In this chapter, we focused on a number of interesting applications of genetic engineering, genomics, and biotechnology. At the same time, we found many opportunities to consider the methods and reasoning by which much of this information was acquired. From the explanations given in the chapter, what answers would you propose to the following fundamental questions? From GWAS how do we know which genes are associated with a particular genetic disorder?

Key Concepts

Genome-Wide Association Studies (GWAS)

GWAS are research methods used to identify genetic variants associated with specific diseases by scanning the genomes of many individuals. By comparing the DNA of affected individuals to that of healthy controls, researchers can pinpoint variations that occur more frequently in those with the disorder, suggesting a link between those genes and the condition.

Single Nucleotide Polymorphisms (SNPs)

SNPs are the most common type of genetic variation among people, where a single nucleotide in the genome differs between individuals. In GWAS, researchers often focus on SNPs to identify associations with diseases, as these variations can influence gene function and contribute to the risk of developing certain genetic disorders.

Statistical Significance in Genetic Studies

Statistical significance is crucial in GWAS to determine whether the observed associations between genetic variants and diseases are likely due to chance. Researchers use p-values to assess significance, with lower values indicating stronger evidence that a particular SNP is genuinely associated with the disorder, thus helping to validate findings and guide further research.