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Phenomics

Phenomics

Phenomics is the systematic study of phenotypes, physical and chemical characteristics that result from interactions between genes and environment, on a genome-wide scale. A phenome is a set of observable or measurable phenotypes. Phenomics is a multidisciplinary field involving fields such as genetics, systems biology and machine learning.

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The International Human Phenome Project (Phase I) was launched in Shanghai in March 2018. The project will be led by Fudan University with collaboration with Shanghai Jiao Tong University, Shanghai Institute of Measurement and Testing Technology and Shanghai Institutes for Biological SciencesBiological Sciences.

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The International Human Phenome Project (Phase I) was launched in Shanghai in March 2018. The project will be led by Fudan University with collaboration with Shanghai Jiao Tong University, Shanghai Institute of Measurement and Testing Technology and Shanghai Institutes for Biological SciencesBiological Sciences.

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In contrast to the human genome, which consists of 3 billion bases made of 4 nucleic acids organized in a one dimensional space, the human phenome contains an unknown number of elements with variation and dimensionality only partly understood. The scientific understanding of genes and genomic variation is restricted by a narrow range of methods to assess phenotypes allowing only certain anatomical and behavioral traits to be recorded, which is often done manually. Phenomics aims to get a more in-depth and unbiased assessment of phenotypic profiles at the whilewhole organism level.

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Edits on 11 Dec, 2018
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In human phenomics, two of the aims are to understand how the environment makes people more or less susceptible to disease and to understand individual reactions to therapies. In 2003, at the time of completion of the Human Genome Project Human Genome Project, the need for more precisely defined phenotypes and high-throughput systems to fully take advantage of genotyping studies was projected and the creation of an international Human Phenome Project was proposed. The theme for a satellite meeting at the 2012 Annual Meeting of the American Society of Human Genetics in San Francisco by The Human Variome Project was “Getting Ready for the Human Phenome Project”. The meeting was cosponsored by the Human Genome Variation Society. At that meeting it was noted that in comparison to phenome projects in model organisms such as mouse, rat and zebrafish which have compiled phenotypic data on the consequences of genetic mutations, similar scale efforts for humans lagged behind.

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Computational approaches are being developed to gather, compare and process phenomics data. Machine learning methods are used for analysing images such as satellite images of plants, medical histology images and words describing medical conditions. For comparison of phenotypes across different organisms, formal ontologies are implemented that are accessible to automated reasoning. Phenotype ontologies are hierarchically-related phenotypic descriptions using controlled vocabulary that allows computation in individuals, populations and across multiple species. Ontologies are being developed in Web Ontology LanguageWeb Ontology Language (OWL) and OBO Flatfile Format.

Meredith Hanel
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The introduction of genetic changes in animal model systems allow for unbiased interrogation of genotype-phenotype interactions. The Mouse Phenome Project was the first major effort in a vertebrate model to catalog baseline phenotypic data, which is housed at the Mouse Phenome Database at the Jackson Laboratory, Bar HarborBar Harbor, ME. The Knockout Mouse Project is a National Institutes of Health (NIH) initiative which aims to generate a resource containing loss of function mutations for every gene in the mouse genome correlated with phenotypic data.

Meredith Hanel
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  • National Plant Phenomics Centre (IBERS Gogerddan, WalesWales, UK)
Meredith Hanel
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In contrast to the human genome, which consists of 3 billion bases made of 4 nucleic acids organized in a one dimensional space, the human phenome contains an unknown number of elements with variation and dimensionality only partly understood. The scientific understanding of genes and genomic variation is restricted by a narrow range of methods to assess phenotypesphenotypes allowing only certain anatomical and behavioral traits to be recorded, which is often done manually. Phenomics aims to get a more in-depth and unbiased assessment of phenotypic profiles at the while organism level.

Meredith Hanel
Meredith Hanel approved a suggestion from Golden's AI on 11 Dec, 2018
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Plant phenomics is used both to understand how crops respond to environmental changes and for crop improvement. Connections between plant genotype and phenotype were historically investigated by identifying a trait of interest and then using DNA markers and breeding to locate the gene responsible for the trait. Seeking the gene responsible for a phenotype is called a forward genetics approach. Reverse genetics approaches which mutate or alter genes first to find the phenotypic consequence of specific genetic changes became more commonly used with the development of mutagens, molecular genetics and bioinformatics. As the price of image data collection has gone down and the capability for computational image processing has increased, plant phenomics researchers are investigating relationships between genotype, phenotype and environment with satellite and drone images. One hurdle is in developing computational methods to extract useful information. Researchers at Iowa State University are using crowdsourcing to for image labeling used to train machine learningmachine learning algorithms. The team used students and Amazon MTurkers for image labeling.

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  • Plant Ontology
  • Gene Ontology Consortium
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Computational approaches to phenomics
  • Web Ontology Language (OWL)

Computational approaches are being developed to gather, compare and process phenomics data. Machine learning methods are used for analysing images such as satellite images of plants, medical histology images and words describing medical conditions. For comparison of phenotypes across different organisms, formal ontologies are implemented that are accessible to automated reasoning. Phenotype ontologies are hierarchically-related phenotypic descriptions using controlled vocabulary that allows computation in individuals, populations and across multiple species. Ontologies are being developed in Web Ontology Language (OWL) and OBO Flatfile Format.

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Meredith Hanel
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In humans, data on genotype-phenotype associations has been generated through genome-wide association studies (GWAS)genome-wide association studies (GWAS) or linking single nucleotide polymorphisms (SNPs)single nucleotide polymorphisms (SNPs) with disease phenotypes. To reduce the disease-centric bias in these approaches, an effort was made to look for associations in complete medical records and complete genome sequences, called Phenome Wide Association Studies (PheWAS). However human phenotype data has a strong clinical bias.

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Most human genes (70%) have a counterpart (ortholog) in zebrafishzebrafish, which combined with their short generation time, standard practises for genetic manipulation and suitability for live imaging make them cost-effective in biomedical research. The Zebrafish Phenome Project is underway and contribute to knowledge about phenotype-genotype associations and genetic diagnosis of human disease. The Chemical Phenomics Initiative, based on chemical genetics, is a high-throughput chemical screen for small molecules that modulate early embryonic development in zebrafish, carried out by the Hong lab at Vanderbilt University. Pharmacological targets for these small molecule developmental modulators are identified and made accessible to the scientific community through the chemotype-phenotype database on Chemical Phenomics interactive web portal. In zebrafish whole body micro-CT scanning has been used for skeletal phenomics studies.

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Phenomics organisations
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  • Definiens (Tissue Phenomics Company)

Phenomics companies in research and drug discovery
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Plant phenomics is used both to understand how crops respond to environmental changes and for crop improvement. Connections between plant genotype and phenotype were historically investigated by identifying a trait of interest and then using DNA markers and breeding to locate the gene responsible for the trait. Seeking the gene responsible for a phenotype is called a forward genetics approach. Reverse genetics approaches which mutate or alter genes first to find the phenotypic consequence of specific genetic changes became more commonly used with the development of mutagens, molecular genetics and bioinformatics. As the price of image data collection has gone down and the capability for computational image processing has increased, plant phenomics researchers are investigating relationships between genotype, phenotype and environment with satellite and drone images. One hurdle is in developing computational methods to extract useful information. Researchers at Iowa State University are using crowdsourcing to for image labeling used to train machine learning algorithms. The team used students and Amazon MTurkers for image labeling.

Researchers at University of Saskatchewan developed the open-source software platform, Deep Plant Phenomics, which uses deep convolutional neural networks for phenotyping plants. The platform was shown to be effective at leaf counting, mutant classification and age regression in top-down images of plant rosettes.

Plant phenomics organizations

  • National Plant Phenomics Centre (IBERS Gogerddan, Wales, UK)
  • PHENOME, the French plant phenomic Infrastructure
  • Australian Plant Phenomics Facility
  • The European Infrastructure for Multi-scale Plant Phenomics and Simulation (EMPHASIS)
  • International Plant Phenotyping Network
  • North American Plant Phenotyping Network

Companies in plant phenomics
  • Qubit Phenomics
  • Zegami Ltd
  • Phenome-Networks
  • LemnaTec
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Phenomics initiatives
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Pharmaceutical companies using phenomics

Edits on 5 Dec, 2018
Jed Christiansen
Jed Christiansen approved a suggestion from Golden's AI on 5 Dec, 2018
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As DNA sequencingDNA sequencing became faster and cheaper, new knowledge about normal genetic variation in the human population allowed genetic variants once thought to cause disease to be reclassified as benign. The ranges and commonality of variations in human phenotypes if better understood could improve the accuracy and treatment of disease in genetic medicine. The Human Phenotype Ontology helps the sharing of phenotype data by standardising the vocabulary for phenotypes. For some types of phenotypic abnormalities, standardized measurements can be used to define the phenotype. To show a causal link between a genetic variant and an abnormal phenotype, it needs to be shown that the two are found together more often then expected by chance. Improvements in data about baseline population frequencies of phenotypes are needed for these calculations.

Jed Christiansen
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The introduction of genetic changes in animal model systems allow for unbiased interrogation of genotype-phenotype interactions. The Mouse Phenome Project was the first major effort in a vertebrate model to catalog baseline phenotypic data, which is housed at the Mouse Phenome Database at the Jackson LaboratoryJackson Laboratory, Bar Harbor, ME. The Knockout Mouse Project is a National Institutes of Health (NIH) initiative which aims to generate a resource containing loss of function mutations for every gene in the mouse genome correlated with phenotypic data.

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Edits on 4 Dec, 2018
Meredith Hanel
Meredith Hanel edited on 4 Dec, 2018
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In human phenomics, two of the aims are to understand how the environment makes people more or less susceptible to disease and to understand individual reactions to therapies. In 2003, at the time of completion of the Human Genome Project, the need for more precisely defined phenotypes and high-throughput systems to fully take advantage of genotyping studies was projected and the creation of an international Human Phenome Project was proposed. The theme for a satellite meeting at the 2012 Annual Meeting of the American Society of Human Genetics in San Francisco by The Human Variome Project was “Getting Ready for the Human Phenome Project”. The meeting was cosponsored by the Human Genome Variation Society. ItAt that meeting it was noted that in comparison to phenome projects in model organisms such as mouse, rat and zebrafish which have compiled phenotypic data on the consequences of genetic mutations, similar scale efforts for humans lagged behind.

In humans, data on genotype-phenotype associations has been generated through genome-wide association studies (GWAS) or linking single nucleotide polymorphisms (SNPs) with disease phenotypes. To reduce the disease-centric bias in these approaches, an effort was made to look for associations in complete medical records and complete genome sequences, called Phenome Wide Association Studies (PheWAS). However human phenotype data has a strong clinical bias.

The introduction of genetic changes in animal model systems allow for unbiased interrogation of genotype-phenotype interactions. The Mouse Phenome Project was the first major effort in a vertebrate model to catalog baseline phenotypic data, which is housed at the Mouse Phenome Database at the Jackson Laboratory, Bar Harbor, ME. The Knockout Mouse Project is a National Institutes of Health (NIH) initiative which aims to generate a resource containing loss of function mutations for every gene in the mouse genome correlated with phenotypic data.

Most human genes (70%) have a counterpart (ortholog) in zebrafish, which combined with their short generation time, standard practises for genetic manipulation and suitability for live imaging make them cost-effective in biomedical research. The Zebrafish Phenome Project is underway and contribute to knowledge about phenotype-genotype associations and genetic diagnosis of human disease. The Chemical Phenomics Initiative, based on chemical genetics, is a high-throughput chemical screen for small molecules that modulate early embryonic development in zebrafish, carried out by the Hong lab at Vanderbilt University. Pharmacological targets for these small molecule developmental modulators are identified and made accessible to the scientific community through the chemotype-phenotype database on Chemical Phenomics interactive web portal. In zebrafish whole body micro-CT scanning has been used for skeletal phenomics studies.

As DNA sequencing became faster and cheaper, new knowledge about normal genetic variation in the human population allowed genetic variants once thought to cause disease to be reclassified as benign. The ranges and commonality of variations in human phenotypes if better understood could improve the accuracy and treatment of disease in genetic medicine. The Human Phenotype Ontology helps the sharing of phenotype data by standardising the vocabulary for phenotypes. For some types of phenotypic abnormalities, standardized measurements can be used to define the phenotype. To show a causal link between a genetic variant and an abnormal phenotype, it needs to be shown that the two are found together more often then expected by chance. Improvements in data about baseline population frequencies of phenotypes are needed for these calculations.

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  • The Knockout Mouse Project
  • Phenome Wide Association Studies (PheWAS)
  • Navigome
  • Chemical Phenomics Initiative
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