Published online by Cambridge University Press: 04 September 2015
Smallholder farmers in Africa and other developing countries raise village chickens under low input production systems characterised by minimal management and veterinary interventions. However, village chickens have a major contribution to village communities as a source of protein, income and cultural needs. The village chickens are described as nondescript birds that have not been developed as a breed and with uncharacterised genetic attributes. Local chickens are found in the most marginalised farming systems, to which they have adapted and survived the harsh production and environmental conditions. Such survival and adaptive attributes need to be characterised, conserved, and utilised. Several studies on Southern African local chickens have revealed high genetic variation within and among the village chicken populations and indicated that village chickens contribute diversity that is unique and different from that of commercial and specialised chicken populations. The availability of whole genome single nucleotide polymorphism (SNP) data facilitates the use of powerful statistical methods for in depth investigations into the evolutionary history and population demographics of village chickens. Linkage disequilibrium (LD), as a function of effective population size, has been used to estimate rate and level of inbreeding as well as selection pressures in the absence of pedigree information. The extent and distribution of LD in the genome has been exploited to shed light on the origin and domestication of animals and facilitate an understanding of breeds’ relatedness. The Illumina iSelect chicken 60K SNP chip has over 54 000 SNPs that have found application in population and quantitative genetics studies and has revealed demographic history, effective population size and level of genetic erosion in commercial and traditional/village chicken populations. The recent launching of the 600 K Affymetrix® Axiom® HD genotyping array for chickens and the ever decreasing cost of sequencing will see improved estimation of LD and the associated population parameters.