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Genome Wide Association Study in Animals

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Identifying genes associated with diseases has always been a promising area for the scientific community. Traditional ways exists for such gene identification which has its own set of limitations. With this comes the development of novel ways that uses the knowledge of a species genome. One such way is through the genome wide association studies (GWAS) whereby the desired traits are identified through finding out genes associated with those specific traits .

Scientists are mostly benefited with such genome wide association studies as it can identify those genes which are associated with complex diseases.  A large number of individuals are considered where the entire genome or the whole pool of DNA is studied to find out variations within their genomes. Mostly, the variations are in the form of single nucleotide polymorphisms, commonly referred to as the SNPs. Other form of variations studied through GWAS is the copy number or the sequence variations. The studies are capable of observing a large number of SNPs at one single time providing the knowledge of which SNPs are more frequently present in the diseased condition compared to the normal state. Often very large sample size is usually required to study these associations [1].

Statistical methodologies are usually a means towards understanding these associations. With much higher statistical power, the sample sizes considered for the GWAS studies can be broadened up to million genome samples from participants. Few benefits in GWAS studies include:

  • Identifying new variants associated with diseased traits.
  • Providing genotypic information which can be applied in the treatment of disease such as drug discovery or early detection.
  • Generating data which is easy shareable. This prompts the researchers and the scientific community to further undergo analysis into the data.

The term genome wide mostly surfaces the fact that a lot of SNPs are looked at a single time within the genome of the population. Apart from the gene identification, scientists could now understand how a disease develops or how it can be treated. Reports have stated the application of genome wide association studies in understanding diseases such as Diabetes, Parkinson's, etc. It has also provided us an insight into the SNPs associated with obesity and condition such as age-related macular degeneration (AMD). Also the association of some new genes could be observed which were absent in the earlier times [2].

The emerging technologies of high throughput sequencing at the whole genome level has aided towards the much higher applicability of the technique.  However, one of the biggest challenges in GWAS is the interpretation of the associations. Meaningful insight into the associations is necessary for understanding the biology of diseases.  GWAS is one of the applications of the high throughput sequencing technique "NGS". The recent years have seen the development of essential tools from NGS in the identification of genetic markers for different genotypes.

Although GWAS has a wide applicability in understanding diseases, practically understanding the influence of the genes over the disease takes some time.  It is only through this practical knowledge that enables the scientist to explore therapeutics or treatments for the disease.

Reference

  1. https://www.nature.com/articles/s43586-021-00056-9
  2. https://www.yourgenome.org/stories/genome-wide-association-studies/

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