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At least 37 records · Page 2Linked to original sources
PubMed2006

A trial of phenome analysis using 4000 Ds-insertional mutants in gene-coding regions of Arabidopsis.

Mutant lines covering all Arabidopsis genes allow us to pursue systematic functional genomics. A comprehensive phenotype description, called a phenome, is highly sought after in the profiling of -omics data. We selected 4000 transposon-insertional lines with transposon insertions in their gene-coding regions, and systematically observed the visible phenotype of each line. For the first 3 weeks after germination, plants were grown on agar plates and the juvenile phenotypes were recorded. Then the plants were transferred to soil and their phenotypes were recorded at each growth stage. About 140 lines showed clear and reproducible visible phenotypes, including novel phenotypic mutants as well as previously reported ones. All descriptions of the mutants showing visible phenotypes were classified into eight primary categories (seedling, leaves, flowering and growth, stems, branching, flowers, siliques and seed yield) and 43 secondary categories of morphological phenotypes. Phenotypic images have been entered into a searchable database (http://rarge.gsc.riken.jp/phenome/). One example investigated through the use of plural alleles was a mutant of a novel gene related to glycerolipid biosynthesis, with a unique visible phenotype of sepal opening. Our results suggest that we can find more novel visible phenotypes and their corresponding genes, and that phenotypic mutants of gene knockouts are not exhausted yet. This study provides basic data on large-scale phenotyping of gene knockout lines in plants, and will contribute to the completion of an international effort to develop a phenome database of all the functional genes in Arabidopsis.

Arabidopsis↗
PubMed2006

BN phenome: detailed characterization of the cardiovascular, renal, and pulmonary systems of the sequenced rat.

The postgenome era has provided resources to link disease phenotypes to the genomic sequence, i.e., creating a disease "phenome." Our detailed characterization of the sequenced BN rat strain (BN/NHsdMcwi) provides the first concerted effort in creating a direct link between a sequenced genome and its resulting biology. For the BN sequence to be of broad value to investigators, these measures need to be put into the context of the spectrum of the laboratory rats, so that their physiology can be benchmarked against the sequenced BN. As a major step in generating a comprehensive cardiovascular and pulmonary disease phenome, we measured 281 traits related to diseases of the heart, lung, and blood (http://pga.mcw.edu) in the sequenced BN. We compared these data with those of the same traits measured across multiple genetic backgrounds, both genders, and differing environments. We show that no single strain, inbred or outbred, can be considered a physiological control strain; what is normal depends on what trait is being measured and the strains' genome backgrounds. We find vast differences between the genders, also dependent on genome background. By combining the values across all strains studied, we generated a "population" mean and normal range of values for each of these traits, which are more genetically representative than the measured values in any single inbred or outbred strain. These data provide a baseline for physiological comparison of traits related to cardiovascular, lung, blood, and renal function in the sequenced BN rats relative to the major strains of rats studied in biomedical research.

Animals↗
PubMed2023

Next-generation phenotyping: introducing phecodeX for enhanced discovery research in medical phenomics.

MOTIVATION: Phecodes are widely used and easily adapted phenotypes based on International Classification of Diseases codes. The current version of phecodes (v1.2) was designed primarily to study common/complex diseases diagnosed in adults; however, there are numerous limitations in the codes and their structure. RESULTS: Here, we present phecodeX, an expanded version of phecodes with a revised structure and 1,761 new codes. PhecodeX adds granularity to phenotypes in key disease domains that are under-represented in the current phecode structure-including infectious disease, pregnancy, congenital anomalies, and neonatology-and is a more robust representation of the medical phenome for global use in discovery research. AVAILABILITY AND IMPLEMENTATION: phecodeX is available at https://github.com/PheWAS/phecodeX.

Phenomics↗
PubMed2026

SAIGE-GPU: accelerating genome- and phenome-wide association studies using GPUs.

MOTIVATION: Genome-wide association studies (GWAS) at biobank scale are computationally intensive, especially for admixed populations requiring robust statistical models. SAIGE is a widely used method for generalized linear mixed-model GWAS but is limited by its CPU-based implementation, making phenome-wide association studies impractical for many research groups. RESULTS: We developed SAIGE-GPU, a GPU-accelerated version of SAIGE that replaces CPU-intensive matrix operations with GPU-optimized kernels. The core innovation is distributing genetic relationship matrix calculations across GPUs and communication layers. Applied to 2068 phenotypes from 635 969 participants in the Million Veteran Program, including diverse and admixed populations, SAIGE-GPU achieved a 5-fold speedup in mixed model fitting on supercomputing infrastructure and cloud platforms. We further optimized the variant association testing step through multi-core and multi-trait parallelization. Deployed on Google Cloud Platform and Azure, the method provided substantial cost and time savings. AVAILABILITY AND IMPLEMENTATION: Source code and binaries are available for download at https://github.com/saigegit/SAIGE/tree/SAIGE-GPU-1.3.3. A code snapshot is archived at Zenodo for reproducibility (DOI: [10.5281/zenodo.17642591]). SAIGE-GPU is available in a containerized format for use across HPC and cloud environments and is implemented in R/C++ and runs on Linux systems.

Genome-Wide Association Study↗
PubMed2026

Aerobic Fitness and Health-Related Phenotypes: A Two-Stage Phenome-Wide Mendelian Randomization Study.

PURPOSE: We investigated potentially causal associations between genetically predicted aerobic fitness and multiple health phenotypes using a two-stage phenome-wide Mendelian randomization (MR) study. METHODS: Genetically determined aerobic fitness, as operationalized by Cai et al., served as the exposure instrument. We screened 712 health-related phenotypes as outcomes using publicly available European-ancestry genome-wide association studies (GWAS) summary statistics from OpenGWAS (Discovery GWAS n > 5000), prioritizing non-UK Biobank/non-FinnGen datasets for Discovery when available and selecting an independent GWAS for validation. Associations were estimated using the MR-Robust Adjusted Profile Score method, controlled for multiple testing (5% false discovery rate) and unaffected by violations of MR assumptions (directional concordance between discovery and validation; no evidence of horizontal pleiotropy across inverse-variance weighted, MR-Egger, weighted-median, and weighted-mode methods; negative control analysis on hair color). RESULTS: We identified 108 discovery associations, of which 34 remained valid and statistically significant after validation. Higher genetically determined aerobic fitness was associated with lower lacunar stroke risk, lower arterial stiffness, higher heart rate variability, lower diastolic blood pressure, more favorable anthropometric measures, lower use of antidiabetic drugs, lower asthma risk, lower C-reactive protein, higher bone mineral density, favorable liver function biomarkers, favorable platelet-related traits, multiple blood count-derived hematological cell indices and counts, as well as higher years of schooling. Adverse associations were confined to atrial fibrillation, valvular heart disease, and systolic blood pressure. CONCLUSIONS: Genetically determined aerobic fitness is linked to a broad pattern of favorable cardiometabolic, inflammatory, musculoskeletal, respiratory, hepatic, and hematological phenotypes, alongside a narrow set of potential cardiovascular hazards.

Humans↗
PubMed2025

Phenomics-Based Discovery of Novel Orthosteric Choline Kinase Inhibitors.

Choline kinase alpha (CHKA) is a central mediator of cell metabolism linked to cancer and immune regulation. Cellular and clinical evaluation of CHKA has been hampered by challenges in the development of drug-like choline kinase inhibitors. Here, we identify CHKA as an unexpected off-target of histone methyltransferase inhibitors using an integrated phenomic approach. We confirm CHKA as a direct protein target of the aminoquinazolines UNC0638 and UNC0737 using a combination of chemoproteomic, biochemical, cellular, and metabolic profiling assays, possibly explaining the previously reported discrepancies observed for different G9a/GLP inhibitor scaffolds in cellular assays. Using primary human cell model systems, we discover that CHKA modulation impairs IgG secretion and B-cell maturation consistent with the notion that choline metabolism plays an important role in immune signalling. Co-crystal structures of UNC0638 and UNC0737 with CHKA unravel an unexpected binding mode and suggest the inhibitors as attractive starting points for the development of selective chemical tools to further explore the biological role of CHKA in cancer and immune metabolism.

Humans↗
PubMed1997

What exactly are genomes, genotypes and phenotypes? And what about phenomes?

The fundamental concepts of genome, genotype and phenotype are not defined in a satisfactory manner within the biological literature. Not only are there inconsistencies in usage between various authors, but even individual authors do not use these concepts in a consistent manner within their own writings. We have found at least five different notions of genome, seven of genotype, and five of phenotype current in the literature. Our goal is to clarify this situation by (a) defining clearly and precisely the notions of genetic complement, genome, genotype, phenetic complement, and phenotype; (b) examining that of phenome; and (c) analysing the logical structure of this family of concepts.

Animals↗
PubMed2005

Focusing on genomic and phenomic correlations in respiration of non-melanotic skin cancers.

In recent years, with the development of techniques in modem molecular biology, it has become possible to study the genetic basis of carcinogenesis down to the level of DNA sequence. Major advances have been made in our understanding of the genes involved in cell cycle control and descriptions of mutations in those genes. These developments have led to the definition of the role of specific oncogenes and tumour suppressor genes in several cancers, including, for example, colon cancers and some forms of breast cancer. Work reported from our laboratory has led to the identification of a number of candidate genes involved in the development of non-melanotic skin cancers. In this chapter, we attempt to further explain the observed (phenomic) alterations in metabolic pathways associated with oxygen consumption with the changes at the genetic level.

Base Sequence↗
PubMed2026

Systemic Comorbidities of Keloid and Hypertrophic Scars: A Phenome-Wide Association Study in a Multiethnic U.S. Pediatric Cohort.

BACKGROUND: Excessive scarring (ES), including keloids and hypertrophic scars, impairs function, appearance, and quality of life in children. Its pediatric comorbidity spectrum is not well defined, limiting anticipatory guidance and multidisciplinary care. This research aims to investigate comorbidities of ES in a diverse pediatric cohort using a phenome-wide association study (PheWAS). METHODS: This population-based study leveraged longitudinal electronic health record (EHR) data from participants enrolled in the Children's Hospital of Philadelphia (CHOP) from 2006. Diagnosis codes (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] and Tenth Revision [ICD-10-CM]) were mapped to 3109 phenotype codes (PheCodes). PheWAS analyses were conducted using logistic regression, with Bonferroni correction applied to account for multiple testing. RESULTS: Among 86,092 pediatric participants, 662 (0.77%) were identified with ES; the remaining served as controls. Multivariable PheWAS screening identified 154 significant associations across 16 disease categories, of which 105 were not reported previously to our knowledge. Dermatologic phenotypes (n = 28; 18%) were most enriched, including acne and other follicular disorders, eczema, pigmentary changes, papulosquamous and granulomatous disorders, and cutaneous infections. Respiratory phenotypes (n = 21; 14%) included respiratory failure, pneumonia, asthma, allergic rhinitis, pharyngitis, and tonsillar hypertrophy. Sense organ disorders (n = 19; 12%) comprised conjunctivitis, refractive errors, otitis, and hearing impairment. Infection-related phenotypes (n = 14; 9%) highlighted susceptibility to viral (influenza, human papillomavirus [HPV], molluscum contagiosum), fungal (candidiasis, dermatophytosis), and bacterial infections. CONCLUSIONS: These findings suggest that ES in children indicates not only localized wound-healing impairment, but also systemic immune, developmental, and proliferative dysregulations, emphasizing the need for genetic and mechanistic studies to clarify causal pathways and multidisciplinary surveillance beyond dermatologic care.

Humans↗
PubMed2005

RNAi as a tool to study cell biology: building the genome-phenome bridge.

In the few short years since its discovery, RNA interference (RNAi) has revolutionized the functional analysis of genomes: both technical and conceptual approaches to the investigation of gene function are being transformed as a result of this new technology. Genome-scale RNAi analyses have already been performed in the model organisms Caenorhabditis elegans (in vivo) and Drosophila melanogaster (in cell lines), ushering in a new era of RNAi-based approaches to probing the inner workings of the cell. The transformation of complex phenotypic data into mineable 'digitized' formats is fostering the emergence of a new area of bioinformatics related to the phenome.

Animals↗
PubMed2005

Dose-response effects of ectopic agouti protein on iron overload and age-associated aspects of the Avy/a obese mouse phenome.

Isogenic and congenic offspring from matings of inbred black a/a dams by sibling (or non-sibling from another inbred strain) yellow agouti Avy/a sires provide an animal model of obese yellow agouti Avy/a and isogenic lean pseudoagouti Avy/a mice exhibiting two different in vivo concentrations (high, very low) of ectopic agouti protein (ASP) with congenic lean black a/a mice as null controls. This makes it possible to differentiate between the high and very low dose levels of ectopic ASP with respect to interactions with diverse physiological and molecular pathways. Assay of differential responses to 12 or 24 months of carbonyl iron overload assessed the possible suitability of this animal model for the study of hemochromatosis. Agouti A/a B6C3F1 mice were used as non-congenic null controls. The age-related waxing and waning of body weight, food consumption, and caloric efficiency, as well as associated changes in pancreatic islets and islet cells, and formation of liver tumors were assayed. While the hypothesis that these mice might serve as a tool for investigating hemochromatosis was not confirmed, the data did provide evidence that even the very low levels of ASP in pseudoagouti Avy/a mice affect the network of molecular/metabolic/physiological response pathways that comprises the yellow agouti obese phenome. We suggest that the combination of yellow agouti Avy/a, pseudoagouti Avy/a, and black a/a congenic mice provides a practical tool for applying a dose-response systems biology approach to understanding the dysregulatory influence of ectopic ASP on the molecular-physiological matrix of the organism.

Aging↗
PubMed2004

Phenomics, lipodystrophy, and the metabolic syndrome.

The metabolic syndrome (MetS) is a common multiplex cluster of phenotypes strongly related to cardiovascular disease that includes central obesity with hypertension, dyslipidemia, and type 2 diabetes. The core molecular defect of the MetS is insulin resistance; indeed, the terms "MetS" and "insulin resistance syndrome" often are used interchangeably. The successful translation to clinical medicine of molecular genetic research on other rare monogenic metabolic disorders has stimulated the evaluation of such rare monogenic forms of insulin resistance as partial lipodystrophy resulting from mutations in either LMNA or PPARG genes. Careful phenotypic evaluation of carriers of monogenic insulin resistance using a range of diagnostic methods--an approach sometimes called "phenomics"--may help to find early presymptomatic biomarkers of cardiovascular disease, which, in turn, may uncover new pathways and targets for interventions for the common MetS, diabetes, and atherosclerosis.

Genetic Markers↗
PubMed2002

Phenomics: fiction or the future?

The ease with which genetic mutations can be induced in or introduced into mammalian organisms, such as the mouse, has created a significant need for phenotypic analysis. Developments in computer technology, instrumentation and bioinformatics, as well as in numerous neuroscience disciplines, will help to meet the demands set by the molecular revolution. As a result, the field of 'phenomics' is being born. This will integrate multidisciplinary research, with the goal of understanding the complex phenotypic consequences of genetic mutations at the level of the organism. This paper focuses on one of the disciplines that show promising developments, behavioral science.

Animals↗
PubMed2002

Finding genes for bipolar disorder in the functional genomics era: from convergent functional genomics to phenomics and back.

Psychiatric genetics, while promising to unravel the mechanisms of psychiatric disorders, has proven to be a challenging field. Psychiatric disorders, like other common genetic traits, are complex and heterogeneous. Psychiatric genetics has also suffered from a lack of quantifiable, biology-based phenotypes. However, the field is currently at an opportune moment. The work of various investigators is on the verge of paying rich dividends. Efforts at positional cloning are being greatly accelerated by the fruits of the Human Genome Project. New tools of functional genomics, such as expression profiling and proteomics, are being applied to animal models. These two methods can complement each other in an approach we have termed convergent functional genomics. Lastly, improvements in the measurement of biologically distinct endophenotypes--or phenomic--will lead to a better understanding of the mapping of genes to phenotypes in both animal and human systems.

Journal Article↗
PubMedDate not supplied

Toward metabolic phenomics: analysis of genomic data using flux balances.

Small genome sequencing and annotations are leading to the definition of metabolic genotypes in an increasing number of organisms. Proteomics is beginning to give insights into the use of the metabolic genotype under given growth conditions. These data sets give the basis for systemically studying the genotype-phenotype relationship. Methods of systems science need to be employed to analyze, interpret, and predict this complex relationship. These endeavors will lead to the development of a new field, tentatively named phenomics. This article illustrates how the metabolic characteristics of annotated small genomes can be analyzed using flux balance analysis (FBA). A general algorithm for the formulation of in silico metabolic genotypes is described. Illustrative analyses of the in silico Escherichia coli K-12 metabolic genotypes are used to show how FBA can be used to study the capabilities of this strain.

Biotechnology↗
PubMed2006

Creation and implications of a phenome-genome network.

Although gene and protein measurements are increasing in quantity and comprehensiveness, they do not characterize a sample's entire phenotype in an environmental or experimental context. Here we comprehensively consider associations between components of phenotype, genotype and environment to identify genes that may govern phenotype and responses to the environment. Context from the annotations of gene expression data sets in the Gene Expression Omnibus is represented using the Unified Medical Language System, a compendium of biomedical vocabularies with nearly 1-million concepts. After showing how data sets can be clustered by annotative concepts, we find a network of relations between phenotypic, disease, environmental and experimental contexts as well as genes with differential expression associated with these concepts. We identify novel genes related to concepts such as aging. Comprehensively identifying genes related to phenotype and environment is a step toward the Human Phenome Project.

Aging↗
PubMed2006

Moving forward in reverse: genetic technologies to enable genome-wide phenomic screens in Arabidopsis.

Genome sequencing, in combination with various computational and empirical approaches to sequence annotation, has made possible the identification of more than 30,000 genes in Arabidopsis thaliana. Increasingly sophisticated genetic tools are being developed with the long-term goal of understanding how the coordinated activity of these genes gives rise to a complex organism. The combination of classical forward genetics with recently developed genome-wide, gene-indexed mutant collections is beginning to revolutionize the way in which gene functions are studied in plants. High-throughput screens using these mutant populations should provide a means to analyse plant gene functions--the phenome--on a genomic scale.

Arabidopsis↗
PubMed2005

RARGE: a large-scale database of RIKEN Arabidopsis resources ranging from transcriptome to phenome.

The RIKEN Arabidopsis Genome Encyclopedia (RARGE) database houses information on biological resources ranging from transcriptome to phenome, including RIKEN Arabidopsis full-length (RAFL) complementary DNAs (cDNAs), their promoter regions, Dissociation (Ds) transposon-tagged lines and expression data from microarray experiments. RARGE provides tools for searching by resource code, sequence homology or keyword, and rapid access to detailed information on the resources. We have isolated 245 946 RAFL cDNA clones and collected 11 933 transposon-tagged lines, which are available from the RIKEN Bioresource Center and are stored in RARGE. The RARGE web interface can be accessed at http://rarge.gsc.riken.jp/. Additionally, we report 90 000 new RAFL cDNA clones here.

Arabidopsis↗