| BackgroundHuman adaptive evolution has long been a hotspot of population genetics research.During the long history of human evolution,populations in different geographic regions have evolved various phenotypic traits to adapt to local survival conditions.Behind these phenotypes are unique favored mutations in the genome of the population.Favored mutations give individuals a survival and reproductive advantages,but genomic hitchhiking on the genome may also allow some neutral or even deleterious mutations to spread through the population,which may affect susceptibility to many diseases,especially when further changes in the survival environment make the original"favored" mutations start to become less favorable.In recent years,several studies have begun to explore this subtle "trade-off" phenomenon,that is,whether adaptive evolution has a corresponding price.In particular,the impact of adaptive evolution on disease susceptibility and drug responsiveness has received increasing attention.A number of questions remain to be explored,including how deep this effect is,whether there is an association between adaptive evolution,disease susceptibility,and drug responsiveness,and to what extent this association is population-specific.Conducting these studies requires the support of data and databases.MethodOur group has previously developed a deep learning network for integrating multiple population genetics statistics and predicting favored mutations on the populations genomes,then predicted favored mutations on the genomes of three populations.This project consists of three parts:(1)further using the deep learning network as a tool to scan the genomes of 17 human populations in Asia,Europe,and Africa,and identify the favored mutations of each population and the hitchhiking mutations nearby,and moreover,the gene function annotation information and expression regulation information of these mutations were collected,(2)disease susceptibility data and drug response data were integrated,and(3)the database PopTradeOff was constructed.ResultThe current version of the PopTradeOff database contains a total of 21,293 favored mutations and 867,379 hitchhiking mutations from 17 populations,encapsulating annotated information such as sequence annotation information,related gene sets and pathway information,QTL locus and transcription factor binding site information,GWAS pathogenic locus information,and drug responsiveness information.The database supports multi-condition combinatorial search,a visual graphical interface based on the IGV genome browser was developed,and the data in the database were preliminary analyzed.ConclusionPreliminary data analysis suggests an association between adaptive evolution,disease susceptibility,and drug responsiveness,and the PopTradeOff database will facilitate in-depth study of this association,with implications for disease research and drug development,and provide a reference for personalized medicine.The PopTradeOff database can be accessed at http.gaemons.net/PopFMSearch. |
