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What Are Omics Sciences?

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Periparturient Diseases of Dairy Cows

Abstract

The word omics refers to a field of study in biological sciences that ends with -omics, such as genomics, transcriptomics, proteomics, or metabolomics. The ending -ome is used to address the objects of study of such fields, such as the genome, proteome, transcriptome, or metabolome, respectively. More specifically genomics is the science that studies the structure, function, evolution, and mapping of genomes and aims at characterization and quantification of genes, which direct the production of proteins with the assistance of enzymes and messenger molecules. Transcriptome is the set of all messenger RNA molecules in one cell, tissue, or organism. It includes the amount or concentration of each RNA molecule in addition to the molecular identities. The term proteome refers to the sum of all the proteins in a cell, tissue, or organism. Proteomics is the science that studies those proteins as related to their biochemical properties and functional roles, and how their quantities, modifications, and structures change during growth and in response to internal and external stimuli. The metabolome represents the collection of all metabolites in a biological cell, tissue, organ, or organism, which are the end products of cellular processes. Metabolomics is the science that studies all chemical processes involving metabolites. More specifically, metabolomics is the study of chemical fingerprints that specific cellular processes establish during their activity; it is the study of all small-molecule metabolite profiles. Overall, the objective of omics sciences is to identify, characterize, and quantify all biological molecules that are involved in the structure, function, and dynamics of a cell, tissue, or organism.

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References

  • Aebersold R, Mann M (2003) Mass spectrometry-based proteomics. Nature 422(6928):198–207. doi:10.1038/nature01511

    Article  CAS  PubMed  Google Scholar 

  • Bai YS, Sartor M, Cavalcoli J (2012) Current status and future perspectives for sequencing livestock genomes. J Anim Sci Biotechnol 3:8. doi:10.1186/2049-1891-3-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Brun V, Dupuis A, Adrait A, Marcellin M, Thomas D, Court M, Vandenesch F, Garin J (2007) Isotope-labeled protein standards: toward absolute quantitative proteomics. Mol Cell Proteomics 6(12):2139–2149. doi:10.1074/mcp.M700163-MCP200

    Article  CAS  PubMed  Google Scholar 

  • Capomaccio S, Milanesi M, Bomba L, Vajana E, Ajmone-Marsan P (2015) MUGBAS: a species free gene-based programme suite for post-GWAS analysis. Bioinformatics 31(14):2380–2381. doi:10.1093/bioinformatics/btv144

    Article  CAS  PubMed  Google Scholar 

  • Chandramouli K, Qian PY (2009) Proteomics: challenges, techniques and possibilities to overcome biological sample complexity. Hum Genomics Proteomics 2009. doi:10.4061/2009/239204

  • Goddard ME, Hayes BJ (2007) Genomic selection. J Anim Breed Genet 124(6):323–330. doi:10.1111/j.1439-0388.2007.00702.x

    Article  CAS  PubMed  Google Scholar 

  • Gondro C, JVD W, Hayes B (2013) Genome-wide association studies and genomic prediction, Methods of molecular biology, vol 1019. Humana Press, New York

    Google Scholar 

  • Hood L (2002) A personal view of molecular technology and how it has changed biology. J Proteome Res 1(5):399–409. doi:10.1021/pr020299f

    Article  CAS  PubMed  Google Scholar 

  • Lippolis JD, Reinhardt TA (2008) Centennial paper: Proteomics in animal science. J Anim Sci 86(9):2430–2441. doi:10.2527/jas.2008-0921

    Article  CAS  PubMed  Google Scholar 

  • Loor JJ (2010) Genomics of metabolic adaptations in the peripartal cow. Animal 4(7):1110–1139. doi:10.1017/S1751731110000960

    Article  CAS  PubMed  Google Scholar 

  • May C, Brosseron F, Chartowski P, Schumbrutzki C, Schoenebeck B, Marcus K (2011) Instruments and methods in proteomics. Methods Mol Biol 696:3–26. doi:10.1007/978-1-60761-987-1

    Article  CAS  PubMed  Google Scholar 

  • Meuwissen THE, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157(4):1819–1829

    CAS  PubMed  PubMed Central  Google Scholar 

  • Nicolazzi EL, Biffani S, Biscarini F, Orozco Ter Wengel P, Caprera A, Nazzicari N, Stella A (2015) Software solutions for the livestock genomics SNP array revolution. Anim Genet 46(4):343–353. doi:10.1111/age.12295

    Article  CAS  PubMed  Google Scholar 

  • Oliver SG, Winson MK, Kell DB, Baganz F (1998) Systematic functional analysis of the yeast genome. Trends Biotechnol 16(9):373–378

    Article  CAS  PubMed  Google Scholar 

  • Poddar S, Kesharwani D, Datta M (2017) Interplay between the miRNome and the epigenetic machinery: implications in health and disease. J Cell Physiol. doi:10.1002/jcp.25819

  • Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, Sham PC (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81(3):559–575. doi:10.1086/519795

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Rivers J, Simpson DM, Robertson DH, Gaskell SJ, Beynon RJ (2007) Absolute multiplexed quantitative analysis of protein expression during muscle development using QconCAT. Mol Cell Proteomics 6(8):1416–1427. doi:10.1074/mcp.M600456-MCP200

    Article  CAS  PubMed  Google Scholar 

  • Romao JM, Jin W, Dodson MV, Hausman GJ, Moore SS, Guan LL (2011) MicroRNA regulation in mammalian adipogenesis. Exp Biol Med 236(9):997–1004. doi:10.1258/ebm.2011.011101

    Article  CAS  Google Scholar 

  • Sauerwein H, Bendixen E, Restelli L, Ceciliani F (2014) The adipose tissue in farm animals: a proteomic approach. Curr Protein Pept Sci 15(2):146–155

    Article  CAS  PubMed  Google Scholar 

  • Schena M, Shalon D, Davis RW, Brown PO (1995) Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270(5235):467–470

    Article  CAS  PubMed  Google Scholar 

  • Vailati-Riboni M, Elolimy A, Loor JJ (2016) Nutritional systems biology to elucidate adaptations in lactation physiology of dairy cows. In: Kadarmideen HN (ed) Systems biology in animal production and health, vol 2. Springer International Publishing, Cham, pp 97–125. doi:10.1007/978-3-319-43332-5

    Chapter  Google Scholar 

  • Voelkerding KV, Dames SA, Durtschi JD (2009) Next-generation sequencing: from basic research to diagnostics. Clin Chem 55(4):641–658. doi:10.1373/clinchem.2008.112789

    Article  CAS  PubMed  Google Scholar 

  • Wasinger VC, Cordwell SJ, Cerpa-Poljak A, Yan JX, Gooley AA, Wilkins MR, Duncan MW, Harris R, Williams KL, Humphery-Smith I (1995) Progress with gene-product mapping of the Mollicutes: Mycoplasma genitalium. Electrophoresis 16(7):1090–1094

    Article  CAS  PubMed  Google Scholar 

  • Zhang A, Sun H, Wang P, Han Y, Wang X (2012) Modern analytical techniques in metabolomics analysis. Analyst 137(2):293–300. doi:10.1039/c1an15605e

    Article  CAS  PubMed  Google Scholar 

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Correspondence to Juan J. Loor Ph.D. .

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Vailati-Riboni, M., Palombo, V., Loor, J.J. (2017). What Are Omics Sciences?. In: Ametaj, B. (eds) Periparturient Diseases of Dairy Cows. Springer, Cham. https://doi.org/10.1007/978-3-319-43033-1_1

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