Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học thế giới đề tài: Consensus genetic structuring and typological value of markers using multiple co-inertia analysis | Genet. Sel. Evol. 39 2007 545-567 INRA EDP Sciences 2007 DOI gse 2007021 Available online at Original article Consensus genetic structuring and typological value of markers using multiple co-inertia analysis Denis LALOẼa Thibaut JOMBARTb Anne-Béatrice DUF0URb Katayoun M0AZAMI-G0UDARZIc a Station de génétique quantitative et appliquée UR337 INRA 78352 Jouy-en-Josas France b Université de Lyon Université Lyon 1 CNRS UMR 5558 Laboratoire de biométrie et biologie évolutive 69622 Villeurbanne Cedex France c Laboratoire de génétique biochimique et de cytogénétique UR339 INRA 78352 Jouy-en-Josas France Received 23 October 2006 accepted 20 April 2007 Abstract - Working with weakly congruent markers means that consensus genetic structuring of populations requires methods explicitly devoted to this purpose. The method which is presented here belongs to the multivariate analyses. This method consists of different steps. First single-marker analyses were performed using a version of principal component analysis which is designed for allelic frequencies PCA . Drawing confidence ellipses around the population positions enhances PCA plots. Second a multiple co-inertia analysis MCOA was performed which reveals the common features of single-marker analyses builds a reference structure and makes it possible to compare single-marker structures with this reference through graphical tools. Finally a typological value is provided for each marker. The typological value measures the efficiency of a marker to structure populations in the same way as other markers. In this study we evaluate the interest and the efficiency of this method applied to a European and African bovine microsatellite data set. The typological value differs among markers indicating that some markers are more efficient in displaying a consensus typology than others. Moreover efficient markers in one collection of populations do not remain efficient in others. The number of markers used in a
