Symposium review: Omics in dairy and animal science--Promise, potential, and pitfalls

Authors: Lippolis, John; POWELL, ELLIS - Oak Ridge Institute For Science And Education (ORISE); Reinhardt, Timothy; Thacker, Tyler; Casas, Eduardo

Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/6/2018
Publication Date: 5/1/2019
Citation: Lippolis, J.D., Powell, E.J., Reinhardt, T.A., Thacker, T.C., Casas, E. 2019. Symposium review: omics in dairy and animal science-promise, potential, and pitfalls. Journal of Dairy Science. 102(5):4741-4754. https://doi.org/10.3168/jds.2018-15267.
DOI: https://doi.org/10.3168/jds.2018-15267

Interpretive Summary: Advances in the last 15 years have allowed the complete sequencing to genomes and their associated transcripts and proteins. In place of studying one gene or protein at a time, technology allows us to almost observe nearly all of them in what are called genomics, transcriptomics, or proteomic experiments. These omic technologies have a lot of potential. However, the potential is mitigated by the quality of the databases that are foundational for these techniques. These technologies also the ability to analyze ‘everything’ that is going on at a single moment with regards to processes involved in animal health, disease resistance, or animal production, with the promise of identifying the most relevant and important factors. However, these observations can provide new insight into basic biological processes, but must be followed up with specific experiments to truly identify the causes of processes involved in animal health and production. Omics technologies can open new avenues to research, but those new avenues must be followed up with basic research to truly understand the biological processes.

Technical Abstract: Sequencing the first genome took 15 years and $3 billion dollars to complete. Today you can sequence a genome in a day for a few thousand dollars. Comparing the relative abundance of nearly every messenger RNA transcript and small RNAs from cells and tissues from different experimental conditions has become so easy that it can take longer to transfer the data between computers than to perform the experiment. Nucleotide sequencing techniques have become so sensitive that the biggest concern is not false negative, but false positive data or transcripts or proteins incorrectly identified as in the sample. Better genome sequencing has led to more complete transcriptomic and proteomic databases and along with more sensitive instrumentation and separation techniques, which are bringing us closer to achieving the detection a complete proteome. The promise of these powerful omics techniques is to lead us to new and unexpected connections between molecular processes in the context of animal health. This promise cannot be achieved without hypothesis-driven research that connects omics data with animal health experiments. Any researcher who wishes to invest the time and resources into an omics experiments should be aware of the common pitfalls and limitations of these techniques. Important questions one should consider are: What is the quality of the databases and how they are annotated? Are the annotations based on experimental results or computational predictions? What assumptions are made by the analysis algorithms and how will this affect the result? Finally, how can the research community use the vast amount of data being generated by omics experiments in ways to achieve the goals of better animal health and production, which is the promise of omics technologies. Until the observation shown in omics dataset is used to achieve these goals of better animal health and production, the promises of omics technology will remain unfulfilled.