HomeOur ScientistsJonathan K. Pritchard

Our Scientists

Jonathan K. Pritchard, PhD
Investigator / 2008–Present

Scientific Discipline

Computational Biology, Genetics

Host Institution

Stanford University

Current Position

Dr. Pritchard is also a professor in the Department of Genetics and the Department of Biology at Stanford University. From 2008 to 2013 he was an HHMI investigator at the University of Chicago.

Current Research

Causes and Consequences of Human Variation

Jonathan Pritchard works to understand the nature of human genetic variation by combining methods from evolutionary biology and statistics. He hopes to determine which of the vast number of individual differences in the human genome contribute to diseases and disease susceptibility.

Read more ›


When Jonathan Pritchard looks at a DNA sequence, he sees more than a string of As, Ts, Gs, and Cs. He sees evidence of vast movements of people and loved ones lost to disease; he sees the lasting signatures of both genetics and…

When Jonathan Pritchard looks at a DNA sequence, he sees more than a string of As, Ts, Gs, and Cs. He sees evidence of vast movements of people and loved ones lost to disease; he sees the lasting signatures of both genetics and chance.

Since he received his Ph.D. just a decade ago, Pritchard has researched a wider range of topics than most biologists cover in a lifetime. He has analyzed the patterns in human DNA created by historical migrations, the consequences of natural selection, and even the tantalizing question of whether modern humans and Neanderthals interbred. "Sometimes I have a hard time describing exactly what I work on," admits the University of Chicago biologist. "But almost everything I do is connected to understanding aspects of human genetic variation."

Pritchard grew up in England about an hour away from Darwin's countryside manor, and he shares Darwin's fascination with natural history. "I collected insects and snakes when I was younger, and still do quite a bit of birding," he says. But he was also captivated by mathematics, which he studied at Pennsylvania State University after his family moved to the United States when he was in high school. "Applying mathematics to understand the evolutionary and genetic mechanisms that create biological diversity was a natural way for me to combine my interests."

In graduate school at Stanford University, he worked with Marc Feldman, who has done groundbreaking mathematical analyses of human evolution. That's where Pritchard began applying his mathematical expertise to understanding the differences in DNA sequences between individuals.

At Stanford, Pritchard and fellow graduate student Noah Rosenberg wrote a landmark paper demonstrating how to keep the shared ancestry of groups—who might share certain gene mutations and traits that are not actually linked to one another—from interfering with the search for human disease genes. After graduate school, he moved back to England to do a postdoctoral fellowship with mathematical biologist Peter Donnelly at the University of Oxford. There, he and colleagues developed a popular method for studying population structure that Pritchard has made freely available in a software package called Structure. This method has been used across a wide range of applications, including in human genetics, conservation biology, forensics, and linguistics. A follow-up paper by Rosenberg, Pritchard, and other colleagues in the journal Science on continental patterns in human genetic variation was named the Paper of the Year by the medical journal The Lancet.

Pritchard has been working to understand the links between genetic variation and human traits. When a particular genetic variant gives an individual a survival advantage in a given environment, such as being able to survive malaria or digest milk from animals, that individual has a greater opportunity to have children and pass on his or her genes to future generations. As a result, the variant can become more common in a population. This natural selection of advantageous genes—the raw material of evolution—leaves signals in our DNA that can be detected when researchers compare human genomes.

In a 2006 paper, Pritchard and his colleagues described the identification of several hundred DNA regions in various human populations that show signals of selection. Included within those regions are genes that influence reproduction, olfaction, degradation of environmental toxins, skin pigmentation, and skeletal development. Using more extensive data that have recently become available, his group has been examining the relative roles of chance (which can lead to changes in the gene pool known as genetic drift) and selection in favoring these genes. "Selection may be a weaker force than we thought," he says. "It seems to be a combination of drift and selection acting together."

Besides altering genes themselves, natural selection can shape when and where genes are turned on in the body. Natural selection often targets the DNA sequences right before and right after a gene, and these sequences generally control the expression of the gene they bracket. "We're starting to generate all kinds of ideas about how these genomic regions function," he says.

With new data on human genetic differences pouring out of sequencing centers, Pritchard's mathematical abilities are in high demand—whether it's analyzing the differences between modern DNA and Neanderthal DNA or tracking the spread of an infectious tumor.

But gene expression is the area he finds especially promising. He plans a comprehensive analysis, cataloging all of the variations in DNA that are common among the human population and have an impact on gene expression. His goal is to determine how these variations alter gene regulation throughout the genome, and to link them to diseases and other traits. "Selection and gene regulation are where we think we can have the biggest impact in the next few years," he says.

Show More


  • BSc, biology and mathematics, Pennsylvania State University
  • PhD, biology, Stanford University


  • Novitski Prize, Genetics Society of America
  • Outstanding Alumni Award, Eberly College of Science, Penn State University
  • Mitchell Prize, International Society of Bayesian Analysis


  • American Academy of Arts and Sciences