Phenome

A phenome is the set of all phenotypes expressed by a cell, tissue, organ, organism, or species.

Not to be confused with phoneme.

Just as the genome and proteome signify all of an organism's genes and proteins, the phenome represents the sum of its phenotypic traits. Examples of human phenotypic traits are skin color, eye color, body height, or specific personality characteristics. Although any phenotype of any organism has a basis in its genotype, phenotypic expression may be influenced by environmental influences, mutation, and genetic variation such as single nucleotide polymorphisms (SNPs), or a combination of these factors.

Phenomics is the study of the phenome and how it is determined, particularly when studied in relation to the set of all genes (genomics) or all proteins (proteomics).

Origin and usage

The term was first used by Davis in 1949, "We here propose the name phenome for the sum total of extragenic, non-autoreproductive portions of the cell, whether cytoplasmic or nuclear. The phenome would be the material basis of the phenotype, just as the genome is the material basis of the genotype."[1]

Although phenome has been in use for many years, the distinction between the use of phenome and phenotype is problematic. A proposed definition for both terms as the "physical totality of all traits of an organism or of one of its subsystems" was put forth by Mahner and Kary in 1997, who argue that although scientists tend to intuitively use these and related terms in a manner that does not impede research, the terms are not well defined and usage of the terms is not consistent.[2]

Some usages of the term suggest that the phenome of a given organism is best understood as a kind of matrix of data representing physical manifestation of phenotype. For example, discussions led by A.Varki among those who had used the term up to 2003 suggested the following definition: “The body of information describing an organism's phenotypes, under the influences of genetic and environmental factors”.[3] Another team of researchers characterize "the human phenome [as] a multidimensional search space with several neurobiological levels, spanning the proteome, cellular systems (e.g., signaling pathways), neural systems and cognitive and behavioural phenotypes."[4]

Plant biologists have started to explore the phenome in the study of plant physiology.[5]

In 2009, a research team demonstrated the feasibility of identifying genotype-phenotype associations using electronic health records (EHRs) linked to DNA biobanks. They called this method phenome-wide association study (PheWAS).[6]

See also

References
  1. Davis BD (January 1949). "The Isolation of Biochemically Deficient Mutants of Bacteria by Means of Penicillin". Proceedings of the National Academy of Sciences of the United States of America. 35 (1): 1–10. Bibcode:1949PNAS...35....1D. doi:10.1073/pnas.35.1.1. PMC 1062948. PMID 16588845.
  2. Loeffler M, Bratke T, Paulus U, Li YQ, Potten CS (May 1997). "Clonality and life cycles of intestinal crypts explained by a state dependent stochastic model of epithelial stem cell organization". Journal of Theoretical Biology. 186 (1): 41–54. doi:10.1006/jtbi.1996.0340. PMID 9176636.
  3. Varki A, Altheide TK (December 2005). "Comparing the human and chimpanzee genomes: searching for needles in a haystack". Genome Research. 15 (12): 1746–58. doi:10.1101/gr.3737405. PMID 16339373.
  4. Siebner HR, Callicott JH, Sommer T, Mattay VS (November 2009). "From the genome to the phenome and back: linking genes with human brain function and structure using genetically informed neuroimaging". Neuroscience. 164 (1): 1–6. doi:10.1016/j.neuroscience.2009.09.009. PMC 3013363. PMID 19751805.
  5. Furbank, Robert T.; Tester, Mark (December 2011). "Phenomics--technologies to relieve the phenotyping bottleneck". Trends in Plant Science. 16 (12): 635–644. doi:10.1016/j.tplants.2011.09.005. ISSN 1878-4372. PMID 22074787.
  6. Denny, Joshua C.; Ritchie, Marylyn D.; Basford, Melissa A.; Pulley, Jill M.; Bastarache, Lisa; Brown-Gentry, Kristin; Wang, Deede; Masys, Dan R.; Roden, Dan M.; Crawford, Dana C. (2010-05-01). "PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations". Bioinformatics (Oxford, England). 26 (9): 1205–1210. doi:10.1093/bioinformatics/btq126. ISSN 1367-4811. PMC 2859132. PMID 20335276.
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.