Literature DB >> 25099785

Admixture analysis in relation to pedigree studies of introgression in a minority British cattle breed: the Lincoln Red.

T C Bray1, S J G Hall, M W Bruford.   

Abstract

Investigation of historic population processes using molecular data has been facilitated by the use of approximate Bayesian computation (ABC), which enables the consideration of multiple alternative demographic scenarios. The Lincoln Red cattle breed provides a relatively simple example of two well-documented admixture events. Using molecular data for this breed, we found that structure did not resolve very low (<5% levels) of introgression, possibly due to sampling limitations. We evaluated the performance of two ABC approaches (2BAD and DIYABC) against those of two earlier methodologies, ADMIX and LEADMIX, by comparing their interpretations with the conclusions drawn from herdbook analysis. The ABC methods gave credible values for the proportions of the Lincoln Red genotype that are attributable to Aberdeen Angus and Limousin, although estimates of effective population size and event timing were not realistic. We suggest ABC methods are a valuable supplement to pedigree-based studies but that the accuracy of admixture determination is likely to diminish with increasing complexity of the admixture scenario.
© 2013 Blackwell Verlag GmbH.

Entities:  

Keywords:  ABC methods; admixture; cattle; livestock biodiversity; pedigree

Mesh:

Year:  2013        PMID: 25099785     DOI: 10.1111/jbg.12047

Source DB:  PubMed          Journal:  J Anim Breed Genet        ISSN: 0931-2668            Impact factor:   2.380


  1 in total

1.  Identifying highly informative genetic markers for quantification of ancestry proportions in crossbred sheep populations: implications for choosing optimum levels of admixture.

Authors:  Tesfaye Getachew; Heather J Huson; Maria Wurzinger; Jörg Burgstaller; Solomon Gizaw; Aynalem Haile; Barbara Rischkowsky; Gottfried Brem; Solomon Antwi Boison; Gábor Mészáros; Ally Okeyo Mwai; Johann Sölkner
Journal:  BMC Genet       Date:  2017-08-24       Impact factor: 2.797

  1 in total

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