Associate Professor, Department of Human Genetics
Phone: (514) 398-8364
740 Dr Penfield Ave, Room 7001
Montréal, Québec, Canada, H3A 0G1
Dr. Hernandez is currently an Associate Professor in the Department of Human Genetics at McGill University. He studied mathematics as an undergraduate at Pitzer College, obtained his PhD from Cornell University, and received postdoctoral training at the University of Chicago. He was a faculty member at the University of California San Francisco from 2010-2018 before joining the the Department of Human Genetics at McGill.
Our work focuses on data-driven modeling of the patterns of genetic variation within and between populations and species. We study both humans and non-human species (such as the medically relevant rhesus macaque and domesticated species like cows and rice). We frequently employ detailed population genetic simulations to better understand the implications of interacting evolutionary forces. We currently have three main lines of research:
Population genetic modeling of human populations
In order to further understand the evolutionary forces that acted on our ancestors, we analyze large-scale sequencing data from populations throughout the world. In collaboration with the 1000 Genomes Project, we employed detailed population genetic models to better understand the implications of complex interactions among evolutionary forces on patterns of genetic variation within and between populations. One current focus is on the implications of a genome’s worth of deleterious mutations that are interacting in complex ways to drive systematic genomic patterns of variation. Using detailed simulations and models of background selection, we seek to learn more about our species’ history and to discover more of the functionally relevant regions of the genome.
Disease susceptibility in complex populations
Next-generation sequencing technologies are providing an unprecedented opportunity to learn about the genetic basis of disease. We strive to leverage evolutionary signals in patterns of genetic variation to uncover the meaningful associations with phenotypic variation. By leveraging evolutionary signatures of natural selection and admixture patterns in trans-ethnic studies of Latino and African American populations, we will be able to gain insights into the genetics of this disease for the betterment of all populations.
Populations do not evolve in isolation. Rather, they are constantly interacting with other species, both mutualistically (as in the human microbiome) as well as competitively (in the case of pathogens). We are developing tools to leverage patterns of genetic diversity within populations and divergence across phylogenies to learn more about the genetic targets of such interactions. In collaboration with Dr. Nevan Krogan, we are investigating interactions between mammals across the phylogenetic tree and their associated immunodeficiency viruses (e.g., HIV, SIV, FIV, etc). Using both phylogenetic and population genetic techniques, we are learning about the nature of these interactions, and addressing pressing questions about the conditions under which viruses jump species barriers.
- Li, X, Li, Z, Zhou, H, Gaynor, SM, Liu, Y, Chen, H et al.. Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale. Nat. Genet. 2020;52 (9):969-983. doi: 10.1038/s41588-020-0676-4. PubMed PMID:32839606 PubMed Central PMC7483769.
- Zekavat, SM, Ruotsalainen, S, Handsaker, RE, Alver, M, Bloom, J, Poterba, T et al.. Publisher Correction: Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries. Nat Commun. 2020;11 (1):1715. doi: 10.1038/s41467-020-15236-6. PubMed PMID:32238811 PubMed Central PMC7113276.
- Torres, R, Stetter, MG, Hernandez, RD, Ross-Ibarra, J. The Temporal Dynamics of Background Selection in Nonequilibrium Populations. Genetics. 2020;214 (4):1019-1030. doi: 10.1534/genetics.119.302892. PubMed PMID:32071195 PubMed Central PMC7153942.
- Kessler, MD, Loesch, DP, Perry, JA, Heard-Costa, NL, Taliun, D, Cade, BE et al.. De novo mutations across 1,465 diverse genomes reveal mutational insights and reductions in the Amish founder population. Proc. Natl. Acad. Sci. U.S.A. 2020;117 (5):2560-2569. doi: 10.1073/pnas.1902766117. PubMed PMID:31964835 PubMed Central PMC7007577.
- Tong, DMH, Hernandez, RD. Population genetic simulation study of power in association testing across genetic architectures and study designs. Genet. Epidemiol. 2020;44 (1):90-103. doi: 10.1002/gepi.22264. PubMed PMID:31587362 PubMed Central PMC6980249.
- Kachroo, P, Hecker, J, Chawes, BL, Ahluwalia, TS, Cho, MH, Qiao, D et al.. Whole Genome Sequencing Identifies CRISPLD2 as a Lung Function Gene in Children With Asthma. Chest. 2019;156 (6):1068-1079. doi: 10.1016/j.chest.2019.08.2202. PubMed PMID:31557467 PubMed Central PMC6904857.
- Szpiech, ZA, Mak, ACY, White, MJ, Hu, D, Eng, C, Burchard, EG et al.. Ancestry-Dependent Enrichment of Deleterious Homozygotes in Runs of Homozygosity. Am. J. Hum. Genet. 2019;105 (4):747-762. doi: 10.1016/j.ajhg.2019.08.011. PubMed PMID:31543216 PubMed Central PMC6817522.
- Daya, M, Rafaels, N, Brunetti, TM, Chavan, S, Levin, AM, Shetty, A et al.. Author Correction: Association study in African-admixed populations across the Americas recapitulates asthma risk loci in non-African populations. Nat Commun. 2019;10 (1):4082. doi: 10.1038/s41467-019-12158-w. PubMed PMID:31484942 PubMed Central PMC6726619.
- Hernandez, RD, Uricchio, LH, Hartman, K, Ye, C, Dahl, A, Zaitlen, N et al.. Ultrarare variants drive substantial cis heritability of human gene expression. Nat. Genet. 2019;51 (9):1349-1355. doi: 10.1038/s41588-019-0487-7. PubMed PMID:31477931 PubMed Central PMC6730564.
- Daya, M, Rafaels, N, Brunetti, TM, Chavan, S, Levin, AM, Shetty, A et al.. Association study in African-admixed populations across the Americas recapitulates asthma risk loci in non-African populations. Nat Commun. 2019;10 (1):880. doi: 10.1038/s41467-019-08469-7. PubMed PMID:30787307 PubMed Central PMC6382865.