Quick Summary

• Undergraduate of the Year Cole Williams can trace his affinity for genetics back to fifth grade
• At UC Davis, he joined the lab of Assoc. Prof. Brenna Henn, studying the genetics of African hunter-gatherer and pastoralist groups
• He designed an algorithm capable of handling diverse populations, technical artifacts and complex family genealogies that runs rapidly on human genomic datasets

Cole Williams was crunched for time. The genetics and genomics senior was deep into the world of human population genetics. In the lab of Associate Professor Brenna Henn, Williams was trying to parse apart familial relationships in African hunter-gatherer and pastoralist groups, some of which are the most diverse human populations on Earth.

But he ran into a problem. The publicly available computer algorithms Williams used couldn’t make sense of his study population’s genomic data.

“While published algorithms are available to sort pairs of individuals into pedigree categories, most were developed with European-descent groups in mind,” said Henn, who holds appointments in the Department of Anthropology and the UC Davis Genome Center. “They don’t work well for populations with multiple ancestries, cousin-cousin marriages or situations where there are many half-siblings in a population.”

Such was the case with the African populations Williams and Henn studied, like the Himba, from northern Namibia. To further emphasize Henn’s point, an article published in Cell reported that 78 percent of individuals in “genome-wide association studies” are of European descent. According to the U.N., Europeans make up only about 10 percent of the world’s population.

Williams needed a fix. He’d spent nearly eight months on a project with little more than an inkling of advancement. He knew an original algorithm was needed, but with graduation looming, he didn’t have time to write it. Then the California wildfires hit and the UC Davis campus closed. Williams turned the closure into an opportunity and wrote the algorithm.

The result, according to Henn, was an algorithm capable of handling diverse populations, technical artifacts and complex family genealogies that runs rapidly on human genomic datasets.

“Cole solved a major problem we were facing, in other words how to accurately construct multi-generational pedigrees in African genomes,” said Henn. “He really put the time into understanding the technical difficulties inherent in genomic data and how other research groups tackled the problem previously.”

For his outstanding research and service, Williams, who graduated this month, was named the 2019 College of Biological Sciences Undergraduate of the Year.

“This award is a testament to my passion for human genetics and all of my hard work of the past four years,” said Williams. “It has been such a privilege to be at UC Davis studying and researching the subject I love; to be given this award is just the cherry on top of such an amazing time here.”

 

Preserving childhood wonder

Williams can trace his affinity for genetics back to fifth grade, when he was introduced to Punnett squares, diagrams used to predict the probability of heritable traits, such as eye or hair color. He became fascinated by the potential power of genetics to help solve diseases. Raised in Davis in an Aggie household, Williams followed his parents’ footsteps and enrolled at UC Davis due to its strong reputation for genetics and because he wanted to stay close to home.

During his freshman year living in the Tercero Residence Hall, Williams learned about Camp Kesem, a nationwide student-run organization that runs camps for children of cancer patients. As a child, Williams’ father was taken by cancer. He was all too familiar with the emotional toll surrounding such a loss and joined the program as a camp counselor. According to Williams, the camp is all about providing a space for kids to just be kids. He now serves as the UC Davis chapter’s treasurer.

“When your parent has cancer, you’re kind of forced to grow up,” he said. “You kind of miss out on some of your childhood.”

Williams himself felt the experience was a struggle and now, he’s ensuring other children don’t feel as he did.

“It turned out it was the most impactful thing that I’ve done,” he said of volunteering. “I’ve had a lot of success with my research and my academics, but I think I’m most proud of the work I’ve done with Camp Kesem.”

Choreographing the ancestral dance of genetics and anthropology

When Williams found the Henn Lab during his junior year, he struck scientific gold.

“I knew that human population genetics was what I wanted to do when I came to Davis,” he said. “I had been looking for a lab like this my whole time here.”

Williams became familiar with the Himba and San populations Henn and her colleagues studied. But with populations like the Himba defining familial relationships with genetic data can be a daunting task.

“They have arranged marriages, so that’s the first layer,” said Williams. “The second layer is that preferred pairings are between first cousins and the third layer is that they can have additional relationships outside of their marriage.” 

Algorithms developed using European ancestry data couldn’t genetically delineate between grandparent-grandchild, half-sibling and avuncular (aunts/uncles-nieces/nephews) relationships. Since individuals in these relationships share about 25 percent of their genetic material with one another, they all looked the same to the publicly available algorithms.

To overcome this hurdle, Williams peered closer at the genomes, zeroing in on segments of DNA known as identical by descent (IBD) segments, which are measured in genetic metric called centiMorgans. It turned out that the three complex relationships differed in size and number of shared IBD segments.

“A grandparent-grandchild, they share fewer segments but they’re longer,” said Williams. “Avuncular relationships, they share more segments of shorter length.”

With this new knowledge, Williams wrote an algorithm capable of delineating between grandparent-grandchild, half-sibling and avuncular relationships with greater accuracy. The algorithm learns and becomes more accurate with each new dataset.

“His solution is both really unique but practical,” said Henn.

The algorithm could help researchers further understand disease spread in African hunter-gatherer and pastoralist populations by highlighting the inherited genetics that lead to disease susceptibility. This could help Henn and her colleagues understand the spread of tuberculosis in their study populations.

Focusing on genetic diseases in underrepresented populations

After graduation, Williams will head to the Colorado Center for Personalized Medicine, where he will continue researching genetic diseases in underrepresented populations. He plans on later pursuing a Ph.D. degree.

“I would like to acknowledge Dr. Brenna Henn, who gave me a chance and afforded me the independence to become a better scientist; the campers and counselors at Camp Kesem UC Davis who have taught me love and empathy and have made me a better person; and lastly, I would like to thank my mom for her endless support and instilling in me the work ethic needed to receive an award like this,” said Williams.

“And for letting me live with her rent-free for the past three years,” he added.