Wolfgang Arthofer, Carina Heussler, Patrick Krapf, Birgit C Schlick-Steiner, Florian M Steiner
{"title":"确定评估种群遗传结构所需的最小微卫星位点数量:以蝇类养殖为例。","authors":"Wolfgang Arthofer, Carina Heussler, Patrick Krapf, Birgit C Schlick-Steiner, Florian M Steiner","doi":"10.1080/19336934.2017.1396400","DOIUrl":null,"url":null,"abstract":"<p><p>Small, isolated populations are constantly threatened by loss of genetic diversity due to drift. Such situations are found, for instance, in laboratory culturing. In guarding against diversity loss, monitoring of potential changes in population structure is paramount; this monitoring is most often achieved using microsatellite markers, which can be costly in terms of time and money when many loci are scored in large numbers of individuals. Here, we present a case study reducing the number of microsatellites to the minimum necessary to correctly detect the population structure of two Drosophila nigrosparsa populations. The number of loci was gradually reduced from 11 to 1, using the Allelic Richness (AR) and Private Allelic Richness (PAR) as criteria for locus removal. The effect of each reduction step was evaluated by the number of genetic clusters detectable from the data and by the allocation of individuals to the clusters; in the latter, excluding ambiguous individuals was tested to reduce the rate of incorrect assignments. We demonstrate that more than 95% of the individuals can still be correctly assigned when using eight loci and that the major population structure is still visible when using two highly polymorphic loci. The differences between sorting the loci by AR and PAR were negligible. The method presented here will most efficiently reduce genotyping costs when small sets of loci (\"core sets\") for long-time use in large-scale population screenings are compiled.</p>","PeriodicalId":12128,"journal":{"name":"Fly","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2018-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19336934.2017.1396400","citationCount":"25","resultStr":"{\"title\":\"Identifying the minimum number of microsatellite loci needed to assess population genetic structure: A case study in fly culturing.\",\"authors\":\"Wolfgang Arthofer, Carina Heussler, Patrick Krapf, Birgit C Schlick-Steiner, Florian M Steiner\",\"doi\":\"10.1080/19336934.2017.1396400\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Small, isolated populations are constantly threatened by loss of genetic diversity due to drift. Such situations are found, for instance, in laboratory culturing. In guarding against diversity loss, monitoring of potential changes in population structure is paramount; this monitoring is most often achieved using microsatellite markers, which can be costly in terms of time and money when many loci are scored in large numbers of individuals. Here, we present a case study reducing the number of microsatellites to the minimum necessary to correctly detect the population structure of two Drosophila nigrosparsa populations. The number of loci was gradually reduced from 11 to 1, using the Allelic Richness (AR) and Private Allelic Richness (PAR) as criteria for locus removal. The effect of each reduction step was evaluated by the number of genetic clusters detectable from the data and by the allocation of individuals to the clusters; in the latter, excluding ambiguous individuals was tested to reduce the rate of incorrect assignments. We demonstrate that more than 95% of the individuals can still be correctly assigned when using eight loci and that the major population structure is still visible when using two highly polymorphic loci. The differences between sorting the loci by AR and PAR were negligible. The method presented here will most efficiently reduce genotyping costs when small sets of loci (\\\"core sets\\\") for long-time use in large-scale population screenings are compiled.</p>\",\"PeriodicalId\":12128,\"journal\":{\"name\":\"Fly\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2018-01-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/19336934.2017.1396400\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fly\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1080/19336934.2017.1396400\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2017/12/1 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fly","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1080/19336934.2017.1396400","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2017/12/1 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Identifying the minimum number of microsatellite loci needed to assess population genetic structure: A case study in fly culturing.
Small, isolated populations are constantly threatened by loss of genetic diversity due to drift. Such situations are found, for instance, in laboratory culturing. In guarding against diversity loss, monitoring of potential changes in population structure is paramount; this monitoring is most often achieved using microsatellite markers, which can be costly in terms of time and money when many loci are scored in large numbers of individuals. Here, we present a case study reducing the number of microsatellites to the minimum necessary to correctly detect the population structure of two Drosophila nigrosparsa populations. The number of loci was gradually reduced from 11 to 1, using the Allelic Richness (AR) and Private Allelic Richness (PAR) as criteria for locus removal. The effect of each reduction step was evaluated by the number of genetic clusters detectable from the data and by the allocation of individuals to the clusters; in the latter, excluding ambiguous individuals was tested to reduce the rate of incorrect assignments. We demonstrate that more than 95% of the individuals can still be correctly assigned when using eight loci and that the major population structure is still visible when using two highly polymorphic loci. The differences between sorting the loci by AR and PAR were negligible. The method presented here will most efficiently reduce genotyping costs when small sets of loci ("core sets") for long-time use in large-scale population screenings are compiled.
期刊介绍:
Fly is the first international peer-reviewed journal to focus on Drosophila research. Fly covers a broad range of biological sub-disciplines, ranging from developmental biology and organogenesis to sensory neurobiology, circadian rhythm and learning and memory, to sex determination, evolutionary biology and speciation. We strive to become the “to go” resource for every researcher working with Drosophila by providing a forum where the specific interests of the Drosophila community can be discussed. With the advance of molecular technologies that enable researchers to manipulate genes and their functions in many other organisms, Fly is now also publishing papers that use other insect model systems used to investigate important biological questions.
Fly offers a variety of papers, including Original Research Articles, Methods and Technical Advances, Brief Communications, Reviews and Meeting Reports. In addition, Fly also features two unconventional types of contributions, Counterpoints and Extra View articles. Counterpoints are opinion pieces that critically discuss controversial papers questioning current paradigms, whether justified or not. Extra View articles, which generally are solicited by Fly editors, provide authors of important forthcoming papers published elsewhere an opportunity to expand on their original findings and discuss the broader impact of their discovery. Extra View authors are strongly encouraged to complement their published observations with additional data not included in the original paper or acquired subsequently.