Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States; Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, United States; Howard Hughes Medical Institute, University of California, Los Angeles, Los Angeles, United States; Institute for Quantitative and Computational Biology, University of California, Los Angeles, Los Angeles, United States
James Boocock
Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States; Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, United States; Howard Hughes Medical Institute, University of California, Los Angeles, Los Angeles, United States; Institute for Quantitative and Computational Biology, University of California, Los Angeles, Los Angeles, United States
Sebastian Treusch
Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States; Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, United States; Howard Hughes Medical Institute, University of California, Los Angeles, Los Angeles, United States; Institute for Quantitative and Computational Biology, University of California, Los Angeles, Los Angeles, United States
Meru J Sadhu
Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States; Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, United States; Howard Hughes Medical Institute, University of California, Los Angeles, Los Angeles, United States; Institute for Quantitative and Computational Biology, University of California, Los Angeles, Los Angeles, United States
Laura Day
Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States; Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, United States; Howard Hughes Medical Institute, University of California, Los Angeles, Los Angeles, United States
Holly Oates-Barker
Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States; Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, United States; Howard Hughes Medical Institute, University of California, Los Angeles, Los Angeles, United States
Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States; Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, United States; Howard Hughes Medical Institute, University of California, Los Angeles, Los Angeles, United States; Institute for Quantitative and Computational Biology, University of California, Los Angeles, Los Angeles, United States
How variants with different frequencies contribute to trait variation is a central question in genetics. We use a unique model system to disentangle the contributions of common and rare variants to quantitative traits. We generated ~14,000 progeny from crosses among 16 diverse yeast strains and identified thousands of quantitative trait loci (QTLs) for 38 traits. We combined our results with sequencing data for 1011 yeast isolates to show that rare variants make a disproportionate contribution to trait variation. Evolutionary analyses revealed that this contribution is driven by rare variants that arose recently, and that negative selection has shaped the relationship between variant frequency and effect size. We leveraged the structure of the crosses to resolve hundreds of QTLs to single genes. These results refine our understanding of trait variation at the population level and suggest that studies of rare variants are a fertile ground for discovery of genetic effects.
