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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 -
Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review.Journal of Advanced Research Jan 2022Linking phenotypes and genotypes to identify genetic architectures that regulate important traits is crucial for plant breeding and the development of plant genomics. In... (Review)
Review
Linking phenotypes and genotypes to identify genetic architectures that regulate important traits is crucial for plant breeding and the development of plant genomics. In recent years, genome-wide association studies (GWASs) have been applied extensively to interpret relationships between genes and traits. Successful GWAS application requires comprehensive genomic and phenotypic data from large populations. Although multiple high-throughput DNA sequencing approaches are available for the generation of genomics data, the capacity to generate high-quality phenotypic data is lagging far behind. Traditional methods for plant phenotyping mostly rely on manual measurements, which are laborious, inaccurate, and time-consuming, greatly impairing the acquisition of phenotypic data from large populations. In contrast, high-throughput phenotyping has unique advantages, facilitating rapid, non-destructive, and high-throughput detection, and, in turn, addressing the shortcomings of traditional methods. This review summarizes the current status with regard to the integration of high-throughput phenotyping and GWAS in plants, in addition to discussing the inherent challenges and future prospects. High-throughput phenotyping, which facilitates non-contact and dynamic measurements, has the potential to offer high-quality trait data for GWAS and, in turn, to enhance the unraveling of genetic structures of complex plant traits. In conclusion, high-throughput phenotyping integration with GWAS could facilitate the revealing of coding information in plant genomes.
Topics: Genome, Plant; Genome-Wide Association Study; Genotype; Phenotype; Plant Breeding
PubMed: 35003802
DOI: 10.1016/j.jare.2021.05.002 -
FEMS Microbiology Reviews Jan 2009The measure of the quality of a systems biology model is how well it can reproduce and predict the behaviors of a biological system such as a microbial cell. In recent... (Review)
Review
The measure of the quality of a systems biology model is how well it can reproduce and predict the behaviors of a biological system such as a microbial cell. In recent years, these models have been built up in layers, and each layer has been growing in sophistication and accuracy in parallel with a global data set to challenge and validate the models in predicting the content or activities of genes (genomics), proteins (proteomics), metabolites (metabolomics), and ultimately cell phenotypes (phenomics). This review focuses on the latter, the phenotypes of microbial cells. The development of Phenotype MicroArrays, which attempt to give a global view of cellular phenotypes, is described. In addition to their use in fleshing out and validating systems biology models, there are many other uses of this global phenotyping technology in basic and applied microbiology research, which are also described.
Topics: Bacteria; Industrial Microbiology; Metabolic Networks and Pathways; Oligonucleotide Array Sequence Analysis; Phenotype; Signal Transduction; Systems Biology
PubMed: 19054113
DOI: 10.1111/j.1574-6976.2008.00149.x -
Plant Communications Nov 2022Plant 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... (Review)
Review
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.
Topics: Phenomics; Plant Breeding; Crops, Agricultural; Remote Sensing Technology; Phenotype
PubMed: 35655429
DOI: 10.1016/j.xplc.2022.100344 -
Human Heredity 2014All human populations exhibit some level of genetic differentiation. This differentiation, or population stratification, has many interacting sources, including... (Review)
Review
All human populations exhibit some level of genetic differentiation. This differentiation, or population stratification, has many interacting sources, including historical migrations, population isolation over time, genetic drift, and selection and adaptation. If differentiated populations remained isolated from each other over a long period of time such that there is no mating of individuals between those populations, then some level of global consanguinity within those populations will lead to the formation of gene pools that will become more and more distinct over time. Global genetic differentiation of this sort can lead to overt phenotypic differences between populations if phenotypically relevant variants either arise uniquely within those populations or begin to exhibit frequency differences across the populations. This can occur at the single variant level for monogenic phenotypes or at the level of aggregate variant frequency differences across the many loci that contribute to a phenotype with a multifactorial or polygenic basis. However, if individuals begin to interbreed (or 'admix') from populations with different frequencies of phenotypically relevant genetic variants, then these admixed individuals will exhibit the phenotype to varying degrees. The level of phenotypic expression will depend on the degree to which the admixed individuals have inherited causative variants that have descended from the ancestral population in which those variants were present (or, more likely, simply more frequent). We review studies that consider the association between the degree of admixture (or ancestry) and phenotypes of clinical relevance. We find a great deal of literature-based evidence for associations between the degree of admixture and phenotypic variation for a number of admixed populations and phenotypes, although not all this evidence is confirmatory. We also consider the implications of such associations for gene-mapping initiatives as well as general clinical epidemiology studies and medical practice. We end with some thoughts on the future of studies exploring phenotypic differences among admixed individuals as well as individuals with different ancestral backgrounds.
Topics: Genetic Diseases, Inborn; Genetic Variation; Genetics, Population; Humans; Phenotype; Reproductive Isolation
PubMed: 25060271
DOI: 10.1159/000362233 -
Advances in Genetics 2016Phenotype is defined as the state of an organism resulting from interactions between genes, environment, disease, molecular mechanisms, and chance. The purpose of the... (Review)
Review
Phenotype is defined as the state of an organism resulting from interactions between genes, environment, disease, molecular mechanisms, and chance. The purpose of the emerging field of phenomics is to systematically determine and measure phenotypes across biology for the sake of understanding. Phenotypes can affect more than one cell type and life stage, so ideal phenotyping would include the state of every cell type within the context of both tissue architecture and the whole organism at each life stage. In medicine, high-resolution anatomic assessment of phenotype is obtained from histology. Histology's interpretative power, codified by Virchow as cellular pathology, is derived from its ability to discern diagnostic and characteristic cellular changes in diseased tissues. Cellular pathology is observed in every major human disease and relies on the ability of histology to detect cellular change in any cell type due to unbiased pan-cellular staining, even in optically opaque tissues. Our laboratory has shown that histology is far more sensitive than stereomicroscopy for detecting phenotypes in zebrafish mutants. Those studies have also shown that more complete sampling, greater consistency in sample orientation, and the inclusion of phenotypes extending over longer length scales would provide greater coverage of common phenotypes. We are developing technical approaches to achieve an ideal detection of cellular pathology using an improved form of X-ray microtomography that retains the strengths and addresses the weaknesses of histology as a screening tool. We are using zebrafish as a vertebrate model based on the overlaps between zebrafish and mammalian tissue architecture, and a body size small enough to allow whole-organism, volumetric imaging at cellular resolution. Automation of whole-organism phenotyping would greatly increase the value of phenomics. Potential societal benefits would include reduction in the cost of drug development, a reduction in the incidence of unexpected severe drug and environmental toxicity, and more rapid elucidation of the contributions of genes and the environment to phenotypes, including the validation of candidate disease alleles identified in population and personal genetics.
Topics: Animals; Environment; Genomics; Humans; Models, Animal; Phenotype; Zebrafish
PubMed: 27503355
DOI: 10.1016/bs.adgen.2016.05.003 -
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 -
Mammalian Genome : Official Journal of... Oct 2015New sequencing technologies have ushered in a new era for diagnosis and discovery of new causative mutations for rare diseases. However, the sheer numbers of candidate... (Review)
Review
New sequencing technologies have ushered in a new era for diagnosis and discovery of new causative mutations for rare diseases. However, the sheer numbers of candidate variants that require interpretation in an exome or genomic analysis are still a challenging prospect. A powerful approach is the comparison of the patient's set of phenotypes (phenotypic profile) to known phenotypic profiles caused by mutations in orthologous genes associated with these variants. The most abundant source of relevant data for this task is available through the efforts of the Mouse Genome Informatics group and the International Mouse Phenotyping Consortium. In this review, we highlight the challenges in comparing human clinical phenotypes with mouse phenotypes and some of the solutions that have been developed by members of the Monarch Initiative. These tools allow the identification of mouse models for known disease-gene associations that may otherwise have been overlooked as well as candidate genes may be prioritized for novel associations. The culmination of these efforts is the Exomiser software package that allows clinical researchers to analyse patient exomes in the context of variant frequency and predicted pathogenicity as well the phenotypic similarity of the patient to any given candidate orthologous gene.
Topics: Animals; Computational Biology; Databases, Genetic; Disease Models, Animal; Exome; Genetic Diseases, Inborn; Genomics; Humans; Mice; Mutation; Phenotype
PubMed: 26092691
DOI: 10.1007/s00335-015-9577-8 -
TAG. Theoretical and Applied Genetics.... Jan 2022Rising temperatures and changing precipitation patterns will affect agricultural production substantially, exposing crops to extended and more intense periods of stress.... (Review)
Review
Rising temperatures and changing precipitation patterns will affect agricultural production substantially, exposing crops to extended and more intense periods of stress. Therefore, breeding of varieties adapted to the constantly changing conditions is pivotal to enable a quantitatively and qualitatively adequate crop production despite the negative effects of climate change. As it is not yet possible to select for adaptation to future climate scenarios in the field, simulations of future conditions in controlled-environment (CE) phenotyping facilities contribute to the understanding of the plant response to special stress conditions and help breeders to select ideal genotypes which cope with future conditions. CE phenotyping facilities enable the collection of traits that are not easy to measure under field conditions and the assessment of a plant's phenotype under repeatable, clearly defined environmental conditions using automated, non-invasive, high-throughput methods. However, extrapolation and translation of results obtained under controlled environments to field environments is ambiguous. This review outlines the opportunities and challenges of phenotyping approaches under controlled environments complementary to conventional field trials. It gives an overview on general principles and introduces existing phenotyping facilities that take up the challenge of obtaining reliable and robust phenotypic data on climate response traits to support breeding of climate-adapted crops.
Topics: Adaptation, Physiological; Climate Change; Droughts; Environment, Controlled; Phenotype; Plant Breeding; Plant Transpiration; Salt Stress
PubMed: 34302493
DOI: 10.1007/s00122-021-03892-1 -
Theoretical Population Biology Feb 2024Natural selection acts on phenotypes constructed over development, which raises the question of how development affects evolution. Classic evolutionary theory indicates...
Natural selection acts on phenotypes constructed over development, which raises the question of how development affects evolution. Classic evolutionary theory indicates that development affects evolution by modulating the genetic covariation upon which selection acts, thus affecting genetic constraints. However, whether genetic constraints are relative, thus diverting adaptation from the direction of steepest fitness ascent, or absolute, thus blocking adaptation in certain directions, remains uncertain. This limits understanding of long-term evolution of developmentally constructed phenotypes. Here we formulate a general, tractable mathematical framework that integrates age progression, explicit development (i.e., the construction of the phenotype across life subject to developmental constraints), and evolutionary dynamics, thus describing the evolutionary and developmental (evo-devo) dynamics. The framework yields simple equations that can be arranged in a layered structure that we call the evo-devo process, whereby five core elementary components generate all equations including those mechanistically describing genetic covariation and the evo-devo dynamics. The framework recovers evolutionary dynamic equations in gradient form and describes the evolution of genetic covariation from the evolution of genotype, phenotype, environment, and mutational covariation. This shows that genotypic and phenotypic evolution must be followed simultaneously to yield a dynamically sufficient description of long-term phenotypic evolution in gradient form, such that evolution described as the climbing of a fitness landscape occurs in "geno-phenotype" space. Genetic constraints in geno-phenotype space are necessarily absolute because the phenotype is related to the genotype by development. Thus, the long-term evolutionary dynamics of developed phenotypes is strongly non-standard: (1) evolutionary equilibria are either absent or infinite in number and depend on genetic covariation and hence on development; (2) developmental constraints determine the admissible evolutionary path and hence which evolutionary equilibria are admissible; and (3) evolutionary outcomes occur at admissible evolutionary equilibria, which do not generally occur at fitness landscape peaks in geno-phenotype space, but at peaks in the admissible evolutionary path where "total genotypic selection" vanishes if exogenous plastic response vanishes and mutational variation exists in all directions of genotype space. Hence, selection and development jointly define the evolutionary outcomes if absolute mutational constraints and exogenous plastic response are absent, rather than the outcomes being defined only by selection. Moreover, our framework provides formulas for the sensitivities of a recurrence and an alternative method to dynamic optimization (i.e., dynamic programming or optimal control) to identify evolutionary outcomes in models with developmentally dynamic traits. These results show that development has major evolutionary effects.
Topics: Biological Evolution; Phenotype; Genotype; Selection, Genetic; Mutation
PubMed: 38043588
DOI: 10.1016/j.tpb.2023.11.003