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 GenABEL1 and 47486 filtered SNPs were used in

downstream analysis. Population structure was assessed using STRUCTURE2

and PCA3. Optimal K was identified using ΔK approach4 as implemented in

Structure Harvester5. Fixation indices were calculated in R6 using custom

scripts. Phylogenetic structure and genetic distances were computed using

MEGA57.

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 FST values ranged from 0.025 (Kenya vs Botswana)

to 0.178 (Burkina Faso vs Cambodia) populations. FIS value was the lowest for

Cambodian population (0.025) and the highest was found in Sri Lankan

population (0.136). The FIT 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 Ho and He (t47485 = 209.98,

P < 0.0001) also confirmed by positive values of fixation indices.

(t47485 = 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.

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K=2

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Y = 0.17 + 0.044x, R2 = 0.22

PC 1 = 6.9%

PC 2

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Indigenous hen Indigenous cock

Flock owners Scavenging flock