Introduction to Multi-Omics

“Healthcare is not a privilege; it is a fundamental right.”

 

This statement of Rod Blagojevich is absolutely true. Healthcare is the basic necessity of all humans. But evolution and pollution have paved the way for several complicated diseases, whose cure is not mentioned in existing papers. Such kinds of diseases are understood and analyzed by the means of Multi-Omics Studies.

 

In this blog, we will study about multi-omics, an emerging field in medical science and the different omic strategies involved in it.

 

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What is Multi-Omics?

 

Multi-Omics is made up of two words, Multi and Omics. Jumping to the literal meaning, Multi means more than one or two. While omics is defined as a part of biology. It can be a genome, microbiome etc. It is also called integrative omics, panomics, or multi-omics. 

 

Thus, Multiomics is defined as the fusion of technology and biology. It is a new biological tactic where different sets of omic groups are combined and analyzed. The different omic approaches may include genome, proteome, epigenome, microbiome, meta-transcriptome, metabolome, and transcriptome.

 

Scientists combine these omics to analyze complex biological big data. It helps in finding novel associations between biological entities, pinpoint relevant biomarkers and to build an elaborate concept between the disease and physiology. Not only this, Multi-Omics also helps in coherently matching geno-pheno-type relationships and associations. 

 

What is a Multiomics Strategy?

 

Multi-Omics strategy is the blend of all omic fields. Climate change, atmospheric change, and human evolution have given cause to complicated syndromes and disorders. An answer or cure to such diseases cannot be done by analyzing a single form of omics. In such circumstances, Multi-Omics strategy turns out to be a savior.

 

Multiomics study combines different omic strategies together to find out the cure and treatment of different complicated diseases and allergies. Multi-Omics strategy employs all the omic fields and helps in understanding the native and altered state of an organism.

 

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Different Softwares used in Multi-Omics Studies

 

The list of different software that are used during multi-omics studies is as follow:

 

1. Omicade

 

2. MultiAssayExperiment

 

3. bioCancer

 

4. mixOmics

 

5. IMAS

 

6. MultiDataSet

 

7. SIGMA

 

8. Omics Pipe

 

9. PaintOmics

 

10. Grimon

 

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Different Omic Strategies of Multiomics Study

 

The different branches and categories of Multi-omics are listed below:

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Different omic strategies of multiomics

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1. Genomics

 

Genomics is defined as a field that involves identification of genes and genetic variants associated with a particular drug or disease. It records the response of the body to certain drugs and medications. In genomics, Genome Wide Association Studies (GWAS) are analyzed and studied to identify the genetic variants in an entire genome syndrome.

 

Genomics is performed on genotypes; a genotype is basically the collection of genes. And is expressed in the form of encoded information. Genotypes are studied to predict the risk of diseases. Thus, application can help in maintaining a healthy individual.

 

Apart from GWAS, genotype arrays, exome sequencing, and next generation sequencing is also applied in genotyping. Genotyping is performed to identify the significant differences in genetic characteristics between the healthy and diseased individuals.

 

 

2. Epigenomics

 

Epigenomics is the technique that is used to identify modifications of DNA or DNA associated proteins. Epigenomics include chemical reactions such as acetylation, deacetylation and methylation. Epigenomics changes are based on the environment and are passed onto progeny.

 

Epigenetic changes in human bodies can be responsible for metabolic syndromes, physiological disorders, and cardiovascular diseases. These tiny modifications in DNA can be responsible for different and major functional changes and most of the time are cell specific and tissue specific.

 

Epigenomics studies are done to detect the immune disorders by studying the reversible DNA modifications. It is used to study how cells control gene activity without modifying or altering the DNA sequence.

 

 

3. Transcriptomes

 

Transcriptomes is the technique used to identify the qualitative and quantitative RNA data. It reads only RNA data out of the entire genome. Only 2% of the DNA is transformed into protein. Out of the rest, 80% of the genome is transcribed, which includes coding RNA, short RNA, microRNA, piwi RNA and small nuclear RNA.

 

Talking about RNA proteins, it performs structural and regulatory functions during native and altered states. RNA also acts as an intermediate between DNA and protein. RNA alterations and defaults have an important role in diseases like adipose differentiation, diabetes, myocardial infarction, endocrine regulation and neuron growth.

 

As the role of RNA is quite crucial in the human body, thus it is essential to understand transcriptomes from time to time. Studying transcripts RNA employs techniques like next generation sequencing, RNA seq and probe-based assays.

 

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4. Proteomics

 

Proteomics is the Multiomics approach that is used to identify protein levels, modification and interaction at genomic level. These types of protein-protein interactions can be analyzed through phage display, affinity purification, and ChiP-Seq. 

 

The proteomics reactions include post-translational modifications such as phosphorylation, nitro-sialylation, acetylation, acylation, glycosylation, and ubiquitination, phosphorylation, etc.

 

These protein modifications are essential in maintaining cellular structure and function. The techniques which are involved in analyzing proteomic changes are broadly spectroscopic techniques such as mass spectroscopy, UV spectroscopy, etc. 

 

 

5. Metabolomics

 

Metabolomics is the emerging technique in biological science. It is the comprehensive analysis of metabolites in a sample. The technology plays a vital role in precising the future of medicines.

 

Metabolites of a tissue or an organism include small molecules, peptides, lipids, carbohydrates, nucleosides, and other catabolic products. Metabolomics present the final product of gene transcription.

 

It includes both signaling and structural molecules. Metabolomics studies are quite easier than proteomics. This is so because the size of the proteome is larger than the metabolome, thus difficult to analyze.

 

 

6. Microbiomics

 

As the name suggests, Microbiomics refers to all kinds of microorganisms of the community. Microbes are found in almost every part of the skin, this includes skin, mucosal surface and gut. In fact, nearly 100 trillion bacteria are present in the human gut.

 

Thus, it is essential to trace and analyze microbiota to track human health. Microbiota is an important factor to study in diseases like diabetes, obesity, cancer, heart failure and autism.

 

The microbiome studies are analyzed using techniques like 16S rRNA genes sequencing and metagenomics quantification. Microbiome study is also a newer subject in science and the process requires a lot of attention to execute. 

 

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Applications of Multiomics

 

Multi-Omics data has a wide range of applications from vaccination to crop improvement. Here is the list of some of the important applications of Multiomics:

 

1. Multi-Omics approach gives us the way to see the impact and effect of a disease on a single cell resolution level.

 

2. It is important to find all the factors responsible for syndromes. These include factors like cell variations and alterations.

 

3. Multi-Omics studies help in collecting data that can never be gathered solely from transcriptomic studies.

 

4. This fusion of machine learning and biomedical data has given the rise to several biomarkers in the market.

 

5. Multiomics has filled the gap between researchers and human health and diseases studies.

 

6. It is a scientific and technical approach to generate and analyze disease related data.

 

7. Multi-Omics data also help in understanding host-pathogen interactions.

 

8. It is the best way to understand communicable and infectious diseases.

 

9. Multi-Omics data help in developing personalized medicines.

 

10. The chronic and complex disease can be cured by analyzing multi omic data.

 

11. The Multi-Omics data help in better understanding of complex reactions of the human immune system.

 

12. Interactive Multiomics has also been employed to check the side effects and effectiveness of vaccines. This field has been in great use during the time of coronavirus vaccine development.

 

13. Multi-Omics studies are also used in improving agriculture by the means of crop development.

 

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Though still in its infancy stage, multi omics are an essential element for the future. The multi omic data in near future can be expected to improve the healthcare facilities and mark an excellence in the same.