Abstract：With the development of modern analytical techniques such as high-throughput sequencing, the research on exploring the relationship between mechanisms and external representations in life, especially the biological phenotyping, has become more and more in-depth.The precise demands of gene, environment and phenotype association research make the standardization research of biological phenome become crucial.Because phenome covers a wide range, many species, and the phenotypic characteristics differ greatly, there is no standard to follow, which seriously restricts scientific research and industrial development.From the perspective of standardization, the related concepts and development of biological phenotypes, as well as the problems faced by the standardization of biological phenome are analyzed and predicted, so as to provide metrological technology and standard support for the high-quality development in the field of biological phenome with various types and data.
张永卓,高颖,牛春艳,傅博强,王晶. 生物表型和表型组标准化的现状与展望[J]. 计量学报, 2022, 43(10): 1382-1388.
ZHANG Yong-zhuo,GAO Ying,NIU Chun-yan,FU Bo-qiang,WANG Jing. Status and Prospects on the Standardization of Biological Phenotype and Phenome. Acta Metrologica Sinica, 2022, 43(10): 1382-1388.
［1］Park H W. Joy of Ping-Pong: Genome-Wide and Phenome-Wide Association Studies［J］. Allergy Asthma Immunol Res, 2020, 12 (5): 748-749.
［2］Gill D, Benyamin B, Moore L, et al. Associations of genetically determined iron status across the phenome: A mendelian randomization study［J］. PLoS Med, 2019, 16 (6): e1002833.
［3］Fernie A R, Gutierrez-Marcos J. From genome to phenome: genome-wide association studies and other approaches that bridge the genotype to phenotype gap［J］. Plant J, 2019, 97 (1): 5-7.
［4］Varki A, Wills C, Perlmutter D, et al. Great Ape Phenome Project?［J］. Science, 1998, 282 (5387): 239-240.
［5］Xuan J, Yu Y, Qing T, et al. Next-generation sequencing in the clinic: promises and challenges［J］. Cancer Lett, 2013, 340 (2): 284-295.
［6］Ozsolak F. Third-generation sequencing techniques and applications to drug discovery［J］. Expert Opin Drug Discov, 2012, 7 (3): 231-243.
［7］Rexroad C, Vallet J, Matukumalli L K, et al. Genome to Phenome: Improving Animal Health, Production, and Well-Being-A New USDA Blueprint for Animal Genome Research 2018-2027［J］. Front Genet, 2019, 10: 327.
［8］York L M. Functional phenomics: an emerging field integrating high-throughput phenotyping, physiology, and bioinformatics［J］. J Exp Bot, 2019, 70 (2): 379-386.
［9］Burnett K G, Durica D S, Mykles D L, et al. Recommendations for Advancing Genome to Phenome Research in Non-model Organisms ［J］. Integr Comp Biol, 2020, 60 (2): 397-401.
［10］Gjuvsland A B, Vik J O, Beard D A, et al. Bridging the genotype-phenotype gap: what does it take? ［J］. J Physiol, 2013, 591 (8): 2055-2066.
［11］Houle D, Govindaraju D R, Omholt S. Phenomics: the next challenge［J］. Nat Rev Genet, 2010, 11 (12): 855-866.
［12］Oetting W S, Robinson P N, Greenblatt M S, et al. Getting ready for the Human Phenome Project: the 2012 forum of the Human Variome Project ［J］. Hum Mutat, 2013, 34 (4): 661-666.
［13］Furbank R T, Tester M. Phenomics-technologies to relieve the phenotyping bottleneck［J］. Trends Plant Sci, 2011, 16 (12): 635-644.
［14］Gerlai R. Phenomics: fiction or the future?［J］. Trends Neurosci, 2002, 25 (10): 506-509.
［15］Braun J M, Kalloo G, Kingsley S L, et al. Using phenome-wide association studies to examine the effect of environmental exposures on human health ［J］. Environ Int, 2019, 130: 104877.
［16］Zhao C, Zhang Y, Du J, et al. Crop Phenomics: Current Status and Perspectives［J］. Front Plant Sci, 2019, 10: 714.
［17］Andrade-Sanchez P, Gore M A, Heun J T, et al. Development and evaluation of a field-based high-throughput phenotyping platform ［J］. Funct Plant Biol, 2013, 41 (1): 68-79.
［18］Fiorani F, Schurr U. Future scenarios for plant phenotyping［J］. Annu Rev Plant Biol, 2013, 64: 267-291.
［19］Kim S L, Chung Y S, Silva R R, et al. The opening of phenome-assisted selection era in the early seedling stage［J］. Sci Rep, 2019, 9 (1): 9948.
［20］Hegele R A, Oshima J. Phenomics and lamins: from disease to therapy［J］. Exp Cell Res, 2007, 313 (10): 2134-2143.
［21］Swinney D C, Anthony J. How were new medicines discovered?［J］. Nat Rev Drug Discov, 2011, 10 (7): 507-519.
［22］Wu D, Cheng Y, Wang X. Definition of clinical gene tests［J］. Cell Biol Toxicol, 2019, 35 (2): 83-87.
［23］Brown S, Nadeau J H. Precision medicine and Mammalian Genome［J］. Mamm Genome, 2019, 30 (5-6): 89.
［24］Robinson P N, Kohler S, Bauer S, et al. The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease［J］. Am J Hum Genet, 2008, 83 (5): 610-615.
［25］Lanktree M B, Johansen C T, Joy T R, et al. A translational view of the genetics of lipodystrophy and ectopic fat deposition ［J］. Prog Mol Biol Transl Sci, 2010, 94: 159-196.
［26］Tracy R P. ‘Deep phenotyping’: characterizing popula-tions in the era of genomics and systems biology［J］. Curr Opin Lipidol, 2008, 19 (2): 151-157.
［27］MacRae C A. Closing the ‘phenotype gap’ in precision medicine: improving what we measure to understand complex disease mechanisms［J］. Mamm Genome, 2019, 30 (7-8): 201-211.
［28］Cheng K C, Katz S R, Lin A Y, et al. Whole-Organism Cellular Pathology: A Systems Approach to Phenomics ［J］. Adv Genet, 2016, 95: 89-115.
［29］Bourdais G, Burdiak P, Gauthier A, et al. Large-Scale Phenomics Identifies Primary and Fine-Tuning Roles for CRKs in Responses Related to Oxidative Stress［J］. PLoS Genet, 2015, 11 (7): e1005373.
［30］Humplik J F, Lazar D, Furst T, et al. Automated integrative high-throughput phenotyping of plant shoots: a case study of the cold-tolerance of pea (Pisum sativum L. )［J］. Plant Methods, 2015, 11: 20.
［31］Shrestha R, Matteis L, Skofic M, et al. Bridging the phenotypic and genetic data useful for integrated breeding through a data annotation using the Crop Ontology developed by the crop communities of practice［J］. Front Physiol, 2012, 3: 326.
［32］Yang W, Guo Z, Huang C, et al. Genome-wide association study of rice (Oryza sativa L. ) leaf traits with a high-throughput leaf scorer ［J］. J Exp Bot, 2015, 66 (18): 5605-5615.
［33］Richesson R L, Rusincovitch S A, Wixted D, et al. A comparison of phenotype definitions for diabetes mellitus ［J］. J Am Med Inform Assoc, 2013, 20 (e2): e319-e326.
［34］Araus J L, Cairns J E. Field high-throughput phenotyping: the new crop breeding frontier［J］. Trends Plant Sci, 2014, 19 (1): 52-61.
［35］Grosskinsky D K, Svensgaard J, Christensen S, et al. Plant phenomics and the need for physiological phenotyping across scales to narrow the genotype-to-phenotype knowledge gap ［J］. J Exp Bot, 2015, 66 (18): 5429-5440.
［36］Das C S, Samal A, Awada T. Leveraging Image Analysis for High-Throughput Plant Phenotyping［J］. Front Plant Sci, 2019, 10: 508.
［37］Muller B, Martre P. Plant and crop simulation models: powerful tools to link physiology, genetics, and phenomics［J］. J Exp Bot, 2019, 70 (9): 2339-2344.
［38］Cobb J N, Declerck G, Greenberg A, et al. Nextgeneration phenotyping: requirements and strategies for enhancing our understanding of genotype-phenotype relationships and its relevance to crop improvement［J］. Theor Appl Genet, 2013, 126 (4): 867-887.
［39］Ochs M F. Knowledge-based data analysis comes of age［J］. Brief Bioinform, 2010, 11 (1): 30-39.
［40］Li R, Tsaih S W, Shockley K, et al. Structural model analysis of multiple quantitative traits［J］. PLoS Genet, 2006, 2 (7): e114.
［41］Schindelman G, Fernandes J S, Bastiani C A, et al. Worm Phenotype Ontology: integrating phenotype data within and beyond the C. elegans community ［J］. BMC Bioinformatics, 2011, 12: 32.
［42］Engel S R, Balakrishnan R, Binkley G, et al. Saccharomyces Genome Database provides mutant phenotype data ［J］. Nucleic Acids Res, 2010, 38 (Database issue): D433-D436.
［43］Hebbring S. Genomic and Phenomic Research in the 21st Century［J］. Trends Genet, 2019, 35 (1): 29-41.
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