Omics technologies such as genomics and high-throughput DNA sequencing were introduced in parallel to the Human Genome Project since 1990s. According to one etymological analysis, the suffix 'ome' is derived from the Sanskrit OM ("completeness and fullness") (Lederberg and McCray, 2001). By combining 'gene' and 'ome', Hans Winkler created the term genom(e), referring to "the haploid chromosome set, which, together with the pertinent protoplasm, specifies the material foundations of the species [...]." (Winkler, 1920). Victor McKusick and Frank Ruddle added 'genomics' to the scientific lexicon as the title for the new journal they co-founded in 1987, with emphasis on linear gene mapping, DNA sequencing and comparison of genomes from different species (McKusick and Ruddle, 1987).
Omics technologies and various neologisms that define their application contexts, however, are more than a simple play on words. They substantially transformed both the throughput and the design of scientific experiments. The omics technologies allow the generation of copious amounts of data at multiple levels of biology from gene sequence and expression to protein and metabolite patterns underlying variability in cellular networks and function of whole organ systems (Nicholson and Lindon, 2008; Wilke et al., 2008). In fact this led to overabundance of data in biomedical experiments recently (Nicholson, 2006). While the 1990s was named as the 'decade of the brain', we are now in the 'decade of measurements'. This signals a new era - in how we approach to scientific inquiries. That is, the arrival of 'big biology' and a systems (integrative) approach to scientific practice with global measurements of molecular pathways in health and disease (Baccini et al., 2008; Naylor et al., 2008; Nicholson and Lindon, 2008; Ozdemir et al., 2009).
In addition to amplified throughput, the process of research is fundamentally altered in 'omics science'. Ordinarily, scientists have accustomed to hypothesis-driven research wherein a clearly articulated scientific question/hypothesis would be posed. Subsequently experiments would be carried out to obtain data in order to test the study hypothesis. With the omics approach, asking an initial research question is not always necessary or a pre-requisite. Genome or proteome wide data can be collected in an omics experiment without an existing hypothesis, followed by generation and testing of biological hypotheses. This reversal from the 'first hypothesize-then-experiment' tradition to 'first experiment-then-hypothesize' mode of operation offers the promise to discover unprecedented pathophysiological mechanisms of disease as well as response and toxicity to drugs and nutrition.
Ultimately, it is thought that the omics science and technologies will markedly improve the simplistic and reductionist experimental models that offer merely a temporal snap shot of the much more complex, longitudinal and dynamic nature of biological networks (and their fluctuations in response to social/environmental exposures) that fundamentally govern human health and disease.
Modified from V. Ozdemir, G. Suarez-Kurtz, R. Stenne, A. A. Somogyi, S. O. Kayaalp and E. Kolker (2009) “Risk assessment and communication tools for genotype associations with multifactorial phenotypes: the concept of ‘edge effect’ and cultivating an ethical bridge between omics innovations and society” OMICS: Journal of Integrative Biology 13(1): 43-62.
References
Baccini, M., Bachmaier, E.M., Biggeri, A., Boekschoten, M.V., Bouwman, F.G., Brennan, L., et al. The NuGO proof of principle study package: a collaborative research effort of the European Nutrigenomics Organisation. Genes Nutr. 2008; 3: 147-51.
Lederberg, J., McCray, A.T. 'Ome sweet 'omics: -- A genealogical treasury of words. The Scientist 2001; 15(7): 8.
McKusick, V.A., Ruddle, F.H. Toward a complete map of the human genome. Genomics 1987; 1: 103-06.
Naylor, S., Culbertson, A.W., Valentine, S.J. Towards a systems level analysis of health and nutrition. Curr Opin Biotechnol 2008; 19(2): 100-09.
Nicholson, J.K. Reviewers peering from under a pile of 'omics' data. Nature 2006; 440(7087): 992.
Ozdemir, V., Suarez-Kurtz, G., Stenne, R., Somogyi, A., Someya, T., Kayaalp, S.O., Kolker, E. Risk assessment and communication tools for genotype associations with multifactorial phenotypes: The concept of ‘edge effect’ and cultivating an ethical bridge between omics innovations and society. OMICS: Journal of Integrative Biology 2009; 13(1) 43-62.
Wilke, R.A., Mareedu, R.K., Moore, J.H. The pathway less traveled: Moving from candidate genes to candidate pathways in the analysis of genome-wide data from large scale pharmacogenetic association studies. Current Pharmacogenomics and Personalized Medicine 2008; 6(3): 150-59.
Winkler, H. (1920) Verbreitung und Ursache der Parthenogenesis im Pflanzen- und Tierreiche. Verlag von Gustav Fischer: Jena.
We updated our literature reviews in the fields of ethics & nutrigenomics, public health genomics, pharmacogenomics, human enhancement, and the genetics of brain disorders. Click on a research area icon (on the main page) and select the... Read more
We updated our literature reviews in the fields of ethics & nutrigenomics, public health genomics, pharmacogenomics, human enhancement, and the genetics of brain disorders. Click on a research area icon (on the main page) and select the section "Related material" to consult our selections of references.
