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Keywords:

  • Cattle;
  • genetic distance;
  • genetic variation;
  • relationship

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

Conservation and improvement strategies in farm animals should be based on a combination of genetic and phenotypic characteristics. Genotype data from 30 microsatellites were used to assess the genetic diversity and relationships among five Cuban cattle breeds (Siboney de Cuba, Criollo Cubano, Cebú Cubano, Mambí de Cuba and Taíno de Cuba). All microsatellite markers were highly polymorphic in all the breeds. The expected heterozygosity ranged from 0.67 ± 0.02 in the Taíno de Cuba breed to 0.75 ± 0.02 in the Mambí de Cuba breed, and the observed heterozygosity ranged from 0.66 ± 0.03 in the Cebú Cubano breed to 0.73 ± 0.02 in the Siboney de Cuba breed. The genetic differentiation between the breeds was significant (p < 0.01) based on the infinitesimal model (FST). The exact test for Hardy-Weinberg equilibrium within breeds showed a significant deviation in each breed (p < 0.0003) for one or more loci. The genetic distance and structure analysis showed that a significant amount of genetic variation is maintained in the local cattle population and that all breeds studied could be considered genetically distinct. The Siboney de Cuba and Mambí de Cuba breeds seem to be the most genetically related among the studied five breeds.


Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

Animal breeds have been selected to fit a wide range of environmental conditions and human needs. In the last 200 years, herd book union restraints have led to the genetic isolation of many cattle breeds (Maudet et al. 2002). The selection of a few highly productive breeds has caused the decline of numerous other populations. However, genetic diversity found in domestic breeds allows farmers to develop new characteristics in response to changes in environment, diseases, or market conditions.

Just as it happened in most European countries and in the US, the rapid growth of the commercially prominent breeds has occurred at the expense of a group of locally adapted, genetically heterogeneous breeds. This group of Creole breeds, also referred to as native, local or naturalized breeds, includes those derived from the first cattle populations introduced by the European conquerors around 1500 (Egito et al. 2007). The native or naturalized breeds often possess gene combinations and special adaptations, such as disease resistance or the acclimatization to harsh conditions or poor-quality feeds that are not found in other breeds (Maudet et al. 2002).

In the early 1960s the Cuban bovine population was mainly composed by Zebu animals (96%), an undetermined number of Mestizos and small groups of dairy and beef breeds. Essentially, there was not an intensive work performed on livestock and the genetic composition was largely unknown. Traditional livestock improvement was predominant. With these variable conditions, the country plotted to make a radical transformation of bovine population with the aim of improving the potential to increase dairy and indirectly meat production through own production herds.

In 1964, the national breeding plan (NBP) was established. In this plan, artificial insemination (AI) played an important role in crossbreeding native Zebu cattle and Holstein sires (Buxadera & Dempfle 1997). The Holstein animals used for those breeds were imported to Cuba from Canada in 1963. The general strategy and some results of NBP are offered in Anonymous (1978) and Prada (1984).

The genetic characterization of these animals may help in developing a rational approach to their conservation (European Cattle Genetic Diversity Consortium 2006). Molecular markers such as microsatellites are now commonly used to estimate genetic diversity and calculate genetic distances as well as to detect admixture, genetic bottlenecks and inbreeding (Maudet et al. 2002; Egito et al. 2007; Martín-Burriel et al. 2007). The genetic diversity of domestic cattle is typically divided into two components: differences occurring between specimens from different breeds and those differences occurring between individuals within a single breed.

The aims of the present study were to assess the extent of the genetic diversity both within and between breeds and to establish the relationships among the five most important Cuban cattle populations, Siboney de Cuba (SC), Criollo de Cuba (CC), Cebú Cubano (CZ), Mambí de Cuba (MC) and Taíno de Cuba (TC), using a set of 30 bovine-specific microsatellite markers. Two of the five Cuban cattle breeds are autochthonous (CC, Cebú Cubano), and the other three are crossbreeds (Siboney de Cuba, Mambí de Cuba and Taíno de Cuba). These new breeds were created using the following proportions of constituent breeds: Siboney de Cuba (5/8 Holstein × 3/8 Cebú Cubano), Mambí de Cuba (3/4 Holstein × ¼ Cebú Cubano) and Taíno de Cuba (5/8 Holstein × 3/8 CC).

Materials and methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

Sampling and microsatellite loci

Blood samples from 317 selected adult females not closely related to one another were collected. The blood collected represented five Cuban cattle breeds (SC = 84, CC = 59, CZ = 60, MC = 58 and TC = 56). A total of 30 microsatellite markers (BM1824, TGLA227, TGLA122, SPS115, ETH225, BM2113, ETH10, ETH3, BM1818, TGLA126, ETH152, ILSTS006, INRA023, CSRM60, INRA005, INRA063, HAUT24, HEL5, INRA35, HEL9, ILSTS005, ETH185, INRA037, CSSM66, MM12, INRA032, HEL1, HAUT27, HEL13 and TGLA53) were analysed to estimate various parameters of genetic diversity. These loci were recommended by the International Society of Animal Genetics (ISAG)/FAO for the analysis of genetic diversity in cattle breeds (FAO/ISAG 2004).

DNA extraction and PCR-based profiling

Genomic DNA was isolated from lymphocyte cells using the procedure described by Miller et al. (1988). The QIAGEN multiplex PCR kit was used for the polymerase chain reactions (PCR) according to the manufacturer’s recommendations. The sizes of the microsatellite alleles were visualized using the abi prism 3130 Genetic Analyzer (Applied Biosystems, Foster City, CA, USA), and the internal size standard GeneScan-500LYS (Applied Biosystems, Warrington, UK) was used for sizing the alleles. Control samples from the EU RESGEN CT 98–118 cattle genetic diversity project were used to ensure compatibility of allele sizes.

Computation and statistical analysis

The genepop package Version 4.0.10 (Raymond & Rousset 1995; Rousset 2008) was used to calculate the allele frequencies and the observed (Ho) and expected (He) heterozygosities and to perform an exact test for the deviation from Hardy-Weinberg equilibrium (HWE) with standard Bonferroni corrections. The information content for the polymorphisms (PIC) was calculated as described by Botstein et al. (1980).

Wright F-statistics (FIT, FST, FIS), mean number of alleles per locus and breed differentiation detected by locus under the step-wise mutation model (RST) were calculated for each locus and across the genome using fstat (Goudet 2002). arlequin software was used to generate Nei’s genetic distance (DA) (Excoffier et al. 2005). The presence of null alleles was estimated in Micro-checker (Van Oosterhout et al. 2004) and the null allele frequency (r) was calculated using the methods described by Chakraborty et al. (1992) and Brookfield (1996).

Neighbor-joining trees were constructed with the PHYLIP (Felsenstein 2004) program neighbor using Reynolds’s genetic distances. Bootstrap values obtained from 1000 datasets were calculated using the PHYLIP programs seqboot, gendist and consense. A network based on Reynolds genetic distances to graphically represent breed relationships and admixtures was calculated using the splitstree 4.0 program (Huson & Bryant 2006) with the populations serving as the operational taxonomic units.

The pairwise genetic distances between all individual animals were estimated by the logarithm of the proportions of shared alleles (Dps) (Bowcock et al. 1994) using microsat (Minch et al. 1998).

Using the multilocus genotypes as a basis, the population structure was analysed by a Bayesian admixture procedure implemented in structure 2.1(http://pritch.bsd.uchicago.edu/structure.html) (Pritchard et al. 2000). The software was run using the ‘admixture model’ and ten repetitions of 1 000 000 iterations following a burn-in period of 100 000 iterations. The most probable number of populations was determined following the recommendation of Evanno et al. (2005). Different values of the number (K) of a priori defined clusters were compared (K = 2–5) and used to calculate the ΔK statistic, which is based on the rate of change in the ‘Log probability of data’ between successive K values.

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

Microsatellite markers

A total of 299 alleles were detected across 30 microsatellite loci in the studied five Cuban cattle breeds. The number of alleles per locus ranged from 5 (ILSTS005) to 17 (TGLA122), with a mean of 9.96 (Table 1). All microsatellite markers showed high PIC values in all breeds, with a mean of 0.771.

Table 1. Descriptive statistics of the 30 microsatellite marker loci. The following statistics are reported for all the studied Cuban breeds: number of alleles (N), observed heterozygosity (Ho), expected heterozygosity (He), polymorphism information content (PIC), Wright F-statistics (Fls, FIT, FST) and breed differentiation as detected by marker locus under the step-wise mutation model (RST)
LOCUS NH0HePICFisFitFstRST
  1. Statistical significance: *p < 0.05; **p < 0.01; ***p < 0.001.

BM182460.7560.7630.7200.0250.078*0.054***0.018
TGLA227140.8690.8120.830−0.0350.126***0.156***0.258
TGLA122170.7020.7930.819−0.0020.068*0.070***0.039
SPS11580.6170.5680.6880.0130.135***0.124***0.038
ETH225100.8690.8300.7780.0140.153***0141***0.119
BM2113100.7740.8430.8470.0050.060*0.055***0.075
ETH1080.7740.7770.7840.0020.115***0.113***0.279
ETH390.7980.7860.7650.0180.094**0.077***0.195
BM181890.6340.6300.697−0.0660.0210.081***0.033
TGLA12680.7140.7410.717−0.0340.0520.083***0.187
ETH152110.8930.8350.819−0.0020.141***0.142***0.202
ILSTS00690.7160.7290.7140.104**0.165***0.069***0.139
INRA023120.8170.7880.832−0.0240.0280.051***0.064
CSRM60110.8190.7340.769−0.0610.0340.089***0.057
INRA00560.6950.7300.721−0.0250.0040.028***0.002
INRA06360.6270.5840.661−0.0190.0550.073***0.090
HAUT24100.7830.7920.8390.166***0.227***0.073***0.152
HEL590.4740.6770.7990.286***0.364***0.109***0.089
INRA35100.4700.6610.6570.337***0.370***0.050***0.026
HEL9120.8800.8640.888−0.0280.061*0.087***0.034
ILSTS00550.4870.6680.6090.03990.123**0.087***0.113
ETH185140.5270.7840.8040.292***0.374***0.115***0.038
INRA037100.7260.7200.7720.0370.087**0.052***0.052
CSSM66110.8930.8810.877−0.0180.059*0.076***0.030
MM12160.9170.7900.832−0.0250.0400.064***0.116
INRA03290.6750.7620.8440.0480.166***0.124***0.164
HEL180.7020.7040.799−0.0200.072*0.090***0.097
HAUT2790.6670.7130.6410.108**0.158***0.056***0.016
HEL1370.7780.7610.7640.0200.148***0.131***0.161
TGLA53150.7800.7990.843−0.0080.051*0.058***0.240
Mean9.9670.7280.7510.7710.0380.1210.0860.104

The expected heterozygosity across the breeds varied from 0.568 (SPS115) to 0.881 (CSSM66), while the observed heterozygosity across the breeds ranged from 0.470 (INRA35) to 0.917 (MM12) (Table 1).

The overall loci estimates of inbreeding showed that Cuban breeds had six loci with significantly reduced heterozygosity (ILSTS006, HAUT24, HEL5, INRA35, ETH185 and HAUT27) due to within population inbreeding (FIS). The contribution of the microsatellite markers to breed differentiation was estimated by FST statistics. All loci had a significant FST (Table 1), with TGLA227 showing the highest FST value of 0.156. The significance and values of the overall estimates of FST among all five breeds would indicate which of the 30 microsatellites could be used as powerful tools for breed differentiation (Arranz et al. 2001; Egito et al. 2007).

The breed differentiation was estimated under the infinitesimal (FST) and step-wise mutation (RST) models. The estimated mean values of differentiation due to genetic drift determined by the RST model (0.104) were higher than the absolute values determined by the FST model (0.086), indicating that 8.6% of the total genetic variation corresponded to differences among the populations.

Genetic diversity within breeds

The number of alleles per locus is around 7.526. The values obtained for the TC and CC breeds were less than the mean, and the SC breed was the most diverse population (Table 2).

Table 2. Summary of the statistics for the population genetic parameters for the five breeds studied.-The following estimates were obtained by averaging across the 30 microsatellites: number of individuals (N); mean number of alleles/locus (MNA); observed heterozygosity (Ho); expected heterozygosity (He); Wright F-statistics (Fls); and number of Hardy-Weinberg equilibrium (HWE) deviated loci using Bonferroni corrections p < 0.0003 (#HWE). Standard errors are in parentheses
BreedNMNAHo (SD)He (SD)Fis#HWE
  1. CC: Criollo de Cuba, CZ: Cebú Cubano, MC: Mambí de Cuba, SC: Siboney de Cuba, TC: Taíno de Cuba.

SC848.23 (0.36)0.73 (0.02)0.75 (0.01)−0.0011
CC597.17 (0.32)0.71 (0.03)0.74 (0.02)0.0113
CZ607.87 (0.39)0.66 (0.03)0.72 (0.02)0.0103
MC588.03 (0.40)0.72 (0.02)0.75 (0.02)0.0102
TC566.33 (0.42)0.67 (0.03)0.67 (0.02)−0.0121
Mean63.47.5260.6980.7260.0042

The He ranged from 0.67 ± 0.02 in the TC breed to 0.75 ± 0.02 in the MC breed, and the Ho ranged from 0.66 ± 0.03 in the CZ breed to 0.73 ± 0.02 in the SC breed. The highest genetic diversity was found in the SC breed (Ho = 0.73 ± 0.02 and He = 0.75 ± 0.01), which also had the highest mean number of alleles/locus (MNA) (8.23). Rare alleles, defined as those with frequencies below 5%, were observed in all breeds.

The exact test for HWE within breed showed a significant deviation in all the breeds at one or more loci (p < 0.0003, adjusted by the Bonferroni correction). There was significant heterozygote deficit in all breeds as follows: SC and TC breeds displayed one locus (INRA35), CC had three (HAUT24, HEL5 and INRA35), CZ also had three (ILSTS006, HEL5 and ETH185) and MC showed two (HEL5 and INRA35). Locus INRA35 shows evidence for a null allele, which r = 0.4 and r = 0.2 by methods Chakraborty et al. (1992) and Brookfield (1996), respectively.

Genetic variation and the relationship between breeds

Estimates of pairwise genetic differentiation based on the infinitesimal model (FST) were all significant (p < 0.01), indicating that the breeds can be considered genetically independent. Allele frequencies were used to generate DA (Nei et al. 1983), which ranged from 0.062 to 0.298 (Table 3).

Table 3. Pairwise estimates of genetic differentiation and genetic distance among all the five Cuban cattle breeds. The FST estimates are above the diagonal, and the Nei genetic distance (DA) is below the diagonal. All estimates of FST were found to be significant (p < 0.01)
 SCCCCZMCTC
  1. CC: Criollo de Cuba, CZ: Cebú Cubano, MC: Mambí de Cuba, SC: Siboney de Cuba, TC: Taíno de Cuba.

SC 0.0640.0930.0230.065
CC0.147 0.1070.0750.072
CZ0.1540.208 0.1100.175
MC0.0620.1670.177 0.077
TC0.1290.1500.2980.147 

The lowest DA was observed between the SC and MC breeds (0.062). The CZ breed was the most distant breed, displaying the highest DA (0.298) when compared with TC breed.

A Neighbor-Net graph analysis based on Reynolds genetic distances corroborates the result obtained with DA, with the SC and MC breeds being clustered together and the CZ breed being the most distant breed (Figure 1).

image

Figure 1.  Neighbor-Net graph of the genetic relationship between the five Cuban breeds based on Reynolds’s genetic distances estimated from 30 microsatellites. Bootstrap percentages higher than 50% are shown.

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An individual-animal-based neighbour-joining dendrogram built from the estimated distances between shared alleles among the 317 individuals showed that most of the animals within each breed were closely assembled in discrete branches. The SC and MC animals, which appeared admixed, were the exception, and this result can be explained by the similar origin of those breeds (Figure 2).

image

Figure 2.  Neighbor-joining tree based on the pairwise genetic distances between all animals estimated from the logarithm of the proportions of shared alleles. Each tip represents a single animal, and the breeds are distinguished by different colours as shown on the legend.

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A structure analysis using a Bayesian approach was performed with increasing numbers of inferred populations. These results showed the highest ΔK at K = 4. The CZ breed was separated from the other populations after the first calculation clusters (K = 2). The SC and MC breeds as well as the CC and TC breeds clustered together at K = 3. The SC and MC breeds clustered together at K = 4. These results confirmed a common origin for each of the two pairs (Figure 3).

image

Figure 3.  Estimated population structure obtained by STRUCTURE analyses. Each individual is represented by a thin vertical line, which is partitioned into coloured segments that represent the proportional contribution of the inferred K clusters. The populations are separated by thin vertical black lines.

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Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

A growing number of investigations aimed at studying the genetic characterization of autochthonous breeds indicate the scientific community’s interest in this topic (Armstrong et al. 2006; Barrera et al. 2006; Liron et al. 2006). Genetic characterizations are free of environmental influences, and this information is a fundamental aspect of the decisions that must be made in conservation programmes or regarding the utilization of animal genetic resources (Groeneveld et al. 2010).

Rare alleles were observed in all the breeds in almost all the analysed loci, similar to the results found by Egito et al. (2007) and Martín-Burriel et al. (2011). Similarly, the loci ILSTS005 and TGLA122 were reported to be the markers with the minimum and maximum number of alleles, respectively, in a study involving six French native breeds (Maudet et al. 2002).

Genetic markers with a heterozygote deficit are relatively common in domestic breeds. Herein, the heterozygosities for a half of all loci analysed were lower than expected (BM1824, TGLA122 BM2113, ETH10, TGLA126, ILSTS006, INRA005, HAUT24, HEL5, INRA35, ILSTS005, ETH185, INRA032, HEL1, HAUT27 and TGLA53), which could be attributed to a low level of inbreeding (Arora & Bhatia 2004) or by population subdivision (Wahlund’s effects) (Maudet et al. 2002). Other studies have reported that the expected heterozygosities for all the studied loci were nominally higher than the observed heterozygosities. For example, Egito et al. (2007) identified only one exception, at the locus ETH3 in a group of zebuine breeds. The overall deficit of heterozygotes (FIT) observed in our study was relatively low, particularly when compared with the values observed in other studies involving local breeds of both taurine and zebuine origin (Egito et al. 2007). Microsatellite markers with the highest heterozygosity and PIC values (e.g. HEL9, CSSM66 and MM12) should be included in future genetic diversity studies in these or other breeds (Armstrong et al. 2006).

The higher estimate of differentiation by the RST when compared with the FST suggests that differences among breeds involve not only allele frequencies but also differences in allele size caused by the tendency of microsatellites to mutate (Liron et al. 2006; Egito et al. 2007).

In domestic species, heterozygote deficiencies can be explained by several factors, including the presence of unamplified or null alleles, selection against heterozygotes, population subdivision (Wahlund’s effects) and inbreeding (Maudet et al. 2002). In Cuba, the current management of four of the studied breeds (SC, CC, MC and TC) uses AI. The slightly low Ho compared to He in the three Cuban breeds could be explained by the human selection. Within loci with significant deviation HWE, the locus INRA35 show evidence for a null allele, this result is similar to the one obtained by Ginja et al. (2010) and Martín-Burriel et al. (2011).

The observed levels of within-breed diversity in Cuban cattle breeds were higher (Table 2) than other levels previously reported in European countries such as Portugal (Ginja et al. 2010) and Spain (Martín-Burriel et al. 2007). Our results are similar to the values previously reported for Brazilian cattle (Egito et al. 2007), suggesting that the diversity of Creole- and zebuine-derived cattle in Central and South America was higher than the European and Eurasian breeds (Kantanen et al. 2000; Liron et al. 2006).

The divergence between the studied Cuban breeds was evaluated using the mean of different values measuring genetic distance. Nei’s genetic distance has been defined in terms of gene identity, such that neither non-random mating nor natural selection affects it. In addition, this metric is intended to estimate the number of net codon differences per locus between populations (Nei & Roychoudhury 1974). In contrast, Reynolds’s distance mainly reflects the effect of genetic drift. Both distance values indicated that the CZ breed was the most distant breed, and this result is in agreement with previous studies (Uffo 2003). The SC and MC breeds were the closest populations, reflecting the common origin of these two breeds. The genetic proximity of both breeds was also demonstrated using the mixture of individuals observed in the trees based on allelic shared distances and the Bayesian clustering approach, which gives more precise information on breed relationships (Leroy et al. 2008). Using the approach of Evanno et al. (2005), the most probable number of inferred clusters (K = 4) failed to differentiate between the SC and MC breeds, confirming the relationship observed in the other analyses. Although most of the individuals included in the SC and MC populations continued to cluster together at K = 5, a few MC individuals appeared to be separated (Figure 3). High ΔK values can potentially reveal the best K, but some weakly defined substructures can be found when only a small number of breeds are analysed (Leroy et al. 2008).

Conclusion

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

The present study of Cuban native cattle breeds will contribute to a genetic characterization of indigenous populations. This genetic analysis showed that a significant amount of genetic variation is maintained in the local cattle populations and that all the breeds studied could be considered distinct genetic entities. The SC and MC breeds appeared to be genetically related, confirming their common origin. The five Cuban breeds constitute an important and diverse reservoir of genetic diversity for bovine breeding and are viable targets for conservation. The Mambí of Cuba and Taíno of Cuba breed were characterized for the first time in this study, and they showed levels of diversity similar to those observed in other Cuban native breeds.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

This work was supported by a research grant from MAEC-AECID. The authors thank the National Control Center of Genetics (Cuba) for their help in collecting blood samples and Carmen Cons for her technical assistance.

References

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References
  • Anonymous (1978) Selection program for dairy and beef production through Artificial Insemination in Cuba. Breeding and Artificial Insemination, FAO/SIDA Seminar, 30 October, 1978, Habana, Cuba.
  • Armstrong E., Postiglioni A., Martínez A., Rincón G., Vega-Pla J.L. (2006) Microsatellite analysis of a sample of Uruguayan Creole bulls (Bos taurus). Genet. Mol. Biol., 29, 267272.
  • Arora R., Bhatia S. (2004) Genetic structure of Muzzafarnagri sheep based on microsatellite analysis. Small Rumin. Res., 54, 227230.
  • Arranz J.J., Bayón Y., Primitivo F.S. (2001) Differentiation among Spanish sheep breeds using microsatellites. Genet. Sel. Evol., 33, 114.
  • Barrera G., Martínez R., Pérez J., Polanco N., Ariza F. (2006) Evaluación de la variabilidad genética en Ganado Criollo Colombiano mediante 12 marcadores microsatélites. Anim. Genet. Resour. Inf., 38, 35.
  • Botstein D., White R.L., Skolnick M., Davis R.W. (1980) Construction of genetic linkage maps in man using restriction fragment length polymorphisms. Am. J. Human Genet., 32, 314331.
  • Bowcock A., Ruiz-Linares A., Tomfohrde J., Minch E., Kidd J., Cavalli-Sforza L. (1994) High resolution of human evolutionary trees with polymorphic microsatellites. Nature, 368, 455457.
  • Brookfield J.F.Y. (1996) A simple new method for estimating null allele frequency from heterozygote deficiency. Mol. Ecol., 5, 453455.
  • Buxadera A.M., Dempfle L. (1997) Genetic and environmental factors affecting some reproductive traits of Holstein cows in Cuba. Genet. Sel. Evol., 29, 114.
  • Chakraborty R., De Andrade M., Daiger S.P., Budowle B. (1992) Apparent heterozygote deficiencies observed in DNA typing data and their implications in forensic applications. Ann. Hum. Genet., 56, 4557.
  • Egito A.A., Paiva S.R., Albuquerque M.S.M., Mariante A.S., Almeida L.D., Castro S.R., Grattapaglia D. (2007) Microsatellite based genetic diversity and relationships among ten Creole and commercial cattle breeds raised in Brazil. BMC Genetics, 8, 83.
  • European Cattle Genetic Diversity Consortium (2006) Marker-assisted conservation of European cattle breeds: an evaluation. Anim. Genet., 37, 475481.
  • Evanno G., Regnaut S., Goudet J. (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol. Ecol., 14, 26112620.
  • Excoffier L., Laval G., Schneider S. (2005) Arlequin ver. 3.0: an integrated software package for population genetics data analysis. Evol. Bioinform. Online, 1, 4750.
  • FAO/ISAG (2004) Secondary Guidelines. Measurement of Domestic Animal Diversity (MoDAD): New Recommended Microsatellite Markers. (also available at: http://dad.fao.org/cgibin/getblob.cgi?sid=-1,50005882; last accessed 5 November 2011).
  • Felsenstein J. (2004) PHYLIP (Phylogeny Inference Package) version 3.6. Distributed by the author. Department of Genome Sciences, University of Washington, Seattle.
  • Ginja C.D.A., Gama L.T., Penedo M.C.T. (2010) Analysis of STR Markers reveals high genetic structure in portuguese native cattle. J. Hered., 101, 201210.
  • Goudet J. (2002) Fstat version 2.9.3.2. Lausanne (Switzerland). Institute of Ecology. (available at: http://www2.unil.ch/izea/sotwares/fstat.html; last accessed 21 October 2011).
  • Groeneveld L.F., Lenstra J.A., Eding H., Toro M.A., Scherf B., Pilling D., Negrini R., Finlay E.K., Jianlin H., Groeneveld E., Weigend S. (2010) Genetic diversity in farm animals – a review. Anim. Genet., 41, 631.
  • Huson D.H., Bryant D. (2006) Application of phylogenetic networks in evolutionary studies. Mol. Biol. Evol., 23, 254267.
  • Kantanen J., Olsaker I., Holm L., Lien S., Vilkki J., Brusgaard K., Eythorsdottir E., Danell B., Adalsteinsson S. (2000) Genetic diversity and population structure of 20 North European cattle breeds. J. Hered., 91, 446457.
  • Leroy G., Verrier E., Meriaux J.C., Rognon X. (2008) Genetic diversity of dog breeds: between-breed diversity, breed assignation and conservation approaches. Anim. Genet., 40, 333343.
  • Liron J., Peral-Garcia P., Giovambattista G. (2006) Genetic characterization of Argentine and Bolivian Creole cattle breeds assessed through microsatellites. J. Hered., 97, 331339.
  • Martín-Burriel I., Rodellar C., Lenstra J., Sanz A., Cons C., Osta R., Reta M., De Argüello S., Sanz A., Zaragoza P. (2007) Genetic diversity and relationships of endangered spanish cattle breeds. J. Hered., 98, 687691.
  • Martín-Burriel I., Rodellar C., Cañón J., Cortés O., Dunner S., Landi V., Martínez-Martínez A., Gama L.T., Ginja C., Penedo M.C.T., Sanz A., Zaragoza P., Delgado J.V. (2011) Genetic diversity, structure, and breed relationships in Iberian cattle. J. Anim. Sci., 89, 893906.
  • Maudet C., Luikart G., Taberlet P. (2002) Genetic diversity and assignment tests among seven French cattle breeds based on microsatellite DNA analysis. J. Anim. Sci., 80, 942950.
  • Miller S.A., Dykes D.D., Polesky H.F. (1988) A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acid Res., 16, 1215.
  • Minch E., Ruiz-Linares A., Goldstein D., Feldman M., Cavalli-Sforza L. (1998) Microsat2: a computer program for calculating various statistics on microsatellite allele data. Department of Genetics, Stanford University, Stanford, CA, USA. (available at: http://hpgl.stanford.edu/projects/microsat/accessed 3 October 2011).
  • Nei M., Roychoudhury A. (1974) Sampling variances of heterozygosity and genetic distance. Genetics, 76, 379390.
  • Nei M., Tajima F., Tateno Y. (1983) Accuracy of estimated phylogenetic trees from molecular data. II. Gene frequency data. J. Mol. Evol., 19, 153170.
  • Prada N. (1984) Programa nacional de mejoramiento genético vacuno. Rev. ACPA, 3, 2026.
  • Pritchard J.K., Stephens M., Donnelly P. (2000) Inference of population structure using multilocus genotype data. Genetics, 155, 945959.
  • Raymond M., Rousset F. (1995) Genepop (Version-1.2) – population-genetics software for exact tests and ecumenicism. J. Hered., 86, 248249.
  • Rousset F. (2008) Genepop’007: a complete reimplementation of the Genepop software for Windows and Linux. Mol. Ecol., 8, 103106.
  • Uffo O. (2003) Aplicación de los marcadores moleculares al estudio de biodiversidad del ganado bivino cubano. Universidad Agraria de la Habana, La Habana, pp. 92.
  • Van Oosterhout C., Hutchinson W.F., Wills D.P.M., Shipley P. (2004) Program note Micro-Checker: software for identifying and correcting genotype errors in microsatellite data. Mol. Ecol. Notes, 4, 535538.