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BMC Genet. 2012; 13: 34.
Published online May 7, 2012. doi:  10.1186/1471-2156-13-34
PMCID: PMC3411438
Gene diversity, agroecological structure and introgression patterns among village chicken populations across North, West and Central Africa
Grégoire Leroy,1,2 Boniface B Kayang,3 Issaka AK Youssao,4 Chia V Yapi-Gnaoré,5 Richard Osei-Amponsah,3 N’Goran E Loukou,5,6 Jean-Claude Fotsa,7 Khalid Benabdeljelil,8 Bertrand Bed’hom,2 Michèle Tixier-Boichard,2 and Xavier Rognoncorresponding author1,2
1AgroParisTech, UMR1313 Génétique Animale et Biologie Intégrative, Paris 05, F-75231, France
2INRA, UMR1313 Génétique Animale et Biologie Intégrative, Jouy-en-Josas, 78352, France
3University of Ghana, Legon, Ghana
4Université d’Abomey-Calavi, Ecole Polytechnique d’Abomey-Calavi, Cotonou, 01 BP 2009, Bénin
5Centre National de la Recherche Agronomique, Abidjan, 01 BP 1740, Côte d’Ivoire
6Université de Cocody, Abidjan, 22 BP 1244, Côte d’Ivoire
7Station Spécialisée de Recherche Agricole de Mankon (SRRAD), Bamenda, BP 4099, Cameroun
8Institut Agronomique et Vétérinaire Hassan II, DPBA, Rabat Instituts, 10101, Rabat, BP 6202, Maroc
corresponding authorCorresponding author.
Grégoire Leroy: gregoire.leroy/at/agroparistech.fr; Boniface B Kayang: bbkayang/at/ug.ed.gh; Issaka AK Youssao: issaka.youssao/at/epac.uac.bj; Chia V Yapi-Gnaoré: evayapi11/at/yahoo.fr; Richard Osei-Amponsah: rich12668/at/yahoo.co.uk; N’Goran E Loukou: nloukou/at/yahou.fr; Jean-Claude Fotsa: fotsajc2002/at/yahoo.fr; Khalid Benabdeljelil: k.jelil/at/iav.ac.ma; Bertrand Bed’hom: bertrand.bedhom/at/jouy.inra.fr; Michèle Tixier-Boichard: michele.boichard/at/jouy.inra.fr; Xavier Rognon: xavier.rognon/at/agroparistech.fr
Received November 4, 2011; Accepted May 7, 2012.
Abstract
Background
Chickens represent an important animal genetic resource for improving farmers’ income in Africa. The present study provides a comparative analysis of the genetic diversity of village chickens across a subset of African countries. Four hundred seventy-two chickens were sampled in 23 administrative provinces across Cameroon, Benin, Ghana, Côte d’Ivoire, and Morocco. Geographical coordinates were recorded to analyze the relationships between geographic distribution and genetic diversity. Molecular characterization was performed with a set of 22 microsatellite markers. Five commercial lines, broilers and layers, were also genotyped to investigate potential gene flow. A genetic diversity analysis was conducted both within and between populations.
Results
High heterozygosity levels, ranging from 0.51 to 0.67, were reported for all local populations, corresponding to the values usually found in scavenging populations worldwide. Allelic richness varied from 2.04 for a commercial line to 4.84 for one population from Côte d’Ivoire. Evidence of gene flow between commercial and local populations was observed in Morocco and in Cameroon, which could be related to long-term improvement programs with the distribution of crossbred chicks. The impact of such introgressions seemed rather limited, probably because of poor adaptation of exotic birds to village conditions, and because of the consumers’ preference for local chickens. No such gene flow was observed in Benin, Ghana, and Côte d’Ivoire, where improvement programs are also less developed. The clustering approach revealed an interesting similarity between local populations found in regions sharing high levels of precipitation, from Cameroon to Côte d’Ivoire. Restricting the study to Benin, Ghana, and Côte d’Ivoire, did not result in a typical breed structure but a south-west to north-east gradient was observed. Three genetically differentiated areas (P < 0.01) were identified, matching with Major Farming Systems (namely Tree Crop, Cereal-Root Crop, and Root Crop) described by the FAO.
Conclusions
Local chickens form a highly variable gene pool constituting a valuable resource for human populations. Climatic conditions, farming systems, and cultural practices may influence the genetic diversity of village chickens in Africa. A higher density of markers would be needed to identify more precisely the relative importance of these factors.
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