Lactic acid bacteria and the fermentation environment interact to form an intertwined system.Lactic acid bacteria are constantly evolving to adapt to different fermentation environments,causing changes in their physio...Lactic acid bacteria and the fermentation environment interact to form an intertwined system.Lactic acid bacteria are constantly evolving to adapt to different fermentation environments,causing changes in their physiological processes.To achieve a targeted improvement of their adaptability to various environments,a detail analysis of their evolutionary physiological processes is required.While several studies have been carried out in the past by using single-omics techniques to investigate their response to environmental stress,most researchers are now using a multi-omics approach to explore more detail in the biological regulatory networks and molecular mechanisms of lactic acid bacteria in response to environmental stress,thereby overcoming the limitations of single-omics analysis.In this review,we describe the various single-omics approaches that have been used to study environmental stress in lactic acid bacteria,present the advantages of various multi-omics combined analysis approaches,and discuss the potential and practicality of applying emerging single-cell transcriptomics and single-cell metabolomics techniques to the molecular mechanism study of microbes response to environmental stress.Multi-omics approaches enable the accurate identification of complex microbial physiological processes in different environments,allow people to comprehensively reveal the molecular mechanisms of microbes response to stress from different perspectives.Single-cell omics techniques,analyze the targeted regulation of microbial functions in a multi-dimensional space,provides a new perspective on understanding microbes responses environment stress.展开更多
Musculoskeletal disorders,including osteoarthritis,rheumatoid arthritis,osteoporosis,bone fracture,intervertebral disc degeneration,tendinopathy,and myopathy,are prevalent conditions that profoundly impact quality of ...Musculoskeletal disorders,including osteoarthritis,rheumatoid arthritis,osteoporosis,bone fracture,intervertebral disc degeneration,tendinopathy,and myopathy,are prevalent conditions that profoundly impact quality of life and place substantial economic burdens on healthcare systems.Traditional bulk transcriptomics,genomics,proteomics,and metabolomics have played a pivotal role in uncovering disease-associated alterations at the population level.However,these approaches are inherently limited in their ability to resolve cellular heterogeneity or to capture the spatial organization of cells within tissues,thus hindering a comprehensive understanding of the complex cellular and molecular mechanisms underlying these diseases.To address these limitations,advanced single-cell and spatial omics techniques have emerged in recent years,offering unparalleled resolution for investigating cellular diversity,tissue microenvironments,and biomolecular interactions within musculoskeletal tissues.These cutting-edge techniques enable the detailed mapping of the molecular landscapes in diseased tissues,providing transformative insights into pathophysiological processes at both the single-cell and spatial levels.This review presents a comprehensive overview of the latest omics technologies as applied to musculoskeletal research,with a particular focus on their potential to revolutionize our understanding of disease mechanisms.Additionally,we explore the power of multi-omics integration in identifying novel therapeutic targets and highlight key challenges that must be overcome to successfully translate these advancements into clinical applications.展开更多
Osteoarthritis(OA)is a degenerative joint disease with significant clinical and societal impact.Traditional diagnostic methods,including subjective clinical assessments and imaging techniques such as X-rays and MRIs,a...Osteoarthritis(OA)is a degenerative joint disease with significant clinical and societal impact.Traditional diagnostic methods,including subjective clinical assessments and imaging techniques such as X-rays and MRIs,are often limited in their ability to detect early-stage OA or capture subtle joint changes.These limitations result in delayed diagnoses and inconsistent outcomes.Additionally,the analysis of omics data is challenged by the complexity and high dimensionality of biological datasets,making it difficult to identify key molecular mechanisms and biomarkers.Recent advancements in artificial intelligence(AI)offer transformative potential to address these challenges.This review systematically explores the integration of AI into OA research,focusing on applications such as AI-driven early screening and risk prediction from electronic health records(EHR),automated grading and morphological analysis of imaging data,and biomarker discovery through multi-omics integration.By consolidating progress across clinical,imaging,and omics domains,this review provides a comprehensive perspective on how AI is reshaping OA research.The findings have the potential to drive innovations in personalized medicine and targeted interventions,addressing longstanding challenges in OA diagnosis and management.展开更多
In this editorial,we comment on the article by Micucci et al published in the recent issue.We focus on the heterogenous nature of gastric cancer(GC)and the potential benefits of integrating traditional Chinese medicin...In this editorial,we comment on the article by Micucci et al published in the recent issue.We focus on the heterogenous nature of gastric cancer(GC)and the potential benefits of integrating traditional Chinese medicine(TCM)with the modern technology of network pharmacology(NP)and omics sequencing.GC is a heterogenous disease,as it incorporates several biochemical pathways that contribute to pathogenesis.TCM acknowledges the multifactorial,heterogenous nature of disease and utilizes an integrative approach to medicine.NP,a modern philosophy within drug development,integrates traditional knowledge of nutraceuticals and modern technologies to address the complex interactions of pathways within the body.Omics technologies,which is at the core of precision medicine,has allowed for this newfound principle of drug development.Metabolic pathways are better distinguished,leading to more targeted drug development.However,the use of omics technology needs to be employed to better characterize the subtypes of GC.This will allow TCM’s use of nutraceuticals in the application of NP to better target metabolic pathways that may aid in the prevention of GC as well as enhance treatment.展开更多
There is growing evidence that lipid metabolism instability in depressive disorder may be a core early pathological event associated with numerous pathogenesis hypotheses.However,spatial distributions and quantitative...There is growing evidence that lipid metabolism instability in depressive disorder may be a core early pathological event associated with numerous pathogenesis hypotheses.However,spatial distributions and quantitative changes of lipids in specific brain regions associated with depressive disorder are far from elucidated.In the present study,lipid profiling characteristics of whole brain sections are systematically determined by using matrix-assisted laser desorption ionization-mass spectrometry imaging(MALDI-MSI)-combined with histomorphological analysis in rats with depressive-like behavior induced by multiple early life stress(mELS)and unstressed control.Lipid dyshomeostasis and different degrees of metabolic disturbance occur in the eight paired representative brain sections from micro-region and molecular level.More specifically,17 lipid molecules show the severe dyshomeostasis between intergroup(control and depressed rats)or intra-group(multiple emotion-regulation-related brain regions).Quite specially,phosphatidylcholine(PC)(39:6)expression in section 7 is significantly upregulated only in the amygdala of depressed rat relative to control rat,by contrast,up-regulated phosphatidylglycerol(PG)(34:2)in section 2 emerges in the medial prefrontal cortex,insular cortex,and nucleus accumbens simultaneously.Linking spatial distribution to quantitative variation of lipids from the whole brain sections contributes the uncovering of new insights in causal mechanism of lipid dyshomeostasis in depression investigation and related targeting interventions.展开更多
Objective:Circadian rhythm disruption(CRD)is a risk factor that correlates with poor prognosis across multiple tumor types,including hepatocellular carcinoma(HCC).However,its mechanism remains unclear.This study aimed...Objective:Circadian rhythm disruption(CRD)is a risk factor that correlates with poor prognosis across multiple tumor types,including hepatocellular carcinoma(HCC).However,its mechanism remains unclear.This study aimed to define HCC subtypes based on CRD and explore their individual heterogeneity.Methods:To quantify CRD,the HCC CRD score(HCCcrds)was developed.Using machine learning algorithms,we identified CRD module genes and defined CRD-related HCC subtypes in The Cancer Genome Atlas liver HCC cohort(n=369),and the robustness of this method was validated.Furthermore,we used bioinformatics tools to investigate the cellular heterogeneity across these CRD subtypes.Results:We defined three distinct HCC subtypes that exhibit significant heterogeneity in prognosis.The CRD-related subtype with high HCCcrds was significantly correlated with worse prognosis,higher pathological grade,and advanced clinical stages,while the CRD-related subtype with low HCCcrds had better clinical outcomes.We also identified novel biomarkers for each subtype,such as nicotinamide nmethyltransferase and myristoylated alanine-rich protein kinase C substrate-like 1.Conclusion:We classify the HCC patients into three distinct groups based on circadian rhythm and identify their specific biomarkers.Within these groups greater HCCcrds was associated with worse prognosis.This approach has the potential to improve prediction of an individual’s prognosis,guide precision treatments,and assist clinical decision making for HCC patients.展开更多
Pediatric cataract,a leading cause of blindness in children globally,imposing a significant financial burden on both families and society.The extensive phenotypic heterogeneity of this condition means that the underly...Pediatric cataract,a leading cause of blindness in children globally,imposing a significant financial burden on both families and society.The extensive phenotypic heterogeneity of this condition means that the underlying mechanisms remain poorly understood,limiting the development of precise and effective treatments.The advent of omics technologies has provided potent tools for unraveling the pathogenesis of pediatric cataract.By mapping expression profiles across various molecular levels,these omics approaches enhance our understanding of the disease’s etiological mechanisms,aid in the identification of novel biomarkers and key pathways,and offer researchers new insights for the innovative strategies in disease diagnosis and targeted therapies.In this review,we summarize the application of omics approaches in clinical and basic research on pediatric cataract over the past decade,encompassing genomics,transcriptomics,proteomics,and metabolomics.Furthermore,we discuss the current challenges and future prospects of omics analyses in pediatric cataract studies.展开更多
Immunotherapies have demonstrated notable clinical benefits in the treatment of cervical cancer(CC).However,the development of therapeutic resistance and diverse adverse effects in immunotherapy stem from complex inte...Immunotherapies have demonstrated notable clinical benefits in the treatment of cervical cancer(CC).However,the development of therapeutic resistance and diverse adverse effects in immunotherapy stem from complex interactions among biological processes and factors within the tumor immune microenvironment(TIME).Advanced omic technologies offer novel insights into a more expansive and thorough layer of the TIME.Furthermore,integrating multidimensional omics within the frameworks of systems biology and computational methodologies facilitates the generation of interpretable data outputs to characterize the clinical and biological trajectories of tumor behavior.In this review,we present advanced omics technologies that utilize various clinical samples to address scientific inquiries related to immunotherapies for CC,highlighting their utility in identifying metastasis dissemination,recurrence risk,and therapeutic resistance in patients treated with immunotherapeutic approaches.This review elaborates on the strategy for integrating multi-omics data through artificial intelligence algorithms.Additionally,an analysis of the obstacles encountered in the multi-omics analysis process and potential avenues for future research in this domain are presented.展开更多
Spatial transcriptomics is an organizational study done on tissue sections that preserves the spatial information of the sample.Spatial transcriptomics aims to combine spatial information with gene expression data to ...Spatial transcriptomics is an organizational study done on tissue sections that preserves the spatial information of the sample.Spatial transcriptomics aims to combine spatial information with gene expression data to quantify the mRNA expression of a large number of genes in the spatial context of tissues and cells.As a paradigm shift in biological research,spatial transcriptomics can provide both spatial location information and transcriptome-level cellular gene expression data,elucidating the interactions between cells and the microenvironment.From the understanding of the entire functional life cycle of RNA to the characterization of molecular mechanisms to the mapping of gene expression in various tissue regions,by choosing the appropriate spatial transcriptome technology,researchers can achieve a deeper exploration of biological developmental processes,disease pathogenesis,etc.In recent years,the field of spatial transcriptomics has ushered in several challenges along with its rapid development,such as the dependence on sample types,the resolution of visualized genes,the difficulty of commercialization,and the ability to obtain detailed single-cell information.In this paper,we summarize and review the four major categories of spatial transcriptome technologies and compare and analyze the technical advantages and major challenges of multiple research strategies to assist current experimental design and research analysis.Finally,the importance of spatial transcriptomics in the integration of multi-omics analysis and disease modeling as well as the future development prospects are summarized and outlined.展开更多
Stem cell transplantation is a potential therapeutic strategy for ischemic stroke. However, despite many years of preclinical research, the application of stem cells is still limited to the clinical trial stage. Altho...Stem cell transplantation is a potential therapeutic strategy for ischemic stroke. However, despite many years of preclinical research, the application of stem cells is still limited to the clinical trial stage. Although stem cell therapy can be highly beneficial in promoting functional recovery, the precise mechanisms of action that are responsible for this effect have yet to be fully elucidated. Omics analysis provides us with a new perspective to investigate the physiological mechanisms and multiple functions of stem cells in ischemic stroke. Transcriptomic, proteomic, and metabolomic analyses have become important tools for discovering biomarkers and analyzing molecular changes under pathological conditions. Omics analysis could help us to identify new pathways mediated by stem cells for the treatment of ischemic stroke via stem cell therapy, thereby facilitating the translation of stem cell therapies into clinical use. In this review, we summarize the pathophysiology of ischemic stroke and discuss recent progress in the development of stem cell therapies for the treatment of ischemic stroke by applying multi-level omics. We also discuss changes in RNAs, proteins, and metabolites in the cerebral tissues and body fluids under stroke conditions and following stem cell treatment, and summarize the regulatory factors that play a key role in stem cell therapy. The exploration of stem cell therapy at the molecular level will facilitate the clinical application of stem cells and provide new treatment possibilities for the complete recovery of neurological function in patients with ischemic stroke.展开更多
In the post-genomic era, biological studies are characterized by the rapid development and wide application of a series of "omics" technologies, including genomics, proteomics, metabolomics, transcriptomics,...In the post-genomic era, biological studies are characterized by the rapid development and wide application of a series of "omics" technologies, including genomics, proteomics, metabolomics, transcriptomics, lipidomics, cytomics, metallomics, ionomics, interactomics, and phenomics. These "omics" are often based on global analyses of biological samples using high through-put analytical approaches and bioinformatics and may provide new insights into biological phenomena. In this paper, the development and advances in these omics made in the past decades are reviewed, especially genomics, transcriptomics, proteomics and metabolomics; the applications of omics technologies in pharmaceutical research are then summarized in the fields of drug target discovery, toxicity evaluation, personalized medicine, and traditional Chinese medicine; and finally, the limitations of omics are discussed, along with the future challenges associated with the multi-omics data processing, dynamics omics analysis, and analytical approaches, as well as amenable solutions and future prospects.展开更多
Although there has been a notable decrease in cancer mortality rates for many common cancers over the last decades,there remains a concerning lack of progress in understanding and treating rare tumors[1].Rare tumors a...Although there has been a notable decrease in cancer mortality rates for many common cancers over the last decades,there remains a concerning lack of progress in understanding and treating rare tumors[1].Rare tumors are types of tumors that are rare in clinical practice,which are the subclass of rare diseases.The classification of rare tumors varies internationally,with the US Food and Drug Administration and National Cancer Institute defining them as tumors with an incidence rate of less than 15 per 100,000 individuals annually,while the European Medicines Agency set the threshold at 6 per 100,000.According to the results from the National Cancer Center PLATFORM study in China,rare tumors are defined as an annual incidence rate of 2.5/100,000 or less.Although the incidence of each rare tumor is low,the total number of rare tumors is not low.The total number of rare tumor incidence in China is about 560,000 per year,accounting for 14.2%of all cancer patients[2].More than half of the rare tumors lack clinical treatment guidelines,or there is no standard treatment in clinical practice,suggesting there is a huge unmet medical need for effective treatments for rare tumors.展开更多
Unmet needs exist in metabolic dysfunction-associated steatotic liver disease(MASLD)risk stratification.Our ability to identify patients with MASLD with advanced fibrosis and at higher risk for adverse outcomes is sti...Unmet needs exist in metabolic dysfunction-associated steatotic liver disease(MASLD)risk stratification.Our ability to identify patients with MASLD with advanced fibrosis and at higher risk for adverse outcomes is still limited.Incorporating novel biomarkers could represent a meaningful improvement to current risk predictors.With this aim,omics technologies have revolutionized the process of MASLD biomarker discovery over the past decades.While the research in this field is thriving,much of the publication has been haphazard,often using single-omics data and specimen sets of convenience,with many identified candidate biomarkers but lacking clinical validation and utility.If we incorporate these biomarkers to direct patients’management,it should be considered that the roadmap for translating a newly discovered omics-based signature to an actual,analytically valid test useful in MASLD clinical practice is rigorous and,therefore,not easily accomplished.This article presents an overview of this area’s current state,the conceivable opportunities and challenges of omics-based laboratory diagnostics,and a roadmap for improving MASLD biomarker research.展开更多
Use of nanomaterials(NMs)to improve plant abiotic stress tolerance(AST)is a hot topic in NM-enabled agriculture.Previous studies mainly focused on the physiological and biochemical responses of plants treated with NMs...Use of nanomaterials(NMs)to improve plant abiotic stress tolerance(AST)is a hot topic in NM-enabled agriculture.Previous studies mainly focused on the physiological and biochemical responses of plants treated with NMs under abiotic stress.To use NMs for improving plant AST,it is necessary to understand how they act on this tolerance at the omics and epigenetics levels.In this review,we summarized the knowledge of NM-improved abiotic stress tolerance in relation to omics(such as metabolic,transcriptomic,proteomic,and microRNA),DNA methylation,and histone modifications.Overall,NMs can improve plant abiotic stress tolerance through the modulation at omics and epigenetics levels.展开更多
Head and neck squamous cell carcinoma(HNSCC)is one of the most frequent cancers worldwide.The main risk factors are consumption of tobacco products and alcohol,as well as infection with human papilloma virus.Approved ...Head and neck squamous cell carcinoma(HNSCC)is one of the most frequent cancers worldwide.The main risk factors are consumption of tobacco products and alcohol,as well as infection with human papilloma virus.Approved therapeutic options comprise surgery,radiation,chemotherapy,targeted therapy through epidermal growth factor receptor inhibition,and immunotherapy,but outcome has remained unsatisfactory due to recurrence rates of~50%and the frequent occurrence of second primaries.The availability of the human genome sequence at the beginning of the millennium heralded the omics era,in which rapid technological progress has advanced our knowledge of the molecular biology of malignant diseases,including HNSCC,at an unprecedented pace.Initially,microarray-based methods,followed by approaches based on next-generation sequencing,were applied to study the genetics,epigenetics,and gene expression patterns of bulk tumors.More recently,the advent of single-cell RNA sequencing(scRNAseq)and spatial transcriptomics methods has facilitated the investigation of the heterogeneity between and within different cell populations in the tumor microenvironment(e.g.,cancer cells,fibroblasts,immune cells,endothelial cells),led to the discovery of novel cell types,and advanced the discovery of cell-cell communication within tumors.This review provides an overview of scRNAseq,spatial transcriptomics,and the associated bioinformatics methods,and summarizes how their application has promoted our understanding of the emergence,composition,progression,and therapy responsiveness of,and intercellular signaling within,HNSCC.展开更多
Spatial omics technology integrates the concept of space into omics research and retains the spatial information of tissues or organs while obtaining molecular information.It is characterized by the ability to visuali...Spatial omics technology integrates the concept of space into omics research and retains the spatial information of tissues or organs while obtaining molecular information.It is characterized by the ability to visualize changes in molecular information and yields intuitive and vivid visual results.Spatial omics technologies include spatial transcriptomics,spatial proteomics,spatial metabolomics,and other technologies,the most widely used of which are spatial transcriptomics and spatial proteomics.The tumor microenvironment refers to the surrounding microenvironment in which tumor cells exist,including the surrounding blood vessels,immune cells,fibroblasts,bone marrow-derived inflammatory cells,various signaling molecules,and extracellular matrix.A key issue in modern tumor biology is the application of spatial omics to the study of the tumor microenvironment,which can reveal problems that conventional research techniques cannot,potentially leading to the development of novel therapeutic agents for cancer.This paper summarizes the progress of research on spatial transcriptomics and spatial proteomics technologies for characterizing the tumor immune microenvironment.展开更多
Recent advances in spatial and single-cell omics have significantly revolutionized biomarker discovery in tumor immunotherapy by addressing critical challenges such as tumor heterogeneity,immune evasion,and variabilit...Recent advances in spatial and single-cell omics have significantly revolutionized biomarker discovery in tumor immunotherapy by addressing critical challenges such as tumor heterogeneity,immune evasion,and variability within the tumor microenvironment(TME).Immunotherapeutic strategies,including immune checkpoint in-hibitors and adoptive T-cell transfer,have demonstrated promising clinical outcomes;however,their efficacy is limited by low response rates and the incidence of immune-related adverse events(irAEs).Therefore,the identification of reliable biomarkers is essential for predicting treatment efficacy,minimizing irAEs,and facili-tating patient stratification.Spatial omics integrates molecular profiling with spatial localization,thereby providing comprehensive insights into the cellular organization and functional states within the TME.By elucidating the spatial patterns of immune cell infiltration and tumor heterogeneity,this approach enhances the prediction of therapeutic responses.Similarly,single-cell omics enables high-resolution analysis of cellular heterogeneity by capturing transcriptomic,epigenomic,and metabolic signatures at the single-cell level.The integrated application of spatial and single-cell omics has enabled the identification of previously undetected biomarkers,including rare immune cell subsets implicated in resistance mechanisms.In addition to spatial transcriptomics(ST),this technological landscape also includes spatial proteomics(SP)and spatial metab-olomics,which further facilitate the study of dynamic tumor-immune interactions.Multi-omics integration provides a comprehensive overview of biomarker landscapes,while the rapid evolution of artificial intelligence(AI)-based approaches enhances the analysis of complex,multidimensional datasets to ultimately enhance pre-dictive potential and clinical utility.Despite substantial progress,several challenges remain in the context of standardization,data integration,and real-time monitoring.Nevertheless,the incorporation of spatial and single-cell omics into biomarker research holds transformative potential for advancing personalized cancer immuno-therapy.These emerging strategies pave the way for the development of innovative diagnostic and therapeutic interventions,thereby enabling precision oncology and improving treatment outcomes across a wide range of tumor profiles.This review aims to provide a comprehensive overview of the integration of spatial omics with single-cell omics in the discovery of biomarkers for tumor immunotherapy.Specifically,it examines the strategies by which these emerging technologies address the challenges related to tumor heterogeneity,immune evasion,and the dynamic nature of the TME.By elaborating on the principles,applications,and clinical potential of these technologies,this review also critically evaluates their limitations,challenges,and the current gaps in clinical translation.展开更多
Fusarium head blight(FHB) is a global wheat disease that devastates wheat production. Resistance to FHB spread within a wheat spike(type Ⅱ resistance) and to mycotoxin accumulation in infected kernel(type Ⅲ resistan...Fusarium head blight(FHB) is a global wheat disease that devastates wheat production. Resistance to FHB spread within a wheat spike(type Ⅱ resistance) and to mycotoxin accumulation in infected kernel(type Ⅲ resistance) are the two main types of resistance. Of hundreds of QTL that have been reported, only a few can be used in wheat breeding because most show minor and/or inconsistent effects in different genetic backgrounds. We describe a new strategy for identifying robust and reliable meta-QTL(mQTL)that can be used for improvement of wheat FHB resistance. It involves integration of mQTL analysis with mQTL physical mapping and identification of single-copy markers and candidate genes. Using metaanalysis, we consolidated 625 original QTL from 113 publications into 118 genetic map-based mQTL(gmQTL). These gmQTL were further located on the Chinese Spring reference sequence map. Finally, 77 high-confidence mQTL(hcmQTL) were selected from the reference sequence-based mQTL(smQTL).Locus-specific single nucleotide polymorphism(SNP) and simple sequence repeat(SSR) markers and17 genes responsive to FHB were then identified in the hcmQTL intervals by combined analysis of transcriptomic and proteomic data. This work may lead to a comprehensive molecular breeding platform for improving wheat resistance to FHB.展开更多
Spatial omics technologies have become powerful methods to provide valuable insights into cells and tissues within a complex context,significantly enhancing our understanding of the intricate and multifaceted biologic...Spatial omics technologies have become powerful methods to provide valuable insights into cells and tissues within a complex context,significantly enhancing our understanding of the intricate and multifaceted biological system.With an increasing focus on spatial heterogeneity,there is a growing need for unbiased,spatially resolved omics technologies.Laser capture microdissection(LCM)is a cutting-edge method for acquiring spatial information that can quickly collect regions of interest(ROIs)from heterogeneous tissues,with resolutions ranging from single cells to cell populations.Thus,LCM has been widely used for studying the cellular and molecular mechanisms of diseases.This review focuses on the differences among four types of commonly used LCM technologies and their applications in omics and disease research.Key attributes of application cases are also highlighted,such as throughput and spatial resolution.In addition,we comprehensively discuss the existing challenges and the great potential of LCM in biomedical research,disease diagnosis,and targeted therapy from the perspective of high-throughput,multi-omics,and single-cell resolution.展开更多
基金supported by the National Natural Science Foundation of China(32160578)the Ningxia Hui Autonomous Region Key Research and Develoment Program(2023BCF01027).
文摘Lactic acid bacteria and the fermentation environment interact to form an intertwined system.Lactic acid bacteria are constantly evolving to adapt to different fermentation environments,causing changes in their physiological processes.To achieve a targeted improvement of their adaptability to various environments,a detail analysis of their evolutionary physiological processes is required.While several studies have been carried out in the past by using single-omics techniques to investigate their response to environmental stress,most researchers are now using a multi-omics approach to explore more detail in the biological regulatory networks and molecular mechanisms of lactic acid bacteria in response to environmental stress,thereby overcoming the limitations of single-omics analysis.In this review,we describe the various single-omics approaches that have been used to study environmental stress in lactic acid bacteria,present the advantages of various multi-omics combined analysis approaches,and discuss the potential and practicality of applying emerging single-cell transcriptomics and single-cell metabolomics techniques to the molecular mechanism study of microbes response to environmental stress.Multi-omics approaches enable the accurate identification of complex microbial physiological processes in different environments,allow people to comprehensively reveal the molecular mechanisms of microbes response to stress from different perspectives.Single-cell omics techniques,analyze the targeted regulation of microbial functions in a multi-dimensional space,provides a new perspective on understanding microbes responses environment stress.
基金supported by two DoD grants(HT94252310534 to R.J.T.and HT94252310519 to C.M.K.)the following NIH/NIAMS grants:R01 grants(AR078035 and AR076900 to C.L.+10 种基金AG069401 and AG067698 to L.Q.AI186118,HD112474,and HD107034 to R.J.T.AR076325 and AR071967 to C.M.K.AR080902 and AR072999 to F.G.AR074441 and AR077678 to S.Y.T.AR082667 and AR077527 to A.E.L.AR083900,AR075860 and AR077616 to J.S.),R21 grants(AR077226 to J.S.AR083217 to A.E.L.AR081517 to S.Y.T.)a T32 grant(HD007434 to D.R.K.)P30 center grants(AR074992 and AR073752).
文摘Musculoskeletal disorders,including osteoarthritis,rheumatoid arthritis,osteoporosis,bone fracture,intervertebral disc degeneration,tendinopathy,and myopathy,are prevalent conditions that profoundly impact quality of life and place substantial economic burdens on healthcare systems.Traditional bulk transcriptomics,genomics,proteomics,and metabolomics have played a pivotal role in uncovering disease-associated alterations at the population level.However,these approaches are inherently limited in their ability to resolve cellular heterogeneity or to capture the spatial organization of cells within tissues,thus hindering a comprehensive understanding of the complex cellular and molecular mechanisms underlying these diseases.To address these limitations,advanced single-cell and spatial omics techniques have emerged in recent years,offering unparalleled resolution for investigating cellular diversity,tissue microenvironments,and biomolecular interactions within musculoskeletal tissues.These cutting-edge techniques enable the detailed mapping of the molecular landscapes in diseased tissues,providing transformative insights into pathophysiological processes at both the single-cell and spatial levels.This review presents a comprehensive overview of the latest omics technologies as applied to musculoskeletal research,with a particular focus on their potential to revolutionize our understanding of disease mechanisms.Additionally,we explore the power of multi-omics integration in identifying novel therapeutic targets and highlight key challenges that must be overcome to successfully translate these advancements into clinical applications.
基金supported by the National Natural Science Foundation of China(82302757)Shenzhen Science and Technology Program(JCY20240813145204006,SGDX20201103095600002,JCYJ20220818103417037,KJZD20230923115200002)+1 种基金Shenzhen Key Laboratory of Digital Surgical Printing Project(ZDSYS201707311542415)Shenzhen Development and Reform Program(XMHT20220106001).
文摘Osteoarthritis(OA)is a degenerative joint disease with significant clinical and societal impact.Traditional diagnostic methods,including subjective clinical assessments and imaging techniques such as X-rays and MRIs,are often limited in their ability to detect early-stage OA or capture subtle joint changes.These limitations result in delayed diagnoses and inconsistent outcomes.Additionally,the analysis of omics data is challenged by the complexity and high dimensionality of biological datasets,making it difficult to identify key molecular mechanisms and biomarkers.Recent advancements in artificial intelligence(AI)offer transformative potential to address these challenges.This review systematically explores the integration of AI into OA research,focusing on applications such as AI-driven early screening and risk prediction from electronic health records(EHR),automated grading and morphological analysis of imaging data,and biomarker discovery through multi-omics integration.By consolidating progress across clinical,imaging,and omics domains,this review provides a comprehensive perspective on how AI is reshaping OA research.The findings have the potential to drive innovations in personalized medicine and targeted interventions,addressing longstanding challenges in OA diagnosis and management.
文摘In this editorial,we comment on the article by Micucci et al published in the recent issue.We focus on the heterogenous nature of gastric cancer(GC)and the potential benefits of integrating traditional Chinese medicine(TCM)with the modern technology of network pharmacology(NP)and omics sequencing.GC is a heterogenous disease,as it incorporates several biochemical pathways that contribute to pathogenesis.TCM acknowledges the multifactorial,heterogenous nature of disease and utilizes an integrative approach to medicine.NP,a modern philosophy within drug development,integrates traditional knowledge of nutraceuticals and modern technologies to address the complex interactions of pathways within the body.Omics technologies,which is at the core of precision medicine,has allowed for this newfound principle of drug development.Metabolic pathways are better distinguished,leading to more targeted drug development.However,the use of omics technology needs to be employed to better characterize the subtypes of GC.This will allow TCM’s use of nutraceuticals in the application of NP to better target metabolic pathways that may aid in the prevention of GC as well as enhance treatment.
基金supported by the China Science and Technology Innovation 2030-Major Project(Nos.2022ZD0211701,2021ZD0200700)the National Natural Science Foundation of China(Nos.82130042,81830040,22176195,82127801)+3 种基金Shenzhen Science and Technology Serial Funds(Nos.GJHZ20210705141400002,KCXFZ20211020164543006,JCYJ20220818101615033,ZDSYS20220606100606014,KQTD 20221101093608028)the National Key R&D Program of China(No.2022YFF0705003)Guangdong Province Zhu Jiang Talents Plan(No.2021QN02Y028)the Guangdong Science and Technology Department(No.2021B1212030004)。
文摘There is growing evidence that lipid metabolism instability in depressive disorder may be a core early pathological event associated with numerous pathogenesis hypotheses.However,spatial distributions and quantitative changes of lipids in specific brain regions associated with depressive disorder are far from elucidated.In the present study,lipid profiling characteristics of whole brain sections are systematically determined by using matrix-assisted laser desorption ionization-mass spectrometry imaging(MALDI-MSI)-combined with histomorphological analysis in rats with depressive-like behavior induced by multiple early life stress(mELS)and unstressed control.Lipid dyshomeostasis and different degrees of metabolic disturbance occur in the eight paired representative brain sections from micro-region and molecular level.More specifically,17 lipid molecules show the severe dyshomeostasis between intergroup(control and depressed rats)or intra-group(multiple emotion-regulation-related brain regions).Quite specially,phosphatidylcholine(PC)(39:6)expression in section 7 is significantly upregulated only in the amygdala of depressed rat relative to control rat,by contrast,up-regulated phosphatidylglycerol(PG)(34:2)in section 2 emerges in the medial prefrontal cortex,insular cortex,and nucleus accumbens simultaneously.Linking spatial distribution to quantitative variation of lipids from the whole brain sections contributes the uncovering of new insights in causal mechanism of lipid dyshomeostasis in depression investigation and related targeting interventions.
基金supported by Tianjian advanced biomedical laboratory key research and development projectHenan Province Natural Science Foundation(grant number:242300421283)+1 种基金Henan Province Science and Technology Research and Development(grant number:242102311176)Henan Province medical science and technology research project(grant number:SBGJ202403038)。
文摘Objective:Circadian rhythm disruption(CRD)is a risk factor that correlates with poor prognosis across multiple tumor types,including hepatocellular carcinoma(HCC).However,its mechanism remains unclear.This study aimed to define HCC subtypes based on CRD and explore their individual heterogeneity.Methods:To quantify CRD,the HCC CRD score(HCCcrds)was developed.Using machine learning algorithms,we identified CRD module genes and defined CRD-related HCC subtypes in The Cancer Genome Atlas liver HCC cohort(n=369),and the robustness of this method was validated.Furthermore,we used bioinformatics tools to investigate the cellular heterogeneity across these CRD subtypes.Results:We defined three distinct HCC subtypes that exhibit significant heterogeneity in prognosis.The CRD-related subtype with high HCCcrds was significantly correlated with worse prognosis,higher pathological grade,and advanced clinical stages,while the CRD-related subtype with low HCCcrds had better clinical outcomes.We also identified novel biomarkers for each subtype,such as nicotinamide nmethyltransferase and myristoylated alanine-rich protein kinase C substrate-like 1.Conclusion:We classify the HCC patients into three distinct groups based on circadian rhythm and identify their specific biomarkers.Within these groups greater HCCcrds was associated with worse prognosis.This approach has the potential to improve prediction of an individual’s prognosis,guide precision treatments,and assist clinical decision making for HCC patients.
基金supported by the General Program of Natural Science Foundation of Guangdong Province(2023A1515011102).
文摘Pediatric cataract,a leading cause of blindness in children globally,imposing a significant financial burden on both families and society.The extensive phenotypic heterogeneity of this condition means that the underlying mechanisms remain poorly understood,limiting the development of precise and effective treatments.The advent of omics technologies has provided potent tools for unraveling the pathogenesis of pediatric cataract.By mapping expression profiles across various molecular levels,these omics approaches enhance our understanding of the disease’s etiological mechanisms,aid in the identification of novel biomarkers and key pathways,and offer researchers new insights for the innovative strategies in disease diagnosis and targeted therapies.In this review,we summarize the application of omics approaches in clinical and basic research on pediatric cataract over the past decade,encompassing genomics,transcriptomics,proteomics,and metabolomics.Furthermore,we discuss the current challenges and future prospects of omics analyses in pediatric cataract studies.
基金supported by the Zhejiang Province Traditional Chinese Medicine Science and Technology Project(GZY-ZJ-KJ-24063)the Natural Science Foundation of Zhejiang Province(Q24H290031)the Key Laboratory for Molecular Medicine and Chinese Medicine Preparations(No.GZY-ZJ-SY-2303).
文摘Immunotherapies have demonstrated notable clinical benefits in the treatment of cervical cancer(CC).However,the development of therapeutic resistance and diverse adverse effects in immunotherapy stem from complex interactions among biological processes and factors within the tumor immune microenvironment(TIME).Advanced omic technologies offer novel insights into a more expansive and thorough layer of the TIME.Furthermore,integrating multidimensional omics within the frameworks of systems biology and computational methodologies facilitates the generation of interpretable data outputs to characterize the clinical and biological trajectories of tumor behavior.In this review,we present advanced omics technologies that utilize various clinical samples to address scientific inquiries related to immunotherapies for CC,highlighting their utility in identifying metastasis dissemination,recurrence risk,and therapeutic resistance in patients treated with immunotherapeutic approaches.This review elaborates on the strategy for integrating multi-omics data through artificial intelligence algorithms.Additionally,an analysis of the obstacles encountered in the multi-omics analysis process and potential avenues for future research in this domain are presented.
基金supported by the National Natural Science Foundation of China(Grant No.22275071)
文摘Spatial transcriptomics is an organizational study done on tissue sections that preserves the spatial information of the sample.Spatial transcriptomics aims to combine spatial information with gene expression data to quantify the mRNA expression of a large number of genes in the spatial context of tissues and cells.As a paradigm shift in biological research,spatial transcriptomics can provide both spatial location information and transcriptome-level cellular gene expression data,elucidating the interactions between cells and the microenvironment.From the understanding of the entire functional life cycle of RNA to the characterization of molecular mechanisms to the mapping of gene expression in various tissue regions,by choosing the appropriate spatial transcriptome technology,researchers can achieve a deeper exploration of biological developmental processes,disease pathogenesis,etc.In recent years,the field of spatial transcriptomics has ushered in several challenges along with its rapid development,such as the dependence on sample types,the resolution of visualized genes,the difficulty of commercialization,and the ability to obtain detailed single-cell information.In this paper,we summarize and review the four major categories of spatial transcriptome technologies and compare and analyze the technical advantages and major challenges of multiple research strategies to assist current experimental design and research analysis.Finally,the importance of spatial transcriptomics in the integration of multi-omics analysis and disease modeling as well as the future development prospects are summarized and outlined.
基金supported by the National Key Research and Development Program of China,No.2018YFA0108602the CAMS Initiative for Innovative Medicine,No.2021-1-I2M-019the National High Level Hospital Clinical Research Funding,No.2022-PUMCH-C-042(all to XB).
文摘Stem cell transplantation is a potential therapeutic strategy for ischemic stroke. However, despite many years of preclinical research, the application of stem cells is still limited to the clinical trial stage. Although stem cell therapy can be highly beneficial in promoting functional recovery, the precise mechanisms of action that are responsible for this effect have yet to be fully elucidated. Omics analysis provides us with a new perspective to investigate the physiological mechanisms and multiple functions of stem cells in ischemic stroke. Transcriptomic, proteomic, and metabolomic analyses have become important tools for discovering biomarkers and analyzing molecular changes under pathological conditions. Omics analysis could help us to identify new pathways mediated by stem cells for the treatment of ischemic stroke via stem cell therapy, thereby facilitating the translation of stem cell therapies into clinical use. In this review, we summarize the pathophysiology of ischemic stroke and discuss recent progress in the development of stem cell therapies for the treatment of ischemic stroke by applying multi-level omics. We also discuss changes in RNAs, proteins, and metabolites in the cerebral tissues and body fluids under stroke conditions and following stem cell treatment, and summarize the regulatory factors that play a key role in stem cell therapy. The exploration of stem cell therapy at the molecular level will facilitate the clinical application of stem cells and provide new treatment possibilities for the complete recovery of neurological function in patients with ischemic stroke.
基金supported by Professor of Chang Jiang Scholars Program,NSFC(No.81230090)Shanghai Leading Academic Discipline Project(B906)+3 种基金Key laboratory of drug research for special environments,PLA,Shanghai Engineering Research Center for the Preparation of Bioactive Natural Products(No.10DZ2251300)the Scientific Foundation of Shanghai,China(Nos.12401900801,13401900 101)National Major Project of China(No.2011ZX09307-002-03)the National Key Technology R&D Program of China(No.2012BAI29B06)
文摘In the post-genomic era, biological studies are characterized by the rapid development and wide application of a series of "omics" technologies, including genomics, proteomics, metabolomics, transcriptomics, lipidomics, cytomics, metallomics, ionomics, interactomics, and phenomics. These "omics" are often based on global analyses of biological samples using high through-put analytical approaches and bioinformatics and may provide new insights into biological phenomena. In this paper, the development and advances in these omics made in the past decades are reviewed, especially genomics, transcriptomics, proteomics and metabolomics; the applications of omics technologies in pharmaceutical research are then summarized in the fields of drug target discovery, toxicity evaluation, personalized medicine, and traditional Chinese medicine; and finally, the limitations of omics are discussed, along with the future challenges associated with the multi-omics data processing, dynamics omics analysis, and analytical approaches, as well as amenable solutions and future prospects.
基金supported by the grant:The National Key Research and Development Program of China(Grant No.2023YFC2508500)Beijing Municipal Health Commission(Beijing Demonstration Research Ward BCRW20200303)+1 种基金National Natural Science Foundation of China(82272951,82272953)Chinese Academy of Medical Sciences(2022-I2M-C&T-B-070).
文摘Although there has been a notable decrease in cancer mortality rates for many common cancers over the last decades,there remains a concerning lack of progress in understanding and treating rare tumors[1].Rare tumors are types of tumors that are rare in clinical practice,which are the subclass of rare diseases.The classification of rare tumors varies internationally,with the US Food and Drug Administration and National Cancer Institute defining them as tumors with an incidence rate of less than 15 per 100,000 individuals annually,while the European Medicines Agency set the threshold at 6 per 100,000.According to the results from the National Cancer Center PLATFORM study in China,rare tumors are defined as an annual incidence rate of 2.5/100,000 or less.Although the incidence of each rare tumor is low,the total number of rare tumors is not low.The total number of rare tumor incidence in China is about 560,000 per year,accounting for 14.2%of all cancer patients[2].More than half of the rare tumors lack clinical treatment guidelines,or there is no standard treatment in clinical practice,suggesting there is a huge unmet medical need for effective treatments for rare tumors.
基金Supported by PIP-CONICET 2021-2023 grant,No.11220200100875COPICT-2020-Serie,No.A-00788and“Florencio Fiorini Foundation”grants.
文摘Unmet needs exist in metabolic dysfunction-associated steatotic liver disease(MASLD)risk stratification.Our ability to identify patients with MASLD with advanced fibrosis and at higher risk for adverse outcomes is still limited.Incorporating novel biomarkers could represent a meaningful improvement to current risk predictors.With this aim,omics technologies have revolutionized the process of MASLD biomarker discovery over the past decades.While the research in this field is thriving,much of the publication has been haphazard,often using single-omics data and specimen sets of convenience,with many identified candidate biomarkers but lacking clinical validation and utility.If we incorporate these biomarkers to direct patients’management,it should be considered that the roadmap for translating a newly discovered omics-based signature to an actual,analytically valid test useful in MASLD clinical practice is rigorous and,therefore,not easily accomplished.This article presents an overview of this area’s current state,the conceivable opportunities and challenges of omics-based laboratory diagnostics,and a roadmap for improving MASLD biomarker research.
基金supported by National Key Research and Development Program of China (2022YFD2300205)the National Natural Science Foundation of China (32071971,32001463)+4 种基金the China Postdoctoral Science Foundation (2022M711278)the Key Research and Development Projects of Henan Province (231111113000)Fundamental Research Funds for the Central Universities (2662023ZKPY002)the HZAU-AGIS Cooperation Fund (SZYJY2021008)the Hubei Agricultural Science and Technology Innovation Center Program (2021-620-000-001-032)。
文摘Use of nanomaterials(NMs)to improve plant abiotic stress tolerance(AST)is a hot topic in NM-enabled agriculture.Previous studies mainly focused on the physiological and biochemical responses of plants treated with NMs under abiotic stress.To use NMs for improving plant AST,it is necessary to understand how they act on this tolerance at the omics and epigenetics levels.In this review,we summarized the knowledge of NM-improved abiotic stress tolerance in relation to omics(such as metabolic,transcriptomic,proteomic,and microRNA),DNA methylation,and histone modifications.Overall,NMs can improve plant abiotic stress tolerance through the modulation at omics and epigenetics levels.
文摘Head and neck squamous cell carcinoma(HNSCC)is one of the most frequent cancers worldwide.The main risk factors are consumption of tobacco products and alcohol,as well as infection with human papilloma virus.Approved therapeutic options comprise surgery,radiation,chemotherapy,targeted therapy through epidermal growth factor receptor inhibition,and immunotherapy,but outcome has remained unsatisfactory due to recurrence rates of~50%and the frequent occurrence of second primaries.The availability of the human genome sequence at the beginning of the millennium heralded the omics era,in which rapid technological progress has advanced our knowledge of the molecular biology of malignant diseases,including HNSCC,at an unprecedented pace.Initially,microarray-based methods,followed by approaches based on next-generation sequencing,were applied to study the genetics,epigenetics,and gene expression patterns of bulk tumors.More recently,the advent of single-cell RNA sequencing(scRNAseq)and spatial transcriptomics methods has facilitated the investigation of the heterogeneity between and within different cell populations in the tumor microenvironment(e.g.,cancer cells,fibroblasts,immune cells,endothelial cells),led to the discovery of novel cell types,and advanced the discovery of cell-cell communication within tumors.This review provides an overview of scRNAseq,spatial transcriptomics,and the associated bioinformatics methods,and summarizes how their application has promoted our understanding of the emergence,composition,progression,and therapy responsiveness of,and intercellular signaling within,HNSCC.
基金supported by Basic and Applied Basic Research Foundation of Guangdong Province(No.2022A1111220217)Medical Scientific Research Foundation of Guangdong Province(Nos.A2023216,A2022124)+3 种基金Science and Technology Program of Guangzhou(Nos.202201010840,202201010810,202102080132,202002030032,202002020023)Health Commission Program of Guangzhou(20212A010021,20201A010081,20211A011116)Science and Technology Project of Panyu,Guangzhou(2022-Z04-009,2022-Z04-090,2022-Z04-072,2021-Z04-013,2020-Z04-026,2019-Z04-02)Scientific Research Project of Guangzhou Panyu Central Hospital(Nos.2022Y002,2021Y004,2021Y002).
文摘Spatial omics technology integrates the concept of space into omics research and retains the spatial information of tissues or organs while obtaining molecular information.It is characterized by the ability to visualize changes in molecular information and yields intuitive and vivid visual results.Spatial omics technologies include spatial transcriptomics,spatial proteomics,spatial metabolomics,and other technologies,the most widely used of which are spatial transcriptomics and spatial proteomics.The tumor microenvironment refers to the surrounding microenvironment in which tumor cells exist,including the surrounding blood vessels,immune cells,fibroblasts,bone marrow-derived inflammatory cells,various signaling molecules,and extracellular matrix.A key issue in modern tumor biology is the application of spatial omics to the study of the tumor microenvironment,which can reveal problems that conventional research techniques cannot,potentially leading to the development of novel therapeutic agents for cancer.This paper summarizes the progress of research on spatial transcriptomics and spatial proteomics technologies for characterizing the tumor immune microenvironment.
基金support from Hangzhou Institute of Medicine,China(No.2024ZZBS11)Chinese Academy of Sciences,China Postdoctoral Science Foundation(No.2024M763331)+1 种基金National Oncology Clinical Key Specialty of China(No.2023-GJZK-001)Zhejiang Provincial Natural Science Foundation of China(No.LQN25H160009).
文摘Recent advances in spatial and single-cell omics have significantly revolutionized biomarker discovery in tumor immunotherapy by addressing critical challenges such as tumor heterogeneity,immune evasion,and variability within the tumor microenvironment(TME).Immunotherapeutic strategies,including immune checkpoint in-hibitors and adoptive T-cell transfer,have demonstrated promising clinical outcomes;however,their efficacy is limited by low response rates and the incidence of immune-related adverse events(irAEs).Therefore,the identification of reliable biomarkers is essential for predicting treatment efficacy,minimizing irAEs,and facili-tating patient stratification.Spatial omics integrates molecular profiling with spatial localization,thereby providing comprehensive insights into the cellular organization and functional states within the TME.By elucidating the spatial patterns of immune cell infiltration and tumor heterogeneity,this approach enhances the prediction of therapeutic responses.Similarly,single-cell omics enables high-resolution analysis of cellular heterogeneity by capturing transcriptomic,epigenomic,and metabolic signatures at the single-cell level.The integrated application of spatial and single-cell omics has enabled the identification of previously undetected biomarkers,including rare immune cell subsets implicated in resistance mechanisms.In addition to spatial transcriptomics(ST),this technological landscape also includes spatial proteomics(SP)and spatial metab-olomics,which further facilitate the study of dynamic tumor-immune interactions.Multi-omics integration provides a comprehensive overview of biomarker landscapes,while the rapid evolution of artificial intelligence(AI)-based approaches enhances the analysis of complex,multidimensional datasets to ultimately enhance pre-dictive potential and clinical utility.Despite substantial progress,several challenges remain in the context of standardization,data integration,and real-time monitoring.Nevertheless,the incorporation of spatial and single-cell omics into biomarker research holds transformative potential for advancing personalized cancer immuno-therapy.These emerging strategies pave the way for the development of innovative diagnostic and therapeutic interventions,thereby enabling precision oncology and improving treatment outcomes across a wide range of tumor profiles.This review aims to provide a comprehensive overview of the integration of spatial omics with single-cell omics in the discovery of biomarkers for tumor immunotherapy.Specifically,it examines the strategies by which these emerging technologies address the challenges related to tumor heterogeneity,immune evasion,and the dynamic nature of the TME.By elaborating on the principles,applications,and clinical potential of these technologies,this review also critically evaluates their limitations,challenges,and the current gaps in clinical translation.
基金supported by the National Key R&D Program,Intergovernmental Key Items for International Scientific and Technological Innovation Cooperation(2018YFE0107700)the National Natural Science Foundation of China(31771772)+2 种基金the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX19_2109)the National Key R&D Program for Breeding of Top-seven Crops(2017YFD0100801)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)。
文摘Fusarium head blight(FHB) is a global wheat disease that devastates wheat production. Resistance to FHB spread within a wheat spike(type Ⅱ resistance) and to mycotoxin accumulation in infected kernel(type Ⅲ resistance) are the two main types of resistance. Of hundreds of QTL that have been reported, only a few can be used in wheat breeding because most show minor and/or inconsistent effects in different genetic backgrounds. We describe a new strategy for identifying robust and reliable meta-QTL(mQTL)that can be used for improvement of wheat FHB resistance. It involves integration of mQTL analysis with mQTL physical mapping and identification of single-copy markers and candidate genes. Using metaanalysis, we consolidated 625 original QTL from 113 publications into 118 genetic map-based mQTL(gmQTL). These gmQTL were further located on the Chinese Spring reference sequence map. Finally, 77 high-confidence mQTL(hcmQTL) were selected from the reference sequence-based mQTL(smQTL).Locus-specific single nucleotide polymorphism(SNP) and simple sequence repeat(SSR) markers and17 genes responsive to FHB were then identified in the hcmQTL intervals by combined analysis of transcriptomic and proteomic data. This work may lead to a comprehensive molecular breeding platform for improving wheat resistance to FHB.
基金supported by the National Natural Science Foundation of China(81973701 and 82204772)the Natural Science Foundation of Zhejiang Province(LZ20H290002)+2 种基金the Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine(ZYYCXTD-D-202002)the China Postdoctoral Science Foundation(2022M712811)Westlake Laboratory(Westlake Laboratory of Life Sciences and Biomedicine).
文摘Spatial omics technologies have become powerful methods to provide valuable insights into cells and tissues within a complex context,significantly enhancing our understanding of the intricate and multifaceted biological system.With an increasing focus on spatial heterogeneity,there is a growing need for unbiased,spatially resolved omics technologies.Laser capture microdissection(LCM)is a cutting-edge method for acquiring spatial information that can quickly collect regions of interest(ROIs)from heterogeneous tissues,with resolutions ranging from single cells to cell populations.Thus,LCM has been widely used for studying the cellular and molecular mechanisms of diseases.This review focuses on the differences among four types of commonly used LCM technologies and their applications in omics and disease research.Key attributes of application cases are also highlighted,such as throughput and spatial resolution.In addition,we comprehensively discuss the existing challenges and the great potential of LCM in biomedical research,disease diagnosis,and targeted therapy from the perspective of high-throughput,multi-omics,and single-cell resolution.
