center Construction of Chinese Academy of Sciences(Grant No.XXH-13514-0202 to YB)Open Biodiversity and Health Big Data Programme of the International Union of Biological Sciences to YBThe Professional Association of the Alliance of International Science Organizations(Grant No.ANSO-PA-2020-07 to YB)National Natural Science Foundation of China(Grant Nos.32030021 and 31871328 to ZZ)International Partnership Program of the Chinese Academy of Sciences(Grant No.153F11KYSB20160008 to ZZ)。
文摘The Genome Sequence Archive(GSA)is a data repository for archiving raw sequence data,which provides data storage and sharing services for worldwide scientific communities.Considering explosive data growth with diverse data types,here we present the GSA family by expanding into a set of resources for raw data archive with different purposes,namely,GSA(https://ngdc.cncb.ac.cn/gsa/),GSA for Human(GSA-Human,https://ngdc.cncb.ac.cn/gsa-human/),and Open Archive for Miscellaneous Data(OMIX,https://ngdc.cncb.ac.cn/omix/).Compared with the 2017 version,GSA has been significantly updated in data model,online functionalities,and web interfaces.GSA-Human,as a new partner of GSA,is a data repository specialized in human genetics-related data with controlled access and security.OMIX,as a critical complement to the two resources mentioned above,is an open archive for miscellaneous data.Together,all these resources form a family of resources dedicated to archiving explosive data with diverse types,accepting data submissions from all over the world,and providing free open access to all publicly available data in support of worldwide research activities.
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences(Grant Nos.XDB38060100 and XDB38030200 to YBXDB38050300 to WZ+9 种基金XDB38030400 to JXXDA19050302 to ZZ)the National Key R&D Program of China(Grant Nos.2016YFE0206600 to YB2020YFC0847000,2018YFD1000505,2017YFC1201202,and 2016YFC0901603 to WZ2017YFC0907502 to ZZ)the 13th Five-year Informatization Plan of Chinese Academy of Sciences(Grant No.XXH13505-05 to YB)the Genomics Data Center Construction of Chinese Academy of Sciences(Grant No.XXH-13514-0202 to YB)the Open Biodiversity and Health Big Data Programme of International Union of Biological Sciences to YB,the Professional Association of the Alliance of International Science Organizations(Grant No.ANSO-PA-2020-07 to YB)the National Natural Science Foundation of China(Grant Nos.32030021 and 31871328 to ZZ)the International Partnership Program of the Chinese Academy of Sciences(Grant No.153F11KYSB20160008 to ZZ)。
文摘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 genomescale 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.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB38030200)the National Key R&D Program of China(Grant No.2021YFF0703701)+2 种基金the Professional Association of the Alliance of International Science Organizations(Grant No.ANSO-PA-2023-07)the International Partnership Program of the Chinese Academy of Sciences(Grant No.161GJHZ2022002MI)the Open Biodiversity and Health Big Data Initiative of International Union of Biological Sciences(IUBS).
文摘The rapid advancement of sequencing technologies poses challenges in managing the large volume and exponential growth of sequence data efficiently and on time.To address this issue,we present GenBase(https://ngdc.cncb.ac.cn/genbase),an open-access data repository that follows the International Nucleotide Sequence Database Collaboration(INSDC)data standards and structures,for efficient nucleotide sequence archiving,searching,and sharing.As a core resource within the National Genomics Data Center(NGDC)of the China National Center for Bioinformation(CNCB;https://ngdc.cncb.ac.cn),GenBase offers bilingual submission pipeline and services,as well as local submission assistance in China.GenBase also provides a unique Excel format for metadata description and feature annotation of nucleotide sequences,along with a real-time data validation system to streamline sequence submissions.As of April 23,2024,GenBase received 68,251 nucleotide sequences and 689,574 annotated protein sequences across 414 species from 2319 submissions.Out of these,63,614(93%)nucleotide sequences and 620,640(90%)annotated protein sequences have been released and are publicly accessible through GenBase’s web search system,File Transfer Protocol(FTP),and Application Programming Interface(API).Additionally,in collaboration with INSDC,GenBase has constructed an effective data exchange mechanism with GenBank and started sharing released nucleotide sequences.Furthermore,GenBase integrates all sequences from GenBank with daily updates,demonstrating its commitment to actively contributing to global sequence data management and sharing.
基金supported by grants from the Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDA08020102 to ZZ and SH)the Youth Innovation Promotion Association of Chinese Academy of Science(Grant No.2018134 to LH)+2 种基金National Programs for High TechnologyResearch and Development(Grant Nos.2015AA020108 and 2012AA020409 to ZZ)the 100-Talent Program of Chinese Academy of Sciences(to YB and ZZ)the National Natural Science Foundation of China(Grant No.31100915 to LH)
文摘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/.
基金supported by grants from the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant Nos.XDA19090116 and XDA19050302)National Key R&D Program of China(Grant No.2017YFC0907502)+2 种基金13th Five-year Informatization Plan of the Chinese Academy of Sciences(Grant No.XXH13505-05)Wong KC Education Foundation to ZZthe International Partnership Program of the Chinese Academy of Sciences(Grant No.153F11KYSB20160008)
文摘Data and their tailored characteristics are inheritable and longlived,surpassing their analyzed results and conclusions regardless if they are produced by their generators or users.Aside from designing experiments for the new acquisition,scientific researchers always begin with a thorough synthesis of the existing data,especially those that have been demonstrated authentic and timely.
基金supported by grants from the National Key R&D Program of China(Grant Nos.2023YFC3041500 and 2021YFF0703703)the Key Collaborative Research Program of the Alliance of International Science Organizations(Grant No.ANSO-CR-KP-2022-09)+2 种基金the National Natural Science Foundation of China(Grant No.32270718)the Beijing Nova Program(Grant No.Z211100002121006)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(Grant Nos.Y2021038 and 2019104),China.
文摘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/.
基金supported by grants from the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant Nos.XDA19090116 and XDA19050302)the National Natural Science Foundation of China(Grant Nos.31871328 and 32030021)+2 种基金the Professional Association of the Alliance of International Science Organizations(Grant No.ANSO-PA-2020-07)the Youth Innovation Promotion Association of Chinese Academy of Sciences(Grant No.2019104)the International Partnership Program of the Chinese Academy of Sciences(Grant No.153F11KYSB20160008).
文摘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/).
基金National Natural Science Foundation of China(32170345 and 31970196 to ZL)Strategic Priority Research Program of the Chinese Academy of Sciences(XDA19050302,XDB13040500 to Z.Z.)+3 种基金National Key Research and Development Program of China,Startup Funding(2017YFC0907502 to Z.Z.)13th Fiveyear Informatization Plan of Chinese Academy of Sciences(XXH13505-05 to Z.Z.)International Partnership Program of the Chinese Academy of Sciences(153F11KYSB20160008)National Key Research and Development Program of China(2019YFA0903904 to H.G.).
文摘Leaf senescence is the final stage of leaf development and involves the active degradation and dynamic transfer of its cellular components to newly growing and storage tissues,which contributes to plant fitness(Gan and Amasino,1997;Lim et al.,2007).The genetic modification of leaf senescence has emerged as a promising strategy for improving nutritional traits and stress tolerance in plants(Rivero et al.,2007).Efforts to dissect the molecular mechanisms underpinning leaf senescence reveal that it is a highly coordinated process regulated by a large number of senescence-associated genes(SAGs)(Guo and Gan,2005;Lim et al.,2007).Functional studies of these SAG genes through reverse genetics strategies and identification of senescence-altered mutants through forward genetic screening have deepened the understanding of leaf senescence(Guo et al.,2021).
