
UCLA scientists build ‘cell villages’ to map the genetics of brain cell fitness
On Aug. 3, 2026, UCLA researchers announced they have grown brain cells from dozens of genetically distinct donors together in a cell village, then built a statistical tool called Townlet to measure each donor’s cell fitness — how well their cells grow and survive.
How readily a cell divides and how well it survives is fundamental to life, shaping everything from organ size to the body’s ability to withstand disease. That combination, known as cell fitness, isn’t the same for everyone. Differences in genetics and environment can tip the scales toward developmental disorders, tissue degeneration and cancer. Pinning down those differences could help explain why some people are more vulnerable than others to a given disease or toxic exposure — and eventually guide more personalized treatment and prevention.
But measuring cell fitness across many genetic backgrounds has long been difficult. Donor diversity is limited, and growing each person’s cells in a separate dish is slow, costly and vulnerable to tiny differences in handling from one well to the next.
In a study published in the American Journal of Human Genetics, UCLA scientists tackle this with a cell village approach: pooling neural progenitor cells — the early cells that build the developing brain — from dozens of genetically distinct donors into a single shared culture, where every donor’s cells grow under identical conditions.
“By using cell villages, we eliminate a lot of the technical noise that can mask real biology, and it means we can include far more genetic diversity in a single experiment,” said co-senior author Michael F. Wells, assistant professor of human genetics at the David Geffen School of Medicine at UCLA and a member of the UCLA Broad Stem Cell Research Center, who pioneered the platform. Pooling cells generates complex, tangled data, so the team built a companion statistical tool, Townlet, that gives researchers a reliable readout of each donor’s fitness within the crowd.
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Source: University of California, Los Angeles
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