Abstract
AbstractThe influence of adaptive evolution on disease susceptibility has drawn attention, but the extent of the influence, whether favored mutations also influence drug responses, and whether the associations between the three are population specific remain little known. Using a deep learning network to integrate seven statistical tests for detecting selection signals, we predicted favored mutations in the genomes of 17 human populations. We integrate these favored mutations with GWAS sites and drug response-related variants into the database PopTradeOff. The database also contains genome annotation information on the SNP, sequence, gene, and pathway levels. The preliminary data analyses suggest that substantial associations exist between adaptive evolution, disease susceptibility, and drug responses. The database may be valuable for disease studies, drug development, and personalized medicine.
Publisher
Cold Spring Harbor Laboratory
Reference37 articles.
1. A global reference for human genetic variation
2. A Comparison of Case-Control and Family-Based Association Methods: The Example of Sickle-Cell and Malaria
3. Gene ontology: tool for the unification of biology;The Gene Ontology Consortium. Nat Genet,2000
4. GWAS Central: a comprehensive resource for the discovery and comparison of genotype and phenotype data from genome-wide association studies;Nucleic Acids Res,2020
5. The influence of evolutionary history on human health and disease;Nat Rev Genet,2021