Combination of multiple microsatellite data sets to investigate genetic diversity and admixture of domestic cattle
Microsatellite markers are commonly used for population genetic analyses of livestock. However, up to now, combinations of microsatellite data sets or Microsatellite markers are commonly used for population genetic analyses of livestock. However, up to now, combinations of microsatellite data sets o...
| Autores principales: | , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Wiley
2006
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/1383 |
| _version_ | 1855533671237287936 |
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| author | Freeman, A.R. Bradley, D.G. Nagda, S.M. Gibson, John P. Hanotte, Olivier H. |
| author_browse | Bradley, D.G. Freeman, A.R. Gibson, John P. Hanotte, Olivier H. Nagda, S.M. |
| author_facet | Freeman, A.R. Bradley, D.G. Nagda, S.M. Gibson, John P. Hanotte, Olivier H. |
| author_sort | Freeman, A.R. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Microsatellite markers are commonly used for population genetic analyses of livestock. However, up to now, combinations of microsatellite data sets or Microsatellite markers are commonly used for population genetic analyses of livestock. However, up to now, combinations of microsatellite data sets or comparison of population genetic parameters from different studies and breeds has proven difficult. Often different genotyping methods have been employed, preventing standardization of microsatellite allele calling. In other cases different sets of markers have been genotyped, providing differing estimates of population genetic parameters. Here, we address these issues and illustrate a general two-step regression approach in cattle using three different sets of microsatellite data, to combine population genetics estimates of diversity and admixture. This regression-based method is independent of the loci genotyped but requires common breeds in the data sets. We show that combining microsatellite data sets can provide new insights on the origin and geographical distribution of genetic diversity and admixture in cattle, which will facilitate global management of this livestock species.comparison of population genetic parameters from different studies and breeds has proven difficult. Often different genotyping methods have been employed, preventing standardization of microsatellite allele calling. In other cases different sets of markers have been genotyped, providing differing estimates of population genetic parameters. Here, we address these issues and illustrate a general two-step regression approach in cattle using three different sets of microsatellite data, to combine population genetics estimates of diversity and admixture. This regression-based method is independent of the loci genotyped but requires common breeds in the data sets. We show that combining microsatellite data sets can provide new insights on the origin and geographical distribution of genetic diversity and admixture in cattle, which will facilitate global management of this livestock species. |
| format | Journal Article |
| id | CGSpace1383 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2006 |
| publishDateRange | 2006 |
| publishDateSort | 2006 |
| publisher | Wiley |
| publisherStr | Wiley |
| record_format | dspace |
| spelling | CGSpace13832023-12-27T19:49:15Z Combination of multiple microsatellite data sets to investigate genetic diversity and admixture of domestic cattle Freeman, A.R. Bradley, D.G. Nagda, S.M. Gibson, John P. Hanotte, Olivier H. genetics cattle Microsatellite markers are commonly used for population genetic analyses of livestock. However, up to now, combinations of microsatellite data sets or Microsatellite markers are commonly used for population genetic analyses of livestock. However, up to now, combinations of microsatellite data sets or comparison of population genetic parameters from different studies and breeds has proven difficult. Often different genotyping methods have been employed, preventing standardization of microsatellite allele calling. In other cases different sets of markers have been genotyped, providing differing estimates of population genetic parameters. Here, we address these issues and illustrate a general two-step regression approach in cattle using three different sets of microsatellite data, to combine population genetics estimates of diversity and admixture. This regression-based method is independent of the loci genotyped but requires common breeds in the data sets. We show that combining microsatellite data sets can provide new insights on the origin and geographical distribution of genetic diversity and admixture in cattle, which will facilitate global management of this livestock species.comparison of population genetic parameters from different studies and breeds has proven difficult. Often different genotyping methods have been employed, preventing standardization of microsatellite allele calling. In other cases different sets of markers have been genotyped, providing differing estimates of population genetic parameters. Here, we address these issues and illustrate a general two-step regression approach in cattle using three different sets of microsatellite data, to combine population genetics estimates of diversity and admixture. This regression-based method is independent of the loci genotyped but requires common breeds in the data sets. We show that combining microsatellite data sets can provide new insights on the origin and geographical distribution of genetic diversity and admixture in cattle, which will facilitate global management of this livestock species. 2006-02 2010-05-06T08:56:34Z 2010-05-06T08:56:34Z Journal Article https://hdl.handle.net/10568/1383 en Limited Access Wiley Freeman, A.R.; Bradley, D.G.; Nagda, S.; Gibson, J.P.; Hanotte, O. 2006. Combination of multiple microsatellite datasets to investigate genetic diversity and admixture of domestic cattle. Animal Genetics 37(1):1-9. |
| spellingShingle | genetics cattle Freeman, A.R. Bradley, D.G. Nagda, S.M. Gibson, John P. Hanotte, Olivier H. Combination of multiple microsatellite data sets to investigate genetic diversity and admixture of domestic cattle |
| title | Combination of multiple microsatellite data sets to investigate genetic diversity and admixture of domestic cattle |
| title_full | Combination of multiple microsatellite data sets to investigate genetic diversity and admixture of domestic cattle |
| title_fullStr | Combination of multiple microsatellite data sets to investigate genetic diversity and admixture of domestic cattle |
| title_full_unstemmed | Combination of multiple microsatellite data sets to investigate genetic diversity and admixture of domestic cattle |
| title_short | Combination of multiple microsatellite data sets to investigate genetic diversity and admixture of domestic cattle |
| title_sort | combination of multiple microsatellite data sets to investigate genetic diversity and admixture of domestic cattle |
| topic | genetics cattle |
| url | https://hdl.handle.net/10568/1383 |
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