The ever-growing genomic encyclopedia has the capacity to reveal the forces shaping complex patterns of genetic variation between individuals, populations, and species—if scientists can only unlock its secrets.
The method, called “conStruct,” allows researchers to analyze complex patterns of genetic variation in large datasets with broad geographic sampling. It overcomes major shortcomings of previous methods and is free and publicly available worldwide.
“One of the first steps in the analysis of these genomic datasets is to describe and categorize variation into discrete populations, like you might find in range maps in a field guide,” says lead author Gideon Bradburd, a population geneticist at Michigan State University. “What often determines relatedness is geography. If you sample two organisms separated by a large distance, you often have to go farther back into the history of their pedigrees to find a shared ancestor.”
“With conStruct, scientists can home in on commonalities and discrepancies among populations with more accuracy.”
This leads to isolation by distance, a pattern that creates statistical challenges for anyone interested in cleanly describing variation within and between groups in their own study system, he adds.
In the paper, which appears in Genetics, Bradburd and his colleagues illustrate the utility of their new approach by applying it to genomic data on North American bears and poplar trees.
For a better understanding, poplars grow throughout the northern hemisphere. Different species of poplar can grow near each other, and, where they overlap, they frequently hybridize.
Using conStruct, the research team reviewed the degree to which the two poplar species have hybridized. They were also able to determine whether the only significant population boundary fell along the species boundary, and if there was substructuring within the species.
“Understanding the genetic relatedness of individuals is central to many important research fields, including conservation biology, human medicine, evolution and ecology, and agriculture,” Bradburd says. “With conStruct, scientists can home in on commonalities and discrepancies among populations with more accuracy. This can prove invaluable, especially in conservation efforts.”
And, of course, these genomic patterns will offer additional insights into human evolution.
For the next phase of this research, Bradburd’s team will attempt to take conStruct into the fourth dimension. They hope to add the ability to model historical or ancient DNA samples to learn how and why populations change—or have their neighbors replace them—through time.
The National Science Foundation and the National Institutes of Health funded the research in part.
Additional researchers from the University of California, Davis, and University of Oregon contributed to the work.
Source: Michigan State University