John Pool

Position title: Professor & Graduate Program Director of Admissions

Phone: 608-265-1036

Address:
Genetics
Population genomics and the genetic basis of adaptive evolution

Address: 2434 Genetics/Biotechnology
Education: Ph.D, Cornell University (2006), Postdoctoral Research (1) University of California, Berkeley and University of Copenhagen (2006-2009) (2) University of California, Davis (2009-2011)
Lab Website: http://www.johnpool.net
Department: Genetics
Research Interests: Population genomics and the genetic basis of adaptive evolution
Research Fields: Computational, Systems & Synthetic Biology, Evolutionary & Population Genetics, Gene Expression, Genomics & Proteomics, Drosophila

Research Description:
Genomic data is revolutionizing the fields of evolutionary and population genetics. Now armed with data sets that offer a relatively complete view of genomic diversity, we are primarily limited by our own creativity – in asking the right questions, devising the most illuminating experiments, and constructing the most informative genomic data analysis methods. Our lab asks fundamental evolutionary questions, often aided by genomic data, including: 1. How does adaptive evolution operate at the genetic level? How many genes are involved in a trait change? Do favored variants come from new mutations or standing variation? Does natural selection manage to elevate them to 100% frequency? 2. What do the earliest stages of reproductive isolation look like at the genetic level? Is this partial isolation caused by genetic variants that are fixed or still variable? How quickly do genetic incompatibilities between population begin to arise? Are these incompatibilities caused by simple pairs of loci, or by more complex networks? 3. How do natural selection and neutral historical processes shape genome-wide genetic diversity? 4. Which types of genetic variation contribute the most to future adaptation? (e.g. within- versus between-population variation) Can we identify sets of populations likely to conserve a species’ maximum adaptive potential? We address these questions using a combination of methods, ranging from large-scale Drosophila experiments to computational simulations and the development of novel statistical genomic methods.

Representative Publications:
Search PubMed for more publications by John Pool

Shpak M, Ghanavi HR, Lange JD, Pool JE, Stensmyr MC (2023) Genomes from 25 historical Drosophila melanogaster specimens illuminate adaptive and demographic changes across more than 200 years of evolution. PLOS Biol, 21(10): e3002333.

Lollar MJ, Biewer-Heisler TJ, Danen CE, Pool JE (2023) Hybrid breakdown in male reproduction between recently-diverged Drosophila melanogaster populations has a complex and variable genetic architecture. Evolution, 77:1550-1563.

Duranton M, Pool JE (2022) Interactions between natural selection and recombination shape the genomic landscape of introgression. Mol Biol Evol, 39:msac122.

da Silva Ribeiro T, Galván JA, Pool JE (2022) SNP-level FST outperforms whole-window statistics for detecting soft sweeps in local adaptation. Genome Biol Evol, 14:evac143.

Huang Y, Lack JB, Hoppel GT, Pool JE (2021) Parallel and population-specific gene regulatory evolution in cold-adapted fly populations. Genetics, 218:iyab077.

Sprengelmeyer QD, Mansourian S, Lange JD, Matute DR, Cooper BS, Jirle EV, Stensmyr MC, Pool JE (2020) Recurrent collection of Drosophila melanogaster from wild African environments and genomic insights into species history. Mol Biol Evol, 37:627-638.