1. Conclusion
The observed genetic divergence likely emanated from limited gene flow,
variation in demographic history and route and time of introduction.
Moreover, the two populations might be descended from different ancestral
origins and they have been established and developed under different
management histories. Ecological variability and demographic structure of
the community may have also contributed to this divergence.
Horro chickens are genetically more homogenous than Jarso chickens
(Figure 4). The optimal K was 2, however biologically meaningful pattern
was observed at K = 4 following the marketsheds sampled.
Population n IBS F He Ho
Horro 380 0.723 (0.013) 0.082 (0.112) 0.332 0.304 (0.038)
Jarso 367 0.734 (0.016) 0.085 (0.124) 0.316 0.290 (0.041)
Total 747 0.709 (0.023) 0.129 (0.112) 0.341 0.297 (0.040)
Table 2. Indicators of genetic diversity (mean (std)).
Study site Horro Jarso
Location W. Ethiopia E. Ethiopia
Agro-ecology Sub-humid Semi-arid
Topography Undulating Rugged
Religion 98% Christians 99% Muslims
Rainfall 1685mm 700mm
Temperature 19°C 21°C
Flock size 8 birds 4 birds
Table 1. Description of the study sites.
Figure 1. The study sites.
Figure 2. The binned MAF.
Analysis of genome-wide single nucleotide polymorphisms unlocks the
genetic structure of non-descript Ethiopian village chickens
Introduction
Village chickens make the largest portion of the extant domestic chickens genetic diversity. Artificial selection is less intense and natural selection is the main
force that shapes the genetic structure of village chickens. Ethiopia is one of the centres of origin of ancient agriculture. Ethiopia’s proximity to ancient trade
routes i.e. the Red Sea Coast and the Blue Nile basin enabled it to serve as a gateway for domesticates. Ethiopia is characterized by high ecological,
ethnographic, floral and faunal (livestock) diversity. Efforts have been made to study the genetic structure of Ethiopian village chickens using microsatellite
markers and the hypervariable mtDNA D-loop region. Here, we studied the population structure and genetic diversity of two Ethiopian village chicken populations
(Horro and Jarso) using a high density SNP (600K) array.
Methodology
The two Ethiopian chicken populations Horro (n = 380) and Jarso (n = 367) (Figure
1) were sampled from two contrasting production environments (Table 1). Data
quality control was performed using the GenABEL (Aulchenko et al. 2007). Genetic
diversity indices were calculated using the GenABEL and ADZE software (Szpiech
et al. 2008). Population structure and genetic admixture were analysed using ade4
(Dray and Dufour 2007) and adegenet (Jombart 2008) respectively. Genetic
relationship tree was constructed from genetic distance matrix generated from
Identity by state (IBS) using MEGA5 (Tamura et al. 2011).
Takele T. Desta§, David Wragg, Judy Bettridge, Stacey E. Lynch, Kassech Melese, Marisol Collins, Tadelle Dessie, Zelalem G. Terfa, Paul Wigley, Pete Kaiser,
Rob M. Christley, Joram M. Mwacharo, Olivier Hanotte
§Ecology and Evolution Group, School of Life Sciences, University of Nottingham, University Park, Nottingham, NG7 2RD, UK. E-mail: plxtd@nottingham.ac.uk
Figure 3. PCA of Horro and Jarso chickens.
Figure 5. Within and between populations genetic relationship.
Figure 4. Admixture plot of Horro and Jarso chickens.
References
Aulchenko, Y. S. et al., 2007. Bioinformatics,1294–1296.
Dray, S. and Dufour, A.B. 2007. J. Stat. Softw. 22(4), 1–20.
Jombart T. 2008. Bioinformatics, 24,1403–1405.
Szpiech Z.A. et al., 2008. Bioinformatics, 24(21), 2498–2504.
Tamura, K. et al., 2011. Mol. Biol. Evol. 28, 2731–2739.
Results
Markers informativeness
Average individual and SNP calling rate were > 99% and > 96% of the SNPs are
polymorphic. The binned minor allele frequency (MAF) is presented in Figure 2.
Genetic diversity
The calculated IBS, inbreeding coefficient (F) and expected (He) and observed (Ho)
heterozygosities values are presented in Table 2. Private allelic richness in Horro
and Jarso chickens was 0.0113 and 0.0117 respectively. Both FST and net genetic
distance were 4%, while the between population genetic variation from AMOVA
explained 28%.
Population structure
Principal component, genetic admixture and relationship analyses all clearly
differentiate the two chicken populations (Figures 3–5).