Many of the traits that we care about, as evolutionary biologists, human geneticists, or simply as human beings, are genetically complex. This means that genetic differences at many genes (as well as differences in environment exposure and developmental trajectory) contribute to differences in the trait among individuals. Traits of this kind include height and other anthropometric measurements, skin pigmentation, life history traits, as well as many medically defined diseases and disorders (e.g. heart disease, diabetes, schizophrenia, and autism). The genetic differences arise as the result of accidental mutations in a single individual, which are then passed down through Mendelian inheritance, reshuffled through genetic recombination, amplified or removed by natural selection, and moved around by migration/gene flow.
Over the last hundred years or so, mathematical geneticists have developed a body of theory to describe how genetically complex traits evolve in response to these fundamental population genetic forces. For most of this period, data was scarce. In the last decade, this script has flipped. We are now swimming in genetic data from genome-wide association studies and other resources, but we lack the theoretical and statistical tools to deal with it's messy reality.
Much of my work is aimed at developing theoretical models and statistical tools that will allow us to learn about the evolution and genetics of complex traits. I am interested in questions such as:
-- How has adaptation impacted variation in complex traits among populations?
-- What forces maintain genetic variation for complex traits within populations?
-- Are human complex traits at or close to mutation-selection balance and what is the relative role of stabilizing vs. directional selection?
-- At how many positions in the genome will a newly arising mutation affect a given trait, and what is the distribution of effect sizes for these newly arising mutations?
-- What role, if any, does linked selection play in determining the genetic architecture of complex traits.
In general, I try to approach problems with a blend of theory and data analysis. Ideally, theoretical modeling will suggest new approaches for analyzing data, and the results of data analysis can suggest new directions for theoretical exploration.
While the main thrust of my work is currently on the evolution of complex traits, I find interest in a broad array of problems in population genetics, including linked selection (e.g. selective sweeps and background selection) and its consequences, pedigree reconstruction and demographic inference, coalescent theory and ARG inference, and the evolution of mutation and recombination rates, to name a few.
Cell-type-specific eQTLs underlie the genetic architecture of complex traits.
Cell-type-specific eQTLs underlie the genetic architecture of complex traits. Nature. 2026 Aug 26.
PMID: 42649298
Extinction vortices are driven more by a shortage of beneficial mutations than by deleterious mutation accumulation.
Extinction vortices are driven more by a shortage of beneficial mutations than by deleterious mutation accumulation. Proc Biol Sci. 2026 06 03; 293(2072).
PMID: 42230116
Training AI to Improve Distinction of Triple-Negative Invasive Breast Cancer from Cysts and Fibroadenomas on Ultrasound.
Training AI to Improve Distinction of Triple-Negative Invasive Breast Cancer from Cysts and Fibroadenomas on Ultrasound. Diagnostics (Basel). 2026 Apr 30; 16(9).
PMID: 42122057
Background selection in recombining genomes and its consequences for the maintenance of variation in complex traits.
Background selection in recombining genomes and its consequences for the maintenance of variation in complex traits. Proc Natl Acad Sci U S A. 2026 Apr 07; 123(14):e2513613123.
PMID: 41915739
Extinction vortices are driven more by a shortage of beneficial mutations than by deleterious mutation accumulation.
Extinction vortices are driven more by a shortage of beneficial mutations than by deleterious mutation accumulation. bioRxiv. 2026 Mar 10.
PMID: 41889900
How data can help to guide NIH funding policy.
How data can help to guide NIH funding policy. Nature. 2026 Mar; 651(8105):308-309.
PMID: 41807566
Mutation-selection-drift balance models of complex diseases.
Mutation-selection-drift balance models of complex diseases. Genetics. 2025 12 10; 231(4).
PMID: 41073879
A new interpretation for oxygen atom-transfer reactions for the Berg-Holm Oxomolybdenum enzyme model: Evidence for a highly active oxygen atom transfer acceptor.
A new interpretation for oxygen atom-transfer reactions for the Berg-Holm Oxomolybdenum enzyme model: Evidence for a highly active oxygen atom transfer acceptor. J Inorg Biochem. 2026 Mar; 276:113163.
PMID: 41330031
Impoundment of funds endangers US investment in science and medical research.
Impoundment of funds endangers US investment in science and medical research. Nature. 2025 Sep; 645(8081):592.
PMID: 40958027
Testing for differences in polygenic scores in the presence of confounding.
Testing for differences in polygenic scores in the presence of confounding. Genetics. 2025 06 04; 230(2).
PMID: 40233174