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PubMed2005

The Rat Genome Database (RGD): developments towards a phenome database.

The Rat Genome Database (RGD) (http://rgd.mcw.edu) aims to meet the needs of its community by providing genetic and genomic infrastructure while also annotating the strengths of rat research: biochemistry, nutrition, pharmacology and physiology. Here, we report on RGD's development towards creating a phenome database. Recent developments can be categorized into three groups. (i) Improved data collection and integration to match increased volume and biological scope of research. (ii) Knowledge representation augmented by the implementation of a new ontology and annotation system. (iii) The addition of quantitative trait loci data, from rat, mouse and human to our advanced comparative genomics tools, as well as the creation of new, and enhancement of existing, tools to enable users to efficiently browse and survey research data. The emphasis is on helping researchers find genes responsible for disease through the use of rat models. These improvements, combined with the genomic sequence of the rat, have led to a successful year at RGD with over two million page accesses that represent an over 4-fold increase in a year. Future plans call for increased annotation of biological information on the rat elucidated through its use as a model for human pathobiology. The continued development of toolsets will facilitate integration of these data into the context of rat genomic sequence, as well as allow comparisons of biological and genomic data with the human genomic sequence and of an increasing number of organisms.

Animals↗
PubMed2005

PROPHECY--a database for high-resolution phenomics.

The rapid recent evolution of the field phenomics--the genome-wide study of gene dispensability by quantitative analysis of phenotypes--has resulted in an increasing demand for new data analysis and visualization tools. Following the introduction of a novel approach for precise, genome-wide quantification of gene dispensability in Saccharomyces cerevisiae we here announce a public resource for mining, filtering and visualizing phenotypic data--the PROPHECY database. PROPHECY is designed to allow easy and flexible access to physiologically relevant quantitative data for the growth behaviour of mutant strains in the yeast deletion collection during conditions of environmental challenges. PROPHECY is publicly accessible at http://prophecy.lundberg.gu.se.

Computer Graphics↗
PubMed2006

Mouse Phenome Database (MPD).

The Mouse Phenome Database (MPD; http://www.jax.org/phenome) is a repository of phenotypic and genotypic data on commonly used and genetically diverse inbred strains of mice. Strain characteristics data are contributed by members of the scientific community. Electronic access to centralized strain data enables biomedical researchers to choose appropriate strains for many systems-based research applications, including physiological studies, drug and toxicology testing and modeling disease processes. MPD provides a community data repository and a platform for data analysis and in silico hypothesis testing. The laboratory mouse is a premier genetic model for understanding human biology and pathology; MPD facilitates research that uses the mouse to identify and determine the function of genes participating in normal and disease pathways.

Animals↗
PubMed2025

Genetic liability to meniscus degeneration and its comorbidity patterns: a phenome-wide association study in the UK Biobank.

Meniscus degeneration is a common knee pathology causing pain, disability, and osteoarthritis. While mechanical factors are established, the contribution of inherited genetic liability to its systemic disease patterns remains unclear. We applied a polygenic risk score (PRS) for meniscus degeneration, derived from FinnGen genome-wide association study (GWAS) results to 323,999 UK Biobank participants and conducted a phenome-wide association study (PRS-PheWAS) across 962 clinical phenotypes. The PRS-PheWAS revealed significant associations beyond musculoskeletal traits, extending to metabolic, cardiovascular, psychiatric, and gastrointestinal domains, indicating broad shared genetic architecture. To support these findings, linkage disequilibrium score regression confirmed strong genetic correlations with osteoarthritis and related arthropathies, and genotype-tissue expression (GTEx) analysis highlighted tissue-specific expression of lead genes (e.g., GDF5, SOX5, BMP6) in connective and metabolic tissues. The results demonstrate that genetic liability to meniscus degeneration extends beyond the knee, sharing pathways with systemic conditions. This systemic genetic architecture underscores the need for integrative management approaches that combine orthopedic care with metabolic and lifestyle interventions.

Journal Article↗
PubMed2004

Toward improving Caenorhabditis elegans phenome mapping with an ORFeome-based RNAi library.

The recently completed Caenorhabditis elegans genome sequence allows application of high-throughput (HT) approaches for phenotypic analyses using RNA interference (RNAi). As large phenotypic data sets become available, "phenoclustering" strategies can be used to begin understanding the complex molecular networks involved in development and other biological processes. The current HT-RNAi resources represent a great asset for phenotypic profiling but are limited by lack of flexibility. For instance, existing resources do not take advantage of the latest improvements in RNAi technology, such as inducible hairpin RNAi. Here we show that a C. elegans ORFeome resource, generated with the Gateway cloning system, can be used as a starting point to generate alternative HT-RNAi resources with enhanced flexibility. The versatility inherent to the Gateway system suggests that additional HT-RNAi libraries can now be readily generated to perform gene knockdowns under various conditions, increasing the possibilities for phenome mapping in C. elegans.

Animals↗
PubMed2005

The search for genenotype/phenotype associations and the phenome scan.

All the approaches to the search for genotype/phenotype associations have their share of problems. Comparing the genome scan and candidate gene approaches, the former makes fewer assumptions at the genetic level or about mechanism but has greater statistical difficulties while the latter partially solves the statistical problem but makes more assumptions at both genetic and mechanistic levels. Among current difficulties is a lack of information about the nature of gene variant/phenotype associations: the frequency with which different classes of gene or sequence are involved; the type of genetic variation most commonly involved; the appropriate genetic models to apply to analysis. The overarching problem is that of multiple testing, one solution to which is to integrate genetic information to create a smaller number of compound variables. At the other end of the scale, decisions about the level of complexity at which to pitch the identification of phenotypes also affect the multiple testing problem: whether to pitch them at the level of disease outcomes, or at any of the multiple levels of intermediate phenotypes or traits. The third issue is how best to deal with gene/gene or gene/environment interactions, or whether to ignore them. Only as more genotype/phenotype associations emerge, by whatever means, will the numbers of results allow these questions to be answered. We describe here a new approach to genotype/phenotype association studies, the phenome scan, in which dense phenotypic information in human cohorts is scanned for associations with individual genetic variants. We believe that this approach can generate data that will be useful in answering generic questions about genotype/phenotype associations as well as in discovering novel ones.

Environmental Exposure↗
PubMed2026

High-variance phenome database reveals important roles of WD40 proteins in the plant pathogenic fungus Fusarium graminearum.

WD40 is a highly conserved protein domain in eukaryotes that functions as a versatile platform for protein-protein interactions and participates in diverse biological processes. We performed a genome-wide functional analysis of WD40 domain-containing proteins in Fusarium graminearum, a phytopathogenic fungus that causes severe yield losses and mycotoxin contamination in major cereal crops. Comprehensive phenotypic profiling of 119 WD40 gene deletion mutants across 22 phenotypic traits established a systematic WD40 phenome dataset, revealing the broad functional involvement of WD40 proteins and a strong correlation between sexual reproduction and virulence. Protein interaction analyses of selected WD40 proteins revealed diverse WD40-mediated interaction patterns and provided further insights into WD40-mediated protein interactions and their roles in protein complex formation. This study provides a foundation for further characterization of WD40 proteins in filamentous fungi.

Fusarium graminearum↗
PubMed1959

Direct experimental observation of cells in phenomic lag.

By employing cells mutating at a very high spontaneous rate and a grid plate containing a medium totally selective against mutant cells, direct microscopic observation was made of mutant cells of recent origin passing through a limited number of phenomic lag divisions.

Cell Division↗
PubMed2005

Rat Phenome Project: the untapped potential of existing rat strains.

The National Bio Resource Project for the Rat in Japan collects, preserves, and distributes rat strains. More than 250 inbred strains have been deposited thus far into the National Bio Resource Project for the Rat and are maintained as specific pathogen-free rats or cryopreserved embryos. We are now comprehensively characterizing deposited strains as part of the Rat Phenome Project to reevaluate their value as models of human diseases. Phenotypic data are being collected for 7 categories and 109 parameters: functional observational battery (neurobehavior), behavior studies, blood pressure, biochemical blood tests, hematology, urology, and anatomy. Furthermore, genotypes are being determined for 370 simple sequence-length polymorphism markers distributed through the whole rat genome. Here, we report these large-scale, high-throughput screening data that have already been collected for 54 rat strains. This comprehensive, original phenotypic data can be systematically viewed by "strain ranking" for each parameter. This allows investigators to explore the relationship between several rat strains, to identify new rat models, and to select the most suitable strains for specific experiments. The discovery of several potential models for human diseases, such as hypertension, hypotension, renal diseases, hyperlipemia, hematological disorders, and neurological disorders, illustrates the potential of many existing rat strains. All deposited strains and obtained data are freely available for any interested researcher worldwide at http://www.anim.med.kyoto-u.ac.jp/nbr.

Animals↗
PubMed2025

Study research protocol for Phenome India-CSIR Health Cohort Knowledgebase: A prospective multi-modal follow-up study on a nationwide employee cohort.

Predicting individual health trajectories based on risk scores can help formulate effective preventive strategies for diseases and their complications. Currently, most risk prediction algorithms rely on epidemiological data from the Caucasian population, which often do not translate well to the Indian population due to ethnic diversity, differing dietary and lifestyle habits, and unique risk profiles. In this multi-center prospective longitudinal study conducted across India, we aim to address these challenges by developing clinically relevant risk prediction scores for cardio-metabolic diseases specifically tailored to the Indian population. India, which accounts for nearly 18% of the global population, also has a significant diaspora worldwide. This program targets longitudinal collection and bio-banking of samples from over 10 000 employees both working and retirees of the Council of Scientific and Industrial Research and their spouses, with baseline sample collection already completed. During the baseline collection, we gathered multi-parametric data including clinical questionnaires, lifestyle and dietary habits, anthropometric parameters, lung function assessments, liver elastography by Fibroscan, electrocardiogram readings, biochemical data, and molecular assays, including but not limited to genomics, plasma proteomics, metabolomics, and fecal microbiome analysis. In addition to exploring associations between these parameters and their cardio-metabolic outcomes, we plan to employ artificial intelligence algorithms to develop predictive models for phenotypic conditions. This study could pave the way for precision medicine tailored to the Indian population, particularly for the middle-income strata, and help refine the normative values for health and disease indicators in India.

cardio-metabolic↗
PubMed2025

Foliar disease resistance phenomics of fungal pathogens: image-based approaches for mapping quantitative resistance in cereal germplasm.

Host plant resistance is the most effective and environmentally sustainable means of reducing yield losses caused by fungal foliar pathogens of cereal species. Cereal genebank collections hold diverse pools of potentially underutilized disease resistance alleles, and cereal genomic resources are well advanced due to large-scale sequencing and genotyping efforts. Genome-Wide Association Studies (GWAS) have emerged as the predominant association genetics technique to initially discover novel disease resistance loci or alleles in these diverse collections. Traditional disease resistance phenotyping methods are reliant on visual estimation of disease symptom severity and have successfully supported genetic mapping studies either via GWAS or QTL mapping in biparental populations facilitating both marker development and gene cloning efforts. Due to foliar pathogens having a high capacity to evolve, there is a need to pyramid disease resistance genes with diverse mechanisms for durable control. Resistance expressed as a quantitative trait, known as quantitative resistance (QR), is hypothesized to be more durable, unlike major R-gene resistance that is race-specific and can be vulnerable to breaking down without gene stewardship. However, assessing QR visually is challenging, particularly when complicated by complex genotype × environment (G × E) effects in the field. High-throughput image-based phenotyping provides accurate and unbiased data that can support foliar disease resistance screening efforts of genebank collections using GWAS. In this review, we discuss image-based disease phenotyping based on macroscopic (visible symptoms) and microscopic features during the host-pathogen interaction. Quantitative image analysis approaches using conventional and artificial intelligence (AI) algorithms are also discussed.

Disease Resistance↗
PubMed2026

Cross-Ancestry and Phenome-Wide Associations of Cancer-Specific Polygenic Risk Scores.

PURPOSE: Genome-wide association studies have identified many common variants associated at low effect sizes with various cancers. Summing the effects of these variants into polygenic risk scores (PRS) can improve cancer risk prediction. However, cross-cancer and cross-phenotype pleiotropic associations of cancer-specific PRS are limited. METHODS: Using logistic regression models, we tested the association of 13 cancer-specific PRS with curated phenotypes representing the same 13 cancers and 340 cancer and cardiometabolic phecodes in 560,287 individuals (114,255 African ancestry [AFR] and 446,032 European ancestry [EUR]) from the Million Veteran Program. Models were stratified by ancestry and used age, principal components, and cancer-specific PRS per standard deviation as independent variables, and correction was applied for multiple comparisons. RESULTS: All 13 cancer-specific PRS were significantly associated with their respective cancers among EUR individuals with odds ratios per standard deviation of PRS (odds ratio [OR]) 1.05-1.70. Among AFR individuals, the effect sizes of the cancer PRS were lower, with OR 1.01-1.48, and cancer-specific PRS were significantly associated with their respective cancers for five of 13 cancers (bladder, breast in female patients, colorectal, prostate, and thyroid). In cancer-cancer pleiotropy studies, only the renal cancer-specific PRS was significantly associated with skin cancer (OR = 1.04, P = 4.5 × 10-06) among EUR individuals. PheWAS demonstrated five positive pleotropic associations with cardiometabolic conditions (thyroid cancer PRS with thyroid goiter, oral cancer PRS with diabetes phenotypes, and hypothyroidism) and two negative associations (oral and lung cancer PRS separately with coronary artery disease). CONCLUSION: Cancer PRS have stronger associations per cancer among EUR versus AFR individuals. In contrast to PRS of other chronic diseases, the majority of cancer-related PRS are highly specific and pleiotropic associations with other cancers and cardiometabolic traits are uncommon.

Female↗
PubMed2000

A mouse phenome project.

A community-wide effort to establish baseline phenotypic data on commonly used and genetically diverse inbred mouse strains and to provide the information through a publicly accessible database.

Animals↗
PubMed2004

High-throughput phenomics: experimental methods for mapping fluxomes.

Many technologies have been developed to help explain the phenotypic consequences of genetic and/or environmental modifications in areas like functional genomics, pharmaceutical research and metabolic engineering. The missing link in contemporary functional analyses that focus on the analysis of cellular components is the capacity to directly observe functional units. By linking genes and proteins to higher level biological functions, the molecular fluxes through metabolic networks (the fluxome) determine the cellular phenotype. Quantitative monitoring of such whole network operations by methods of metabolic flux analysis, thus bridges the gap by providing a global perspective of the integrated regulation at the transcriptional, translational and metabolic level. This review highlights recent developments towards high-throughput flux analysis.

Animals↗