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Clinical Genetics Feb 2019In clinical genetics, the Human Phenotype Ontology as well as disease ontologies are often used for deep phenotyping of patients and coding of clinical diagnoses....
In clinical genetics, the Human Phenotype Ontology as well as disease ontologies are often used for deep phenotyping of patients and coding of clinical diagnoses. However, assigning ontology classes to patient descriptions is often disconnected from writing patient reports or manuscripts in word processing software. This additional workload and the requirement to install dedicated software may discourage usage of ontologies for parts of the target audience. Here we present Phenotero, a freely available and simple solution to annotate patient phenotypes and diseases at the time of writing clinical reports or manuscripts. We adopt Zotero, a citation management software to create a tool which allows to reference classes from ontologies within text at the time of writing. We expect this approach to decrease the additional workload to a minimum while ensuring high quality associations with ontology classes. Standardized collection of phenotypic information at the time of describing the patient allows for streamlining the clinic workflow and efficient data entry. It will subsequently promote clinical and molecular diagnosis with the ultimate goal of better understanding genetic diseases. Thus, we believe that Phenotero eases the usage of ontologies and controlled vocabularies in the field of clinical genetics.
Topics: Databases, Factual; Databases, Genetic; Genetics, Medical; Humans; Phenotype; Software; User-Computer Interface; Web Browser; Workflow
PubMed: 30417324
DOI: 10.1111/cge.13471 -
Neuropsychopharmacology : Official... Jan 2021Focusing on biomarker identification and using biomarkers individually or in clusters to define biological subgroups in psychiatry requires a re-orientation from... (Review)
Review
Focusing on biomarker identification and using biomarkers individually or in clusters to define biological subgroups in psychiatry requires a re-orientation from behavioral phenomenology to quantifying brain features, requiring big data approaches for data integration. Much still needs to be accomplished, not only to refine but also to build support for the application and customization of such an analytical phenotypic approach. In this review, we present some of what Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) has learned so far to guide future applications of multivariate phenotyping and their analyses to understanding psychosis. This paper describes several B-SNIP projects that use phenotype data and big data computations to generate novel outcomes and glimpse what phenotypes contribute to disease understanding and, with aspiration, to treatment. The source of the phenotypes varies from genetic data, structural neuroanatomic localization, immune markers, brain physiology, and cognition. We aim to see guiding principles emerge and areas of commonality revealed. And, we will need to demonstrate not only data stability but also the usefulness of biomarker information for subgroup identification enhancing target identification and treatment development.
Topics: Bipolar Disorder; Brain; Humans; Phenotype; Psychotic Disorders; Schizophrenia
PubMed: 32979849
DOI: 10.1038/s41386-020-00849-8 -
Human Mutation Nov 2022Making a specific diagnosis in neurodevelopmental disorders is traditionally based on recognizing clinical features of a distinct syndrome, which guides testing of its... (Review)
Review
Making a specific diagnosis in neurodevelopmental disorders is traditionally based on recognizing clinical features of a distinct syndrome, which guides testing of its possible genetic etiologies. Scalable frameworks for genomic diagnostics, however, have struggled to integrate meaningful measurements of clinical phenotypic features. While standardization has enabled generation and interpretation of genomic data for clinical diagnostics at unprecedented scale, making the equivalent breakthrough for clinical data has proven challenging. However, increasingly clinical features are being recorded using controlled dictionaries with machine readable formats such as the Human Phenotype Ontology (HPO), which greatly facilitates their use in the diagnostic space. Improving the tractability of large-scale clinical information will present new opportunities to inform genomic research and diagnostics from a clinical perspective. Here, we describe novel approaches for computational phenotyping to harmonize clinical features, improve data translation through revising domain-specific dictionaries, quantify phenotypic features, and determine clinical relatedness. We demonstrate how these concepts can be applied to longitudinal phenotypic information, which represents a critical element of developmental disorders and pediatric conditions. Finally, we expand our discussion to clinical data derived from electronic medical records, a largely untapped resource of deep clinical information with distinct strengths and weaknesses.
Topics: Child; Electronic Health Records; Genomics; Humans; Phenotype
PubMed: 35460582
DOI: 10.1002/humu.24389 -
Cell Systems May 2023Cellular and organismal phenotypes are controlled by complex gene regulatory networks. However, reference maps of gene function are still scarce across different...
Cellular and organismal phenotypes are controlled by complex gene regulatory networks. However, reference maps of gene function are still scarce across different organisms. Here, we generated synthetic genetic interaction and cell morphology profiles of more than 6,800 genes in cultured Drosophila cells. The resulting map of genetic interactions was used for machine learning-based gene function discovery, assigning functions to genes in 47 modules. Furthermore, we devised Cytoclass as a method to dissect genetic interactions for discrete cell states at the single-cell resolution. This approach identified an interaction of Cdk2 and the Cop9 signalosome complex, triggering senescence-associated secretory phenotypes and immunogenic conversion in hemocytic cells. Together, our data constitute a genome-scale resource of functional gene profiles to uncover the mechanisms underlying genetic interactions and their plasticity at the single-cell level.
Topics: Animals; Gene Regulatory Networks; Phenotype; Drosophila
PubMed: 37116498
DOI: 10.1016/j.cels.2023.03.003 -
The Plant Journal : For Cell and... Jan 2019Recent advances in genomics technologies have greatly accelerated the progress in both fundamental plant science and applied breeding research. Concurrently,... (Review)
Review
Recent advances in genomics technologies have greatly accelerated the progress in both fundamental plant science and applied breeding research. Concurrently, high-throughput plant phenotyping is becoming widely adopted in the plant community, promising to alleviate the phenotypic bottleneck. While these technological breakthroughs are significantly accelerating quantitative trait locus (QTL) and causal gene identification, challenges to enable even more sophisticated analyses remain. In particular, care needs to be taken to standardize, describe and conduct experiments robustly while relying on plant physiology expertise. In this article, we review the state of the art regarding genome assembly and the future potential of pangenomics in plant research. We also describe the necessity of standardizing and describing phenotypic studies using the Minimum Information About a Plant Phenotyping Experiment (MIAPPE) standard to enable the reuse and integration of phenotypic data. In addition, we show how deep phenotypic data might yield novel trait-trait correlations and review how to link phenotypic data to genomic data. Finally, we provide perspectives on the golden future of machine learning and their potential in linking phenotypes to genomic features.
Topics: Genetic Association Studies; Genome, Plant; Genomics; Machine Learning; Phenomics; Phenotype; Plants; Quantitative Trait Loci
PubMed: 30500991
DOI: 10.1111/tpj.14179 -
Genes Jun 2022Network and systemic approaches to studying human pathologies are helping us to gain insight into the molecular mechanisms of and potential therapeutic interventions for... (Review)
Review
Network and systemic approaches to studying human pathologies are helping us to gain insight into the molecular mechanisms of and potential therapeutic interventions for human diseases, especially for complex diseases where large numbers of genes are involved. The complex human pathological landscape is traditionally partitioned into discrete "diseases"; however, that partition is sometimes problematic, as diseases are highly heterogeneous and can differ greatly from one patient to another. Moreover, for many pathological states, the set of symptoms (phenotypes) manifested by the patient is not enough to diagnose a particular disease. On the contrary, phenotypes, by definition, are directly observable and can be closer to the molecular basis of the pathology. These clinical phenotypes are also important for personalised medicine, as they can help stratify patients and design personalised interventions. For these reasons, network and systemic approaches to pathologies are gradually incorporating phenotypic information. This review covers the current landscape of phenotype-centred network approaches to study different aspects of human diseases.
Topics: Humans; Phenotype
PubMed: 35741843
DOI: 10.3390/genes13061081 -
Mechanisms of Development Dec 2018Understanding how the genome instructs the phenotypic characteristics of an organism is one of the major scientific endeavors of our time. Advances in genetics have... (Review)
Review
Understanding how the genome instructs the phenotypic characteristics of an organism is one of the major scientific endeavors of our time. Advances in genetics have progressively deciphered the inheritance, identity and biological relevance of genetically encoded information, contributing to the rise of several, complementary omic disciplines. One of them is phenomics, an emergent area of biology dedicated to the systematic multi-scale analysis of phenotypic traits. This discipline provides valuable gene function information to the rapidly evolving field of genetics. Current molecular tools enable genome-wide analyses that link gene sequence to function in multi-cellular organisms, illuminating the genome-phenome relationship. Among vertebrates, zebrafish has emerged as an outstanding model organism for high-throughput phenotyping and modeling of human disorders. Advances in both systematic mutagenesis and phenotypic analyses of embryonic and post-embryonic stages in zebrafish have revealed the function of a valuable collection of genes and the general structure of several complex traits. In this review, we summarize multiple large-scale genetic efforts addressing parental, embryonic, and adult phenotyping in the zebrafish. The genetic and quantitative tools available in the zebrafish model, coupled with the broad spectrum of phenotypes that can be assayed, make it a powerful model for phenomics, well suited for the dissection of genotype-phenotype associations in development, physiology, health and disease.
Topics: Animals; Genome; Genome-Wide Association Study; Humans; Phenotype; Zebrafish
PubMed: 30130581
DOI: 10.1016/j.mod.2018.08.007 -
Plant Science : An International... Mar 2015The genomic makeup and phenotypes of plants are diversifying, in part due to artificial or natural selection in agricultural and natural environments. Utilization of... (Review)
Review
The genomic makeup and phenotypes of plants are diversifying, in part due to artificial or natural selection in agricultural and natural environments. Utilization of these variations to enhance crop productivity requires an understanding of the relationships between genotype and phenotype in inbreds and hybrids derived from crosses between these populations. This review highlights recent studies on hybrid vigor (heterosis) and the related phenomenon of hybrid weakness - two types of non-additive inheritance. Heterosis is a phenomenon whereby the phenotype of first-generation hybrids is superior to that of their parents. Intralocus interactions between alleles, complementation of dominant alleles, or inter-loci epistatic interactions are genetic mechanisms that may cause non-additive phenotypic inheritance in hybrids. However, there are different views on what portion of the heterotic variation is modulated by each of these mechanisms. Another aspect of plant vigor is phenotypic stability or robustness in different environments and how this is influenced by gene heterozygosity. Hybrids are not necessarily more phenotypically stable than inbreds since local heterozygosity might be associated with negative effects on biochemical activities. This review integrates genetic and biochemical considerations to illustrate how these relationships may be tightly linked with breeding system and sequence divergence.
Topics: Genotype; Heterozygote; Hybrid Vigor; Hybridization, Genetic; Phenotype; Plants
PubMed: 25617321
DOI: 10.1016/j.plantsci.2014.11.014 -
Current Topics in Medicinal Chemistry 2016Asthma is a chronic inflammatory airways disorder mainly characterized by heterogeneity. A phenotype is defined as a group of patients that present similar clinically... (Review)
Review
Asthma is a chronic inflammatory airways disorder mainly characterized by heterogeneity. A phenotype is defined as a group of patients that present similar clinically observable characteristics, without establishing a direct etiologic relationship with a distinct pathophysiologic mechanism. An endotype, on the other hand, describes a subgroup that shares the same pathophysiologic processes that lead to the development, the progression and the presentation of a disease. A biomarker has been defined as a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes or pharmacologic responses to a therapeutic intervention. Several inflammatory phenotypes have been identified by the use of biomarkers. Most of them are based on the predominant type of cells in different biological fluids with sputum to be remained the most representative one. Eosinophilia represents the major characteristic of what we called classic atopic asthma. This particular phenotype usually responds well to corticosteroids, except for a small subgroup of severe asthma where even in the presence of eosinophils the ICS seem to have a less responsive role. Neutrophilic phenotype driven by the presence of neutrophils shows inadequate response to corticosteroid treatment, even in mild asthma. The major approach in order to define an endotype is driven by three main parameters. The statistical clustering approach, use of advanced statistical mathematics to create distinct patient clusters, the specific targeted immune therapies and finally the application of omics' approach. Both phenotypes and endotypes are trying to clarify mechanisms and processes that driven the complexity of asthma. Both concepts could identify approaches which could establish new targeted to specific biomarkers treatment therapies/strategies.
Topics: Asthma; Biomarkers; Endophenotypes; Humans; Phenotype
PubMed: 26420366
DOI: 10.2174/1568026616666150930120803 -
Progress in Biophysics and Molecular... Mar 2023In the predominately gene-centered view of 20th century biology, the relationship between genotype and phenotype was essentially a relationship between cause and effect,... (Review)
Review
In the predominately gene-centered view of 20th century biology, the relationship between genotype and phenotype was essentially a relationship between cause and effect, between a plan and a product. Abandoning the idea of genes as inherited instructions or blueprints for phenotypes raises the question of how to best account for observed phenotypic stability and variability within and across generations of a population. We argue that the processes responsible for phenotypic stability and the processes responsible for phenotypic variability are one and the same, namely, the dynamics of development. This argument proposes that stability of phenotypic form is found not because of the transmission of genotypes, genetic programs, or the transfer of internal blueprints, but because similar internal and external conditions-collectively conceptualized as resources of development-can be reliably reconstituted in each generation. Variability of phenotypic form, which is an indispensable feature of any evolving system, relies on these same resources, but because the internal and external conditions of development are not reconstituted identically in succeeding generations, these conditions-and the phenotypes to which they give rise-will always be characterized by at least some variability.
Topics: Biological Evolution; Genetic Determinism; Phenotype; Genotype
PubMed: 36682588
DOI: 10.1016/j.pbiomolbio.2023.01.003