Genes that contribute to variable traits
Characteristics of living things are determined by an organism's genes, and can be passed from parent to offspring. Many variations within a population cannot, however, be explained simply by the action of a single gene, and are rather a result of interactions between genes, proteins and other cellular components. Type 2 diabetes is a prime example of a complex trait. While certain genes make an individual more susceptible to developing insulin resistance, there are a host of cellular interactions that help determine whether that person develops diabetes. The EU-funded INTGENMAP (Genetic mapping of complex trait intermediates) project aimed to understand the genetic basis of complex traits and looked into ways of influencing these traits. When traits are controlled by quantitative trait loci in genes, gene and protein interactions at the level of cells, tissues and organs influence the global trait. To understand how gene products impact global traits, INTGENMAP measured protein levels in a genetically well-characterised yeast strain. By looking at the entire yeast genome, researchers "mapped" where genes for complex traits were located. They also determined how each gene contributed to changes in protein abundance in single cells and in populations. They found that the sequence of a gene and the DNA surrounding that gene together have the largest effect on protein levels. Finally, researchers used this data to design guide RNA molecules (gRNA’s) to use with the CRISPR/Cas9 gene editing system to repress specific genes such as those involved in drug resistance. They showed that this strategy could successfully influence complex traits at the cellular level, paving the way for future gene therapy. In the future, similar work on human cells may lead to therapies targeting genes that make people more susceptible to conditions like diabetes or Alzheimer's disease. Furthermore, the research can now be expanded to address the worsening situation brought about by antimicrobial resistance.
Keywords
Genes, diabetes, complex trait, genetic mapping, protein level, yeast genome
