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Evolution; International Journal of... Feb 2022Forms of phenotypic plasticity in key traits, and forms of selection on and genetic variation in such plasticity, fundamentally underpin phenotypic, population dynamic,...
Forms of phenotypic plasticity in key traits, and forms of selection on and genetic variation in such plasticity, fundamentally underpin phenotypic, population dynamic, and evolutionary responses to environmental variation and directional change. Accordingly, numerous theoretical and empirical studies have examined properties and consequences of plasticity, primarily considering traits that are continuously distributed on observed phenotypic scales with linear reaction norms. However, many environmentally sensitive traits are expressed as discrete alternative phenotypes and are appropriately characterized as quantitative genetic threshold traits. Here, we highlight that forms of phenotypic plasticity, genetic variation, and inheritance in plasticity, and outcomes of selection on plasticity, could differ substantially between threshold traits and continuously distributed traits (as are typically considered). We thereby highlight theoretical developments that are required to rationalize and predict phenotypic and microevolutionary dynamics involving plastic threshold traits, and outline how intrinsic properties of such traits could provide relatively straightforward explanations for apparently idiosyncratic observed patterns of phenotypic variation. We summarize how key quantitative genetic parameters underlying threshold traits can be estimated, and thereby set the scene for embedding dynamic discrete traits into theoretical and empirical understanding of the role of plasticity in driving phenotypic, population, and evolutionary responses to environmental variation and change.
Topics: Adaptation, Physiological; Biological Evolution; Genetic Variation; Phenotype
PubMed: 34874068
DOI: 10.1111/evo.14408 -
PLoS Computational Biology Jan 2020Functional annotation of genes remains a challenge in fundamental biology and is a limiting factor for translational medicine. Computational approaches have been...
Functional annotation of genes remains a challenge in fundamental biology and is a limiting factor for translational medicine. Computational approaches have been developed to process heterogeneous data into meaningful metrics, but often do not address how findings might be updated when new evidence comes to light. To address this challenge, we describe requirements for a framework for incremental data integration and propose an implementation based on phenotype ontologies and Bayesian probability updates. We apply the framework to quantify similarities between gene annotations and disease profiles. Within this scope, we categorize human diseases according to how well they can be recapitulated by animal models and quantify similarities between human diseases and mouse models produced by the International Mouse Phenotyping Consortium. The flexibility of the approach allows us to incorporate negative phenotypic data to better prioritize candidate genes, and to stratify disease mapping using sex-dependent phenotypes. All our association scores can be updated and we exploit this feature to showcase integration with curated annotations from high-precision assays. Incremental integration is thus a suitable framework for tracking functional annotations and linking to complex human pathology.
Topics: Animals; Computational Biology; Disease Models, Animal; Genetic Predisposition to Disease; Genotype; Humans; Mice; Molecular Sequence Annotation; Phenotype
PubMed: 31986132
DOI: 10.1371/journal.pcbi.1007586 -
Scientific Reports Mar 2020To date, reliable relationships between mammalian phenotypes, based on diagnostic test measurements, have not been reported on a large scale. The purpose of this study...
To date, reliable relationships between mammalian phenotypes, based on diagnostic test measurements, have not been reported on a large scale. The purpose of this study was to present a large mouse phenotype-phenotype relationships dataset as a reference resource, alongside detailed evaluation of the resource. We used bias-minimized comprehensive mouse phenotype data and applied association rule mining to a dataset consisting of only binary (normal and abnormal phenotypes) data to determine relationships among phenotypes. We present 3,686 evidence-based significant associations, comprising 345 phenotypes covering 60 biological systems (functions), and evaluate their characteristics in detail. To evaluate the relationships, we defined a set of phenotype-phenotype association pairs (PPAPs) as a module of phenotypic expression for each of the 345 phenotypes. By analyzing each PPAP, we identified phenotype sub-networks consisting of the largest numbers of phenotypes and distinct biological systems. Furthermore, using hierarchical clustering based on phenotype similarities among the 345 PPAPs, we identified seven community types within a putative phenome-wide association network. Moreover, to promote leverage of these data, we developed and published web-application tools. These mouse phenome-wide phenotype-phenotype association data reveal general principles of relationships among mammalian phenotypes and provide a reference resource for biomedical analyses.
Topics: Animals; Genome-Wide Association Study; Mice; Phenotype
PubMed: 32127602
DOI: 10.1038/s41598-020-60891-w -
Scientific Reports Jan 2023Thoracic insufficiency syndromes are a genetically and phenotypically heterogeneous group of disorders characterized by congenital abnormalities or progressive...
Thoracic insufficiency syndromes are a genetically and phenotypically heterogeneous group of disorders characterized by congenital abnormalities or progressive deformation of the chest wall and/or vertebrae that result in restrictive lung disease and compromised respiratory capacity. We performed whole exome sequencing on a cohort of 42 children with thoracic insufficiency to elucidate the underlying molecular etiologies of syndromic and non-syndromic thoracic insufficiency and predict extra-skeletal manifestations and disease progression. Molecular diagnosis was established in 24/42 probands (57%), with 18/24 (75%) probands having definitive diagnoses as defined by laboratory and clinical criteria and 6/24 (25%) probands having strong candidate genes. Gene identified in cohort patients most commonly encoded components of the primary cilium, connective tissue, and extracellular matrix. A novel association between KIF7 and USP9X variants and thoracic insufficiency was identified. We report and expand the genetic and phenotypic spectrum of a cohort of children with thoracic insufficiency, reinforce the prevalence of extra-skeletal manifestations in thoracic insufficiency syndromes, and expand the phenotype of KIF7 and USP9X-related disease to include thoracic insufficiency.
Topics: Phenotype; Spine
PubMed: 36653407
DOI: 10.1038/s41598-023-27641-0 -
Journal of Biomedical Informatics Apr 2023Identifying patient cohorts meeting the criteria of specific phenotypes is essential in biomedicine and particularly timely in precision medicine. Many research groups... (Review)
Review
Identifying patient cohorts meeting the criteria of specific phenotypes is essential in biomedicine and particularly timely in precision medicine. Many research groups deliver pipelines that automatically retrieve and analyze data elements from one or more sources to automate this task and deliver high-performing computable phenotypes. We applied a systematic approach based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to conduct a thorough scoping review on computable clinical phenotyping. Five databases were searched using a query that combined the concepts of automation, clinical context, and phenotyping. Subsequently, four reviewers screened 7960 records (after removing over 4000 duplicates) and selected 139 that satisfied the inclusion criteria. This dataset was analyzed to extract information on target use cases, data-related topics, phenotyping methodologies, evaluation strategies, and portability of developed solutions. Most studies supported patient cohort selection without discussing the application to specific use cases, such as precision medicine. Electronic Health Records were the primary source in 87.1 % (N = 121) of all studies, and International Classification of Diseases codes were heavily used in 55.4 % (N = 77) of all studies, however, only 25.9 % (N = 36) of the records described compliance with a common data model. In terms of the presented methods, traditional Machine Learning (ML) was the dominant method, often combined with natural language processing and other approaches, while external validation and portability of computable phenotypes were pursued in many cases. These findings revealed that defining target use cases precisely, moving away from sole ML strategies, and evaluating the proposed solutions in the real setting are essential opportunities for future work. There is also momentum and an emerging need for computable phenotyping to support clinical and epidemiological research and precision medicine.
Topics: Algorithms; Electronic Health Records; Machine Learning; Natural Language Processing; Phenotype
PubMed: 36933631
DOI: 10.1016/j.jbi.2023.104335 -
Beyond the behavioural phenotype: Uncovering mechanistic foundations in aquatic eco-neurotoxicology.The Science of the Total Environment Jul 2022During the last decade, there has been an increase in awareness of how anthropogenic pollution can alter behavioural traits of diverse aquatic organisms. Apart from... (Review)
Review
During the last decade, there has been an increase in awareness of how anthropogenic pollution can alter behavioural traits of diverse aquatic organisms. Apart from understanding profound ecological implications, alterations in neuro-behavioural indices have emerged as sensitive and physiologically integrative endpoints in chemical risk assessment. Accordingly, behavioural ecotoxicology and broader eco-neurotoxicology are becoming increasingly popular fields of research that span a plethora of fundamental laboratory experimentations as well as applied field-based studies. Despite mounting interest in aquatic behavioural ecotoxicology studies, there is, however, a considerable paucity in deciphering the mechanistic foundations underlying behavioural alterations upon exposure to pollutants. The behavioural phenotype is indeed the highest-level integrative neurobiological phenomenon, but at its core lie myriads of intertwined biochemical, cellular, and physiological processes. Therefore, the mechanisms that underlie changes in behavioural phenotypes can stem among others from dysregulation of neurotransmitter pathways, electrical signalling, and cell death of discrete cell populations in the central and peripheral nervous systems. They can, however, also be a result of toxicity to sensory organs and even metabolic dysfunctions. In this critical review, we outline why behavioural phenotyping should be the starting point that leads to actual discovery of fundamental mechanisms underlying actions of neurotoxic and neuromodulating contaminants. We highlight potential applications of the currently existing and emerging neurobiology and neurophysiology analytical strategies that should be embraced and more broadly adopted in behavioural ecotoxicology. Such strategies can provide new mechanistic discoveries instead of only observing the end sum phenotypic effects.
Topics: Aquatic Organisms; Ecotoxicology; Environmental Pollution; Phenotype; Water Pollutants, Chemical
PubMed: 35306067
DOI: 10.1016/j.scitotenv.2022.154584 -
Molecular Aspects of Medicine Jun 2022Although there is still no consensus on the definition of Asthma-COPD Overlap (ACO), it is generally accepted that some patients with airway disease have features of... (Review)
Review
Although there is still no consensus on the definition of Asthma-COPD Overlap (ACO), it is generally accepted that some patients with airway disease have features of both asthma and COPD. Just as its constituents, ACO consists of different phenotypes, possibly depending on the predominance of the underlying asthma or COPD-associated pathophysiological mechanisms. The clinical picture is influenced by the development of airway inflammatory processes either eosinophilic, neutrophilic or mixed, in addition to glandular changes leading to mucus hypersecretion and a variety of other airway structural changes. Although animal models have exposed how smoking-related changes can interact with those observed in asthma, much remains to be known about their interactions in humans and the additional modulating effects of environmental exposures. There is currently no solid evidence to establish the optimal treatment of ACO but it should understandably include an avoidance of environmental triggers such as smoking and relevant allergens. The recognition and targeting of "treatable traits" following phenotyping is a pragmatic approach to select the optimal pharmacological treatment for ACO, although an association of inhaled corticosteroids and bronchodilators is always required in these patients. This association acts both as an anti-inflammatory treatment for the asthma component and as a functional antagonist for the airway remodeling features. Research should be promoted on well phenotyped subgroups of ACO patients to determine their optimal management.
Topics: Asthma; Bronchodilator Agents; Humans; Phenotype; Pulmonary Disease, Chronic Obstructive
PubMed: 34521557
DOI: 10.1016/j.mam.2021.101021 -
Journal of Microbiology (Seoul, Korea) Mar 2021Raman spectroscopy is a promising tool for identifying microbial phenotypes based on single cell Raman spectra reflecting cellular biochemical biomolecules. Recent... (Review)
Review
Raman spectroscopy is a promising tool for identifying microbial phenotypes based on single cell Raman spectra reflecting cellular biochemical biomolecules. Recent studies using Raman spectroscopy have mainly analyzed phenotypic changes caused by microbial interactions or stress responses (e.g., antibiotics) and evaluated the microbial activity or substrate specificity under a given experimental condition using stable isotopes. Lack of labelling and the nondestructive pretreatment and measurement process of Raman spectroscopy have also aided in the sorting of microbial cells with interesting phenotypes for subsequently conducting physiology experiments through cultivation or genome analysis. In this review, we provide an overview of the principles, advantages, and status of utilization of Raman spectroscopy for studies linking microbial phenotypes and functions. We expect Raman spectroscopy to become a next-generation phenotyping tool that will greatly contribute in enhancing our understanding of microbial functions in natural and engineered systems.
Topics: Bacteria; Bacterial Physiological Phenomena; Phenomics; Phenotype; Spectrum Analysis, Raman
PubMed: 33496936
DOI: 10.1007/s12275-021-0590-1 -
Journal of Experimental Botany Sep 2015Plants emit a great variety of volatile organic compounds (VOCs) that can actively participate in plant growth and protection against biotic and abiotic stresses. VOC... (Review)
Review
Plants emit a great variety of volatile organic compounds (VOCs) that can actively participate in plant growth and protection against biotic and abiotic stresses. VOC emissions are strongly dependent on environmental conditions; the greatest ambiguity is whether or not the predicted change in climate will influence and modify plant-pest interactions that are mediated by VOCs. The constitutive and induced emission patterns between plant genotypes, species, and taxa are highly variable and can be used as pheno(chemo)typic markers to distinguish between different origins and provenances. In recent years significant progress has been made in molecular and genetic plant breeding. However, there is actually a lack of knowledge in functionally linking genotypes and phenotypes, particularly in analyses of plant-environment interactions. Plant phenotyping, the assessment of complex plant traits such as growth, development, tolerance, resistance, etc., has become a major bottleneck, and quantitative information on genotype-environment relationships is the key to addressing major future challenges. With increasing demand to support and accelerate progress in breeding for novel traits, the plant research community faces the need to measure accurately increasingly large numbers of plants and plant traits. In this review article, we focus on the promising outlook of VOC phenotyping as a fast and non-invasive measure of phenotypic dynamics. The basic principle is to define plant phenotypes according to their disease resistance and stress tolerance, which in turn will help in improving the performance and yield of economically relevant plants.
Topics: Crops, Agricultural; Genetic Markers; Mass Spectrometry; Phenotype; Plant Breeding; Volatile Organic Compounds
PubMed: 25969554
DOI: 10.1093/jxb/erv219 -
Obesity (Silver Spring, Md.) Oct 2017Risk for obesity is determined by a complex mix of genetics and lifetime exposures at multiple levels, from the metabolic milieu to psychosocial and environmental... (Review)
Review
OBJECTIVE
Risk for obesity is determined by a complex mix of genetics and lifetime exposures at multiple levels, from the metabolic milieu to psychosocial and environmental influences. These phenotypic differences underlie the variability in risk for obesity and response to weight management interventions, including differences in physical activity and sedentary behavior.
METHODS
As part of a broader effort focused on behavioral and psychological phenotyping in obesity research, the National Institutes of Health convened a multidisciplinary workshop to explore the state of the science in behavioral and psychological phenotyping in humans to explain individual differences in physical activity, both as a risk factor for obesity development and in response to activity-enhancing interventions.
RESULTS
Understanding the behavioral and psychological phenotypes that contribute to differences in physical activity and sedentary behavior could allow for improved treatment matching and inform new targets for tailored, innovative, and effective weight management interventions.
CONCLUSIONS
This summary provides the rationale for identifying psychological and behavioral phenotypes relevant to physical activity and identifies opportunities for future research to better understand, define, measure, and validate putative phenotypic factors and characterize emerging phenotypes that are empirically associated with initiation of physical activity, response to intervention, and sustained changes in physical activity.
Topics: Body Weight Maintenance; Exercise; Humans; Obesity; Phenotype; Risk Factors; Sedentary Behavior
PubMed: 28948719
DOI: 10.1002/oby.21924