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Guy Sella
Associate Professor
Our group uses mathematical models and statistical analyses of genetic variation data in order to learn about evolutionary processes.

Much of our work focuses on questions about natural selection in the genome: How many of the differences between species are adaptive? Are there few beneficial changes of major effect or many fine-tunings? Do adaptations wait for new mutations or do they arise from genetic variation that pre-existed changes in selection pressures? Why do the answers to these questions seem to vary across taxa? Different modes of natural selection leave distinct footprints in patterns of genetic variation within and between species that can be used to answer these questions. We use models to characterize these footprints and statistical analysis to detect them and make inferences about natural selection and its effects on genetic variation in humans and other species.

More recently, we have become interested in how quantitative traits evolve. Most phenotypes of interest are quantitative, including anthropomorphic traits such as height or body mass index, as well as the risk of developing many diseases. This means that the heritable variation in a trait is the outcome of genetic variants at many loci across the genome. Thanks to massive efforts at uncovering the genetic basis of quantitative traits in humans and other species, a preliminary picture of the frequencies and effect sizes of the underlying variants is emerging. From an evolutionary perspective, these findings raise many questions about how we might expect these genetic architectures to look; for example, should they differ for anthropomorphic traits and for the risk of developing early onset diseases? Conversely, what can we learn from the variants that have been mapped about the evolutionary forces that shape quantitative genetic variation? We also study related questions, such as how the differences in recent demographic history among human populations affect their burden of genetic diseases, or how the genetic basis of a quantitative trait affects the response to novel selection pressures. To this end, we combine mathematical models and data analysis in humans and other species.

Representative Recent Publications
  • Simons, Y., Turchin, M., Pritchard, J. K., and G. Sella (2013) The deleterious mutation load is insensitive to recent population history Article
  • Hernandez, R. D., Kelley, J. L., Elyashiv, E., Melton, S. C., Auton, A., McVean, G., 1000 Genomes Project, Sella G. and M. Przeworski (2011) Classic selective sweeps were rare in recent human evolution Science 331: 920-4.
  • Sattath, S., Elyavish, E., Kolodny, O., Rinott, Y., and G. Sella (2011) Pervasive adaptive protein evolution apparent from diversity patterns around amino-acid substitutions in Drosophila simulans PLoS Genetics 7: e1001302.
  • Elyavish, E., Bullaughey, K., Sattath, S., Rinott, Y., Przeworski, M. and G. Sella (2010) Variation in the intensity of purifying selection: An analysis of genome-wide polymorphism data from two closely related yeast species Genome Research 20: 1558-73.
  • G. Sella, D. A. Petrov, M. Przeworski, and P. Andolfatto (2009) Evidence for Pervasive Natural Selection in Drosophila? PLoS Genetics 5: e1000495.
  • G. Sella and D. H. Ardell (2006) The Coevolution of Genes and Genetic Codes: Crick's Frozen Accident Revisited. J Mol. Evol 63: 297-313.
  • G. Sella and A. E. Hirsh (2005) The Application of Statistical Physics to Evolutionary Biology PNAS 102: 9541-46.
Guy Sella