Researchers Establish a Baseline to Help Better Understand Gene Regulation and Expression

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Scientists first decoded a draft of the human genome back in 2000, but since then many other questions have arisen that have yet to be answered including these two are due to be addressed in a new Princeton study:  Is it possible to develop a mechanistic model to successfully demonstrate how healthy bodies function?; and Could this model be used to understand how certain diseases develop?

Earlier this month a group of international researchers came very close to answering yes to those questions.  Genetic variation effects gene regulation in 44 different human tissue types.  This information gives researchers a baseline in which to work from to gain a better understanding as to the diversity of the genetic roles in maintaining human tissues.  The work is proof that it is possible to use multi-tissue, multi-individual data to correctly identify gene regulation mechanisms and in doing so gives researchers the chance to learn the genetic basis of various complex diseases.

Researchers Establish a Baseline to Help Better Understand Gene Regulation and Expression

An international team of researchers reached a major milestone in decoding the human genome by linking genes across all chromosome of many individual people to specific tissues and disease processes. Using tissue samples donated from 449 people, the researchers linked nearly 20,000 genes to 44 tissue types. In the illustration, each tissue type is followed by the number of genes whose level of activity is controlled by nearby genes on the same chromosome (cis); those whose activity is associated with genes on other chromosomes (trans); and the number of tissue samples studied. GTEx consortium

“The ultimate goal is to understand gene expression and gene regulation in a diversity of tissue types,” said Barbara Engelhardt, one of the authors of the study, a GTEx principal investigator, and an assistant professor in the Department of Computer Science at Princeton University.”  “This is absolutely critical to understanding how dysregulation may lead to disease.”  So far, we’re only at the start of uncovering how genetic variation in our genes helps to shape the way a person develops and what traits they may have.  Next scientists want to learn how these genes interact with the environment.

To uncover these complexities, researchers first need to characterize how healthy tissues function.  To do this tissue samples were required.  The researchers obtained the samples of 50 different tissues immediately following the donor’s death.  These samples varied from blood to organs and covered the ten sub-regions of the brain.  In total, the data from 449 donors was used.  “These types of tissue are incredibly difficult to get from healthy living donors,” said Engelhardt.  “With endless thanks to the donors, we have these samples as a resource.  We can now explain observed relationships between genotype and disease by looking at the effects of the genotypes that lead to higher risk of the disease on gene expression levels in disease-specific tissues, including the brain.”

This latest study is the largest analysis seen so far and includes more than 7,000 tissue samples.  Engelhardt’s team’s role was to map associations between genetic variants and gene expression levels for different chromosomes.  This connection is referred to as “trans-expression quantitative trait loci (trans-eQTLS).”  At the opposite end of the scale are cis-eQTLs regulate those genes on the same chromosome that are close by.  While trans-eQTLS are notoriously difficult to identify due to their complexity, they could still reveal better clues than cis-eQTLs to help us understand these complex traits.

After mapping and interpreting the trans-eQTLs they’d found in the tissue sample, Engelhardt and colleagues performed 3.5 trillion statistical tests against each mutation in the genome.  After applying additional statistical techniques they were left with several hundred trans-eQTLs.  They also discovered during the study that nearby genetic variation in the form of cis-eQTLs affected the expression of around half of the sample genes.  As more samples are added, researchers suggest this figure will climb to nearer 100 percent.

“The extensive catalog generated by the GTEx consortium takes us one step closer to decoding the regulatory code of the genome,” said Yoav Gilad, a geneticist at the University of Chicago who was a scientific reviewer on the paper.  “The consequences of genetic variation on gene expression are gradually becoming clearer.”  The study is a big step forward in understanding how eQTLs affect gene regulation and expression, but there’s still a very long way to go.  Still, the researchers are hoping to extend their study soon to cover new and underrepresented populations as well as building on existing data.

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