Application of Omics Tools in Veterinary & Animal Science Research
Omics is a term that refers to the recently developed high throughput technologies that include genomics, functional genomics (transcriptomics), proteomics, and metabolomics.
Omics is a term that is used to refer to the combination of technologies used to characterize and quantify pools of biological molecules. These technologies also aid us in exploring the roles and actions of the biological molecules in the cells of living beings. Some common types of omics are proteomics (examination of proteins), metabolomics (the chemical processes involving metabolites), transcriptomics (study of RNA molecules), and genomics (detection of genes).
Omics, which is a multiple biotechnology based on the genomics, focuses on global and high-throughput analytical methods to investigate the mechanisms of life evolution and the role of genes (Yan et al., 2015). Saving genomics, omics includes proteomics, transcriptomics, and metabolomics. Meanwhile, a large quantity of information, such as the information about phylogeny, virulence, antibiotic resistance and other aspects of microbes, has been revealed about cells, microbes, and human in the past two decades. With abundant data and increasing accuracy, omics is applied in many life science aspects including microorganism. Genus Streptococcus is one of the most invasive groups of bacteria that causes both human and animal’s disease.
Technologies that measure some characteristic of a large family of cellular molecules, such as genes, proteins, or small metabolites, have been named by appending the suffix “-omics,” as in “genomics.” Omics refers to the collective technologies used to explore the roles, relationships, and actions of the various types of molecules that make up the cells of an organism.
These technologies include:
- Genomics, “the study of genes and their function” (Human Genome Project (HGP), 2003)
- Proteomics, the study of proteins
- Metabonomics, the study of molecules involved in cellular metabolism
- Transcriptomics, the study of the mRNA
- Glycomics, the study of cellular carbohydrates
- Lipomics, the study of cellular lipids
Omics technologies provide the tools needed to look at the differences in DNA, RNA, proteins, and other cellular molecules between species and among individuals of a species. These types of molecular profiles can vary with cell or tissue exposure to chemicals or drugs and thus have potential use in toxicological assessments. Omics experiments can often be conducted in high-throughput assays that produce tremendous amounts of data on the functional and/or structural alterations within the cell. “These new methods have already facilitated significant advances in our understanding of the molecular responses to cell and tissue damage, and of perturbations in functional cellular systems” (Aardema & MacGregor, 2002).
The -omics technologies will continue to contribute to our understanding of toxicity mechanisms. Regulators are interested in these new technologies but are still sorting out how to incorporate the new information and technologies in regulatory decision making. For example, the US Food and Drug Administration’s Pharmacogenomic Data Submissions guidance document encourages the voluntary submission of genomics data but notes that the field of pharmacogenomics is still in its early developmental stages.
These state-of-the-art technologies can be applied to the measurement of metabolism on an organism, tissue, or cell at a molecular level. Genomics is the study of an organism’s entire genome and especially the analysis of the relationship between genetics and the phenotype (the measurable traits of the organism).
The whole genome sequence is now available for most livestock species and this has allowed researchers to discover and assess the unique genomic features and the complexity and structure of the genomes of livestock. This provides the molecular basis to link genomic information to economically important traits. For example, these tools can be used to “genotype” individual animals and begin to predict their breeding value or performance for traits such as feed efficiency, product quality or even susceptibility to disease.
Transcriptomics (measuring abundance of messenger RNA) studies when and how the genes in the genome can be turned on and off, which allows new molecular phenotypes to be identified or new insights into the processes underlying metabolism; for example under different nutritional management or across different stages of production.
Furthermore, proteomics and metabolomics can determine the entire set of proteins and metabolites in a biological system and how they can directly determine the biological process relating to traits of interest.
The integration of Omics technologies generates information that links variation in the genome with metabolism and nutritional physiology of livestock species. In turn, producers can use this information to apply a systematic approach to improve the breeding and management of their animals: improving performance potential, health, or the animal’s response to different nutrition or management measures.
Application of livestock has great potential for the future development of breeding and nutritional strategies to the improve efficiency and sustainability of animal production.
The first omics technologies were the automated DNA sequencer and the ink-jet DNA synthesizer, which were developed by Leroy Hood and colleagues in the early 1990s. Around the same time, the same group of scientists introduced the protein sequencer and protein synthesizer to study proteins. Concomitantly, Frank Baganz and his group were leading the emergence of metabolomics studies.
The fundamental principle of these approaches is that a complex system can be better understood if considered as a whole. They are high-throughput biochemical assays, which measure identical molecules from a biological sample. The “omics” notion alludes to the fact that nearly all instances of the targeted molecular space are measured in a particular assay. Therefore, omics provide thorough and holistic views of a given biological system.
Genomics
Genomics (study of the genome) refers to the detailed study of the complete set of DNA in an organism. Next-generation sequencing (NGS) has been instrumental in the acquisition of genome-scale data. Scientists are now much better equipped to understand whole genomes and reduce the existing gap between genotype and phenotype.
Owing to genomics, genome-wide association studies (GWAS) have become the gold standard to detect regions, in humans and other species, associated with complex traits of interest. They can easily map causal genes with modest effects. A large number of genes are being simultaneously mapped and this can help us eliminate the drawbacks of traditional genetic association approaches, thereby, furthering our knowledge of peripartal diseases.
In the future, individual genome sequencing will help us understand the quantitative differences associated with environmental factors and, thereby, guide the design for more effective animal disease control.
Transcriptomics
The transcriptome can be defined as the complete set of RNAs being produced from the genome at a given point in time. RNA-based sequencing technologies have developed immensely, which has brought about an expansion of transcriptomics. This advancement allows for the determination of both the presence and amount of different RNA molecules.
The Columbia University’s transcriptome test, which is used in pediatric oncology cases, is an example of the clinical impact of these latest advancements. Furthermore, the recent introduction of NGS technology has revolutionized transcriptomics. It allows RNA analysis through cDNA sequencing on a massive scale and helps eliminate several challenges posed by microarray technologies. The latest advancements in RNA sequencing have also enabled the understanding of complex regulatory mechanisms (e.g., epigenetics).
Proteomics
Proteomics involves the study of the overall composition, function, structure, and interaction of the proteins that influence the activities within cells. It has brought about rapid advances in medicine.
In the case of Alzheimer’s disease, proteomics has led to the identification of proteins not previously associated with the condition. This has provided novel insights into the molecular basis of the disease and potential new diagnostic markers.
In oncology, proteomics provides information on many clinically relevant protein targets for therapeutic intervention. Proteomics is also being adopted by livestock researchers to identify and quantify protein species of complex biological samples. In terms of methods, the core of modern proteomics is mass spectrometry (MS). However, different types of liquid chromatography (LC or HPLC) are also used to create a streamed pipeline analysis and enhance automation.
Metabolomics
Metabolomics is the study of all metabolites and low molecular weight compounds contained in a particular biological specimen. Nuclear magnetic resonance imaging (NMR) and mass spectroscopy techniques are used for the analysis and current metabolomics testing can profile hundreds to thousands of metabolites.
Many diseases can be diagnosed by thoroughly analyzing the metabolome and this presents the opportunity to discover new biomarkers for therapeutic monitoring, diagnosing, and devising new therapeutic targets. The application of metabolomics in diagnostics is not new.
In the United States, a urine-based test to detect metabolites, related to pre-cancerous colorectal polyps, is licensed and is significantly more sensitive than pre-existing methods. In the case of rare diseases, there has been an exciting new development. Scientists have now adopted a mass spectroscopy approach to diagnose cholesterol storage disorder from newborn bloodspot samples. This has allowed faster diagnosis and treatment so that the disease does not worsen and bears neurological symptoms.
- Epigenomics:is the study of all of the reversible modifications attached to the DNA or to the histone molecules that house the DNA. These modifications can influence the rate of gene expression, without altering the DNA. A wide variety of environmental factors, such as stress and nutrition, can influence the epigenome.
The use of Omics techniques to investigate the effects of challenges and treatments in livestock on a broad molecular level is a major development in animal and nutrition research.
These new types of analyses allow a much deeper systematic insight into the biology of animals and their interaction with nutrition, but they also bring new challenges. Omics is not a field of science, rather a set of methods used to measure experimental subjects in specific research questions.
At their core, Omics techniques aim to measure the total composition of a specific biochemical group: (meta)genomics for DNAs, transcriptomics for RNAs, proteomics for proteins, metabolomics for small hydrophilic compounds, and lipidomics for small lipophilic compounds. The physiochemical properties of the chemical entities of interest determine the analytical method used. Therefore, there is a split in Omics between sequencing-based methods for DNA and RNA and mostly mass-spectrometry based methods for proteins, metabolites and lipids.
In all methods, however, the ability to measure many molecules at once is traded off with the ability to measure the absolute concentration of those molecules. Additional trade-offs are a limited sensitivity for sequenced-based methods, and a lower precision for mass-spectrometry-based methods in comparison to their targeted counterparts.
Notably, due to the amount of data generated in comparison to classical analytical methods, visualisation of data and results with graphs is an essential step in any Omics data analysis. Usually, Principal Component Analysis (PCAs) or Principal Coordinate Analysis (PCoAs) are utilised to investigate general differences between samples and show the effect of experimental treatment on the Omics entity under investigation.
For statistically significant effects, heatmaps or volcano plots are useful to guide the selection of interesting molecular patterns. Furthermore, researchers categorise the genes, and other molecules, according to an associated function, which was previously described by other researchers and collected in databases. Often one molecule is involved in many processes, and one process is comprised of many molecules. These many-to-many relationships make interpretation of the data difficult, but with careful consideration of the biological context, these pathway associations can guide the researcher to a useful, testable hypothesis about the inner working of the investigated samples.
The fundamental achievement of Omics is that a phenotypic observation – the composite observable characteristics or traits of an organism – in an animal trial can be combined with measurements of most molecules which make up the biological environment in a sample (Figure 1). Thus, visual and other known differences between the samples can support the interpretation of Omics results and lead to a conclusion that explains the molecular mechanism causing the phenotype.
However, while Omics methods give an idea about how the whole biological system under investigation changes, it is not the best choice to show how a specific part of the system changes. Thus, targeted methods, or a targeted new experiment, need to complement trials with Omics methods to test the hypotheses from the Omics results.
Omics methods cannot replace a phenotypic finding like better feed conversion ratio or faster vaccination response, but they can guide the researcher towards a targeted, testable, hypothesis about the underlying molecular mechanism behind it.
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