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
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
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
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
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
Skin is a complex ecosystem colonized by millions of microorganisms,including bacteria,fungi,and viruses.Skin microbiota is believed to exert critical functions in maintaining host skin health.Profiling the structure ...Skin is a complex ecosystem colonized by millions of microorganisms,including bacteria,fungi,and viruses.Skin microbiota is believed to exert critical functions in maintaining host skin health.Profiling the structure of skin microbial community is the first step to overview the ecosystem.However,the community composition is highly individualized and extremely complex.To explore the fundamental factors driving the complexity of the ecosystem,namely the selection pressures,we review the present studies on skin microbiome from the perspectives of ecology.This review summarizes the following:(1)the composition of substances/nutrients in the cutaneous ecological environment that are derived from the host and the environment,highlighting their proposed function on skin microbiota;(2)the features of dominant skin commensals to occupy ecological niches,through self-adaptation and microbe–microbe interactions;(3)how skin microbes,by their structures or bioactive molecules,reshape host skin phenotypes,including skin immunity,maintenance of skin physiology such as pH and hydration,ultraviolet(UV)protection,odor production,and wound healing.This review aims to re-examine the host–microbe interactions from the ecological perspectives and hopefully to give new inspiration to this field.展开更多
Due to the limitations of existing approaches,a rapid,sensitive,accurate,comprehensive,and generally applicable strategy to diagnose and treat bacterial and fungal infections remains a major challenge.Here,based on th...Due to the limitations of existing approaches,a rapid,sensitive,accurate,comprehensive,and generally applicable strategy to diagnose and treat bacterial and fungal infections remains a major challenge.Here,based on the ramanome technology platform,we propose a culture‐free,one cell resolution,phenome‐genome‐combined strategy called single‐cell identification,viability and vitality tests and source tracking(SCIVVS).For each cell directly extracted from a clinical specimen,the fingerprint region of the D2O‐probed single cell Raman spectrum(SCRS)enables species‐level identification based on a reference SCRS database of pathogen species,whereas the C‐D band accurately quantifies viability,metabolic vitality,phenotypic susceptibility to antimicrobials,and their intercellular heterogeneity.Moreover,to source track a cell,Raman‐activated cell sorting followed by sequencing or cultivation proceeds,producinging an indexed,high coverage genome assembly or a pure culture from precisely one pathogenic cell.Finally,an integrated SCIVVS workflow that features automated profiling and sorting of metabolic and morphological phenomes can complete the entire process in only a few hours.Because it resolves heterogeneity for both the metabolic phenome and genome,targets functions,can be automated,and is orders‐of‐magnitude faster while cost‐effective,SCIVVS is a new technological and data framework to diagnose and treat bacterial and fungal infections in various clinical and disease control settings.展开更多
Despite the skin microbiome has been linked to skin health and diseases,its role in modulating human skin appearance remains understudied.Using a total of 1244 face imaging phenomes and 246 cheek metagenomes,we first ...Despite the skin microbiome has been linked to skin health and diseases,its role in modulating human skin appearance remains understudied.Using a total of 1244 face imaging phenomes and 246 cheek metagenomes,we first established three skin age indices by machine learning,including skin phenotype age(SPA),skin microbiota age(SMA),and skin integration age(SIA)as surrogates of phenotypic aging,microbial aging,and their combination,respectively.Moreover,we found that besides aging and gender as intrinsic factors,skin microbiome might also play a role in shaping skin imaging phenotypes(SIPs).Skin taxonomic and functionalαdiversity was positively linked to melanin,pore,pigment,and ultraviolet spot levels,but negatively linked to sebum,lightening,and porphyrin levels.Furthermore,certain species were correlated with specific SIPs,such as sebum and lightening levels negatively correlated with Corynebacterium matruchotii,Staphylococcus capitis,and Streptococcus sanguinis.Notably,we demonstrated skin microbial potential in predicting SIPs,among which the lightening level presented the least error of 1.8%.Lastly,we provided a reservoir of potential mechanisms through which skin microbiome adjusted the SIPs,including the modulation of pore,wrinkle,and sebum levels by cobalamin and heme synthesis pathways,predominantly driven by Cutibacterium acnes.This pioneering study unveils the paradigm for the hidden links between skin microbiome and skin imaging phenome,providing novel insights into how skin microbiome shapes skin appearance and its healthy aging.展开更多
The bacterial family Mycobacteriaceae includes pathogenic and nonpathogenic bacteria,and systematic research on their genome and phenome can give comprehensive perspectives for exploring their disease mechanism.In thi...The bacterial family Mycobacteriaceae includes pathogenic and nonpathogenic bacteria,and systematic research on their genome and phenome can give comprehensive perspectives for exploring their disease mechanism.In this study,the pheno-types of Mycobacteriaceae were inferred from available phenomic data,and 82 microbial phenotypic traits were recruited as data elements of the microbial phenome.This Mycobacteriaceae phenome contains five categories and 20 subcategories of polyphasic phenotypes,and three categories and eight subcategories of functional phenotypes,all of which are complemen-tary to the existing data standards of microbial phenotypes.The phenomic data of Mycobacteriaceae strains were compiled by literature mining,third-party database integration,and bioinformatics annotation.The phenotypes were searchable and comparable from the website of the Mycobacteriaceae Phenome Atlas(MPA,https://www.biosi no.org/mpa/).A topological data analysis of MPA revealed the co-evolution between Mycobacterium tuberculosis and virulence factors,and uncovered potential pathogenicity-associated phenotypes.Two hundred and sixty potential pathogen-enriched pathways were found by Fisher's exact test.The application of MPA may provide novel insights into the pathogenicity mechanism and antimicrobial targets of Mycobacteriaceae.展开更多
The spin echo (SE) phenomenon discovered in the pulse nuclear magnetic resonance (PNMR) exerts significant influence on the field of magnetic resonance. It was first reported by E. L. Hahn in 1950. The discovery of SE...The spin echo (SE) phenomenon discovered in the pulse nuclear magnetic resonance (PNMR) exerts significant influence on the field of magnetic resonance. It was first reported by E. L. Hahn in 1950. The discovery of SE provided a new method for a better understanding of NMR phenomenon. For example, it solved the difficul-展开更多
Linking natural genetic variation to trait variation can help determine the functional roles ofdifferent genes.Variations of one or several traits are often assessed separately.High-throughput phenotyping and data min...Linking natural genetic variation to trait variation can help determine the functional roles ofdifferent genes.Variations of one or several traits are often assessed separately.High-throughput phenotyping and data mining can capture dozens or hundreds of traits from the same individuals.Here,we test the association between markers within a gene and many traits simultaneously.This genome–phenome wide association study(GPWAS)is both a multi-marker and multi-trait test.Genes identified using GPWAS with 260 phenotypic traits in maize were enriched for genes independently linked to phenotypic variation.Traits associated with classical mutants were consistent with reported phenotypes for mutant alleles.Genes linked to phenomic variation in maize using GPWAS shared molecular,population genetic,and evolutionary features with classical mutants in maize.Genes linked to phenomic variation in Arabidopsis using GPWAS are significantly enriched in genes with known loss-of-function phenotypes.GPWAS may be an effective strategy to identify genes in which loss-of-function alleles produce mutant phenotypes.The shared signatures present in classical mutants and genes identified using GPWAS may be markers for genes with a role in specifying plant phenotypes generally or pleiotropy specifically.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
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
Evidence has shown that differential transcriptomic profiles among human populations from diverse ancestries,supporting the role of genetic architecture in regulating gene expression alongside environmental stimuli.Ge...Evidence has shown that differential transcriptomic profiles among human populations from diverse ancestries,supporting the role of genetic architecture in regulating gene expression alongside environmental stimuli.Genetic variants that regulate gene expression,known as expression quantitative trait loci(eQTL),are primarily shaped by human migration history and evolutionary forces,likewise,regulation of gene expression in principle could have been influenced by these events.Therefore,a comprehensive understanding of how human evolution impacts eQTL offers important insights into how phenotypic diversity is shaped.Recent studies,however,suggest that eQTL is enriched in genes that are selectively constrained.Whether eQTL is minimally affected by selective pressures remains an open question and requires comprehensive investigations.In addition,such studies are primarily dominated by the major populations of European ancestry,leaving many marginalized populations underrepresented.These observations indicate there exists a fundamental knowledge gap in the role of genomics variation on phenotypic diversity,which potentially hinders precision medicine.This article aims to revisit the abundance of eQTL across diverse populations and provide an overview of their impact from the population and evolutionary genetics perspective,subsequently discuss their influence on phenomics,as well as challenges and opportunities in the applications to precision medicine.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
The tree shrew(Tupaia belangeri)has long been proposed as a suitable alternative to non-human primates(NHPs)in biomedical and laboratory research due to its close evolutionary relationship with primates.In recent year...The tree shrew(Tupaia belangeri)has long been proposed as a suitable alternative to non-human primates(NHPs)in biomedical and laboratory research due to its close evolutionary relationship with primates.In recent years,significant advances have facilitated tree shrew studies,including the determination of the tree shrew genome,genetic manipulation using spermatogonial stem cells,viral vector-mediated gene delivery,and mapping of the tree shrew brain atlas.However,the limited availability of tree shrews globally remains a substantial challenge in the field.Additionally,determining the key questions best answered using tree shrews constitutes another difficulty.Tree shrew models have historically been used to study hepatitis B virus(HBV)and hepatitis C virus(HCV)infection,myopia,and psychosocial stress-induced depression,with more recent studies focusing on developing animal models for infectious and neurodegenerative diseases.Despite these efforts,the impact of tree shrew models has not yet matched that of rodent or NHP models in biomedical research.This review summarizes the prominent advancements in tree shrew research and reflects on the key biological questions addressed using this model.We emphasize that intensive dedication and robust international collaboration are essential for achieving breakthroughs in tree shrew studies.The use of tree shrews as a unique resource is expected to gain considerable attention with the application of advanced techniques and the development of viable animal models,meeting the increasing demands of life science and biomedical research.展开更多
With the rapid development of genetic analysis techniques and crop population size,phenotyping has become the bottleneck restricting crop breeding.Breaking through this bottleneck will require phenomics,defined as the...With the rapid development of genetic analysis techniques and crop population size,phenotyping has become the bottleneck restricting crop breeding.Breaking through this bottleneck will require phenomics,defined as the accurate,high-throughput acquisition and analysis of multi-dimensional phenotypes during crop growth at organism-wide levels,ranging from cells to organs,individual plants,plots,and fields.Here we offer an overview of crop phenomics research from technological and platform viewpoints at various scales,including microscopic,ground-based,and aerial phenotyping and phenotypic data analysis.We describe recent applications of high-throughput phenotyping platforms for abiotic/biotic stress and yield assessment.Finally,we discuss current challenges and offer perspectives on future phenomics research.展开更多
Fish morphological phenotypes are important resources in artificial breeding,functional gene mapping,and population-based studies in aquaculture and ecology.Traditional morphological measurement of phenotypes is rathe...Fish morphological phenotypes are important resources in artificial breeding,functional gene mapping,and population-based studies in aquaculture and ecology.Traditional morphological measurement of phenotypes is rather expensive in terms of time and labor.More importantly,manual measurement is highly dependent on operational experience,which can lead to subjective phenotyping results.Here,we developed 3DPhenoFish software to extract fish morphological phenotypes from three-dimensional(3D)point cloud data.Algorithms for background elimination,coordinate normalization,image segmentation,key point recognition,and phenotype extraction were developed and integrated into an intuitive user interface.Furthermore,18 key points and traditional 2D morphological traits,along with 3D phenotypes,including area and volume,can be automatically obtained in a visualized manner.Intuitive fine-tuning of key points and customized definitions of phenotypes are also allowed in the software.Using 3DPhenoFish,we performed high-throughput phenotyping for four endemic Schizothoracinae species,including Schizopygopsis younghusbandi,Oxygymnocypris stewartii,Ptychobarbus dipogon,and Schizothorax oconnori.Results indicated that the morphological phenotypes from 3DPhenoFish exhibited high linear correlation(>0.94)with manual measurements and offered informative traits to discriminate samples of different species and even for different populations of the same species.In summary,we developed an efficient,accurate,and customizable tool,3DPhenoFish,to extract morphological phenotypes from point cloud data,which should help overcome traditional challenges in manual measurements.3DPhenoFish can be used for research on morphological phenotypes in fish,including functional gene mapping,artificial selection,and conservation studies.3DPhenoFish is an open-source software and can be downloaded for free at https://github.com/lyh24k/3DPhenoFish/tree/master.展开更多
Phenomics is a new branch of science that provides high-throughput quantification of plant and animal traits at systems level.The last decade has witnessed great successes in high-throughput phenotyping of numerous mo...Phenomics is a new branch of science that provides high-throughput quantification of plant and animal traits at systems level.The last decade has witnessed great successes in high-throughput phenotyping of numerous morphological traits,yet major challenges still exist in precise phenotyping of physiological traits such as transpiration and photosynthesis.Due to the highly dynamic nature of physiological traits in responses to the environment,appropriate selection criteria and efficient screening systems at the physiological level for abiotic stress tolerance have been largely absent in plants.In this review,the current status of phenomics techniques was briefly summarized in horticultural plants.Specifically,the emerging field of high-throughput physiology-based phenotyping,which is referred to as“physiolomics”,for drought stress responseswas highlighted.In addition to analyzing the advantages of physiology-based phenotyping overmorphology-based approaches,recent examples that applied high-throughput physiological phenotyping to model and non-model horticultural plants were revisited and discussed.Based on the collective findings,we propose that high-throughput,non-destructive,and automatic physiological assays can and should be used as routine methods for phenotyping stress response traits in horticultural plants.展开更多
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.
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.
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 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.
基金This work was supported by the Shanghai Municipal Science and Technology Major Project(2017SHZDZX01)the CAMS Innovation Fund for Medical Sciences(2019-I2M-5-066)+1 种基金the 111 Project(B13016)a startup grant from the Greater Bay Area Institute of Precision Medicine(Guangzhou),Fudan University to JX.
文摘Skin is a complex ecosystem colonized by millions of microorganisms,including bacteria,fungi,and viruses.Skin microbiota is believed to exert critical functions in maintaining host skin health.Profiling the structure of skin microbial community is the first step to overview the ecosystem.However,the community composition is highly individualized and extremely complex.To explore the fundamental factors driving the complexity of the ecosystem,namely the selection pressures,we review the present studies on skin microbiome from the perspectives of ecology.This review summarizes the following:(1)the composition of substances/nutrients in the cutaneous ecological environment that are derived from the host and the environment,highlighting their proposed function on skin microbiota;(2)the features of dominant skin commensals to occupy ecological niches,through self-adaptation and microbe–microbe interactions;(3)how skin microbes,by their structures or bioactive molecules,reshape host skin phenotypes,including skin immunity,maintenance of skin physiology such as pH and hydration,ultraviolet(UV)protection,odor production,and wound healing.This review aims to re-examine the host–microbe interactions from the ecological perspectives and hopefully to give new inspiration to this field.
基金National Key R&D Program of China,Grant/Award Number:2022YFA1304101CAS,Grant/Award Number:XDB29050400+1 种基金National Natural Science Foundation of China,Grant/Award Number:32030003Shenzhen‐Hong Kong Innovation Circle Plan,Grant/Award Number:SGDX2019081623060946。
文摘Due to the limitations of existing approaches,a rapid,sensitive,accurate,comprehensive,and generally applicable strategy to diagnose and treat bacterial and fungal infections remains a major challenge.Here,based on the ramanome technology platform,we propose a culture‐free,one cell resolution,phenome‐genome‐combined strategy called single‐cell identification,viability and vitality tests and source tracking(SCIVVS).For each cell directly extracted from a clinical specimen,the fingerprint region of the D2O‐probed single cell Raman spectrum(SCRS)enables species‐level identification based on a reference SCRS database of pathogen species,whereas the C‐D band accurately quantifies viability,metabolic vitality,phenotypic susceptibility to antimicrobials,and their intercellular heterogeneity.Moreover,to source track a cell,Raman‐activated cell sorting followed by sequencing or cultivation proceeds,producinging an indexed,high coverage genome assembly or a pure culture from precisely one pathogenic cell.Finally,an integrated SCIVVS workflow that features automated profiling and sorting of metabolic and morphological phenomes can complete the entire process in only a few hours.Because it resolves heterogeneity for both the metabolic phenome and genome,targets functions,can be automated,and is orders‐of‐magnitude faster while cost‐effective,SCIVVS is a new technological and data framework to diagnose and treat bacterial and fungal infections in various clinical and disease control settings.
基金supported by the National Natural Science Foundation of China(Grant Nos.32071465,31871334,and 31671374)the National Key R&D Program of China(Grant No.2018YFC0910502)Yuhao Zhang(Huazhong University of Science and Technology,China)to improve the analysis of this study。
文摘Despite the skin microbiome has been linked to skin health and diseases,its role in modulating human skin appearance remains understudied.Using a total of 1244 face imaging phenomes and 246 cheek metagenomes,we first established three skin age indices by machine learning,including skin phenotype age(SPA),skin microbiota age(SMA),and skin integration age(SIA)as surrogates of phenotypic aging,microbial aging,and their combination,respectively.Moreover,we found that besides aging and gender as intrinsic factors,skin microbiome might also play a role in shaping skin imaging phenotypes(SIPs).Skin taxonomic and functionalαdiversity was positively linked to melanin,pore,pigment,and ultraviolet spot levels,but negatively linked to sebum,lightening,and porphyrin levels.Furthermore,certain species were correlated with specific SIPs,such as sebum and lightening levels negatively correlated with Corynebacterium matruchotii,Staphylococcus capitis,and Streptococcus sanguinis.Notably,we demonstrated skin microbial potential in predicting SIPs,among which the lightening level presented the least error of 1.8%.Lastly,we provided a reservoir of potential mechanisms through which skin microbiome adjusted the SIPs,including the modulation of pore,wrinkle,and sebum levels by cobalamin and heme synthesis pathways,predominantly driven by Cutibacterium acnes.This pioneering study unveils the paradigm for the hidden links between skin microbiome and skin imaging phenome,providing novel insights into how skin microbiome shapes skin appearance and its healthy aging.
基金supported by the National Key R&D Program of China(2021YFF0703702,2021YFC2301502,and 2018YFA0900704)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB38030100)+1 种基金Shanghai Municipal Science and Technology Major Project(2017SHZDZX01)the Biological Resources Programme,Chinese Academy of Sciences(KFJ-BRP-017-79 and KFJ-BRP-009-001).
文摘The bacterial family Mycobacteriaceae includes pathogenic and nonpathogenic bacteria,and systematic research on their genome and phenome can give comprehensive perspectives for exploring their disease mechanism.In this study,the pheno-types of Mycobacteriaceae were inferred from available phenomic data,and 82 microbial phenotypic traits were recruited as data elements of the microbial phenome.This Mycobacteriaceae phenome contains five categories and 20 subcategories of polyphasic phenotypes,and three categories and eight subcategories of functional phenotypes,all of which are complemen-tary to the existing data standards of microbial phenotypes.The phenomic data of Mycobacteriaceae strains were compiled by literature mining,third-party database integration,and bioinformatics annotation.The phenotypes were searchable and comparable from the website of the Mycobacteriaceae Phenome Atlas(MPA,https://www.biosi no.org/mpa/).A topological data analysis of MPA revealed the co-evolution between Mycobacterium tuberculosis and virulence factors,and uncovered potential pathogenicity-associated phenotypes.Two hundred and sixty potential pathogen-enriched pathways were found by Fisher's exact test.The application of MPA may provide novel insights into the pathogenicity mechanism and antimicrobial targets of Mycobacteriaceae.
文摘The spin echo (SE) phenomenon discovered in the pulse nuclear magnetic resonance (PNMR) exerts significant influence on the field of magnetic resonance. It was first reported by E. L. Hahn in 1950. The discovery of SE provided a new method for a better understanding of NMR phenomenon. For example, it solved the difficul-
基金This work is supported by National Science Foundation Awards MCB-1838307 and OIA-1826781 to J.C.S.In additionwe received support from the Quantitative Life Sciences Initiative at the University of Nebraska-Lincoln+1 种基金which in turn received support from the University of Nebraska Program of ExcellenceThis work was completed utilizing the Holla nd Computi ng Center of the University of Nebraska,which receives support from the Nebraska Research Initiative.
文摘Linking natural genetic variation to trait variation can help determine the functional roles ofdifferent genes.Variations of one or several traits are often assessed separately.High-throughput phenotyping and data mining can capture dozens or hundreds of traits from the same individuals.Here,we test the association between markers within a gene and many traits simultaneously.This genome–phenome wide association study(GPWAS)is both a multi-marker and multi-trait test.Genes identified using GPWAS with 260 phenotypic traits in maize were enriched for genes independently linked to phenotypic variation.Traits associated with classical mutants were consistent with reported phenotypes for mutant alleles.Genes linked to phenomic variation in maize using GPWAS shared molecular,population genetic,and evolutionary features with classical mutants in maize.Genes linked to phenomic variation in Arabidopsis using GPWAS are significantly enriched in genes with known loss-of-function phenotypes.GPWAS may be an effective strategy to identify genes in which loss-of-function alleles produce mutant phenotypes.The shared signatures present in classical mutants and genes identified using GPWAS may be markers for genes with a role in specifying plant phenotypes generally or pleiotropy specifically.
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supported by the Ministry of Higher Education(MOHE)Malaysia through Fundamental Research Grant Scheme(FRGS)with project code:FRGS/1/2021/STG01/UCSI/01/.SX was funded by the National Natural Science Foundation of China(NSFC)grants 32030020 and 32288101funded by the NSFC grant 32270665.
文摘Evidence has shown that differential transcriptomic profiles among human populations from diverse ancestries,supporting the role of genetic architecture in regulating gene expression alongside environmental stimuli.Genetic variants that regulate gene expression,known as expression quantitative trait loci(eQTL),are primarily shaped by human migration history and evolutionary forces,likewise,regulation of gene expression in principle could have been influenced by these events.Therefore,a comprehensive understanding of how human evolution impacts eQTL offers important insights into how phenotypic diversity is shaped.Recent studies,however,suggest that eQTL is enriched in genes that are selectively constrained.Whether eQTL is minimally affected by selective pressures remains an open question and requires comprehensive investigations.In addition,such studies are primarily dominated by the major populations of European ancestry,leaving many marginalized populations underrepresented.These observations indicate there exists a fundamental knowledge gap in the role of genomics variation on phenotypic diversity,which potentially hinders precision medicine.This article aims to revisit the abundance of eQTL across diverse populations and provide an overview of their impact from the population and evolutionary genetics perspective,subsequently discuss their influence on phenomics,as well as challenges and opportunities in the applications to precision medicine.
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”.
基金supported by the STI2030-Major Projects(2021ZD0200900 to Y.G.Y.)"Light of West China" Program of the Chinese Academy of Sciences(xbzg-zdsys-202302 to Y.G.Y.)
文摘The tree shrew(Tupaia belangeri)has long been proposed as a suitable alternative to non-human primates(NHPs)in biomedical and laboratory research due to its close evolutionary relationship with primates.In recent years,significant advances have facilitated tree shrew studies,including the determination of the tree shrew genome,genetic manipulation using spermatogonial stem cells,viral vector-mediated gene delivery,and mapping of the tree shrew brain atlas.However,the limited availability of tree shrews globally remains a substantial challenge in the field.Additionally,determining the key questions best answered using tree shrews constitutes another difficulty.Tree shrew models have historically been used to study hepatitis B virus(HBV)and hepatitis C virus(HCV)infection,myopia,and psychosocial stress-induced depression,with more recent studies focusing on developing animal models for infectious and neurodegenerative diseases.Despite these efforts,the impact of tree shrew models has not yet matched that of rodent or NHP models in biomedical research.This review summarizes the prominent advancements in tree shrew research and reflects on the key biological questions addressed using this model.We emphasize that intensive dedication and robust international collaboration are essential for achieving breakthroughs in tree shrew studies.The use of tree shrews as a unique resource is expected to gain considerable attention with the application of advanced techniques and the development of viable animal models,meeting the increasing demands of life science and biomedical research.
基金supported by the National Key Research and Development Program of China(2016YFD0100101-18,2020YFD1000904-1-3)the National Natural Science Foundation of China(31601216,31770397)Fundamental Research Funds for the Central Universities(2662019QD053,2662020ZKPY017)。
文摘With the rapid development of genetic analysis techniques and crop population size,phenotyping has become the bottleneck restricting crop breeding.Breaking through this bottleneck will require phenomics,defined as the accurate,high-throughput acquisition and analysis of multi-dimensional phenotypes during crop growth at organism-wide levels,ranging from cells to organs,individual plants,plots,and fields.Here we offer an overview of crop phenomics research from technological and platform viewpoints at various scales,including microscopic,ground-based,and aerial phenotyping and phenotypic data analysis.We describe recent applications of high-throughput phenotyping platforms for abiotic/biotic stress and yield assessment.Finally,we discuss current challenges and offer perspectives on future phenomics research.
基金supported by the National Natural Science Foundation of China(32072980)Key Research and Development Projects in Tibet(XZ202001ZY0016N,XZ201902NB02,XZNKY-2019-C-053)。
文摘Fish morphological phenotypes are important resources in artificial breeding,functional gene mapping,and population-based studies in aquaculture and ecology.Traditional morphological measurement of phenotypes is rather expensive in terms of time and labor.More importantly,manual measurement is highly dependent on operational experience,which can lead to subjective phenotyping results.Here,we developed 3DPhenoFish software to extract fish morphological phenotypes from three-dimensional(3D)point cloud data.Algorithms for background elimination,coordinate normalization,image segmentation,key point recognition,and phenotype extraction were developed and integrated into an intuitive user interface.Furthermore,18 key points and traditional 2D morphological traits,along with 3D phenotypes,including area and volume,can be automatically obtained in a visualized manner.Intuitive fine-tuning of key points and customized definitions of phenotypes are also allowed in the software.Using 3DPhenoFish,we performed high-throughput phenotyping for four endemic Schizothoracinae species,including Schizopygopsis younghusbandi,Oxygymnocypris stewartii,Ptychobarbus dipogon,and Schizothorax oconnori.Results indicated that the morphological phenotypes from 3DPhenoFish exhibited high linear correlation(>0.94)with manual measurements and offered informative traits to discriminate samples of different species and even for different populations of the same species.In summary,we developed an efficient,accurate,and customizable tool,3DPhenoFish,to extract morphological phenotypes from point cloud data,which should help overcome traditional challenges in manual measurements.3DPhenoFish can be used for research on morphological phenotypes in fish,including functional gene mapping,artificial selection,and conservation studies.3DPhenoFish is an open-source software and can be downloaded for free at https://github.com/lyh24k/3DPhenoFish/tree/master.
基金The authors wish to thank Menachem Moshelion for useful discussions.This work is supported by National Natural Science Foundation(NSFC)of China(Grant No.31772299)NSFC-Israeli Science Foundation(ISF)joint project(Grant No.31861143044)National Program for Support of Top-Notch Young Professionals(to P.X.).
文摘Phenomics is a new branch of science that provides high-throughput quantification of plant and animal traits at systems level.The last decade has witnessed great successes in high-throughput phenotyping of numerous morphological traits,yet major challenges still exist in precise phenotyping of physiological traits such as transpiration and photosynthesis.Due to the highly dynamic nature of physiological traits in responses to the environment,appropriate selection criteria and efficient screening systems at the physiological level for abiotic stress tolerance have been largely absent in plants.In this review,the current status of phenomics techniques was briefly summarized in horticultural plants.Specifically,the emerging field of high-throughput physiology-based phenotyping,which is referred to as“physiolomics”,for drought stress responseswas highlighted.In addition to analyzing the advantages of physiology-based phenotyping overmorphology-based approaches,recent examples that applied high-throughput physiological phenotyping to model and non-model horticultural plants were revisited and discussed.Based on the collective findings,we propose that high-throughput,non-destructive,and automatic physiological assays can and should be used as routine methods for phenotyping stress response traits in horticultural plants.
