Traditional Chinese medicine(TCM)has demonstrated unique advantages in the prevention and treatment of chronic diseases such as glycolipid metabolism disorder.However,its widespread application has been hindered by th...Traditional Chinese medicine(TCM)has demonstrated unique advantages in the prevention and treatment of chronic diseases such as glycolipid metabolism disorder.However,its widespread application has been hindered by the unclear biological essence of TCM syndromes and therapeutic mechanisms.As an emerging interdisciplinary field,phenomics integrates multi-dimensional data including genome,transcriptome,proteome,metabolome,and microbiome.When combined with TCM's holistic philosophy,it forms TCM phenomics,providing novel approaches to reveal the biological connotation of TCM syndromes and the mechanisms of herbal medicine.Taking glycolipid metabolism disorder as an example,this paper explores the application of TCM phenomics in glycolipid metabolism disorder.By analyzing molecular characteristics of related syndromes,TCM phenomics identifies differentially expressed genes,metabolites,and gut microbiota biomarkers to elucidate the dynamic evolution patterns of syndromes.Simultaneously,it deciphers the multi-target regulatory networks of herbal formulas,demonstrating their therapeutic effects through mechanisms including modulation of insulin signaling pathways,improvement of gut microbiota imbalance,and suppression of inflammatory responses.Current challenges include the subjective nature of syndrome diagnosis,insufficient standardization of animal models,and lack of integrated multi-omics analysis.Future research should employ machine learning,multimodal data integration,and cross-omics longitudinal studies to establish quantitative diagnostic systems for syndromes,promote the integration of precision medicine in TCM and western medicine,and accelerate the modernization of TCM.展开更多
Modern western medicine typically focuses on treating specific symptoms or diseases,and traditional Chinese medicine(TCM)emphasizes the interconnections of the body’s various systems under external environment and ta...Modern western medicine typically focuses on treating specific symptoms or diseases,and traditional Chinese medicine(TCM)emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases.Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics.While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou(a TCM definition of clinical phenome),bottlenecks remain in data standardization,mechanistic interpretation,and precision intervention.Here,we systematically elaborates on the theoretical foundations,technical pathways,and future challenges of integrating digital medicine with TCM phenomics under the framework of“TCM phenomics 2.0”,which is supported by digital medicine technologies such as artificial intelligence,wearable devices,medical digital twins,and multi-omics integration.This framework aims to construct a closed-loop system of“Zhenghou–Phenome–Mechanism–Intervention”and to enable the digitization,standardization,and precision of disease diagnosis and treatment.The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine.In practice,digital tools facilitate multi-source clinical data acquisition and standardization,while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms,thereby improving scientific rigor in diagnosis,efficacy evaluation,and personalized intervention.Nevertheless,challenges persist,including data quality and standardization issues,shortage of interdisciplinary talents,and insufficiency of ethical and legal regulations.Future development requires establishing national data-sharing platforms,strengthening international collaboration,fostering interdisciplinary professionals,and improving ethical and legal frameworks.Ultimately,this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance,innovation,and modernization of TCM diagnostic and therapeutic patterns.展开更多
Advances in gene editing and natural genetic variability present significant opportunities to generate novel alleles and select natural sources of genetic variation for horticulture crop improvement.The genetic improv...Advances in gene editing and natural genetic variability present significant opportunities to generate novel alleles and select natural sources of genetic variation for horticulture crop improvement.The genetic improvement of crops to enhance their resilience to abiotic stresses and new pests due to climate change is essential for future food security.The field of genomics has made significant strides over the past few decades,enabling us to sequence and analyze entire genomes.However,understanding the complex relationship between genes and their expression in phenotypes-the observable characteristics of an organism-requires a deeper understanding of phenomics.Phenomics seeks to link genetic information with biological processes and environmental factors to better understand complex traits and diseases.Recent breakthroughs in this field include the development of advanced imaging technologies,artificial intelligence algorithms,and large-scale data analysis techniques.These tools have enabled us to explore the relationships between genotype,phenotype,and environment in unprecedented detail.This review explores the importance of understanding the complex relationship between genes and their expression in phenotypes.Integration of genomics with efficient high throughput plant phenotyping as well as the potential of machine learning approaches for genomic and phenomics trait discovery.展开更多
Traditional Chinese medicine (TCM) with its millenniaold wisdom rooted in the principles of holistic Yin-Yang balance and “Bianzheng Lunzhi”[辨证论治, Zhenghou(证候) differentiation and treatment], has long offered ...Traditional Chinese medicine (TCM) with its millenniaold wisdom rooted in the principles of holistic Yin-Yang balance and “Bianzheng Lunzhi”[辨证论治, Zhenghou(证候) differentiation and treatment], has long offered a unique lens to understand human health and disease.However, the modern scientific interpretation of TCM remains at the stage of “knowing that it works, but not knowing why it works”.展开更多
Recent fast advance in biomedical research at the“omic”levels has led to an explosion of big data for the understanding the molecular makeup of diseases,which have revealed the intimate unmatched relationships betwe...Recent fast advance in biomedical research at the“omic”levels has led to an explosion of big data for the understanding the molecular makeup of diseases,which have revealed the intimate unmatched relationships between the genomic variabilities and the current organ-or system-based definition and classification of disease in Western medi⁃cine.The major challenges in the effort to establish and develop precision medicine are how diseases should be defined and classified in an integrated systemic or omic scale and also on an individualized basis.The phenomics approach to the understanding of diseases will allow the transition from focused phenotype/genotype studies to a systemic largescale phenome and genome,proteome,metabolome approach and the identification of a systemically integrated setof biomarkers for diagnosis and prognosis of disease phenome(or Zhenghou).Phenome-wide associated study(PheWAS)may soon lead the field of medical research and provide insightful and novel clues for redefinition of the disease phenome and its clinical classifications and personalized treatment and ultimately precision medicine.Pharma⁃cophenomics is to characterize the phenomes of drug response and also to identify the corresponding therapeutic targets at the level of systems biology.As a complement of pharmacogenomics/proteomics/metabolomics,pharmacoph⁃enomics offers a suite of new technologies and platforms for the transition from focused phenotype-genotype study to a systematic phenome-genome approach and refine drug research with systematically-defined drug response and thera⁃peutic targets.Therefore,pharmacophenomics will provide a new paradigm for the study of drug response including effects and toxicities at the level of systems biology and will identify the corresponding therapeutic targets and principles for combination treatment and prevention of disease using Fangji or Fufang that takes into account individual variability in genes,environment,and lifestyle for each person.展开更多
Genome sequencing opened the flood gate of ＂-omics＂ studies, among which the research about correlations between genomic and phenomic variables is an important part. With the development of functional genomics and s...Genome sequencing opened the flood gate of ＂-omics＂ studies, among which the research about correlations between genomic and phenomic variables is an important part. With the development of functional genomics and systems biology, genome-wide investigation of the correlations between many genomic and phenomic variables became possible. In this review, five genomic variables, such as evolution rate （or ＂age＂ of the gene）, the length of intron and ORF （protein length） in one gene, the biases of amino acid composition and codon usage, along with the phenomic variables related to expression patterns （level and breadth） are focused on. In most cases, genes with higher mRNA/protein expression level tend to evolve slowly, have less intronic DNA, code for smaller proteins, and have higher biases of amino acid composition and codon usage. In addition, broadly expressed proteins evolve more slowly and are shorter than tissue-specific proteins. Studies in this field are helpful for deeper understanding the signatures of selection mediated by the features of gene expression and are of great significance to enrich the evolution theory.展开更多
Crop phenomics enables the collection of diverse plant traits for a large number of samples along different time scales,representing a greater data collection throughput compared with traditional measurements.Most mod...Crop phenomics enables the collection of diverse plant traits for a large number of samples along different time scales,representing a greater data collection throughput compared with traditional measurements.Most modern crop phenomics use different sensors to collect reflective,emitted,and fluorescence signals,etc.,from plant organs at different spatial and temporal resolutions.Such multi-modal,high-dimensional data not only accelerates basic research on crop physiology,genetics,and whole plant systems modeling,but also supports the optimization of field agronomic practices,internal environments of plant factories,and ultimately crop breeding.Major challenges and opportunities facing the current crop phenomics research community include developing community consensus or standards for data collection,management,sharing,and processing,developing capabilities to measure physiological parameters,and enabling farmers and breeders to effectively use phenomics in the field to directly support agricultural production.展开更多
Crop phenomics has rapidly progressed in recent years due to the growing need for crop functional geno-mics,digital breeding,and smart cultivation.Despite this advancement,the lack of standards for the cre-ation and u...Crop phenomics has rapidly progressed in recent years due to the growing need for crop functional geno-mics,digital breeding,and smart cultivation.Despite this advancement,the lack of standards for the cre-ation and usage of crop phenomics technology and equipment has become a bottleneck,limiting the industry’s high-quality development.This paper begins with an overview of the crop phenotyping indus-try and presents an industrial mapping of technology and equipment for big data in crop phenomics.It analyzes the necessity and current state of constructing a standard framework for crop phenotyping.Furthermore,this paper proposes the intended organizational structure and goals of the standard frame-work.It details the essentials of the standard framework in the research and development of hardware and equipment,data acquisition,and the storage and management of crop phenotyping data.Finally,it discusses promoting the construction and evaluation of the standard framework,aiming to provide ideas for developing a high-quality standard framework for crop phenotyping.展开更多
Objective: This study aimed to explore the experiences of women in the process of formula feeding their infants. The World Health Organization has emphasized the importance of breastfeeding for infant health. After de...Objective: This study aimed to explore the experiences of women in the process of formula feeding their infants. The World Health Organization has emphasized the importance of breastfeeding for infant health. After decades of breastfeeding promotions,breastfeeding rates in Hong Kong have been rising consistently; however, the low continuation rate is alarming. This study explores women's experiences with formula feeding their infants, including factors affecting their decision to do so.Methods: A qualitative approach using an interpretative phenomenological analysis(IPA) was adopted as the study design. Data were collected from 2014 to 2015 through individual in-depth unstructured interviews with 16 women, conducted between 3 and 12 months after the birth of their infant. Data were analyzed using IPA.Results: Three main themes emerged as follows:(1) self-struggle, with the subthemes of feeling like a milk cow and feeling trapped;(2) family conflict, with the subtheme of sharing the spotlight; and(3) interpersonal tensions, with the subthemes of embarrassment,staring, and innocence. Many mothers suffered various stressors and frustrations during breastfeeding. These findings suggest a number of pertinent areas that need to be considered in preparing an infant feeding campaign.Conclusions: The findings of this study reinforce our knowledge of women's struggles with multiple sources of pressure, such as career demands, childcare demands, and family life after giving birth. All mothers should be given assistance in making informed decisions about the optimal approach to feeding their babies given their individual situation and be provided with support to pursue their chosen feeding method.展开更多
An emerging area of interest in understanding disease phenotypes is systems genomics.Complex diseases such as diabetes have played an important role towards understanding the susceptible genes and mutations.A wide num...An emerging area of interest in understanding disease phenotypes is systems genomics.Complex diseases such as diabetes have played an important role towards understanding the susceptible genes and mutations.A wide number of methods have been employed and strategies such as polygenic risk score and allele frequencies have been useful,but understanding the candidate genes harboring those mutations is an unmet goal.In this perspective,using systems genomic approaches,we highlight the application of phenome-interactome networks in diabetes and provide deep insights.LINC01128,which we previously described as candidate for diabetes,is shown as an example to discuss the approach.展开更多
Schizothoracine fishes are distributed in the Nagqu region,which is the hinterland of the Tibetan Plateau.They have adapted to the cold and strongly ultraviolet environment of the plateau and show diverse morphologies...Schizothoracine fishes are distributed in the Nagqu region,which is the hinterland of the Tibetan Plateau.They have adapted to the cold and strongly ultraviolet environment of the plateau and show diverse morphologies,which makes them ideal for studying the relationship between phenotype and environment.However,traditional morphological measurements are time consuming and labor costly.In this study,we propose a deep-learningbased method for acquiring high-throughput phenotypic data of fishes,including image dataset construction of schizothoracine fishes(including front,side,and top views),fish keypoint detection based on the You Only Look Once(YOLO)model,and reconstruction of 2D and 3D keypoint coordinates based on multiple views.A total of 7050 phenotypic data points consisting of keypoint distances and angles were constructed for each fish and were highly correlated(>0.98)with the corresponding data measured manually.We obtained phenotypic data for a total of 525 fishes from three schizothoracine fish groups inhabiting riverine,lacustrine,and river–lake transitional environments using the proposed phenotypic data acquisition method.We employed a random forest algorithm to classify the groups,achieving a classification accuracy of 96%,and identified 15 morphometric indices that exhibited statistically significant differences.,of which 6 were related to head morphology,6 related to body shape,and 3 related to tail morphology,based on the random forest algorithm.Specifically,river-living schizothoracine fishes showed a blunt head,robust body,and elongated caudal peduncle which may reflect adaptations to the turbulence of the river,while the lake-living schizothoracine fishes have the opposite effect.Schizothoracine fishes at the river–lake transitional zones were phenotypically characterized as being in the middle of the two phenotypes,and these presumably reflect adaptations to their lake habitat.This study provides a methodological reference for obtaining high-throughput phenotypic data on fish and a theoretical basis for understanding the adaptation of very high-altitude schizothoracine fishes to their environment.展开更多
Machine learning models for crop image analysis and phenomics are highly important for precision agriculture and breeding and have been the subject of intensive research.However,the lack of publicly available high-qua...Machine learning models for crop image analysis and phenomics are highly important for precision agriculture and breeding and have been the subject of intensive research.However,the lack of publicly available high-quality image datasets with detailed annotations has severely hindered the development of these models.In this work,we present a comprehensive multicultivar and multiview rice plant image dataset(CVRP)created from 231 landraces and 50 modern cultivars grown under dense planting in paddy fields.The dataset includes images capturing rice plants in their natural environment,as well as indoor images focusing specifically on panicles,allowing for a detailed investigation of cultivar-specific differences.A semiautomatic annotation process using deep learning models was designed for annotations,followed by rigorous manual curation.We demonstrated the utility of the CVRP by evaluating the performance of four state-of-the-art(SOTA)semantic segmentation models.We also conducted 3D plant reconstruction with organ segmentation via images and annotations.The database not only facilitates general-purpose image-based panicle identification and segmentation but also provides valuable re-sources for challenging tasks such as automatic rice cultivar identification,panicle and grain counting,and 3D plant reconstruction.The database and the model for image annotation are available at.展开更多
Research in high-income countries has established the health benefits of physical activity(PA),but evidence from low-and middle-income countries,including China,where PA patterns vary from those in high-income countri...Research in high-income countries has established the health benefits of physical activity(PA),but evidence from low-and middle-income countries,including China,where PA patterns vary from those in high-income countries,remains limited.Moreover,previous research,mainly focused on specific diseases,failing to fully capture the health impacts of PA.We investigated the associations of PA with 425 distinct diseases and 53 causes of death using data from 511,088 participants aged 30–79 years in the China Kadoorie Biobank.Baseline PA was assessed using a questionnaire between 2004 and 2008,and usual PA levels were estimated using the resurvey data in 2013–2014.Cox regression was employed to estimate the associations between PA and outcomes,adjusting for potential confounders.During a median follow-up time of 12 years,722,183 incident events and 39,320 deaths were recorded across 18 chapters of the International Classification of Diseases,10th Revision(ICD-10).Total PA was significantly and inversely associated with incidence risks of 14 ICD-10 chapters,specifically 65 diseases and 19 causes of death,with the highest quintile group of PA showing a 14%lower disease incidence and 40%lower all-cause mortality compared with the lowest group.Of these diseases,54 were not highlighted in World Health Organization PA guidelines.Dose-response analyses revealed L-shaped associations for most PA types,except moderate-tovigorous intensity PA,which showed a U-shaped relationship.In this population,physical inactivity accounted for 12.8%of PA-related deaths.The findings underscore the broad health benefits of PA across a variety of body systems and the significant disease burden due to inactivity in China,highlighting the urgent need for PA promotion.展开更多
Dissecting the mechanism of drought resistance(DR)and designing drought-resistant rice varieties are promising strategies to address the challenge of climate change.Here,we selected a typical droughtavoidant(DA)variet...Dissecting the mechanism of drought resistance(DR)and designing drought-resistant rice varieties are promising strategies to address the challenge of climate change.Here,we selected a typical droughtavoidant(DA)variety,IRAT109,and a drought-tolerant(DT)variety,Hanhui15,as parents to develop a stable recombinant inbred line(RIL)population(F8,1262 lines).The de novo assembled genomes of both parents were released.By resequencing of the RIL population,a set of 1189216 reliable SNPs were obtained and used to construct a dense genetic map.Using above-and belowground phenomic platforms and multimodal cameras,we captured 139040 image-based traits(i-traits)of whole-plant phenotypes in response to drought stress throughout the entire rice growth period and identified 32586 drought-responsive quantitative trait loci(QTLs),including 2097 unique QTLs.QTLs associated with panicle i-traits occurred more than 600 times on the middle of chromosome 8,and QTLs associated with leaf i-traits occurred more than 800 times on the 50 end of chromosome 3,indicating the potential effects of these QTLs on plant phenotypes.We selected three candidate genes(OsMADS50,OsGhd8,OsSAUR11)related to leaf,panicle,and root traits,respectively,and verified their functions in DR.OsMADS50 was found to negatively regulate DR by modulating leaf dehydration,grain size,and downward root growth.A total of 18 and 21 composite QTLs significantly related to grain weight and plant biomass were also screened from 597 lines in the RIL population under drought conditions in field experiments,and the composite QTL regions showed substantial overlap(76.9%)with known DR gene regions.Based on three candidate DR genes,we proposed a haplotype design suitable for different environments and breeding objectives.This study provides a valuable reference for multimodal and time-series phenomic analyses,deciphers the genetic mechanisms of DA and DT rice varieties,and offers a molecular navigation map for breeding of DR varieties.展开更多
Phenome has become a consensus as the next innovation source of biomedicine.As the global network dedicated to largescale research efforts on human phenome and promoting the Human Phenome Project,the Board of Internat...Phenome has become a consensus as the next innovation source of biomedicine.As the global network dedicated to largescale research efforts on human phenome and promoting the Human Phenome Project,the Board of International Human Phenome Consortium(IHPC)plays an essential role to guide the strategy and implementation of international human phenome project and to ensure coordination across the IHPC members.The 4th International Human Phenome Consortium Board Meeting was held virtually on December 13,2022.During the meeting,the keynote speeches highlighted the latest advancements in phenomics.The construction and discoveries of the first human phenome Atlas had shown promising potential in limb development,disease prevention,and early diagnosis.Combining genome-phenome sequencing,analysis,and wellness coaching enhanced individual wellness.Phenomics trajectories from healthy to diseased states and recovery provided insight into the metabolic risk spaces associated with COVID-19.Board members from Ghana,Malaysia,India,and Russia presented their own plans and research progress.The IHPC Board deliberated on the“Framework Guidelines for Human Phenome-related Measurements”and“Proposal of the PhenoBank Initiative”.The meeting also featured a presentation of the annual report of the IHPC Journal Phenomics.Laboratory coordination,interoperable databases,and standard-ized platforms were productively discussed,which would enable concerted research efforts of the Human Phenome Project.展开更多
面向作物表型组大数据获取解析、作物种质资源表型鉴定等亟需高效率、智能化和低成本技术、装备及系统的问题,在系统梳理分析国内外农作物高通量表型平台相关技术产品研究现状的基础上,通过组织多学科的协同技术攻关,突破了作物表型组...面向作物表型组大数据获取解析、作物种质资源表型鉴定等亟需高效率、智能化和低成本技术、装备及系统的问题,在系统梳理分析国内外农作物高通量表型平台相关技术产品研究现状的基础上,通过组织多学科的协同技术攻关,突破了作物表型组大数据高通量获取和智能化解析中的关键技术难题,设计了具有自主知识产权的轻小敏捷型多传感器阵列、通用化成像单元和适用于多生境的固定式、移动式高通量表型平台装备,以及配套算法和软件平台,构建了农作物表型组大数据工厂成套技术装备体系。该体系由大田和设施作物高通量自主作业表型平台、室内器官和显微表型平台、大田和设施环境自动化种植管控设备、作物模型系统、数字孪生智慧管控平台和大数据计算服务中心等构成,可实现多生境、自动化、高通量、高效率、高精度的多源作物表型-环境数据协同采集,涵盖农作物群体、个体、器官和显微多重尺度,能够重建农林作物的三维形态结构并精准解析株型、产品、品质、抗性等表型组指标,是发展数字育种和智慧栽培的新一代信息化基础设施。农作物表型组大数据工厂技术装备体系创新了作物表型组大数据的产生、处理和服务模式,可为作物表型组理论技术的发展、基于AI for Science的平台化科研和工厂化的作物种质资源表型鉴定等提供体系化的技术装备支撑。展开更多
Phenomic selection is a recent approach suggested as a low-cost,high-throughput alternative to genomic selection.Instead of using genetic markers,it employs spectral data to predict complex traits using equivalent sta...Phenomic selection is a recent approach suggested as a low-cost,high-throughput alternative to genomic selection.Instead of using genetic markers,it employs spectral data to predict complex traits using equivalent statistical models.Phenomic selection has been shown to outperform genomic selection when using spectral data that was obtained within the same generation as the traits that were predicted.However,for hybrid breeding,the key question is whether spectral data from parental genotypes can be used to effectively predict traits in the hybrid generation.Here,we aimed to evaluate the potential of phenomic selection for hybrid rapeseed breeding.We performed predictions for various traits in a structured population of 410 test hybrids,grown in multiple environments,using near-infrared spectroscopy data obtained from harvested seeds of both the hybrids and their parental lines with different linear and nonlinear models.We found that phenomic selection within the hybrid generation outperformed genomic selection for seed yield and plant height,even when spectral data was collected at single locations,while being less affected by population structure.Furthermore,we demonstrate that phenomic prediction across generations is feasible,and selecting hybrids based on spectral data obtained from parental genotypes is competitive with genomic selection.We conclude that phenomic selection is a promising approach for rapeseed breeding that can be easily implemented without any additional costs or efforts as near-infrared spectroscopy is routinely assessed in rapeseed breeding.展开更多
Since whole-genome sequencing of many crops has been achieved,crop functional genomics studies have stepped into the big-data and high-throughput era.However,acquisition of large-scale phenotypic data has become one o...Since whole-genome sequencing of many crops has been achieved,crop functional genomics studies have stepped into the big-data and high-throughput era.However,acquisition of large-scale phenotypic data has become one of the major bottlenecks hindering crop breeding and functional genomics studies.Nevertheless,recent technological advances provide us potential solutions to relieve this bottleneck and to explore advanced methods for large-scale phenotyping data acquisition and processing in the coming years.In this article,we review the major progress on high-throughput phenotyping in controlled environments and field conditions as well as its use for post-harvest yield and quality assessment in the past decades.We then discuss the latest multi-omics research combining high-throughput phenotyping with genetic studies.Finally,we propose some conceptual challenges and provide our perspectives on how to bridge the phenotype-genotype gap.It is no doubt that accurate high-throughput phenotyping will accelerate plant genetic improvements and promote the next green revolution in crop breeding.展开更多
Plant phenomics(PP)has been recognized as a bottleneck in studying the interactions of genomics and environment on plants,limiting the progress of smart breeding and precise cultivation.High-throughput plant phenotypi...Plant phenomics(PP)has been recognized as a bottleneck in studying the interactions of genomics and environment on plants,limiting the progress of smart breeding and precise cultivation.High-throughput plant phenotyping is challenging owing to the spatio-temporal dynamics of traits.Proximal and remote sensing(PRS)techniques are increasingly used for plant phenotyping because of their advantages in multi-dimensional data acquisition and analysis.Substantial progress of PRS applications in PP has been observed over the last two decades and is analyzed here from an interdisciplinary perspective based on 2972 publications.This progress covers most aspects of PRS application in PP,including patterns of global spatial distribution and temporal dynamics,specific PRS technologies,phenotypic research fields,working environments,species,and traits.Subsequently,we demonstrate how to link PRS to multi-omics studies,including how to achieve multi-dimensional PRS data acquisition and processing,how to systematically integrate all kinds of phenotypic information and derive phenotypic knowledge with biological significance,and how to link PP to multi-omics association analysis.Finally,we identify three future perspectives for PRS-based PP:(1)strengthening the spatial and temporal consistency of PRS data,(2)exploring novel phenotypic traits,and(3)facilitating multi-omics communication.展开更多
基金National Natural Science Foundation of China(82474323)High Level Chinese Medical Hospital Promotion Project(HLCMHPP20230CZ40907)China Academy of Chinese Medical Sciences Outstanding Young Scientific and Technological Talents Program(ZZ13-YQ-026).
文摘Traditional Chinese medicine(TCM)has demonstrated unique advantages in the prevention and treatment of chronic diseases such as glycolipid metabolism disorder.However,its widespread application has been hindered by the unclear biological essence of TCM syndromes and therapeutic mechanisms.As an emerging interdisciplinary field,phenomics integrates multi-dimensional data including genome,transcriptome,proteome,metabolome,and microbiome.When combined with TCM's holistic philosophy,it forms TCM phenomics,providing novel approaches to reveal the biological connotation of TCM syndromes and the mechanisms of herbal medicine.Taking glycolipid metabolism disorder as an example,this paper explores the application of TCM phenomics in glycolipid metabolism disorder.By analyzing molecular characteristics of related syndromes,TCM phenomics identifies differentially expressed genes,metabolites,and gut microbiota biomarkers to elucidate the dynamic evolution patterns of syndromes.Simultaneously,it deciphers the multi-target regulatory networks of herbal formulas,demonstrating their therapeutic effects through mechanisms including modulation of insulin signaling pathways,improvement of gut microbiota imbalance,and suppression of inflammatory responses.Current challenges include the subjective nature of syndrome diagnosis,insufficient standardization of animal models,and lack of integrated multi-omics analysis.Future research should employ machine learning,multimodal data integration,and cross-omics longitudinal studies to establish quantitative diagnostic systems for syndromes,promote the integration of precision medicine in TCM and western medicine,and accelerate the modernization of TCM.
基金Science and Technology strategic cooperation Programs of Luzhou Municipal People’s Government and Southwest Medical University (2019LZXNYD-P01DUAN)National Key R&D Program of China (2024YFC3505400)Regional Key R&D Program of Ningxia Hui Autonomous Region (2024BEG01003)。
文摘Modern western medicine typically focuses on treating specific symptoms or diseases,and traditional Chinese medicine(TCM)emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases.Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics.While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou(a TCM definition of clinical phenome),bottlenecks remain in data standardization,mechanistic interpretation,and precision intervention.Here,we systematically elaborates on the theoretical foundations,technical pathways,and future challenges of integrating digital medicine with TCM phenomics under the framework of“TCM phenomics 2.0”,which is supported by digital medicine technologies such as artificial intelligence,wearable devices,medical digital twins,and multi-omics integration.This framework aims to construct a closed-loop system of“Zhenghou–Phenome–Mechanism–Intervention”and to enable the digitization,standardization,and precision of disease diagnosis and treatment.The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine.In practice,digital tools facilitate multi-source clinical data acquisition and standardization,while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms,thereby improving scientific rigor in diagnosis,efficacy evaluation,and personalized intervention.Nevertheless,challenges persist,including data quality and standardization issues,shortage of interdisciplinary talents,and insufficiency of ethical and legal regulations.Future development requires establishing national data-sharing platforms,strengthening international collaboration,fostering interdisciplinary professionals,and improving ethical and legal frameworks.Ultimately,this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance,innovation,and modernization of TCM diagnostic and therapeutic patterns.
基金supported this research through the National Research Foundation of Korea(NRF),funded by the Ministry of Education(2019R1A6A1A11052070)。
文摘Advances in gene editing and natural genetic variability present significant opportunities to generate novel alleles and select natural sources of genetic variation for horticulture crop improvement.The genetic improvement of crops to enhance their resilience to abiotic stresses and new pests due to climate change is essential for future food security.The field of genomics has made significant strides over the past few decades,enabling us to sequence and analyze entire genomes.However,understanding the complex relationship between genes and their expression in phenotypes-the observable characteristics of an organism-requires a deeper understanding of phenomics.Phenomics seeks to link genetic information with biological processes and environmental factors to better understand complex traits and diseases.Recent breakthroughs in this field include the development of advanced imaging technologies,artificial intelligence algorithms,and large-scale data analysis techniques.These tools have enabled us to explore the relationships between genotype,phenotype,and environment in unprecedented detail.This review explores the importance of understanding the complex relationship between genes and their expression in phenotypes.Integration of genomics with efficient high throughput plant phenotyping as well as the potential of machine learning approaches for genomic and phenomics trait discovery.
文摘Traditional Chinese medicine (TCM) with its millenniaold wisdom rooted in the principles of holistic Yin-Yang balance and “Bianzheng Lunzhi”[辨证论治, Zhenghou(证候) differentiation and treatment], has long offered a unique lens to understand human health and disease.However, the modern scientific interpretation of TCM remains at the stage of “knowing that it works, but not knowing why it works”.
文摘Recent fast advance in biomedical research at the“omic”levels has led to an explosion of big data for the understanding the molecular makeup of diseases,which have revealed the intimate unmatched relationships between the genomic variabilities and the current organ-or system-based definition and classification of disease in Western medi⁃cine.The major challenges in the effort to establish and develop precision medicine are how diseases should be defined and classified in an integrated systemic or omic scale and also on an individualized basis.The phenomics approach to the understanding of diseases will allow the transition from focused phenotype/genotype studies to a systemic largescale phenome and genome,proteome,metabolome approach and the identification of a systemically integrated setof biomarkers for diagnosis and prognosis of disease phenome(or Zhenghou).Phenome-wide associated study(PheWAS)may soon lead the field of medical research and provide insightful and novel clues for redefinition of the disease phenome and its clinical classifications and personalized treatment and ultimately precision medicine.Pharma⁃cophenomics is to characterize the phenomes of drug response and also to identify the corresponding therapeutic targets at the level of systems biology.As a complement of pharmacogenomics/proteomics/metabolomics,pharmacoph⁃enomics offers a suite of new technologies and platforms for the transition from focused phenotype-genotype study to a systematic phenome-genome approach and refine drug research with systematically-defined drug response and thera⁃peutic targets.Therefore,pharmacophenomics will provide a new paradigm for the study of drug response including effects and toxicities at the level of systems biology and will identify the corresponding therapeutic targets and principles for combination treatment and prevention of disease using Fangji or Fufang that takes into account individual variability in genes,environment,and lifestyle for each person.
基金supported by the National Hightech R&D Program (863 Program) (No. 2006AA02A308)the National Basic Research Program of China (973 Program) (No. 2006CB910401, 2006CB910801 and 2006CB910600)+3 种基金the National Natural Science Foundation of China (No. 30700988 and 30700356)the National Natural Science Foundation of China for Creative Research Groups (No. 30621063)the Chinese State Key Project Specialized for Infectious Diseases (No. 2008ZX10002-016, 2009ZX10004-103 and 2009ZX09301002)supported by the State Key Laboratory of Proteomics (No. SKLP-Y200801)
文摘Genome sequencing opened the flood gate of ＂-omics＂ studies, among which the research about correlations between genomic and phenomic variables is an important part. With the development of functional genomics and systems biology, genome-wide investigation of the correlations between many genomic and phenomic variables became possible. In this review, five genomic variables, such as evolution rate （or ＂age＂ of the gene）, the length of intron and ORF （protein length） in one gene, the biases of amino acid composition and codon usage, along with the phenomic variables related to expression patterns （level and breadth） are focused on. In most cases, genes with higher mRNA/protein expression level tend to evolve slowly, have less intronic DNA, code for smaller proteins, and have higher biases of amino acid composition and codon usage. In addition, broadly expressed proteins evolve more slowly and are shorter than tissue-specific proteins. Studies in this field are helpful for deeper understanding the signatures of selection mediated by the features of gene expression and are of great significance to enrich the evolution theory.
基金supported by National Research and Development Program of Ministry of Science and Technology of China(2020YFA0907600,2018YFA0900600,2019YFA09004600)Strategic Priority Research Program of the Chinese Academy of Sciences(XDB27020105,XDB37020104,XDA24010203,XDA0450202)+2 种基金National Science Foundation of China(31870214)the National Key Research and Development Program of China(2023YFF1000100)STI2030eMajor Projects(2023ZD04076).
文摘Crop phenomics enables the collection of diverse plant traits for a large number of samples along different time scales,representing a greater data collection throughput compared with traditional measurements.Most modern crop phenomics use different sensors to collect reflective,emitted,and fluorescence signals,etc.,from plant organs at different spatial and temporal resolutions.Such multi-modal,high-dimensional data not only accelerates basic research on crop physiology,genetics,and whole plant systems modeling,but also supports the optimization of field agronomic practices,internal environments of plant factories,and ultimately crop breeding.Major challenges and opportunities facing the current crop phenomics research community include developing community consensus or standards for data collection,management,sharing,and processing,developing capabilities to measure physiological parameters,and enabling farmers and breeders to effectively use phenomics in the field to directly support agricultural production.
基金supported by the National Key R&D Program of China(2022YFD2002300)the Construction of Collaborative Innovation Center of Beijing Academy of Agricultural and Forestry Sciences(KJCX20240406)+1 种基金the National Natural Science Foundation of China(32071891)the earmarked fund(CARS-02 and CARS-054).
文摘Crop phenomics has rapidly progressed in recent years due to the growing need for crop functional geno-mics,digital breeding,and smart cultivation.Despite this advancement,the lack of standards for the cre-ation and usage of crop phenomics technology and equipment has become a bottleneck,limiting the industry’s high-quality development.This paper begins with an overview of the crop phenotyping indus-try and presents an industrial mapping of technology and equipment for big data in crop phenomics.It analyzes the necessity and current state of constructing a standard framework for crop phenotyping.Furthermore,this paper proposes the intended organizational structure and goals of the standard frame-work.It details the essentials of the standard framework in the research and development of hardware and equipment,data acquisition,and the storage and management of crop phenotyping data.Finally,it discusses promoting the construction and evaluation of the standard framework,aiming to provide ideas for developing a high-quality standard framework for crop phenotyping.
文摘Objective: This study aimed to explore the experiences of women in the process of formula feeding their infants. The World Health Organization has emphasized the importance of breastfeeding for infant health. After decades of breastfeeding promotions,breastfeeding rates in Hong Kong have been rising consistently; however, the low continuation rate is alarming. This study explores women's experiences with formula feeding their infants, including factors affecting their decision to do so.Methods: A qualitative approach using an interpretative phenomenological analysis(IPA) was adopted as the study design. Data were collected from 2014 to 2015 through individual in-depth unstructured interviews with 16 women, conducted between 3 and 12 months after the birth of their infant. Data were analyzed using IPA.Results: Three main themes emerged as follows:(1) self-struggle, with the subthemes of feeling like a milk cow and feeling trapped;(2) family conflict, with the subtheme of sharing the spotlight; and(3) interpersonal tensions, with the subthemes of embarrassment,staring, and innocence. Many mothers suffered various stressors and frustrations during breastfeeding. These findings suggest a number of pertinent areas that need to be considered in preparing an infant feeding campaign.Conclusions: The findings of this study reinforce our knowledge of women's struggles with multiple sources of pressure, such as career demands, childcare demands, and family life after giving birth. All mothers should be given assistance in making informed decisions about the optimal approach to feeding their babies given their individual situation and be provided with support to pursue their chosen feeding method.
文摘An emerging area of interest in understanding disease phenotypes is systems genomics.Complex diseases such as diabetes have played an important role towards understanding the susceptible genes and mutations.A wide number of methods have been employed and strategies such as polygenic risk score and allele frequencies have been useful,but understanding the candidate genes harboring those mutations is an unmet goal.In this perspective,using systems genomic approaches,we highlight the application of phenome-interactome networks in diabetes and provide deep insights.LINC01128,which we previously described as candidate for diabetes,is shown as an example to discuss the approach.
基金funded by the National Natural Science Foundation of China(NSFC)Joint Fund Priority Support Program(U23A20249)the“Special fund for youth team of the Southwest University”(SWUXJPY202302)+3 种基金the“National Talent Research Grant for 2023”(5330500953)National Natural Science Foundation of China(32072980)Chongqing Innovation Program for Graduate Research(CYB240106)the National Key R&D Program of China(grant no.2024YFD1200703).
文摘Schizothoracine fishes are distributed in the Nagqu region,which is the hinterland of the Tibetan Plateau.They have adapted to the cold and strongly ultraviolet environment of the plateau and show diverse morphologies,which makes them ideal for studying the relationship between phenotype and environment.However,traditional morphological measurements are time consuming and labor costly.In this study,we propose a deep-learningbased method for acquiring high-throughput phenotypic data of fishes,including image dataset construction of schizothoracine fishes(including front,side,and top views),fish keypoint detection based on the You Only Look Once(YOLO)model,and reconstruction of 2D and 3D keypoint coordinates based on multiple views.A total of 7050 phenotypic data points consisting of keypoint distances and angles were constructed for each fish and were highly correlated(>0.98)with the corresponding data measured manually.We obtained phenotypic data for a total of 525 fishes from three schizothoracine fish groups inhabiting riverine,lacustrine,and river–lake transitional environments using the proposed phenotypic data acquisition method.We employed a random forest algorithm to classify the groups,achieving a classification accuracy of 96%,and identified 15 morphometric indices that exhibited statistically significant differences.,of which 6 were related to head morphology,6 related to body shape,and 3 related to tail morphology,based on the random forest algorithm.Specifically,river-living schizothoracine fishes showed a blunt head,robust body,and elongated caudal peduncle which may reflect adaptations to the turbulence of the river,while the lake-living schizothoracine fishes have the opposite effect.Schizothoracine fishes at the river–lake transitional zones were phenotypically characterized as being in the middle of the two phenotypes,and these presumably reflect adaptations to their lake habitat.This study provides a methodological reference for obtaining high-throughput phenotypic data on fish and a theoretical basis for understanding the adaptation of very high-altitude schizothoracine fishes to their environment.
基金supported in part by grants from Biological Breeding-National Science and Technology Major Project(Grant No.2023ZD04076)the National Natural Science Foundation of China(Grant No.32170647)+2 种基金the National Science Foundation of Jiangsu Province in China(Grant Nos.BK20212010 and BE2022383)the Jiangsu Engineering Research Center for Plant Genome Editing,Southern Japonica Rice Research and Development Co.LTDthe Jiangsu Collaborative Innovation Center for Modern Crop Production.
文摘Machine learning models for crop image analysis and phenomics are highly important for precision agriculture and breeding and have been the subject of intensive research.However,the lack of publicly available high-quality image datasets with detailed annotations has severely hindered the development of these models.In this work,we present a comprehensive multicultivar and multiview rice plant image dataset(CVRP)created from 231 landraces and 50 modern cultivars grown under dense planting in paddy fields.The dataset includes images capturing rice plants in their natural environment,as well as indoor images focusing specifically on panicles,allowing for a detailed investigation of cultivar-specific differences.A semiautomatic annotation process using deep learning models was designed for annotations,followed by rigorous manual curation.We demonstrated the utility of the CVRP by evaluating the performance of four state-of-the-art(SOTA)semantic segmentation models.We also conducted 3D plant reconstruction with organ segmentation via images and annotations.The database not only facilitates general-purpose image-based panicle identification and segmentation but also provides valuable re-sources for challenging tasks such as automatic rice cultivar identification,panicle and grain counting,and 3D plant reconstruction.The database and the model for image annotation are available at.
基金supported by the Noncommunicable Chronic Diseases-National Science and Technology Major Project(2023ZD0510100)supported by the Kadoorie Charitable Foundation in Hong Kong.The long-term follow-up has been supported by Wellcome grants to Oxford University(212946/Z/18/Z,202922/Z/16/Z,104085/Z/14/Z,088158/Z/09/Z)and grants(2016YFC0900500)+4 种基金the National Key Research and Development Programof China,theNational Natural Science Foundation of China(82192900,82388102,81390540,91846303,81941018)the ChineseMinistry of Science and Technology(2011BAI09B01)The UK Medical Research Council(MC_UU_00017/1,MC_UU_12026/2,MC_U137686851),Cancer Research UK(C16077/A29186C500/A16896)the British Heart Foundation(CH/1996001/9454),provide core funding to the Clinical Trial Service Unit and Epidemiological Studies Unit at Oxford University for the project.
文摘Research in high-income countries has established the health benefits of physical activity(PA),but evidence from low-and middle-income countries,including China,where PA patterns vary from those in high-income countries,remains limited.Moreover,previous research,mainly focused on specific diseases,failing to fully capture the health impacts of PA.We investigated the associations of PA with 425 distinct diseases and 53 causes of death using data from 511,088 participants aged 30–79 years in the China Kadoorie Biobank.Baseline PA was assessed using a questionnaire between 2004 and 2008,and usual PA levels were estimated using the resurvey data in 2013–2014.Cox regression was employed to estimate the associations between PA and outcomes,adjusting for potential confounders.During a median follow-up time of 12 years,722,183 incident events and 39,320 deaths were recorded across 18 chapters of the International Classification of Diseases,10th Revision(ICD-10).Total PA was significantly and inversely associated with incidence risks of 14 ICD-10 chapters,specifically 65 diseases and 19 causes of death,with the highest quintile group of PA showing a 14%lower disease incidence and 40%lower all-cause mortality compared with the lowest group.Of these diseases,54 were not highlighted in World Health Organization PA guidelines.Dose-response analyses revealed L-shaped associations for most PA types,except moderate-tovigorous intensity PA,which showed a U-shaped relationship.In this population,physical inactivity accounted for 12.8%of PA-related deaths.The findings underscore the broad health benefits of PA across a variety of body systems and the significant disease burden due to inactivity in China,highlighting the urgent need for PA promotion.
基金supported by the National Natural Science Foundation of China(32172098 and U21A20205)the Natural Science Foundation of Shanghai(23ZR1455900 and 22ZR1455200).
文摘Dissecting the mechanism of drought resistance(DR)and designing drought-resistant rice varieties are promising strategies to address the challenge of climate change.Here,we selected a typical droughtavoidant(DA)variety,IRAT109,and a drought-tolerant(DT)variety,Hanhui15,as parents to develop a stable recombinant inbred line(RIL)population(F8,1262 lines).The de novo assembled genomes of both parents were released.By resequencing of the RIL population,a set of 1189216 reliable SNPs were obtained and used to construct a dense genetic map.Using above-and belowground phenomic platforms and multimodal cameras,we captured 139040 image-based traits(i-traits)of whole-plant phenotypes in response to drought stress throughout the entire rice growth period and identified 32586 drought-responsive quantitative trait loci(QTLs),including 2097 unique QTLs.QTLs associated with panicle i-traits occurred more than 600 times on the middle of chromosome 8,and QTLs associated with leaf i-traits occurred more than 800 times on the 50 end of chromosome 3,indicating the potential effects of these QTLs on plant phenotypes.We selected three candidate genes(OsMADS50,OsGhd8,OsSAUR11)related to leaf,panicle,and root traits,respectively,and verified their functions in DR.OsMADS50 was found to negatively regulate DR by modulating leaf dehydration,grain size,and downward root growth.A total of 18 and 21 composite QTLs significantly related to grain weight and plant biomass were also screened from 597 lines in the RIL population under drought conditions in field experiments,and the composite QTL regions showed substantial overlap(76.9%)with known DR gene regions.Based on three candidate DR genes,we proposed a haplotype design suitable for different environments and breeding objectives.This study provides a valuable reference for multimodal and time-series phenomic analyses,deciphers the genetic mechanisms of DA and DT rice varieties,and offers a molecular navigation map for breeding of DR varieties.
基金Funding Shanghai Soft Science Research Project(21692101800,21692102400,22692102000)Shanghai Municipal Science and Technology International Partnership Project(20490780100).
文摘Phenome has become a consensus as the next innovation source of biomedicine.As the global network dedicated to largescale research efforts on human phenome and promoting the Human Phenome Project,the Board of International Human Phenome Consortium(IHPC)plays an essential role to guide the strategy and implementation of international human phenome project and to ensure coordination across the IHPC members.The 4th International Human Phenome Consortium Board Meeting was held virtually on December 13,2022.During the meeting,the keynote speeches highlighted the latest advancements in phenomics.The construction and discoveries of the first human phenome Atlas had shown promising potential in limb development,disease prevention,and early diagnosis.Combining genome-phenome sequencing,analysis,and wellness coaching enhanced individual wellness.Phenomics trajectories from healthy to diseased states and recovery provided insight into the metabolic risk spaces associated with COVID-19.Board members from Ghana,Malaysia,India,and Russia presented their own plans and research progress.The IHPC Board deliberated on the“Framework Guidelines for Human Phenome-related Measurements”and“Proposal of the PhenoBank Initiative”.The meeting also featured a presentation of the annual report of the IHPC Journal Phenomics.Laboratory coordination,interoperable databases,and standard-ized platforms were productively discussed,which would enable concerted research efforts of the Human Phenome Project.
文摘面向作物表型组大数据获取解析、作物种质资源表型鉴定等亟需高效率、智能化和低成本技术、装备及系统的问题,在系统梳理分析国内外农作物高通量表型平台相关技术产品研究现状的基础上,通过组织多学科的协同技术攻关,突破了作物表型组大数据高通量获取和智能化解析中的关键技术难题,设计了具有自主知识产权的轻小敏捷型多传感器阵列、通用化成像单元和适用于多生境的固定式、移动式高通量表型平台装备,以及配套算法和软件平台,构建了农作物表型组大数据工厂成套技术装备体系。该体系由大田和设施作物高通量自主作业表型平台、室内器官和显微表型平台、大田和设施环境自动化种植管控设备、作物模型系统、数字孪生智慧管控平台和大数据计算服务中心等构成,可实现多生境、自动化、高通量、高效率、高精度的多源作物表型-环境数据协同采集,涵盖农作物群体、个体、器官和显微多重尺度,能够重建农林作物的三维形态结构并精准解析株型、产品、品质、抗性等表型组指标,是发展数字育种和智慧栽培的新一代信息化基础设施。农作物表型组大数据工厂技术装备体系创新了作物表型组大数据的产生、处理和服务模式,可为作物表型组理论技术的发展、基于AI for Science的平台化科研和工厂化的作物种质资源表型鉴定等提供体系化的技术装备支撑。
基金funded by Federal Ministry for Food and Agriculture grant 281B200416.
文摘Phenomic selection is a recent approach suggested as a low-cost,high-throughput alternative to genomic selection.Instead of using genetic markers,it employs spectral data to predict complex traits using equivalent statistical models.Phenomic selection has been shown to outperform genomic selection when using spectral data that was obtained within the same generation as the traits that were predicted.However,for hybrid breeding,the key question is whether spectral data from parental genotypes can be used to effectively predict traits in the hybrid generation.Here,we aimed to evaluate the potential of phenomic selection for hybrid rapeseed breeding.We performed predictions for various traits in a structured population of 410 test hybrids,grown in multiple environments,using near-infrared spectroscopy data obtained from harvested seeds of both the hybrids and their parental lines with different linear and nonlinear models.We found that phenomic selection within the hybrid generation outperformed genomic selection for seed yield and plant height,even when spectral data was collected at single locations,while being less affected by population structure.Furthermore,we demonstrate that phenomic prediction across generations is feasible,and selecting hybrids based on spectral data obtained from parental genotypes is competitive with genomic selection.We conclude that phenomic selection is a promising approach for rapeseed breeding that can be easily implemented without any additional costs or efforts as near-infrared spectroscopy is routinely assessed in rapeseed breeding.
基金the National Key Research and Development Program of China(2016YFD0100101-18,2016YFD0100103)the National Natural Science Foundation of China(31770397,21800305)+2 种基金the Fundamental Research Funds for the Central Universities(2662017PY058,2662017QD044)UK-China grant BBSRC(grant no.BB/R02118X/1)the National Institute of Food and Agriculture,U.S.Department of Agriculture,Hatch project(ALA014-1-16016).
文摘Since whole-genome sequencing of many crops has been achieved,crop functional genomics studies have stepped into the big-data and high-throughput era.However,acquisition of large-scale phenotypic data has become one of the major bottlenecks hindering crop breeding and functional genomics studies.Nevertheless,recent technological advances provide us potential solutions to relieve this bottleneck and to explore advanced methods for large-scale phenotyping data acquisition and processing in the coming years.In this article,we review the major progress on high-throughput phenotyping in controlled environments and field conditions as well as its use for post-harvest yield and quality assessment in the past decades.We then discuss the latest multi-omics research combining high-throughput phenotyping with genetic studies.Finally,we propose some conceptual challenges and provide our perspectives on how to bridge the phenotype-genotype gap.It is no doubt that accurate high-throughput phenotyping will accelerate plant genetic improvements and promote the next green revolution in crop breeding.
基金supported by the Hainan Yazhou Bay Seed Lab(no.B21HJ1005)the Fundamental Research Funds for the Central Universities(no.KYCYXT2022017)+5 种基金the Open Project of Key Laboratory of Oasis Eco-agriculture,Xinjiang Production and Construction Corps(no.202101)the Jiangsu Association for Science and Technology Independent Innovation Fund Project(no.CX(21)3107)the High Level Personnel Project of Jiangsu Province(no.JSSCBS20210271)the China Postdoctoral Science Foundation(no.2021M691490)the Jiangsu Planned Projects for Postdoctoral Research Funds(no.2021K520C)the JBGS Project of Seed Industry Revitalization in Jiangsu Province(no.JBGS[2021]007).
文摘Plant phenomics(PP)has been recognized as a bottleneck in studying the interactions of genomics and environment on plants,limiting the progress of smart breeding and precise cultivation.High-throughput plant phenotyping is challenging owing to the spatio-temporal dynamics of traits.Proximal and remote sensing(PRS)techniques are increasingly used for plant phenotyping because of their advantages in multi-dimensional data acquisition and analysis.Substantial progress of PRS applications in PP has been observed over the last two decades and is analyzed here from an interdisciplinary perspective based on 2972 publications.This progress covers most aspects of PRS application in PP,including patterns of global spatial distribution and temporal dynamics,specific PRS technologies,phenotypic research fields,working environments,species,and traits.Subsequently,we demonstrate how to link PRS to multi-omics studies,including how to achieve multi-dimensional PRS data acquisition and processing,how to systematically integrate all kinds of phenotypic information and derive phenotypic knowledge with biological significance,and how to link PP to multi-omics association analysis.Finally,we identify three future perspectives for PRS-based PP:(1)strengthening the spatial and temporal consistency of PRS data,(2)exploring novel phenotypic traits,and(3)facilitating multi-omics communication.
