Leon Hilgers, Shenglin Liu, Axel Jensen, Thomas Brown, Trevor Cousins, Regev Schweiger, Katerina Guschanski, Michael Hiller
{"title":"Avoidable false PSMC population size peaks occur across numerous studies","authors":"Leon Hilgers, Shenglin Liu, Axel Jensen, Thomas Brown, Trevor Cousins, Regev Schweiger, Katerina Guschanski, Michael Hiller","doi":"10.1101/2024.06.17.599025","DOIUrl":null,"url":null,"abstract":"Inferring historical population sizes is key to identify drivers of ecological and evolutionary change, and crucial to predict the future of species on our rapidly changing planet. The pairwise sequentially Markovian coalescent (PSMC) method provided a revolutionary framework to reconstruct species demographic histories over millions of years based on the genome sequence of a single individual 1. Here, we detected and solved a common artifact in PSMC and related methods: recent population peaks followed by population collapses. Combining real and simulated genomes, we show that these peaks do not represent true population dynamics. Instead, ill-set default parameters cause false peaks in our own and published data, which can be avoided by adjusted parameter settings. Furthermore, we show that certain population structure changes can cause similar patterns. Newer methods like Beta-PSMC perform better, but do not always avoid this artifact. Our results suggest testing multiple parameters before interpreting recent population peaks followed by collapses, and call for the development of robust methods.","PeriodicalId":501183,"journal":{"name":"bioRxiv - Evolutionary Biology","volume":"7 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"bioRxiv - Evolutionary Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.06.17.599025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Inferring historical population sizes is key to identify drivers of ecological and evolutionary change, and crucial to predict the future of species on our rapidly changing planet. The pairwise sequentially Markovian coalescent (PSMC) method provided a revolutionary framework to reconstruct species demographic histories over millions of years based on the genome sequence of a single individual 1. Here, we detected and solved a common artifact in PSMC and related methods: recent population peaks followed by population collapses. Combining real and simulated genomes, we show that these peaks do not represent true population dynamics. Instead, ill-set default parameters cause false peaks in our own and published data, which can be avoided by adjusted parameter settings. Furthermore, we show that certain population structure changes can cause similar patterns. Newer methods like Beta-PSMC perform better, but do not always avoid this artifact. Our results suggest testing multiple parameters before interpreting recent population peaks followed by collapses, and call for the development of robust methods.