Genetic diversity and population structure in Portuguese goat breeds

Livestock Science 135 (2011) 131–139

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Livestock Science j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / l i v s c i

Genetic diversity and population structure in Portuguese goat breeds C. Bruno-de-Sousa a,b, A.M. Martinez c, C. Ginja a,d, F. Santos-Silva a, M.I. Carolino a, J.V. Delgado c, L.T. Gama a,b,⁎ a b c d

L-INIA, Instituto Nacional de Recursos Biológicos, 2005-048 Vale de Santarém, Portugal Faculdade de Medicina Veterinária, Universidade Técnica de Lisboa, 1300-477 Lisboa, Portugal Departamento de Genética, Universidad de Córdoba, Campus Rabanales C-5 14071, Córdoba, Spain Veterinary Genetics Laboratory, University of California, One Shields Avenue, Davis, CA 95616, USA

a r t i c l e

i n f o

Article history: Received 21 January 2010 Received in revised form 13 June 2010 Accepted 28 June 2010 Keywords: Genetic diversity Goats Microsatellites Native breeds Population structure

a b s t r a c t Genetic diversity was assessed in the Portuguese native breeds of goats Algarvia (AL), Bravia (BR), Charnequeira (CH), Preta de Montesinho (PM), Serpentina (SP) and Serrana (SR), by analyzing 25 microsatellite markers in 193 animals. Genetic variability was high, with means for expected heterozygosity of 0.70 across loci, and nearly 7.0 and 4.4 for total and effective number of alleles per locus, respectively. The six breeds analyzed had similar levels of genetic variability, and the estimated FST was 0.031, indicating that, with the neutral genetic markers used, the proportion of genetic variability accounted for by differences among breeds is small. Depending on the breed considered, between 0.16 and 0.28 of the loci presented significant departures from Hardy–Weinberg proportions, mostly because of a deficit in heterozygosity, with a significant positive FIS in most breeds, particularly in PM. The dendrogram based on Nei's standard genetic distance and the analysis by principal components indicate a separation of AL and BR from the remaining breeds, with some clustering of PM with SR, and of SP with CH, in agreement with their geographical distribution. Individual distances based on allele sharing indicate that only AL and BR animals tended to cluster together, while overlapping was common for the other breeds. The analysis with STRUCTURE confirmed the separation of AL and BR, which were more closely identified with independent clusters of potential ancestral populations. For the other breeds, there was clear evidence of admixture, with various ancestral populations contributing differently to the current breeds. Evidence was found of a geographical cline, with a given ancestral population contributing more to breeds located nearby, and with a declining contribution as the geographical distribution of breeds became more distant. Our results indicate that native breeds of goats in Portugal present high levels of genetic diversity, but the differentiation among closely located breeds is weak. Some of the breeds show signs of genetic erosion, which imply the need for urgent measures of conservation and sustainable management of their gene pool. © 2010 Elsevier B.V. All rights reserved.

1. Introduction As in most countries of the Mediterranean region, native goat breeds in Portugal play a major role in utilizing resources available under extensive production systems and marginal areas, thus contributing for environmental and socio-economic ⁎ Corresponding author. Tel.: + 351 243767382; fax: + 351 243767307. E-mail address: [email protected] (L.T. Gama). 1871-1413/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.livsci.2010.06.159

stability. Traditionally, local breeds of goats have been an integral part of local culture and are the basis of several high quality food products, but their major role is the productive use of shrub and forest areas which, if not used by goats, would be left abandoned (Gama, 2006). Breeds of goats in Portugal have evolved over time to fit the diversity of local environmental conditions, and five native breeds were recognized until recently, specifically Algarvia, Bravia, Charnequeira, Serpentina and Serrana (Direcção Geral

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da Pecuária, 1987). In the recent past, one very small and isolated population was officially recognized as a differentiated breed (Preta de Montesinho). These breeds have in common their ability to take advantage of marginal and forest areas, but show large differences in type and production abilities, summarized in Table 1, and have a geographical dispersion shown in Supplementary Fig. S1. In the past, goats in Portugal were often kept jointly with sheep flocks, and transhumance was a common practice throughout the Iberian Peninsula, with seasonal movements from mountain to plain areas and vice-versa (Rigueiro-Rodríguez et al., 2009). This practice may have provided the opportunity for occasional admixing among herds and breeds from different regions, which would be reflected in reduced levels of genetic differentiation between the breeds currently existing. This pattern was shown in studies carried out at a more global level, covering several breeds from Europe, Asia and Africa (Luikart et al., 2001, Naderi et al., 2007), which showed that, comparatively to other livestock, goats have very low levels of phylogeographic structure, possibly due to the high mobility of the species. The intensification of agriculture, which took place mostly during the second half of the 20th century, led to the widespread use of a reduced number of exotic breeds under intensive systems. These breeds were often used in uncontrolled crossbreeding with local breeds, and this resulted in the extinction or endangerment of several native livestock breeds in Portugal, as in some other countries. Among those, goat breeds were the most threatened over the last few years, with a reduction of nearly 20% in the census of registered animals of the different breeds between 1999 and 2004 (Gama et al., 2005). The majority of the native breeds of goats in Portugal currently have a census that places them in an endangered status (Table 1), such that presently only the Serrana breed is not considered to be at risk of extinction, and all the other breeds receive financial support in the framework of national programs aimed at preventing breed extinction. Maintenance of genetic diversity in livestock species depends upon the definition and implementation of appropriate conservation and sustainable management programs, which should be based on comprehensive information regarding the structure of the populations, including sources of genetic variability among and within-breeds (Notter, 1999). The loss in genetic diversity resulting from extinction of a given breed can be used in the definition of conservation priorities (Weitzman, 1993) and Caballero and Toro (2002) have proposed that the contribution of a breed to both betweenand within-breed variability should be taken into account when

evaluating its contribution to overall genetic diversity. Neutral genetic markers, such as microsatellites, are extremely useful for the analysis of population structure and relationships, and have been widely used for genetic characterization of several species and populations, including goats (Araújo et al., 2006; Barker et al., 2001; Behl et al., 2003; Cañon et al., 2006; Fatima et al., 2008; Ganai and Yadav, 2001; Glowatzki-Mullis et al., 2008; Gour et al., 2006; Iamartino et al., 2005; Li et al., 2002; Luikart et al., 1999; Martínez et al., 2006; Muema et al., 2009; Oliveira et al., 2007; Qi et al., 2009; Saitbekova et al., 1999; Sechi et al., 2005; Tadlaoui-Ouafi et al., 2002; Traoré et al., 2009; XiangLong and Valentini, 2004; Wang et al., 2008). It is widely accepted that, when genetic diversity studies are conducted for a given species, it is desirable that a common panel of genetic markers is used, as this promotes broad-scope studies combining information derived from different analyses and breed groups (Baumung et al., 2004). Support measures have been in place to prevent the extinction of endangered breeds of goats in Portugal, in the framework of European Union programs. Nevertheless, information on genetic diversity and differentiation of Portuguese goat breeds is essential to the establishment of appropriate conservation and sustainable management programs, in order to prevent extinction and genetic erosion of these breeds, which are, in most cases, highly endangered. Information on the genetic structure and variability of native breeds of goats in Portugal is very limited, and mostly based on results obtained with monoparental genetic markers (Pereira et al., 2005, 2009). This study was carried out to obtain a better understanding of the degree and pattern of genetic variability in Portuguese breeds of goats, with the final goal of defining conservation priorities and establish appropriate breeding strategies. With this purpose, a set of 25 microsatellite markers was used to 1) assess the within- and among breeds genetic diversity and 2) investigate population structure and the degree of admixture among the six native breeds of goats currently existing in Portugal. 2. Materials and methods Blood samples were collected from a total of 193 herdbook-registered animals of the six Portuguese native breeds of goats, including Algarvia (AL), Bravia (BR), Charnequeira (CH), Preta de Montesinho (PM), Serpentina (SP) and Serrana (SR). The number of animals sampled per breed is specified in Table 1. Samples were collected in 10 to 39 herds per breed,

Table 1 Number of animals and herds sampled, major characteristics, census and main geographical location of Portuguese native goat breeds. Breed characteristics Breed

Animals/ herds

Hair length

Hair colour

Major purpose

Mature weight (kg)

Census a

Geographical distribution

Algarvia (AL) Bravia (BR) Charnequeira (CH) Preta de Montesinho (PM) Serpentina (SP) Serrana (SR)

29/29 39/39 29/10 36/13 30/17 30/26

Short Short Short Short Short Long

White with brown spots Brown Red to dark brown Black White with black dorsal stripe Gray or dark brown to black

Milk Meat Dual Milk Dual Milk

45–55 25–35 45–55 35–45 50–60 30–40

4700 9700 5100 200 4200 19,500

South Northwest Center-east Northeast Mid-south North and Center

a

Number of registered breeding females.

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and an attempt was made to have both sexes equally represented, and to avoid sampling of animals related up to the second generation. A set of 25 microsatellite markers was selected from those recommended by the FAO-ISAG group (Hoffmann et al., 2004), as specified in Table 2. The markers were chosen taking into account their polymorphism as observed in previous studies, compatibility in the range of allele sizes and the ability to coamplify in multiplex PCR reactions. Genomic DNA was isolated from whole blood using a commercial extraction and purification kit (DNeasy™ Blood Kit — Qiagen), according to the manufacturer's protocol. The selected markers were PCR amplified in eight multiplex reactions (Table 2), as described by Santos-Silva et al. (2008). The PCR products were separated by capillary electrophoresis in automated sequencers ABI377XL and ABI310 (Applied Biosystems, Madrid, Spain) and the results were read directly with the Genescan® software and interpreted with Genotyper®. The Genetix 4.0.4 software (Belkhir et al., 1998) was used to estimate allele frequencies, mean number of alleles, mean observed (Ho) and unbiased expected (He) heterozygosities, per locus and population, and the effective number of alleles per locus was calculated from the expected heterozygosity (Hartl and Clark, 1997). The polymorphic information content (PIC) and the probability of parentage exclusion when both parents are known (PE), were calculated with Cervus 2.0 software (Marshall, 2001). Deviations from Hardy–Weinberg expectations were tested per locus and per breed with the Genepop statistical package version 3.4 (Raymond and Rousset, 2001) and the Fstatistics of Wright (1969) were calculated according to Weir and Cockerham (1984) using the Genetix 4.0.4 software (Belkhir et al., 1998). Inbreeding (FIS) was estimated for each breed, and P-values obtained based on 1000 permutations. The Populations 1.2.28 software (Langella, 2002) was used to obtain Nei's standard genetic distances among breeds and allele sharing distances among individuals. The neighbourjoining dendrograms were constructed with Populations and edited in TreeView (Page, 1996). Robustness of the dendrograms was assessed by bootstrap re-sampling procedures, using 1000 replicates. Representation of the genetic relationships among the goat populations analyzed was also obtained by the multivariate method of correspondence analysis (Lebart et al., 1984), using the Genetix 4.0.4. software (Belkhir et al., 1998). The Bayesian clustering algorithm implemented by the STRUCTURE v.2.1. software (Pritchard et al., 2000) was used to assess the number of ancestral populations underlying the breeds analyzed, and the proportion of mixed ancestry among them. With this approach, it is assumed that an individual may show contributions from different underlying populations, and a Monte Carlo–Markov Chain simulation is used to infer the most probable number of population clusters, and to estimate the proportional contribution of each of the assumed populations to the genotype of an individual. In our study, the number of assumed populations (K) was evaluated for K values ranging from 2 to 7, and the probability (or likelihood) of the different values was tested by assessing Ln Pr(X|K), i.e., the likelihood of the observed distribution of genotypes given the assumed number of ancestral populations. For each value of K, five independent

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analyses were carried out under an admixture model, with a burn-in period of 1 ⁎ 105 iterations, followed by run lengths of 5 ⁎ 105 iterations, to obtain the corresponding Ln Pr(X|K). The proportional contribution of each inferred ancestral populations to a given individual was obtained for each value of K, and the results were graphically displayed with the DISTRUCT software (Rosenberg, 2002). After determining the most likely number of underlying populations, the contribution of each of the K populations to each breed was estimated. 3. Results 3.1. Microsatellite markers Allele frequencies are available from the authors upon request. All the 25 loci analyzed were found to be polymorphic, with a total of 240 alleles detected in the 193 individuals of six populations studied. The number of alleles per locus ranged from 3 (MAF209) to 18 (HSC), with a global mean of 9.60 ± 4.09 for the total and 4.38± 2.29 for the effective number of alleles (Table 2). Most markers had high levels of polymorphism, with PIC ranging from 0.181 (ETH225) to 0.896 (HSC), with a global mean of 0.665 ± 0.182. The probability of exclusion in parentage testing was nearly 0.80 for the HSC and MM12 markers, but only about 0.10 for ETH225 and MAF209, with an overall mean of 0.506 ± 0.187. The mean He across loci was 0.702±0.176, with estimates per locus ranging from 0.188 (ETH225) to 0.907 (HSC). For Ho, the mean for all loci was 0.636±0.169, and the range was between 0.191 (ETH225) and 0.844 (MM12). With the exception of ETH225, the Ho was lower than He in all the loci studied. Of the 150 breed-loci combinations, nearly 23% deviated significantly (P b 0.05) from Hardy–Weinberg proportions, with six loci (BM6526, OarFCB304, HSC, SRCRSP8, BM1329, and OarFCB048) for which half of the breeds were not in equilibrium. The mean estimated FST for the 25 loci was 0.031 ± 0.016, and the range was between −0.007 (ETH225) and 0.076 (TGLA122). The mean within-breed deficit in heterozygosity (FIS), pooled across loci and breeds, was 0.071 ± 0.055. Nevertheless, there were differences among loci for this deficit, with most values ranging between 0.01 and 0.13, while lower values were observed for CSRM60 and ETH225, and higher values for SPS115 and SRCRSP8. Overall, exclusive alleles (i.e., where one allele at a given locus was found exclusively in one population) were detected in 18 of the 25 loci studied, with higher incidence in INRA006 (four breeds) and in CSRD247, HSC and OarFCB048 (three breeds). 3.2. Breed diversity and relationships The means for number of alleles per breed, number of loci with exclusive alleles, and number of loci not complying with Hardy–Weinberg proportions, observed and expected heterozygosities and FIS estimates computed across the 25 loci for each population, are shown in Table 3. The mean number of alleles per breed per locus had an average of 7.50 ± 0.41 for the breeds studied, ranging from a minimum of 7.0 in AL and BR to a maximum of 7.9 in SR. The effective number of alleles was very similar in the breeds

134 Table 2 Microsatellite markers, multiplex reactions, total number of alleles (TNA), mean number of alleles per breed (MNA), effective number of alleles (Na), polymorphic information content (PIC), probability of paternity exclusion with two parents known (PE), observed (Ho) and expected (He) heterozygozity, F-statistics (FIT, FST and FIS) per locus, proportion of breeds not in Hardy–Weinberg equilibrium (HWD) and breeds where exclusive alleles were detected (EA). Multiplex

TNA

MNA

Na

PIC

PE

Ho

He

FIT

FST

FIS

HWD

1

17 10 8 10 8 7 5 10 5 7 4 13 14 13 17 18 8 8 7 9 5 11 12 3 11 9.60 ± 4.09

7.00 7.67 5.00 6.33 6.33 5.67 3.67 7.83 3.50 5.83 2.83 10.00 7.50 9.33 13.50 12.67 5.67 6.67 6.83 7.00 3.67 8.83 9.67 2.67 8.00 6.95 ± 2.75

4.26 5.92 2.53 3.44 3.61 4.29 2.10 6.17 2.74 3.12 2.14 4.00 3.77 6.06 9.52 10.75 3.09 3.53 4.59 4.74 1.23 3.75 6.67 1.33 6.06 4.38 ± 2.29

0.729 0.810 0.529 0.671 0.686 0.726 0.452 0.815 0.570 0.628 0.437 0.716 0.695 0.812 0.884 0.896 0.616 0.684 0.750 0.758 0.181 0.710 0.831 0.233 0.813 0.665 ± 0.182

0.556 0.670 0.330 0.488 0.505 0.541 0.266 0.673 0.369 0.436 0.245 0.548 0.521 0.671 0.787 0.807 0.419 0.508 0.581 0.594 0.098 0.550 0.702 0.126 0.671 0.506 ± 0.187

0.691 0.758 0.513 0.655 0.697 0.656 0.486 0.814 0.575 0.644 0.417 0.740 0.670 0.741 0.844 0.832 0.585 0.585 0.772 0.698 0.191 0.630 0.770 0.207 0.728 0.636 ± 0.169

0.765 0.831 0.605 0.709 0.723 0.767 0.523 0.838 0.635 0.679 0.533 0.750 0.735 0.835 0.895 0.907 0.676 0.717 0.782 0.789 0.188 0.733 0.850 0.250 0.835 0.702 ± 0.176

0.101 0.094 0.161 0.090 0.042 0.150 0.077 0.031 0.102 0.055 0.218 0.015 0.099 0.116 0.060 0.089 0.138 0.189 0.019 0.120 −0.019 0.146 0.097 0.173 0.134 0.099 ± 0.057

0.025 0.041 0.047 0.076 0.030 0.035 0.021 0.021 0.036 0.024 0.013 0.009 0.047 0.033 0.023 0.047 0.018 0.026 0.027 0.030 −0.007 0.029 0.020 0.055 0.040 0.031 ± 0.016

0.078 0.055 0.120 0.015 0.012 0.119 0.057 0.010 0.068 0.032 0.208 0.006 0.055 0.086 0.038 0.044 0.122 0.167 −0.008 0.093 −0.012 0.120 0.079 0.125 0.098 0.071 ± 0.055

0.33 0.00 0.17 0.17 0.17 0.00 0.00 0.00 0.17 0.00 0.33 0.50 0.50 0.17 0.33 0.50 0.33 0.50 0.00 0.50 0.00 0.17 0.33 0.17 0.50 0.23 ± 0.19

2

3

4 5 6

7 8

EA SR, AL, PM PM (2) AL SR SR SP SP SR, AL SR, CH, SP, PM SP BR (2), SR, PM PM CH SR CH CH PM BR, CH, PM

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Marker BM6506 CSRD247 INRA063 TGLA122 BM8125 HAUT27 INRA005 BM1818 ETH10 ILSTS011 SPS115 BM6526 OarFCB304 INRA006 MM12 HSC McM527 SRCRSP8 CSRM60 BM1329 ETH225 INRA023 MAF65 MAF209 OarFCB048 Mean

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Table 3 Mean number of alleles (MNA), effective number of alleles (Na), number of loci with exclusive alleles (LEA), proportion of loci not in Hardy–Weinberg equilibrium (LHWD), mean unbiased expected (He) and observed (Ho) heterozygosity and FIS estimates computed per breed for 25 loci.

a

Breed

MNA

Na

LEA

LHWD

He

Ho

Fais

AL BR CH PM SP SR Mean

7.0 7.0 7.5 7.8 7.8 7.9 7.50 ± 0.41

3.22 2.83 3.39 3.20 3.24 3.22 3.18 ± 0.19

3 2 5 7 4 7 4.7 ± 2.1

0.16 0.24 0.24 0.28 0.20 0.28 0.23 ± 0.05

0.69 ± 0.16 0.65 ± 0.20 0.71 ± 0.15 0.69 ± 0.19 0.69 ± 0.19 0.69 ± 0.17 0.69 ± 0.02

0.67 ± 0.17 0.63 ± 0.20 0.66 ± 0.18 0.60 ± 0.19 0.64 ± 0.20 0.63 ± 0.18 0.64 ± 0.03

0.031 0.029 0.062** 0.124*** 0.080*** 0.094*** 0.07 ± 0.04

*(P b 0.05), **(P b 0.01), and ***(P b 0.001).

studied, with means ranging from 3.20 to 3.39, except for the BR breed, which had a mean of 2.83. The ratio between effective and mean number of alleles for each breed ranged from 0.40 to 0.46, indicating that the distribution of allele frequencies was similar in the breeds studied. The number of loci with exclusive alleles was highest in PM and SR (7) and lowest in BR (2), while the proportion of loci not in Hardy–Weinberg equilibrium was highest in PM and SR, and lowest in AL. The expected heterozygosity had a mean across breeds of 0.69 ± 0.02, with the lowest mean in BR (0.65), and similar levels observed in all the other breeds (between 0.69 and 0.71). The observed heterozygosity per breed ranged between 0.60 (PM) and 0.67 (AL), with a global mean of 0.64 ± 0.16. A deficit in heterozygosity (FIS) was observed in all the breeds studied, very pronounced in the PM population (0.124), less in CH, SP and SR (between 0.062 and 0.094), and not significant (P N 0.05) in AL and BR. Overall, these results indicate that, even though He and Ho were not widely different for the breeds studied, the deficit found in within-breed heterozygosity was different among the breeds analyzed. For the analysis of breed relationships, three loci which were considered less informative (ETH225 and MAF209 because of the low effective number of alleles and SPS115 because of the high FIS estimate) were excluded, and the subsequent analyses were carried out with the remaining 22 microsatellite markers. The matrix of FST estimates among breeds and Nei's standard genetic distances (Table 4) indicates that the closest breeds are SR and PM, and CH and SP, with the largest difference observed for the pair AL and BR. The mean distance with the remaining breeds was highest for AL and lowest for SP. The dendrogram representing distances among breeds (Fig. 1) enables the visualization of genetic relationships between populations, with the values in the nodes of the tree indicating the proportion of bootstrap replicates in a

bootstrap re-sampling of 1000 trees. The bootstrap values were moderate, suggesting that the robustness of the tree is not high. Nevertheless, the tree indicates the existence of two clusters clearly defined, one including SR and PM, and the other AL and SP. A third cluster with lower reliability, as assessed by the bootstrap values, was of CH with BR. The results of the correspondence analysis are graphically presented for the first three factors (Fig. 2), which accounted for 34.1, 26.6 and 15.1% of the total inertia, respectively. In this analysis, axis 1 results in the clustering of CH, SP, PM and SR in the center, and clearly separates AL to one side, and BR to the other. Axis 2 then separates CH and SP from PM and SR, while axis 3 provides a separation of SP from CH. 3.3. Population structure The proportion of shared alleles between animals was used to build a neighbour-joining dendrogram of individuals, and the results are presented in Supplementary Fig. S2. The dendrogram shows that only AL animals tended to cluster together, and BR grouped in two separate clusters. The remaining breeds did not separate clearly, and in some cases animals from two breeds with a close geographic location tended to cluster together (e.g., SR and PM). The number of ancestral populations underlying the observed genetic diversity was assessed with the Bayesian approach implemented by STRUCTURE. The likelihood of the observed data given the number of inferred ancestral populations [Ln Pr(X|K)] is shown in Fig. 3 for numbers of inferred populations ranging from K = 2 to K = 6, with five replications at each value of K. The mean value of Ln Pr(X|K)

Table 4 Matrix of FST (below diagonal) and Nei's standard genetic distances (above diagonal) among breeds.

AL BR CH PM SP SR Mean

AL

BR

CH

PM

SP

SR

Mean

– 0.061 0.033 0.041 0.028 0.042 0.041

0.170 – 0.032 0.045 0.031 0.036 0.041

0.123 0.100 – 0.018 0.013 0.022 0.024

0.136 0.126 0.083 – 0.022 0.012 0.028

0.105 0.096 0.072 0.088 – 0.017 0.022

0.144 0.109 0.096 0.067 0.080 – 0.026

0.136 0.120 0.095 0.100 0.088 0.099 –

Fig. 1. Neighbour-joining tree depicting phylogenetic relationships among Portuguese native breeds of goats based on Nei's standard genetic distances. Numbers indicate bootstrap values (%).

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and 0.679, respectively. For the PM, CH, SP and SR breeds, four underlying populations had mixed contributions. Nevertheless, a geographical cline of contributions from the four ancestral populations was observed, such that a given population had a stronger contribution to breeds located nearby, and a decline as breeds were located further apart. Overall, with the exception of AL and BR, no clear distinction could be established among the breeds analyzed based on the contribution of ancestral populations. 4. Discussion

Fig. 2. Spatial representation of breed relationships based on factorial correspondence analysis. Numbers in parentheses represent the percentage of total inertia accounted for by each axis.

increased up to K = 6 and dropped afterwards, with a large increase in its variance. It was therefore assumed that K = 6 is the most likely number of ancestral populations that contribute to the observed genetic variability in the six breeds studied. The contributions of the assumed ancestral populations to the six breeds under study are graphically presented in Fig. 4, for values of K ranging between 2 and 6. When K = 2, BR separates from the other breeds, while for K = 3 it is AL that also appears isolated. From then on, as K increases, no clear separation of the remaining breeds was obtained, as individuals seem to have mixed contributions from the inferred ancestral populations, and breeds are not clearly identified with one specific underlying population. Assuming K = 6, the proportional contribution of the assumed ancestral populations to each one of the current breeds was computed, and the corresponding results are summarized in Fig. 5, with breeds ordered geographically. Only the AL and BR breeds seem to be identified each with one major ancestral population, with contributions of 0.763

Fig. 3. Plot of estimated posterior probabilities of the data [Ln Pr(X|K)] for different number of inferred clusters (K=2 to 7), with representation of probabilities obtained for individual runs (○) and for the mean of five runs (♦) at each K.

This study presents the first results on characterization of genetic variability detected through microsatellite markers in the six native goat breeds recognized in Portugal. All the 25 microsatellite loci studied were polymorphic, but their usefulness for genetic diversity studies was different. For example, the ETH225 and MAF209 markers had a very low effective number of alleles, while the SPS115 locus had a high FIS estimate, which could indicate the presence of null alleles (Sancristobal et al., 2006). With the exception of the abovementioned loci and of INRA005, all the other markers had a polymorphic information content above 0.5, which makes them useful in genetic diversity studies with goats. The level of genetic diversity found in Portuguese goat breeds is high, with a mean expected heterozygosity across loci of 0.70. This is in the interval reported for different goat breeds, which has ranged from 0.6 for Swiss breeds (Saitbekova et al., 1999) to 0.82 for Chinese breeds (Qi et al., 2009), and is close to the mean He of 0.69 reported by Cañon et al. (2006) for a large group of goat breeds from Europe and the Middle-East. The mean number of about 7.5 alleles/locus/breed found in our work is within the range of values reported in other studies, which have spread from 5.9 in goat breeds from the Canary islands (Martínez et al., 2006) to 10.2 in the study of Qi et al. (2009). When compared with the high genetic diversity found in Portuguese goat breeds, the relatively low number of alleles per locus could be a result of sample size or perhaps a consequence of past bottlenecks, which are known to affect more allelic richness than the level of genetic variability (Luikart and Cornuet, 1998, Kantanen et al., 2000). The six native breeds included in this study had similar levels of genetic variability, with means for He ranging from 0.65 to 0.71, for number of alleles/locus from 7.0 to 7.9, and for effective number of alleles/locus from about 2.8 to 3.4. Taken together, these results indicate that there are no appreciable differences in the level of genetic diversity found in Portuguese goat breeds. The estimated FST, which corresponds to the proportion of genetic variability accounted for by differences among breeds, was 0.031, indicating that genetic diversity quantified by microsatellite markers shows very little differentiation among Portuguese breeds of goats. This is lower than what has been observed in the majority of studies with goats, where FST has usually ranged between 0.04 (Sechi et al., 2005) and 0.11 (Glowatzki-Mullis et al., 2008), but this comparison would depend on the diversity of the breeds included in different studies. For example, in the work of Cañon et al. (2006), the estimated FST was 0.069, which is still a rather small level of breed differentiation, even though 45 breeds from different countries of

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Fig. 4. Graphical representation of the estimated membership fractions of individuals of the breeds analyzed in each of the K inferred clusters, for K = 2 to 6.

the Mediterranean region were included. In studies with other livestock species in Portugal, the mean FST was around 0.08 in cattle (Ginja et al., 2010), 0.18 in pigs (Vicente et al., 2008) and 0.03 in native sheep breeds (Santos-Silva et al., 2008). Taken together, these results indicate a much lower level of breed differentiation in sheep and goats, probably as a result of a common origin or past admixture among the populations which have originated the breeds currently recognized. This could be a result of the higher mobility of sheep and goats across different regions, which in the past would have provided the opportunity for some gene flow among populations, and result in their reduced differentiation (Luikart et al., 2001; Naderi et al., 2007). This pattern would be less likely in cattle, and even less in pigs, because transhumance was not a common practice in these species, and geographic isolation is more pronounced than in small ruminants. In the analysis of within-breed genetic variability, and depending on the breed considered, between 0.16 and 0.28 of the loci presented significant departures from Hardy–Weinberg proportions, mostly because of a deficit in heterozygosity, with a significant positive FIS in most breeds, particularly in PM. Several factors can contribute to a lower than expected heterozygosity in a population, especially inbreeding and population subdivision (Wahlund effect), but the presence of null alleles and lack of neutrality relative to selection, with selection in favour of homozygotes (Maudet et al., 2002), may also cause a reduction in heterozygosity. In our work,

Fig. 5. Proportional contribution of the inferred clusters (K = 6) to each breed, with breeds geographically ordered from North to South.

probably inbreeding was the major cause of reduced heterozygosity in all the breeds, even though the sampling process, with many herds represented per breed, could also result in a hidden substructure which would be reflected in a positive FIS. Nevertheless, the high deficit observed in PM (FIS = 0.124), together with its extremely reduced population size, would suggest that inbreeding is the major problem found in this breed. On the other hand, population subdivision may be the cause of reduced heterozygosity in SR and CH, as these two breeds have isolated subpopulations spread in different geographical regions. The low level of differentiation among breeds was confirmed by the poor clustering in the neighbour-joining tree of individuals based on allele sharing distances, where only the AL and BR animals grouped together. When relationships between breeds were analyzed by Nei's standard genetic distance, the AL and BR breeds distanced themselves from the center of the radial tree, and breeds with a closer geographical distribution generally tended to cluster together, suggesting that they may share a common ancestry. The principal components analysis confirmed the separation of AL and BR from the remaining breeds, with some clustering of PM with SR, and of SP with CH, again in agreement with their geographical distribution. The analysis with STRUCTURE also confirmed the separation of AL and BR, as these were more closely identified with independent clusters of potential ancestral populations. For the other breeds, however, there was clear evidence of admixture, with various ancestral populations contributing differently to the current breeds. Moreover, evidence was found of a geographical cline, with a given ancestral population contributing more to breeds located nearby, and with a declining contribution as the geographical distribution of breeds became more distant. This result confirms the low genetic differentiation between Portuguese native breeds of goats, already indicated by the low FST, and suggests that,

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based on the neutral genetic markers used, only the AL and BR breeds are really distinct, while the remaining breeds are the result of mixed contributions from different ancestral populations, with a gradual geographic transition as breeds are located further apart. The weak differentiation among goat and sheep breeds has been shown in other studies with microsatellite markers (Cañon et al., 2006, Peter et al., 2007), and confirmed by analyses of mitochondrial DNA variation (Luikart et al., 2001; Naderi et al., 2007). These results have been interpreted as being a consequence of the high mobility of these species, which have accompanied human migrations and commercial routes (MacHugh and Bradley, 2001; Naderi et al., 2007). On a local scale, our results lend support to this idea, as there is a clear gradual transition among breeds according to their geographical proximity, the only exception being the AL and BR breeds, which are genetically very distinct from the others. The BR breed is thought to have had some influence from French Alpine goats in the mid-20th century, which could justify its distinctiveness. On the other hand, the AL is located in the Algarve, which is the southern-most region of Portugal, and has had a strong influence from northern Africa for several centuries. The introduction of domestic animals into the Iberian Peninsula through this route has been suggested for cattle (Beja-Pereira et al., 2006), and could also have existed for other species. If that's the case, perhaps the AL could be the result of goats introduced from northern Africa into Portugal during the period of Moorish domination, which lasted until the 13th century. Otherwise, the AL breed could also result from the introduction of animals from other areas along the Mediterranean, as suggested by Cañon et al. (2006) for Spanish goats, because commercial exchanges in this area were very active in medieval times, and livestock trade was a common practice (Pereira et al., 2005). Further studies involving breeds from other regions, including Northern Africa and the Middle-East, and using monoparental and non-neutral genetic markers, in addition to microsatellites, could help in better clarifying the origins and gene flow which underlie the genetic structure currently observed in Portuguese goat breeds. The results presented here can be useful in outlining conservation strategies, even though it remains a subject of discussion what are the optimum weights to be given to the between- and within-breed components of genetic diversity in defining conservation priorities (Ollivier et al., 2005, Toro et al., 2006). In any case, it is very clear from our results that the PM breed, which has a very small breeding population, presents high levels of inbreeding, and the resulting inbreeding depression could put at risk its survival for the future. It is, therefore, one case which requires that urgent steps be taken to insure its maintenance and appropriate genetic management, for which genetic markers can be extremely useful. In addition to the contribution of a given breed to overall genetic diversity, other factors should be taken into account when defining conservation priorities, including aspects such as the economic, demographic, social, ecological and cultural roles associated with a given breed (Ruane, 2000). In the case of native goat breeds, their specific production and adaptation features, which result in many highly-valued local products, as well as the role that goats play in maintaining marginal and forest areas which would otherwise be left abandoned, must also be

considered when the importance of maintaining those breeds is appraised. 5. Conclusions Overall, our work with Portuguese native goat breeds using neutral genetic markers indicates that genetic diversity is high, but genetic differentiation among breeds is not strong. The Bayesian approach implemented by the STRUCTURE software was effective in detecting gene flow among populations, and suggests the existence of a geographical cline in genetic contributions of ancestral populations to the native goat breeds currently recognized. Of the breeds studied, the highly endangered Preta de Montesinho is the one showing stronger signs of genetic erosion, clearly indicating that urgent measures of conservation and sustainable management of its gene pool must be undertaken. Acknowledgements The authors wish to express thanks to the Breeders Associations for providing biological samples used in this study, and to Direcção Geral de Veterinária, the Estação Zootécnica Nacional and the Universidad de Cordoba for financial support. Esperança Maurício, Elisa Morais and Isabelina P. Costa are thanked for the technical support. C. Bruno-de-Sousa was supported by a grant from the Portuguese Foundation for Science and Technology. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.livsci.2010.06.159. References Araújo, A.M., Guimarães, S.E.F., Machado, T.M.M., Lopes, P.S., Pereira, C.S., Silva, F.L.R., Rodrigues, M.T., Columbiano, V.S., Fonseca, C.G., 2006. Genetic diversity between herds of Alpine and Saanen dairy goats and naturalized Brazilian Moxotó breed. Genet. Mol. Biol. 29, 67–74. Barker, J.S.F., Tan, S.G., Moore, S.S., Mukherjee, T.K., Matheson, J.L., Selvaraj, O.S., 2001. Genetic variation within and relationships among populations of Asian goats (Capra hircus). J. Anim. Breed. Genet. 118, 213–233. Baumung, R., Simianer, H., Hoffmann, I., 2004. Genetic diversity studies in farm animals—a survey. J. Anim. Breed. Genet. 121, 361–373. Behl, R., Sheoran, N., Behl, J., Vijh, R.K., Tantia, M.S., 2003. Analysis of 22 heterologous microsatellite markers for genetic variability in Indian goats. Anim. Biotechnol. 14, 167–175. Beja-Pereira, A., Caramelli, D., Lalueza-Fox, C., Vernesi, C., Ferrand, N., Casolih, A., Goyache, F., Royo, L.J., Conti, S., Lari, M., Martini, A., Ouragh, L., Magid, A., Atash, A., Zsolnai, A., Boscaton, P., Triantaphylidis, C., Ploumi, K., Sineo, L., Mallegni, F., Taberlet, P., Erhardt, G., Sampietro, L., Bertranpetit, J., Barbujani, G., Luikart, G., Bertorelle, G., 2006. The origin of European cattle: Evidence from modern and ancient DNA. Proc. Natl Acad. Sci. USA 103, 8113–8118. Belkhir, K., Borsa, P., Goudet, J., Chikhi, L., Bonhomme, F., 1998. GENETIX, logiciel sous Windows TM pour la génétique des populations. Laboratoire Génome et Populations. CNRS UPR 9060. Université de Montpellier, Montpellier. France. Caballero, A., Toro, M.A., 2002. Analysis of genetic diversity for the management of conserved subdivided populations. Conserv. Genet. 3, 289–299. Cañon, J., García, D., García-Atance, M.A., Obexer-Ruff, G., Lenstra, J.A., Ajmone-Marsan, P., Dunner, S., ECONOGENE Consortium, 2006. Geographical partitioning of goat diversity in Europe and the Middle East. Anim. Genet. 37, 327–334. Direcção Geral da Pecuária, 1987. Animal genetic resources. Indigenous Breeds of Sheep and Goats. Lisboa, Portugal. 207 pp.

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