Sohini Ramachandran is a population geneticist at Brown University.
Image credit:PORTER GIFFORD, Rythum Vinoben, Modified by Erin Lemieux
When The Scientist first spoke with Sohini Ramachandran, the population geneticist was a freshly minted principal investigator setting up her own lab at Brown University. Ramachandran first stepped into a research lab at the age of 15, joining mathematical geneticist Marcus Feldman’s lab at Stanford University for the summer. “I was hooked from then on,” she shared in her original profile 14 years ago.
Years later, as a graduate student in Feldman’s lab, Ramachandran analyzed samples from the Human Genome Diversity Panel, a collection of over 1,000 cell lines from distinct populations. Her work demonstrated an inverse association between the genetic diversity of modern human populations and their geographic distance from Africa, the cradle of modern human migration. During her postdoctoral research in the lab of theoretical geneticist John Wakeley at Harvard University, she developed a mathematical framework to explain how X-chromosome data can be used to estimate evolutionary patterns, including migration rates.
In honor of The Scientist’s 40th anniversary, we reconnect with Ramachandran to trace how her research has evolved over nearly a decade and a half. Today, her team leverages the immense genetic wealth of large medical biobanks to explore how complex traits and parent-of-origin genetic inheritance shape human genomes.
Biobanks and Population Genetics: A Perfect Match
Over the last two decades, massive population biorepositories—such as the UK Biobank and the All of Us biobank—have become invaluable resources for researchers globally. For population geneticists like Ramachandran, these vast datasets, containing genetic information from hundreds of thousands of individuals, represent an unprecedented opportunity to understand human genetics at scale.
“I couldn’t have imagined a dataset of tens of thousands of genomes even when I was starting my lab, let alone hundreds of thousands of genomes like we have access to now,” she noted.
Ramachandran’s team recently began investigating whether inheriting a specific gene variant, or allele, from one’s mother or father influences particular traits. A key challenge is reliably assigning the parent of origin to haplotypes—groups of alleles on a single chromosome inherited together from one parent. With modern biobank data, researchers can now identify genetic connections that individuals themselves might not realize, such as finding individuals who are eighth cousins in the UK Biobank because they share a recent common ancestor.
To map these connections, Ramachandran’s team utilized genetic data from the UK Biobank and research-consented 23andMe customers, focusing on long DNA segments shared between individuals, known as identity-by-descent (IBD) segments. While traditional methods analyze chromosomes one by one, Ramachandran and her team developed a novel approach called HAPlotype Tiling and Clustering (HAPTiC). This method determines which IBD segments on one chromosome correspond to segments on another chromosome. Their analysis revealed that many individuals share IBD segments on both their maternal and paternal haplotypes.
“That gave us a neat population genetic insight: Since those segments are on both haplotypes, [these people] must have had ancestors in the past who were related to each other,” Ramachandran explained. “That gives us a new view in recent time about how connected our ancestors were—maybe much more connected than our classic models would assume.”
Beyond ancestry mapping, Ramachandran’s team is leveraging biobank data to bring a more genetically diverse perspective to complex traits. Less than 20 percent of scientific publications include non-European ancestry cohorts in genome-wide association studies (GWAS), severely limiting how transferable genetic findings are to global populations. In a major study, her group applied enrichment analyses to examine 25 complex traits across more than 600,000 people of diverse ancestries. Genes and pathways associated with traits like triglyceride levels showed associations that differed significantly between European and non-European cohorts.
“Genome-wide association study results are a huge investment that’s been made in our field. They’ve obviously taught us a lot about many traits, particularly how complex traits can be,” Ramachandran remarked. Integrating biobank data with GWAS findings could help researchers determine which discoveries can be reliably extrapolated to different groups, paving the way for more equitable genomic medicine.
Science: The Infinite Game
Reflecting on her career, Ramachandran views scientific inquiry as a continuous, collaborative journey. “The longer I am a scientist, the more I see it as an infinite game. A finite game is where there’s a winner and a loser, and at some point, it ends. [In] an infinite game, you want to play to keep playing,” she said. Scientific papers, she notes, represent the best work researchers can achieve at a specific moment, but they rarely have the final word.
While scientific publications are often the legacy of a researcher, Ramachandran believes the true lasting legacy lies in mentorship. “I really love mentoring young scientists. I feel so lucky [to have had] each of the graduate students and postdocs who’ve come to my lab and chosen to work with me,” she shared. “I really see myself as just trying to create the best environment I can for my graduate students, postdocs, and undergraduates to just run with their ideas and not have obstacles in their way.”