Scientists at Dana–Farber Cancer Institute said they have made an important step toward understanding how variations in the human genetic blueprint determine complex traits such as normal body functions and susceptibility to cancer and other diseases.

Their findings, reported in the Proceedings of the National Academy of Sciences journal, help explain how a person's genome – an individual's complete, distinctive genetic program encoded in DNA – can generate different types of cells and tissues with different functions. The research also reveals how thousands of genetic variants, each having a very small effect, work in concert through networks to influence complex traits such as disease risk.

Led by John Quackenbush, PhD, director of the Center for Cancer Computational Biology at Dana–Farber, the investigators said their findings "provide new insight into the genotype–phenotype relationship." Genotype refers to the specific genetic instructions in an individual's cells; phenotype is defined as the observable characteristics of an individual, which can be anything from physical traits such as height or eye color to risks of disease.

Despite the deciphering of the human genetic code more than a decade ago, "our understanding of the relationship between genetic variation and complex traits remains limited," the authors said. First author is Maud Fagny, PhD, of Dana–Farber. Corresponding authors are Quackenbush and John Platig, PhD, also of Dana–Farber.

The scientists studied genetic variants – points in the genome of individuals that differ by a single letter of the genetic code. These variants are known as single nucleotide polymorphisms, or SNPs, and there are about 6 million of them in the human genome.

Most SNPs don't alter the code of genes, which carry instructions for making proteins, but instead tweak the expression of genes: that is, they increase or decrease the rate at which the genes cause cells to produce proteins. What is new in the findings being reported by Quackenbush and his colleagues is how the different variants – the SNPs — interact with each other to regulate the output of the genes and how those interactions change between tissues.

"We decided to ask if we could understand how these weak variants might work together to influence genetic traits," said Quackenbush, who is a professor of biostatistics and computational biology at the Harvard T.H. Chan School of Public Health.

He and his colleagues performed an analysis known as expression quantitative trait loci (eQTL) mapping to determine the regulatory effects of common SNP variants in 13 human tissues. The tissues were collected from several hundred individuals and are stored in a database by the federal Genotype–Tissue Expression (GTEx) project, whose goal is to examine how genetic expression varies among tissues within individuals.

"We found that there were tens of thousands of SNPs that were correlated with the expression levels of thousands of genes," he said.

The scientists developed advanced computational tools that allowed them to discover that the variants work together in networks, "and the structure of the network tells us something about how the genes in each tissue are regulated," Quackenbush explained. The structure of these networks, which organize groups of SNPs and genes into complex "communities," "provides a natural framework for understanding both the shared and tissue–specific effects of genetic variants," according to the investigators.

Studies known as genome–wide association studies have tried to connect variations in DNA code with susceptibility to complex diseases like hypertension, diabetes, and coronary artery disease, or traits such as longevity.