Genetic diversity and conservation of South African indigenous chicken populations

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1 J. Anim. Breed. Genet. ISSN ORIGINAL ARTICLE Genetic diversity and conservation of South African indigenous chicken populations B. J. Mtileni 1,2, F. C. Muchadeyi 2, A. Maiwashe 1, E. Groeneveld 3, L. F. Groeneveld 3, K. Dzama 2 & S. Weigend 3 1 ARC-Animal Production Institute, Irene, South Africa 2 Department of Animal Science, Stellenbosch University, Matieland, South Africa 3 Institute of Farm Animal Genetics, Friedrich Loeffler Institut, Neustadt-Mariensee, Germany Keywords Chicken genetic resources; conservation flocks; genetic diversity. Correspondence B.J. Mtileni, ARC-Animal Production Institute, Private Bag X2, Irene, 0062, South Africa. Tel: ; Fax: ; jmtileni@arc.agric.za Received: 10 March 2010 accepted: 20 July 2010 Summary In this study, we compare the level and distribution of genetic variation between South African conserved and village chicken populations using microsatellite markers. In addition, diversity in South African chickens was compared to that of a reference data set consisting of other African and purebred commercial lines. Three chicken populations Venda, Ovambo and Eastern Cape and four conserved flocks of the Venda, Ovambo, Naked Neck and Potchefstroom Koekoek from the Poultry Breeding Resource Unit of the Agricultural Research Council were genotyped at 29 autosomal microsatellite loci. All markers were polymorphic. Village chicken populations were more diverse than conservation flocks. structure software was used to cluster individuals to a predefined number of 2 K 6 clusters. The most probable clustering was found at K=5(95% identical runs). At this level of differentiation, the four conservation flocks separated as four independent clusters, while the three village chicken populations together formed another cluster. Thus, cluster analysis indicated a clear subdivision of each of the conservation flocks that were different from the three village chicken populations. The contribution of each South African chicken populations to the total diversity of the chickens studied was determined by calculating the optimal core set contributions based on Marker estimated kinship. Safe set analysis was carried out using bootstrapped kinship values calculated to relate the added genetic diversity of seven South African chicken populations to a set of reference populations consisting of other African and purebred commercial broiler and layer chickens. In both core set and the safe set analyses, village chicken populations scored slightly higher to the reference set compared to conservation flocks. Overall, the present study demonstrated that the conservation flocks of South African chickens displayed considerable genetic variability that is different from that of the assumed founder populations (village chickens). Introduction Village chickens kept under smallholder-low input systems are considered important genetic resources that should be conserved against production threats and replacement with commercial hybrids (Muchadeyi et al. 2005, 2007a). In South Africa and most African countries, indigenous chickens are raised by smallholder farmers with little resources. Characterization of these genetic resources will serve as an ª 2011 Blackwell Verlag GmbH J. Anim. Breed. Genet. 128 (2011) doi: /j x

2 South African chicken genetic resources B. J. Mtileni et al. essential prerequisite for the identification and effective management and utilization of South African indigenous chickens, which will facilitate their conservation. The importance of conservation of chicken genetic resources has long been recognized in South Africa (ARC 2006). An indigenous chicken conservation programme known as the Fowls for Africa Project ( was initiated by the Animal Production Institute of the Agricultural Research Council in Under this programme, four native chicken breeds are kept at the Agricultural Research Council at Irene as conservation flocks of indigenous populations (van Marle-Köster & Nel 2000). The breeds that form part of the conservation flocks include the Venda (VD_C), which is said to have been sampled from the village chicken populations in the Venda region in the Limpopo Province, while Ovambo (OV_C) was sampled from the village chickens from Ovambo region at the border to Namibia. The origin of the Naked Neck (NN) chickens is not well documented, and it is thought that they have been sampled from the communal farmers throughout South Africa and are representative of the genetic reservoir of naked neck village chickens. The Potchefstroom Koekoek (PK) was bred at the former Potchefstroom Agricultural Research Institute during the late forties from a cross between White Leghorn females and Black Australorp males. The Barred Plymouth Rock was later introduced to the breeding programme (Viljoen 1986). This synthetic breed is kept as conservation reservoir of chickens that could be used by communal farmers in South Africa and other African countries. In principle, these conservation flocks, particularly the VD_C, OV_C and NN should efficiently preserve genetic diversity contained in the village chicken Table 1 Allele size ranges and number of alleles per population Number of alleles per population Village (n = 98) Conservation (n = 114) Locus Allele range [bp] OV_F VD_F EC_F OV_C PK_C NN_C VD_C ADL ADL ADL LEI LEI LEI MCW MCW MCW MCW MCW MCW MCW MCW MCW MCW MCW MCW MCW MCW MCW MCW MCW MCW MCW MCW MCW MCW MCW Total ª 2011 Blackwell Verlag GmbH J. Anim. Breed. Genet. 128 (2011)

3 B. J. Mtileni et al. South African chicken genetic resources populations of South Africa. Although research has been conducted to quantify genetic diversity of the South African conservation flocks (van Marle-Köster & Nel 2000; van Marle-Köster et al. 2008; Hassen et al. 2009), no studies have been conducted to determine whether the current conservation flocks are a true representation of the genetic diversity that is found in the village chicken populations of South Africa. Efficient methods have been developed to characterize and quantify differences in genetic make-up of different populations. Microsatellite markers provide insight into the diversity within and between chicken populations (Soller et al. 2006; Hillel et al. 2007; Muchadeyi et al. 2007b; Mwacharo et al. 2007; Bodzsar et al. 2009). The within-population diversity measures have been described as an important component of species variation particularly for recently domesticated species such as chickens (Caballero & Toro 2002). An analysis of the within-population diversity of the conserved and the village chicken population will show whether these two categories have similar genetic makeup or not, while the between-population diversity indices will give an indication of the level of divergence between populations expected to be genetically related. Eding & Meuwissen (2001) proposed the use of marker estimated kinship coefficients between populations based on similarities of marker alleles. Kinship estimates between conserved and village chicken populations will give insight into the level of coancestry between the two groups of South African chickens. Eding et al. (2002) further suggested a core set contribution of a population to the total diversity and safe set method for conservation decisions. Using a core set analysis, in this study will show the genetic contribution of the current conservation population to the total diversity found in village chickens of South, other African village chicken populations as well as intensively raised commercial lines. The overall goal of this study was to determine the effectiveness of the current South African chicken conservation programmes in conserving the diversity of village chicken populations. Specifically, the study sought to compare (i) the level and distribution of genetic variation between South African conserved and village chicken populations using microsatellite markers, and (ii) diversity in South African chicken populations to a reference data set consisting of other African and purebred commercial lines. Data of reference populations were taken from a previous study (Muchadeyi et al. 2007a,b). Materials and methods South African chickens A random sample of chickens from three village chicken populations of the Venda (VD_F, n = 30), Ovambo (OV_F, n = 42) and Eastern Cape (EC_F, n = 26) and four conserved chickens of the Venda (VD_C, n = 30), Ovambo (OV_C, n = 26), Naked Neck (NN_C, n = 29) and Potchefstroom Koekoek (PK_C, n = 29) from the Poultry Breeding Resource Unit of the Agricultural Research Council were used in this study (Table 2). Village chicken populations were sampled from farming regions from which the current conservation flocks originated, which are Limpopo Province (VD_F chickens) and Northern Cape Province along the border with Namibia (OV_F chickens) as well as the Eastern Cape Province (EC_F chickens). Ninety-eight households were randomly selected from 23 villages of Vhembe and Mopani Districts in the Limpopo Province, Kgalagadi and Namaqua Districts of the Northern Cape Province and Alfred Nzo and OR Tambo Districts of the Eastern Cape Province. For each district, 2 5 villages were selected. The distance between villages within a district ranged from km, km between districts within a province and over 1000 km between provinces. One chicken was Table 2 Mean number of alleles (MNA) per locus, expected (H E ) and observed (H O ) heterozygosity and inbreeding coefficient (F IS ) per population Population Sample size MNA SD H O SD H E SD F IS OV_F VD_F EC_F OV_C PK_C NN_C VD_C ª 2011 Blackwell Verlag GmbH J. Anim. Breed. Genet. 128 (2011)

4 South African chicken genetic resources B. J. Mtileni et al. sampled per household. Blood samples were collected from the wing vein onto FTA Micro Cards (Whatman Bio Science, Kent, UK). DNA isolation was carried out following a standard Phenol Chloroform extraction protocol (Sambrook & Russell 2001). Reference populations Data of reference populations consisting of other African (Zimbabwean, Malawian and Sudanese) and purebred commercial lines were taken from previous studies (Muchadeyi et al. 2007b; Bodzsar et al. 2009) to relate genetic diversity in South African chicken populations to a wider data set. Two hundred and thirty-eight scavenging chickens representing a subset of five local chicken ecotypes from Zimbabwe, sixty scavenging chickens that were sampled from Malawi and 48 Sudanese chickens from a similar extensive system of production were used as reference populations in this study. Similar to South African village chicken populations, Zimbabwe, Malawi and Sudanese chickens have not been selected for any particular production traits and show high levels of phenotypic heterogeneity. In addition, six populations were selected from the AVIANDIV project, a European collaborative project on chicken biodiversity. These consisted of broiler dam (BRD) and sire (BRS) lines, two brown egg layers (BL_A and BL_C) and two white egg layers (WL_A and WL_C), with 30 individuals per population. These purebred lines are managed as closed populations with known pedigree and breed histories. These characteristics made them well suited to be used as reference populations in comparison with extensively raised village and intensively raised conserved chickens of South Africa. DNA polymorphism DNA polymorphism was determined using a set of 29 autosomal microsatellite markers (Table 1). These markers have been used in several chicken biodiversity studies (Cuc et al. 2006; Granevitze et al. 2007; Muchadeyi et al. 2007a,b; Bodzsar et al. 2009), and some of the markers were established during the AVIANDIV ( ) project ( fal.de/primer_table.html). They were selected based on their wide distribution over the genome, ease of use, informativeness and suitability for multiplexing. The marker loci correspond to the revised set of microsatellites, which were suggested by FAO-ISAG (2004) for the MoDAD project ( en/refer/library/guidelin/marker.pdf). PCR was used to amplify the specific DNA fragments containing microsatellites as described elsewhere (Muchadeyi et al. 2007b). PCR products were generated using primers fluorescently labelled with IRD700 and IRD800 and visualized on 8% polyacrylamide gel with a LICOR semi-automated DNA analyser (LICOR Biotechnology Division, Lincoln, NE68504). Allele ladders for each locus were used to adjust allele scoring. Allele scoring was performed using RFLPscan software, version 3.5 (Scanalytics Inc., Division of CSP, Billerica, MA, USA) based on LICOR Gene image IR (LI-COR Biotechnology Division). The genotyping of the South African chickens was carried out in the same lab using the same thermocyclers, and the same set of markers as was used for all the reference populations by Muchadeyi et al. (2007b). Statistical analysis Genetic variation within and between populations The observed mean number of alleles (MNA), observed and expected heterozygosity and the inbreeding coefficient (F IS ) per population were computed using the fstat software, version (Goudet 2001). The level of genetic differentiation within and among conservation and village chicken populations were determined using Weir & Cockerham s (1984) estimations of Wright s (1951) fixation indices. Cluster analysis The structure software was used for clustering individuals into populations based on multilocus genotypes (Pritchard et al. 2000). The analysis involved an admixture model with correlated allele frequencies and no linkage. A burn-in phase of iterations followed by iterations was performed for 2 K 6 user-defined number of clusters. The adequacy of this burn-in and subsequent length of the MCMC was checked visually by plotting the parameters a and the Ln against the number of iterations (Granevitze et al. 2009). For each K-value, 100 repeated runs were compared, by calculating similarity coefficients (Rosenberg et al. 2002), in which solutions with similarity coefficients over 95% were considered to be identical. The most frequent solution of each K-value was visualized using the distruct software (Rosenberg 2004). Marker estimated kinship Between and within kinship for South African chicken populations was estimated using Malecot s 212 ª 2011 Blackwell Verlag GmbH J. Anim. Breed. Genet. 128 (2011)

5 B. J. Mtileni et al. South African chicken genetic resources definition of similarity according to Eding & Meuwissen (2001). To construct a phylogenetic network, the values in the Marker estimated kinship (MEK) matrix were converted to distances according to Mateus et al. (2004). Using MEK distances derived from meksafe 1.0 software package (Eding et al. 2002), relationships among seven South African conservation and village chicken populations, as well as the reference populations (Zimbabwean, Malawian, Sudanese and purebred commercial chicken populations) were visualized in a phylogenetic network using splitstree4 software (Hudson & Bryant 2006). Core set contributions and Safe set analysis The contribution of each South African breed to the total diversity of the chickens studied was determined by calculating the optimal core set contributions c(i) of MEK according to Eding et al. (2002). Safe set analysis (Thaon d Arnoldi et al. 1998; Eding et al. 2002) was carried out using bootstrapped kinship values to evaluate the individual contribution each of seven South African chicken populations to the genetic diversity still present in the set of nine reference populations. Results Marker polymorphism, within- and between-population variations All microsatellites typed were found to be polymorphic. A total of 222 alleles were observed for seven South African chicken populations. The MNA per locus, expected (H E ) and observed (H O ) heterozygosity, and inbreeding coefficient (F IS ) per population are presented in Table 2. The MNA per locus ranged from for the VD_C to for the OV_F. Conservation flocks had fewer alleles per locus compared to the village chicken populations. Mean observed heterozygosity (H O ) ranged from to , while expected heterozygosity (H E ) ranged from to in the conservation flocks (mean = 0.56). The corresponding values for the village chicken populations were to for H O and to for H E, respectively. The mean F IT,F ST and F IS coefficients of the conservation and village chicken populations are given in Table 3. The overall inbreeding coefficient (F IT SE) observed for all seven South African populations was High F IT estimate ( ) was observed in the conservation flocks. Between-population variability (F ST estimates) Table 3 Overall-population (F IT ), between-populations (F ST ) and withinpopulation (F IS ) inbreeding coefficients and their standard errors (SE) of village and conservation chicken populations Population F IT SE F ST SE F IS SE Village Conservation ) Overall was in this group of populations. An F IT of and an F ST of were observed in the village chicken populations. The conservation flocks showed higher genetic differentiation between populations than the village chicken populations. The F IS estimate for conservation flocks was lower () ) than that of the village chicken populations ( ). Cluster analysis structure software was applied for clustering individuals to 2 K 6 clusters (Figure 1). At the lowest K-value (K =2), the VD_C and NN_C conservation flocks split from others to form their own cluster. At K=3, VD_C and NN_C separated and formed independent clusters, while the other breeds remained together. While PK_C split at K=4, the most probable clustering was found at K=5 (n =95). VD_C, OV_C, PK_C and NN_C conservation flocks made up independent clusters, while the VD_F, OV_F and EC_F village chicken populations formed one common cluster for any K-value. Figure 1 structure clustering of seven South African conserved and village chicken populations. Numbers in parentheses indicate the number of identical solutions at 95% threshold. Keys Conservation flock: OV_C = Ovambo; VD_C = Venda; NN_C = Naked Neck; PK_C = Potchefstroom Koekoek; Village chicken population: OV_F = Ovambo; VD_F = Venda; EC_F = Eastern Cape. ª 2011 Blackwell Verlag GmbH J. Anim. Breed. Genet. 128 (2011)

6 South African chicken genetic resources B. J. Mtileni et al. Marker estimated kinship Between (below diagonal) and within (on the diagonal) MEK for South African chicken populations are presented in Table 4. Within-breed kinship estimates were higher in the conservation flock, varying between and for OV_C and VD_C compared to estimates between and for OV_F and VD_F village chicken populations, respectively. The lowest between-breed kinship estimate of was observed between VD_C and PK_C, while the highest value of was found between PK_C and OV_C conservation flocks. Relationships between South African and reference chicken populations A phylogenetic network of the relationships between the South African conserved and village chicken populations, other African and commercial lines based on MEK distances is presented in Figure 2. The South African and other African populations clustered together in the middle, while the commercial lines WL_A, WL_C, BL_A, BL_C, BRD_A and BRS_A formed three separate clusters away from African populations. Core set contributions and Safe set analysis Data of reference populations consisting of other African (Zimbabwean, Malawian and Sudanese) and purebred commercial lines (Broiler dam line A, Broiler sire line A, Brown egg layer A, Brown egg layer C, White egg layer A and White egg layer C) were taken from previous studies (Muchadeyi et al. 2007b; Bodzsar et al. 2009) to relate South African chicken populations to a reference data set. The relative core set contributions c(i) of South African chicken populations and the total diversity of the reference set of populations, that are considered as safe, are given in Table 5. A total core set of conserved diversity Table 4 Between (below diagonal) and within (bold) Marker estimated kinship values for South African chicken populations Population OV_F VD_F EC_F OV_C PK_C NN_C VD_C OV_F VD_F EC_F OV_C PK_C NN_C VD_C Figure 2 Network tree on the relationships between the South African conserved and village chicken populations, African and commercial lines based on Marker Estimated Kinships (MEK) distances. Keys Conservation flock: OV_C = Ovambo; VD_C = Venda; NN_C = Naked Neck; PK_C = Potchefstroom Koekoek; Village chicken population: OV_F = Ovambo; VD_F = Venda; EC_F = Eastern Cape; African population: ZIM = Zimbabwe ecotypes; MAL = Malawi; SUD = Sudan; Commercial breeds: BRD_A = Broiler dam line A; BRS_A = Broiler sire line A; BL_A = Brown egg layer A; BL_C = Brown egg layer C; WL_A = White egg layer A; WL_C, White egg layer C. was observed in the South African chicken populations (data not shown). The highest contribution to the total diversity of South African populations c(i) = was observed for OV_F, a contribution of c(i) = was obtained for PK_C. The total diversity of the reference safe set was and for other African populations (Zimbabwe, Malawi and Sudan) and purebred lines, respectively, which suggests that 92 and 90% of the genetic variance in a potential founder population is conserved in both sets of reference populations. The total genetic diversity of both safe sets plus one South African breed Div(S + i) and the diversity added by one South African breed not in the safe set d(i)*1000 are shown. The highest diversity added (d(i)*1000 = ) was observed for OV_F and EC_F (d(i)*1000 = ) for African and purebred commercial lines, respectively, while the lowest diversity for both reference sets was added by PK_C. Discussion The observed within-population diversity measures indicated that the village chicken populations were more diverse than the conservation flocks. The relatively fewer alleles (lower than 4) in the NN_C and VD_C conservation flocks than in village chickens (Table 2) indicate that each conserved population 214 ª 2011 Blackwell Verlag GmbH J. Anim. Breed. Genet. 128 (2011)

7 B. J. Mtileni et al. South African chicken genetic resources Table 5 Core set contributions c(i) and added genetic diversity Div(S+i) of seven South African chicken populations to safe set consisting of reference populations of three African populations and six purebred commercial lines, respectively Population c(i) Other African populations Purebred commercial lines Div(S+i) d(i)*1000 Div(S+i) d(i)*1000 OV_F VD_F EC_F OV_C PK_C NN_C VD_C SAFE SET represents a limited sample of the gene pool. Similarly, low MNA observed in Spanish native chicken breeds maintained in a conservation programme was reported by Dávila et al. (2009). On the other hand, the village chicken populations in this study had more alleles (greater than 4). This could be attributed to continuous gene flow, where the chickens are kept more or less free ranging and mixing with other chicken flocks. A similar MNA was observed in other free-ranging chickens reported by Muchadeyi et al. (2007b) in Zimbabwean, Malawian and Sudanese chicken populations. The high F ST estimates (Table 3) showed a high level of population differentiation between the VD_C, OV_C, NN_C and PK_C conservation flocks. These conservation flocks behaved in a similar way as Spanish native chicken breeds (Dávila et al. 2009) and purebred commercial lines (Muchadeyi et al. 2007a,b) that exhibited high between population variations because of population substructuring. Estimated inbreeding coefficients (F IS, Table 2) of conservation flocks were lower than that of the village chicken populations, which is in contrast to the report by van Marle-Köster et al. (2008), who found higher levels of potential inbreeding in these conservation flocks. Our results suggest that although raised as closed populations with restricted gene flow between populations and based on limited size of founder population, the current conservation flocks are of both sufficient population size and management leading to low levels of inbreeding. Relative to the total genetic diversity (F IT ), the village chicken populations showed lower F ST values, and higher F IS (Table 3) suggesting lack of population substructuring between the VD_F, OV_F and EC_F groups. In Africa, recent molecular studies on local chickens have shown that Zimbabwean populations separated by km were also not genetically differentiated, with an F ST averaging (Muchadeyi et al. 2007b). Mwacharo et al. (2007) identified genetic subdivisions between the Kenyan and Ugandan chicken populations and the Ethiopian and Sudanese chicken populations, but within a country, the F ST values were always lower than 0.1. Within the different subpopulations of village chickens, however, a higher heterozygosity was expected based on allele frequencies found, but observed heterozygosity was lower suggesting further substructuring. The resultant elevated F IS (Table 2) suggests further substructuring of village chicken populations encompassing several smaller flocks each being less diverse. Overall, the assessment of within- and between-population diversity indices showed that the conserved and village chicken populations have different characteristics. The village chicken populations are highly diverse with no clear substructuring based on sampling location. The conservation flocks on the other hand are less diverse and highly substructured into distinct breeds raised as different flocks. Similar lack of population substructuring was observed for the Zimbabwean chickens by Muchadeyi et al. (2007b), whereas the opposite situation of low level of admixture was evidenced for Hungarian chicken breeds (Bodzsar et al. 2009). structure-based clustering indicated a clear subdivision between the conservation flocks and village chicken populations. The most probable clustering was found at K=5, in which the four conservation flocks separated as independent clusters, while the three village chicken populations formed one cluster for any K-value. The placement of the conservation and village chickens flocks in different assumed clusters is an indication of differences in allele frequencies between the two groups of populations. Our working hypotheses assumed that populations of the same founder population such as VD_F and VD_C have similar allele frequencies and therefore cluster together. Results showed, however, that the village chickens and conservation flocks were associated with different allele frequencies. Differences in allele frequencies could either be because of differences in the founder populations between both conservation and village chicken flocks. This would lead to a rejection of the assumption that the conservation flocks were established from the studied village chicken populations. Alternatively, the conservation flocks may have been founded on the respective ª 2011 Blackwell Verlag GmbH J. Anim. Breed. Genet. 128 (2011)

8 South African chicken genetic resources B. J. Mtileni et al. village chicken flocks but diverged randomly with time because of small effective population size. Considering the population management and the cumulative founder effect of a conservation programme, where a breed was based on only a limited number of sampled individuals, the conservation flocks could have drifted from the founder village chicken flocks. A loss of genetic variation because of founder effect was also reported by Zanetti et al. (2010) for the Veneto local chicken breeds when involved in a conservation scheme. Either way the results of structure clustering and those of F Statistics discussed earlier clearly show that the conservation flocks are genetically different from the village chicken populations of South Africa. Within-breed kinship estimates (MEK) were higher in the conservation flocks, compared to village chicken populations. The higher kinship observed in the conservation flocks could be because of mating of more closely related individuals than in village chickens because of limited population size (Granevitze et al. 2007). Furthermore, although the populations seem to be well managed as evidenced by low F IS estimates discussed earlier, it could be that they were started based on a small number of founder males and females leading to high kinship estimates. The low kinship estimates in the village chicken populations, on the other hand, could be associated with having several small flocks managed more or less independent of each other coupled with continuous but limited gene flow between the subpopulations (Muchadeyi et al. 2007b). The network analysis based on MEK confirmed the clustering observed in the structure analysis (Figure 2). Genetic differentiation exists between the four conservation flocks and village chicken populations. Relating South African chickens to a reference data set consisting of other African and purebred commercial lines, the network analysis showed considerable genetic diversity between the African populations and the purebred commercial lines. Except BRD_A and BRS_A lines, purebred commercial lines have longer branches indicating a larger distance. The contribution of all South African chicken populations studied to the total diversity of a given set of populations was higher when added to the reference set consisting of other African populations than when added to the purebred commercial lines. The significant differences between the village chicken populations and conservation flocks of South Africa implies that more genetic benefit will be gained if village chicken populations are incorporated in the current conservation programme. Ruane (1999) further confirmed that adaptive features, traits of scientific and economic interest, cultural-historical values, strong links to regional traditions, and ability to generate income associated with most of these village chicken populations further justify conservation efforts. For this reason, phenotypic observations or monitoring of productive traits combined with molecular analysis can be useful information for conservation decisions. In conclusion, the conservation flocks displayed a considerable between breeds genetic variability that is different from that of the respective village chicken populations. Therefore, the current conservation flocks are at most a partial representation of the genetic diversity that is found in the village chicken populations of South Africa. In both core set and the safe set analyses, village chicken populations scored slightly higher to the reference set compared to conservation flocks. For effective management and utilization of South African indigenous chicken populations, effort should be made to incorporate the unique genetic resources of the village chicken populations into the conservation programme. Resampling from the current village chicken population might be the appropriate action. This should be coupled with proper management of these conservation flocks to ensure genetic diversity is maintained in time. Acknowledgements Department of Science and Technology in South Africa and the Federal Ministry of Food, Agriculture and Consumer Protection of Germany are acknowledged for financial support of this study. The project was supported by the bilateral cooperation programme in agricultural research between South Africa and the Federal Republic of Germany. We also thank farmers in the three provinces of South Africa for their cooperation during blood collection and the University of Western Cape where DNA isolation was carried out. 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