Genetic disconnectedness in indigenous village chickens Takele Taye Desta § , David Wragg, Joram Mwacharo, Olivier Hanotte Centre for Genetics and Genomics, School of Biology, University of Nottingham, University Park, Nottingham, UK § plxtd@nottingham.ac.uk Introduction Village chickens have been kept by smallholder farmers since the domestication of Gallus gallus. They are characterized by hypervariable phenomic landscape. Specifically, high intra population phenotypic diversity has made largely impractical to assign these populations into clearly defined breeds. Dissecting the genetic structure of admixed populations of this kind requires a large number of genetic markers. Exploring this genetic diversity is important for genetic improvement and conservation management. Here we present the genetic structure of eight village chicken populations sampled from Africa, Asia and Latin America. Study tools Indigenous chickens from Cambodia (n = 4), Sri Lanka (n = 4), Ethiopia (n = 23), Kenya (n = 25), Burkina Faso (n = 8), Botswana (n = 8), Madagascar (n = 8) and Chile (n = 14) were genotyped using 60K Illumina SNP chip. Quality checks were performed in GenABEL 1 and 47486 filtered SNPs were used in downstream analysis. Population structure was assessed using STRUCTURE 2 and PCA 3 . Optimal K was identified using ΔK approach 4 as implemented in Structure Harvester 5 . Fixation indices were calculated in R 6 using custom scripts. Phylogenetic structure and genetic distances were computed using MEGA5 7 . Results and discussions Ancestral population: The ΔK indicated eight ancestral populations. At K = 8, a single predominant genetic background was observed in all populations except Cambodia and Chile, and only two genetic backgrounds were found in the former. The Kenyan population show two genetic groups. The Ethiopian and Burkina Faso populations were differentiated from the remaining populations from K = 2 and k = 3 onwards, respectively. Figure 1. Proportions of admixtures observed in the sampled chicken populations. Population structure: PCA revealed three genetic groups (Fig. 2): (1) Ethiopian, (2) Burkina Faso and (3) the remaining populations. Figure 2. Cluster of populations found using PCA. This genetic stratification was possibly observed due to limited gene flow and/or chickens may have arrived in these regions through different routes and/or at different time periods and/or they may derived from different populations and/or developed under different management histories. Fixation indices: Pairwise F ST values ranged from 0.025 (Kenya vs Botswana) to 0.178 (Burkina Faso vs Cambodia) populations. F IS value was the lowest for Cambodian population (0.025) and the highest was found in Sri Lankan population (0.136). The F IT value was 0.141. These results may indicate little to moderate genetic differentiation and mild level of inbreeding. The deficiency of heterozygotes obtained from paired t-test of global H o and H e (t 47485 = 209.98, P < 0.0001) also confirmed by positive values of fixation indices. (t 47485 = 209.98, P < 0.0001) Genetic distances: Pairwise genetic distance was the lowest between Madagascar and Cambodia populations (0.312), whereas it was the highest between Burkina Faso and Sri Lanka populations (0.369). Within population genetic distance was the lowest for Burkina Faso population (0.207) whereas the highest was found in Sri Lanka population (0.331). Moderate and positive correlation was found at global level between genetic and geographic distances (r = 0.47, P = 0.009, Fig. 3). Figure 3. Regression of genetic distance on geographic distance. Phylogenetic tree: A neighbour-joining phylogenetic tree (Fig. 4) indicates that, except Botswana and Sri Lanka chickens, chickens that sampled from the same country were grouped into their original population group. Figure 4. Neighbour joining phylogenetic tree of sampled chicken populations. Conclusions 1. The admixed nature of village chickens has confounded our ability to observe the expected level of genetic differentiation and to uniquely cluster each population even using large number of genetic markers. 2. The moderate level of population stratification observed at global level might be the consequence of local founder events and management histories. 3. A geographically proportionate and larger sample sizes are required to refine further the genetic structure of these populations. Acknowledgements: This study was financed by BBSRC research grant BB/H009051/1 and hosted by The University of Nottingham. CH4D project is credited for the photographs. Literatures cited 1 Aulchenko, Y. S. et al., 2007. Bioinformatics,1294–1296. 2 Pritchard, J. K. et al., 2000. Genetics 155, 945–959. 3 Dray, S. and Dufour, A.B. 2007. J. Stat. Softw. 22(4), 1–20. 4 Evanno, G. et al., 2005. Mol. Ecol. 14, 2611–2620. 5 Earl, D.A. and vonHoldt, B.M. 2012. Conservation Genet. Resour. 4 (2), 359–361. 6 R Development Core Team, 2012. R Version 2.15.1. 7 Tamura, K. et al., 2011. Mol. Biol. Evol. 28, 2731–2739. Cambodia Ethiopia Sri Lanka Kenya Burkina Faso Botswana Madagascar Chile K=2 K=3 K=4 K=5 K=6 K=7 K=8 K=9 Y = 0.17 + 0.044x, R 2 = 0.22 PC 1 = 6.9% PC 2 = 5.6% Indigenous hen Indigenous cock Flock owners Scavenging flock