{"title":"基因组分析真的能估计过去的人口规模吗?","authors":"Janeesh K Bansal, Richard A Nichols","doi":"10.1016/j.tig.2025.03.003","DOIUrl":null,"url":null,"abstract":"<p><p>Genomic data can be used to reconstruct population size over thousands of generations, using a new class of algorithms [sequentially Markovian coalescent (SMC) methods]. These analyses often show a recent decline in N<sub>e</sub> (effective size), which at face value implies a conservation or demographic crisis: a population crash and loss of genetic diversity. This interpretation is frequently mistaken. Here we outline how SMC methods work, why they generate this misleading signal, and suggest simple approaches for exploiting the rich information produced by these algorithms. In most species, genomic patterns reflect major changes in the species' range and subdivision over tens or hundreds of thousands of years. Consequently, collaboration between geneticists, palaeoecologists, palaeoclimatologists, and geologists is crucial for evaluating the outputs of SMC algorithms.</p>","PeriodicalId":54413,"journal":{"name":"Trends in Genetics","volume":" ","pages":"559-567"},"PeriodicalIF":16.3000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Can genomic analysis actually estimate past population size?\",\"authors\":\"Janeesh K Bansal, Richard A Nichols\",\"doi\":\"10.1016/j.tig.2025.03.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Genomic data can be used to reconstruct population size over thousands of generations, using a new class of algorithms [sequentially Markovian coalescent (SMC) methods]. These analyses often show a recent decline in N<sub>e</sub> (effective size), which at face value implies a conservation or demographic crisis: a population crash and loss of genetic diversity. This interpretation is frequently mistaken. Here we outline how SMC methods work, why they generate this misleading signal, and suggest simple approaches for exploiting the rich information produced by these algorithms. In most species, genomic patterns reflect major changes in the species' range and subdivision over tens or hundreds of thousands of years. Consequently, collaboration between geneticists, palaeoecologists, palaeoclimatologists, and geologists is crucial for evaluating the outputs of SMC algorithms.</p>\",\"PeriodicalId\":54413,\"journal\":{\"name\":\"Trends in Genetics\",\"volume\":\" \",\"pages\":\"559-567\"},\"PeriodicalIF\":16.3000,\"publicationDate\":\"2025-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Trends in Genetics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1016/j.tig.2025.03.003\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/4/25 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trends in Genetics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.tig.2025.03.003","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/4/25 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
Can genomic analysis actually estimate past population size?
Genomic data can be used to reconstruct population size over thousands of generations, using a new class of algorithms [sequentially Markovian coalescent (SMC) methods]. These analyses often show a recent decline in Ne (effective size), which at face value implies a conservation or demographic crisis: a population crash and loss of genetic diversity. This interpretation is frequently mistaken. Here we outline how SMC methods work, why they generate this misleading signal, and suggest simple approaches for exploiting the rich information produced by these algorithms. In most species, genomic patterns reflect major changes in the species' range and subdivision over tens or hundreds of thousands of years. Consequently, collaboration between geneticists, palaeoecologists, palaeoclimatologists, and geologists is crucial for evaluating the outputs of SMC algorithms.
期刊介绍:
Launched in 1985, Trends in Genetics swiftly established itself as a "must-read" for geneticists, offering concise, accessible articles covering a spectrum of topics from developmental biology to evolution. This reputation endures, making TiG a cherished resource in the genetic research community. While evolving with the field, the journal now embraces new areas like genomics, epigenetics, and computational genetics, alongside its continued coverage of traditional subjects such as transcriptional regulation, population genetics, and chromosome biology.
Despite expanding its scope, the core objective of TiG remains steadfast: to furnish researchers and students with high-quality, innovative reviews, commentaries, and discussions, fostering an appreciation for advances in genetic research. Each issue of TiG presents lively and up-to-date Reviews and Opinions, alongside shorter articles like Science & Society and Spotlight pieces. Invited from leading researchers, Reviews objectively chronicle recent developments, Opinions provide a forum for debate and hypothesis, and shorter articles explore the intersection of genetics with science and policy, as well as emerging ideas in the field. All articles undergo rigorous peer-review.