Simon Gravel

Academic title(s): 

Assistant Professor, Department of Human Genetics

Investigator, Victor Phillip Dahdaleh Institute of Genomic Medicine

Simon Gravel
Contact Information
Address: 

740 Dr Penfield Ave, Montreal, QC H3A 0G1

Email address: 
simon.gravel [at] mcgill.ca
Department: 
Human Genetics
McGill Genome Centre
Area(s): 
Genetics
Degree(s): 

PhD - Physics, Cornell University, 2009.

Postdoctoral Fellowship, Physics Department, Universität zu Köln.

Postdoctoral Fellowship - Theoretical Physics, Kavli Institute, Santa Barbara.

Postdoctoral Fellowship, Genetics Department, Stanford University.

Biography: 

Simon Gravel obtained his BSc and MSc in Mathematics and Physics from the Université de Montréal and his PhD in Physics from Cornell University in 2009. His research in Genetics began during a short postdoc in the Physics department at the Universität zu Köln and the Kavli Institute for Theoretical Physics in Santa Barbara, and continued in the Genetics department at Stanford University. He joined the Department of Human Genetics at McGill and the Genome Quebec Innovation Centre in 2013.

Current research: 

Professor Gravel’s is interested in learning about biology and evolution through creative analysis of high-throughput biological data. His group develops mathematical and statistical methods that take advantage of diverse data sources to refine our understanding of fundamental parameters of human history and biology. His recent research has focused on how the history of diverse human populations affected patterns of genetic diversity and disease. His group made contributions about the origins of modern humans, the successive waves of migrations that led to the formations of contemporary populations in the Americas, as well as the identification of genetic predispositions for disease.

This research is largely data-driven, and it combines modeling at multiple levels: we first wish to understand the fundamental biology underpinning evolution, such as the processes of mutation, recombination, and selection. To understand human genomes, we also need to understand how recent and ancient human history affected patterns of genetic diversity: ancient population expansions, recent migrations, and marriage patterns all impact genomic diversity, and in many cases we can reconstruct these events through careful modelling. Finally, we need to understand the behavior of cutting edge technology involved in the latest datasets. Professor Gravel’s group has projects focusing on anthropology and history, technology development, biology, and medicine, and is always happy to explore new opportunities involving new technologies and creative mathematical modeling.

Selected publications: 
  • Mishra, A, Malik, R, Hachiya, T, Jürgenson, T, Namba, S, Posner, DC et al.. Publisher Correction: Stroke genetics informs drug discovery and risk prediction across ancestries. Nature. 2022;612 (7938):E7. doi: 10.1038/s41586-022-05492-5. PubMed PMID:36376532 .
  • Mishra, A, Malik, R, Hachiya, T, Jürgenson, T, Namba, S, Posner, DC et al.. Stroke genetics informs drug discovery and risk prediction across ancestries. Nature. 2022;611 (7934):115-123. doi: 10.1038/s41586-022-05165-3. PubMed PMID:36180795 PubMed Central PMC9524349.
  • Alenezi, WM, Milano, L, Fierheller, CT, Serruya, C, Revil, T, Oros, KK et al.. The Genetic and Molecular Analyses of RAD51C and RAD51D Identifies Rare Variants Implicated in Hereditary Ovarian Cancer from a Genetically Unique Population. Cancers (Basel). 2022;14 (9):. doi: 10.3390/cancers14092251. PubMed PMID:35565380 PubMed Central PMC9104874.
  • Moldoveanu, D, Ramsay, L, Lajoie, M, Anderson-Trocme, L, Lingrand, M, Berry, D et al.. Spatially mapping the immune landscape of melanoma using imaging mass cytometry. Sci Immunol. 2022;7 (70):eabi5072. doi: 10.1126/sciimmunol.abi5072. PubMed PMID:35363543 .
  • Baumdicker, F, Bisschop, G, Goldstein, D, Gower, G, Ragsdale, AP, Tsambos, G et al.. Efficient ancestry and mutation simulation with msprime 1.0. Genetics. 2022;220 (3):. doi: 10.1093/genetics/iyab229. PubMed PMID:34897427 PubMed Central PMC9176297.
  • Zabad, S, Ragsdale, AP, Sun, R, Li, Y, Gravel, S. Assumptions about frequency-dependent architectures of complex traits bias measures of functional enrichment. Genet Epidemiol. 2021;45 (6):621-632. doi: 10.1002/gepi.22388. PubMed PMID:34157784 .
  • Spear, ML, Diaz-Papkovich, A, Ziv, E, Yracheta, JM, Gravel, S, Torgerson, DG et al.. Recent shifts in the genomic ancestry of Mexican Americans may alter the genetic architecture of biomedical traits. Elife. 2020;9 :. doi: 10.7554/eLife.56029. PubMed PMID:33372659 PubMed Central PMC7771964.
  • Diaz-Papkovich, A, Anderson-Trocmé, L, Gravel, S. A review of UMAP in population genetics. J Hum Genet. 2021;66 (1):85-91. doi: 10.1038/s10038-020-00851-4. PubMed PMID:33057159 PubMed Central PMC7728596.
  • Martin, AR, Gignoux, CR, Walters, RK, Wojcik, GL, Neale, BM, Gravel, S et al.. Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations. Am J Hum Genet. 2020;107 (4):788-789. doi: 10.1016/j.ajhg.2020.08.020. PubMed PMID:33007199 PubMed Central PMC7536609.
  • Ragsdale, AP, Nelson, D, Gravel, S, Kelleher, J. Lessons Learned from Bugs in Models of Human History. Am J Hum Genet. 2020;107 (4):583-588. doi: 10.1016/j.ajhg.2020.08.017. PubMed PMID:33007197 PubMed Central PMC7536610.
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