Pharmacophenomics and Fangjiomics:new pharmacological research paradigm in era of precision medicine

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.

Modern phenomics to empower holistic crop science, agronomy, and breeding research

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.

Crop Phenomics and High-Throughput Phenotyping:Past Decades,Current Challenges,and Future Perspectives

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.

Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives

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.

Chinese Medicine Phenomics(Chinmedphenomics):Personalized,Precise and Promising

The systematicness of phenomics and Traditional Chinese Medicine(TCM)enable these two disciplines to interlink with each other.This article discussed the similarity in theory and application between TCM and phenomics and illustrates their respective advantages in diagnosis and treatment of diseases,forming a new discipline eventually.Chinese medicine phe-nomics(Chinmedphenomics)is built on classic TCM,combined with phenomics technology,and the development of which needs the mega cohort with TCM syndrome and the characteristics of precision medicine as well as multi-disciplinary coop-eration,which is personalized,precise and promising,providing unique scientific insights into understanding human health.

Study of tree shrew biology and models: A booming and prosperous field for biomedical research

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.

The indigenous populations as the model by nature to understand human genomic-phenomics interactions

Background:The advancement of genomics has progressed in lightning speed over the past two decades.Numerous large-scale genome sequencing initiatives were announced,along with the rise of the holistic precision medicine approach.However,the field of genomic medicine has now come to a bottleneck since genomic-phenomic interactions are not fully comprehended due to the complexity of the human systems biology and environmental influence,hence the emergence of human phenomics.Results:This review attempts to provide an overview of the potential advantages of investigating the human phenomics of indigenous populations and the challenges ahead.Conclusion:We believe that the indigenous populations serve as an ideal model to excavate our understanding of genomic-environmental-phenomics interactions.

Mapping Cell Phenomics with Multiparametric Flow Cytometry Assays

Phenomics explores the complex interactions among genes,epigenetics,symbiotic microorganisms,diet,and environmental exposure based on the physical,chemical,and biological characteristics of individuals and groups.Increasingly efficient and comprehensive phenotyping techniques have been integrated into modern phenomics-related research.Multicolor flow cytometry technology provides more measurement parameters than conventional flow cytometry.Based on detailed descriptions of cell phenotypes,rare cell populations and cell subsets can be distinguished,new cell phenotypes can be discovered,and cell apoptosis characteristics can be detected,which will expand the potential of cell phenomics research.Based on the enhancements in multicolor flow cytometry hardware,software,reagents,and method design,the present review summarizes the recent advances and applications of multicolor flow cytometry in cell phenomics,illuminating the potential of applying phenomics in future studies.

High-throughput phenotyping: Breaking through the bottleneck in future crop breeding

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.

High-Throughput physiology-based stress response phenotyping:Advantages,applications and prospective in horticultural plants

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.

3DPhenoFish:Application for two-and three-dimensional fish morphological phenotype extraction from point cloud analysis

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.

Women's experiences of formula feeding their infants:an interpretative phenomenological study

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.

Diabetes mellitus susceptibility with varied diseased phenotypes and its comparison with phenome interactome networks

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.

Integration of high-throughput phenotyping,GWAS,and predictive models reveals the genetic architecture of plant height in maize

Plant height(PH)is an essential trait in maize(Zea mays)that is tightly associated with planting density,biomass,lodging resistance,and grain yield in the field.Dissecting the dynamics of maize plant architecture will be beneficial for ideotype-based maize breeding and prediction,as the genetic basis controlling PH in maize remains largely unknown.In this study,we developed an automated high-throughput phenotyping platform(HTP)to systematically and noninvasively quantify 77 image-based traits(i-traits)and 20 field traits(f-traits)for 228 maize inbred lines across all developmental stages.Time-resolved i-traits with novel digital phenotypes and complex correlations with agronomic traits were characterized to reveal the dynamics of maize growth.An i-trait-based genome-wide association study identified 4945 traitassociated SNPs,2603 genetic loci,and 1974 corresponding candidate genes.We found that rapid growth of maize plants occurs mainly at two developmental stages,stage 2(S2)to S3 and S5 to S6,accounting for the final PH indicators.By integrating the PH-association network with the transcriptome profiles of specific internodes,we revealed 13 hub genes that may play vital roles during rapid growth.The candidate genes and novel i-traits identified at multiple growth stages may be used as potential indicators for final PH in maize.One candidate gene,ZmVATE,was functionally validated and shown to regulate PH-related traits in maize using genetic mutation.Furthermore,machine learning was used to build predictive models for final PH based on i-traits,and their performancewas assessed across developmental stages.Moderate,strong,and very strong correlations between predictions and experimental datasets were achieved from the early S4(tenth-leaf)stage.Colletively,our study provides a valuable tool for dissecting the spatiotemporal formation of specific internodes and the genetic architecture of PH,as well as resources and predictive models that are useful for molecular design breeding and predicting maize varieties with ideal plant architectures.

Phenomic Studies on Diseases:Potential and Challenges

The rapid development of such research field as multi-omics and artificial intelligence(AI)has made it possible to acquire and analyze the multi-dimensional big data of human phenomes.Increasing evidence has indicated that phenomics can pro-vide a revolutionary strategy and approach for discovering new risk factors,diagnostic biomarkers and precision therapies of diseases,which holds profound advantages over conventional approaches for realizing precision medicine:first,the big data of patients'phenomes can provide remarkably richer information than that of the genomes;second,phenomic studies on diseases may expose the correlations among cross-scale and multi-dimensional phenomic parameters as well as the mecha-nisms underlying the correlations;and third,phenomics-based studies are big data-driven studies,which can significantly enhance the possibility and efficiency for generating novel discoveries.However,phenomic studies on human diseases are still in early developmental stage,which are facing multiple major challenges and tasks:first,there is significant deficiency in analytical and modeling approaches for analyzing the multi-dimensional data of human phenomes;second,it is crucial to establish universal standards for acquirement and management of phenomic data of patients;third,new methods and devices for acquirement of phenomic data of patients under clinical settings should be developed;fourth,it is of significance to establish the regulatory and ethical guidelines for phenomic studies on diseases;and fifth,it is important to develop effective international cooperation.It is expected that phenomic studies on diseases would profoundly and comprehensively enhance our capacity in prevention,diagnosis and treatment of diseases.

Phenomic Imaging

Human phenomics is defned as the comprehensive collection of observable phenotypes and characteristics infuenced by a complex interplay among factors at multiple scales.These factors include genes,epigenetics at the microscopic level,organs,microbiome at the mesoscopic level,and diet and environmental exposures at the macroscopic level.“Phenomic imaging”utilizes various imaging techniques to visualize and measure anatomical structures,biological functions,metabolic processes,and biochemical activities across diferent scales,both in vivo and ex vivo.Unlike conventional medical imaging focused on disease diagnosis,phenomic imaging captures both normal and abnormal traits,facilitating detailed correlations between macro-and micro-phenotypes.This approach plays a crucial role in deciphering phenomes.This review provides an overview of diferent phenomic imaging modalities and their applications in human phenomics.Additionally,it explores the associations between phenomic imaging and other omics disciplines,including genomics,transcriptomics,proteomics,immunomics,and metabolomics.By integrating phenomic imaging with other omics data,such as genomics and metabolomics,a comprehensive understanding of biological systems can be achieved.This integration paves the way for the development of new therapeutic approaches and diagnostic tools.

Single cell metabolic phenome and genome via the ramanome technology platform:Precision medicine of infectious diseases at the ultimate precision?

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.

Protocol for Brain Magnetic Resonance Imaging and Extraction of Imaging‑Derived Phenotypes from the China Phenobank Project

Imaging-derived phenotypes(IDPs)have been increasingly used in population-based cohort studies in recent years.As widely reported,magnetic resonance imaging(MRI)is an important imaging modality for assessing the anatomical structure and function of the brain with high resolution and excellent soft-tissue contrast.The purpose of this article was to describe the imaging protocol of the brain MRI in the China Phenobank Project(CHPP).Each participant underwent a 30-min brain MRI scan as part of a 2-h whole-body imaging protocol in CHPP.The brain imaging sequences included T1-magnetization that prepared rapid gradient echo,T2 fuid-attenuated inversion-recovery,magnetic resonance angiography,difusion MRI,and resting-state functional MRI.The detailed descriptions of image acquisition,interpretation,and post-processing were provided in this article.The measured IDPs included volumes of brain subregions,cerebral vessel geometrical parameters,microstructural tracts,and function connectivity metrics.

Mycobacteriaceae Phenome Atlas(MPA):A Standardized Atlas for the Mycobacteriaceae Phenome Based on Heterogeneous Sources

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.

High‑Resolution and Multidimensional Phenotypes Can Complement Genomics Data to Diagnose Diseases in the Neonatal Population

Advances in genomic medicine have greatly improved our understanding of human diseases.However,phenome is not well understood.High-resolution and multidimensional phenotypes have shed light on the mechanisms underlying neonatal diseases in greater details and have the potential to optimize clinical strategies.In this review,we first highlight the value of analyzing traditional phenotypes using a data science approach in the neonatal population.We then discuss recent research on high-resolution,multidimensional,and structured phenotypes in neonatal critical diseases.Finally,we briefly introduce current technologies available for the analysis of multidimensional data and the value that can be provided by integrating these data into clinical practice.In summary,a time series of multidimensional phenome can improve our understanding of disease mechanisms and diagnostic decision-making,stratify patients,and provide clinicians with optimized strategies for therapeutic intervention;however,the available technologies for collecting multidimensional data and the best platform for connecting multiple modalities should be considered.