SciELO - Scientific Electronic Library Online

 
vol.30 issue2Fecal culture and two fecal-PCR methods for the diagnosis of Mycobacterium avium subsp. paratuberculosis in a seropositive herdGenetic evaluation of dystocia and its relationship with productive and reproductive traits in Holstein cows¤ author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Article

Indicators

Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google

Share


Revista Colombiana de Ciencias Pecuarias

Print version ISSN 0120-0690

Rev Colom Cienc Pecua vol.30 no.2 Medellín Apr./June 2017

http://dx.doi.org/10.17533/udea.rccp.v30n2a03 

Original Articles

Genetic characterization of Colombian indigenous sheep1

Caracterización genética de ovinos criollos colombianos

Caracterização genética de ovinos crioulos colombianos

Ricardo J Ocampo1, 2*1  2  *  , Rodrigo A Martinez11  , Juan F Rocha1  , Henry Cardona2 

11Grupo de Investigación en Recursos Genéticos y Biotecnología Animal, Corporación Colombiana de Investigación Agropecuaria CORPOICA, Mosquera, Cundinamarca (Colombia)

22Grupo de Investigación GaMMA, Facultad de Ciencias Agrarias, Universidad de Antioquia, Medellín, Colombia.

Abstract

Background:

indigenous breeds are important for poor farmers because of their natural selection against harsh environments and adaptation to regional conditions. However, inbreeding of indigenous sheep populations has increased in Colombia due to indiscriminate cross-breeding with foreign animals and lack of reproductive controls, with subsequent loss in productivity, which poses a great risk for the conservation of valuable genes.

Objective:

to determine the genetic diversity in Colombian indigenous sheep by using a panel of 10 microsatellite molecular markers.

Methods:

blood samples from 362 individuals from 43 farms in 11 Colombian provinces were genotyped and analyzed for a panel of 10 microsatellite markers.

Results:

a total of 134 alleles were found (13.4 alleles/locus on average) with a range of observed and expected heterozygosity of 0.428 to 0.831 and 0.615 to 0.855, respectively, and 0.742 polymorphic information content

(PIC). The average Wright F-statistics (FIS ) of the breeds was 0.107, suggesting moderate levels of inbreeding. Colombian sheep showed a low level of genetic differentiation among breeds (FST = 0.054) and STRUCTURE analysis showed complex patterns of admixture in the breeds.

Conclusion:

overall, Colombian sheep have high genetic variability, which is very important for future conservation programs and genetic improvement.

Key words: conservation; DNA; genetic diversity; ovine cattle; population structure

Resumen

Antecedentes:

las razas animales autóctonas son importantes para los agricultores de escasos recursos a causa de su selección natural contra el duro ambiente y su adaptación a condiciones regionales. Sin embargo

en Colombia, debido al cruce indiscriminado con razas foráneas y a la falta de control de la reproducción, ha aumentado la consanguinidad en las poblaciones de ovinos criollos y por lo tanto la pérdida en la productividad, lo que supone un gran riesgo para la conservación de genes valiosos.

Objetivo:

determinar la diversidad genética en razas criollas de ovinos colombianos utilizando análisis por microsatélites.

Métodos:

se visitaron 43 granjas localizadas en 11 departamentos del país, en las cuales se tomaron muestras de sangre a 362 individuos. Las muestras fueron genotipadas y analizadas para un panel de 10 marcadores microsatélites.

Resultados:

un total de 134 alelos fueron encontrados (13,4 alelos/locus en promedio), con un rango de heterocigocidad observada y esperada de 0,428 a 0,831 y 0,615 a 0,855, respectivamente, y un contenido de información polimórfica (PIC) promedio de 0,742. El Wright F-statistics (FIS) promedio de las razas evaluadas fue 0,107, lo cual sugiere que las razas tienen niveles moderados de consanguinidad. Las ovejas colombianas presentaron un bajo grado de diferenciación genética entre las distintas razas (FST = 0,054) y el análisis de STRUCTURE mostró complejos patrones de mezcla en las razas estudiadas.

Conclusión:

en términos generales, las ovejas colombianas presentan una alta variabilidad genética lo cual es muy importante para futuros programas de conservación y mejoramiento genético.

Palabras-clave: ADN; conservación; diversidad genética; estructura poblacional; ganado ovino

Resumo

Antecedentes:

as raças crioulas, devido a sua seleção natural em ambientes hostis e adaptação às condições regionais, são importantes para os agricultores de poucos recursos econômicos. Porém, na Colômbia, devido ao cruzamento indiscriminado com raças estrangeiras e a falta de controle na reprodução, tem aumentado a consanguinidade nas populações de ovinos crioulos e por tanto tem gerado perda na produtividade, o que faz supor um grande risco para a conservação de genes valiosos.

Objetivo:

determinar a diversidade genética em raças crioulas colombianas utilizando um painel de 10 marcadores moleculares microssatélites.

Métodos:

visitaram-se 43 granjas localizadas em 11 departamentos do país, nos quais foram amostrados 362 indivíduos, que foram genotipados e analisados para um painel de 10 marcadores microssatélites.

Resultados:

um total de 134 alelos foram encontrados (média de 13,4 alelos/locus), com um rango de heterocigocidade observada e esperada de 0,428 a 0,831 e 0,615 a 0,855, respectivamente, e um conteúdo de informação polimórfica (PIC) médio de 0,742. O Wright F-statistics (FIS) médio das raças avaliadas foi de 0,107, o qual sugere que as raças apresentam níveis moderados de consanguinidade. As ovelhas colombianas apresentaram um baixo grau de diferenciação genética entre as diferentes raças (FST = 0,054) e o análise de STRUCTURE mostrou complexos patrões de mistura nas raças estudadas.

Conclusão:

em termos gerais, as ovelhas colombianas apresentaram uma alta variabilidade genética, o qual é muito importante para futuros programas de conservação e melhoramento genético.

Palavras-Chave: conservação; diversidade genética; DNA; estrutura populacional; gado ovino

Introduction

Sheep play an important role in food production systems and are frequently recognized as a multi- purpose species capable of improving the rural economy. Rusticity, high fertility, and adaptability to harsh conditions are noticeable traits of these animals (Radhikag et al., 2015).

Sheep farming represents a profitable production system in Colombia due to the favorable conditions of the market, in which the demand for products from these animals has increased over time. This situation makes sheep one of the most promising livestock species in the rural sector of the country (Barrios, 2005).

According to the national inventory of Instituto Colombiano Agropecuario (ICA), for 2016 Colombia had a population of 1,423,466 sheep across the country. However, Guajira, Boyacá, Córdoba, and Cesar provinces concentrate 74% of the total sheep population.

The origins of Colombian sheep date back to the indigenous wool sheep resulting from crosses between European breeds and indigenous hair sheep breeds which, in turn, descended from African breeds. These animals were introduced to the country 500 years ago during the conquest and have experienced a process of adaptation to Colombian tropics (Delgado et al., 2009).

Other foreign breeds such as Katahdin, Santa Inés, Dorset, Dorper, and Hampshire are also present in Colombia. These breeds have been extensively used because of their higher productive performance compared with local indigenous breeds, however, the former do not have the adaptation level of the latter (Egito et al., 2002). On the other hand, the use of only a few genetic superior males for intensive mating might cause a reduction of the effective population size, higher levels of inbreeding and finally, decreased genetic diversity within breeds (Pastrana et al., 1996).

The increasing interest in the conservation of genetic resources has encouraged studies to characterize the genetic diversity of several livestock species and breeds (Sodhi et al., 2006). Microsatellite molecular markers have been extensively used with this purpose by several authors (Kugonza et al., 2011; Dixit et al., 2012; Souza et al., 2012; Awobajo et al., 2015; Jiang et al., 2015) taking advantage of their high polymorphism, codominant inheritance, abundant presence with wide dispersion in the genome, and high repeatability (Dodgson et al., 1997).

The objective of this study was to estimate the genetic diversity of three Colombian sheep breeds using a panel of 10 microsatellite markers and to determine the genetic structure between these populations.

Materials and methods

Ethical considerations

The protocol used to obtain blood samples was approved by the ethics committee for animal experimentation of the Universidad de Antioquia (Act 71, June, 2012).

Animals and samples

Blood samples were collected from 362 sheep of the following Colombian breeds: ovino de pelo colombiano (OPC), criollo de lana (CRL), and Mora Colombiana (MORA). The animals were located in 43 farms in 11 Colombian provinces (Antioquia, Boyacá, Caldas, Cesar, Córdoba, La Guajira, Magdalena, Nariño, Santander, Sucre, and Valle del Cauca). The samples were taken following recommendations by the MoDAD (FAO, 1996).

DNA extraction and genotyping

Genomic DNA was extracted from white blood cells using MOBIO commercial kit (Ultra Clean DNA Blood Isolation Kit, Calalog # 12000-100, Los Ángeles, California, USA). The quantity and quality of the extracted DNA was measured with a NanoDrop 2000 spectrophotometer (Thermo Scientific, Wilmington, Delaware, USA).

The panel used for genotyping the animals contained 10 microsatellites (Table 1) recommended by the Food and Agriculture Organization (FAO, 2011), and the International Society of Animal Genetics (ISAG) for diversity studies in sheep. The markers were chosen according with their polymorphism level detected in previous studies (Bozzi et al., 2009; Zhong et al., 2010; Álvarez et al., 2012; Ben Sassi et al., 2014) and their location in different chromosomes.

Microsatellites were amplified in two multiplex PCR assay: Multiplex 1 (SRCRPS9, MCM140, OARCB226, MAF214, ILSTS5, SRCRSP1) and Multiplex 2 (MAF33, ILSTS28, SRCRSP5, ILSTS11). Each PCR tube with a final volume of 10 μL contained ?120 ng genomic DNA, 0.2 mM of each dNTP, 1.85 U Taq Hot Start polymerase (ABM), 0.2 μM fluorolabeled forward primer and unlabeled reverse primer, 1.14 µL GC Enhancer (Applied Biosystems, Foster City, California), 1.5 mM MgCl2 and miliQ water up to adjust the final volume.

Amplification was carried out in a PTC 100 thermocycler (MJ Research Inc., Waltham, Massachusetts, USA) and PCR cycling conditions were as follows: initial denaturation at 95°C for 5 min followed by 35 cycles of denaturation at 95°C for 75 sec, annealing at 55°C for 45 sec, and extension at 72°C for 60 sec, and a final extension at 72°C for 10 min.

The fluorescent labelled PCR products were mixed with Hi Di formamide and Liz 500 TM internal size standard, denatured at 95°C for 5 min and genotyped on a capillary electrophoresis ABI PRISM® 310 DNA analyser (Applied Biosystems). The analysis for allele identification was performed using GENEMAPPER 4.1 software (Applied Biosystems).

Statistical analysis

The allele frequencies for all loci, number of alleles (NA) and the effective number of alleles (ENA) observed per locus, observed (OH) and expected (EH) heterozygosities were estimated for each marker with GenAIEx 6.5 software (Peakall y Smouse, 2012). The polymorphic information content (PIC) was calculated with the Excel Microsatellite Toolkit V 3.1.1 (Park, 2001).

The tests to obtain the deviations from the Hardy- Weinberg (HW) were estimated for each breed using Markov Chain Monte Carlo simulations with Genepop 4.2 software (Rousset, 2008). The population genetic structure was analysed by obtaining the Wright F-statistics (FIS, FST, and FIT) following the methods described by Weir y Cockerham (1984) and using Fstat 2.9.3.2 software (Goudet, 2002).

The genetic differentiation was examined in two steps. First, the genetic distances between breeds were determined using the method of Nei (1987) with GenAIEx 6.5 and Genepop 4.2. Software. These values were used to create a consensus tree through the un-weighted pair group method with arithmetic mean (UPGMA) included in MEGA 6 software (Tamura et al., 2013).

Subsequently, the population genetic structure was calculated with a Bayesian iterative algorithm using STRUCTURE software (Pritchard et al., 2000), which randomly assigns individuals to a pre- determined number of genetic groups K, according with the genotype of the multiple loci evaluated, measuring the admixture levels within individuals and

Table 1 Description of the microsatellite markers used in PCR. 

determining the K value for the parental populations. The analysis of the present study included a correlated allele frequencies model, assuming a level of non- independence (Pritchard et al., 2000; Zuccaro et al., 2008; Ciani et al., 2013).

A representative K value for the sample set was obtained by running three independent simulations for three pre-selected K values (1 ≤ K ≤ 3). All runs were performed with 200,000 burn-in period and 1,000,000 MCMC iterations after burn-in. Finally, the most appropriate K value in the populations was calculated with the ΔK algorithm used by Evanno et al. (2005).

Results

Population genetic variability

In total, 134 alleles were identified in the 362 genotyped individuals. The NA ranged from 9 to 21 for loci SRCRSP1 and ILSTS28, respectively, with an average NA of 13.4. Parameters evaluating population genetic variability by locus are presented in Table 2.

The EH ranged between 0.615 (ILSTS 5) and 0.855 (OarCB2256), with a population mean of 0.63, indicating high levels of genetic variability in the breeds.

The OH ranged between 0.428 (SRCRSP5) and 0.831 (ILSTS 28), with an average of 0.672 for all the loci.

The average PIC for the 10 markers was 0.742 with no values lower than 0.5, suggesting that all loci were highly polymorphic. The average FIS value was different from zero (0.102; p<0.05). Several microsatellites such as SRCRSP 5, ILSTS 11, MAF 214, and OarCB2256 showed FIS values higher than 0.1, indicating an excess of homozygote individuals for these markers in the populations.

The FIT, which measures individual heterozygosis respect to that of the total population was 0.151 (p<0.05), indicating a 15.1% general deficit of heterozygote individuals in these populations. The FST, which measures the genetic variability explained by differences between breeds was 0.054. Therefore, most of the total genetic variability comes from differences among individuals (94.6%), while only 5.4% is due to differences between breeds. This suggests a very low level of genetic differentiation between the populations studied.

Genetic variability within breeds

The MNA for all breeds was 9.6. The OPC sheep had the highest MNA (12.40), while MORA showed the lowest MNA (7.90). Different parameters to evaluate genetic variability for each breed are presented in Table 3.

Table 2 Summary statistics in Colombian indigenous sheep population analysed by 10 microsatellite loci. 

*p<0.05. NA: number of alleles. ENA: effective number of alleles. OH: observed and EH: expected heterozygosities. PIC: polymorphic information content. F-statistics (FIS, FST, FIT).

Table 3 Summary statistics for three Colombian indigenous sheep breeds analysed by 10 microsatellite loci. 

N: number of animal sampled. MNA: mean number of alleles. MENA: mean effective number of alleles. OH: observed and EH: expected heterozygosities. FIS: F-statistic. OPC: ovino de pelo colombiano. CRL: criollo de lana

The lowest values of OH and EH were observed in MORA breed (0.606 and 0.671, respectively), while the highest OH and EH were obtained for the CRL breed (0.689 and 0.762, respectively). There were no large differences between EH and OH, with the CRL and MORA breeds showing the highest and lowest differences, respectively. In general, all breeds showed high genetic diversity.

Inbreeding parameters (FIS) for each breed had a mean of 0.107. All breeds showed FIS levels higher than zero, indicating a general deficit of heterozigote individuals.

From a total of 30 tests to evaluate HW equilibrium in each breed (Table 4), 15 showed significant deviations (p<0.05), which is explained by the heterozygosity deficit.

Figure 1 shows the phylogenetic tree constructed from the matrix of Nei standard genetic distances.

The CRL and MORA breeds are grouped in the same node, separated from the OPC individuals.

Population structure was analyzed using STRUCTURE program with the expected number of clusters (K) ranging from 1 to 3. According with the method proposed by Evanno et al. (2005), it was assumed that K = 3 is the most likely number of ancestral populations that contribute to the genetic diversity observed in Colombian sheep breeds. There was no clear differentiation between populations under any of the K values tested (Figure 2), which indicates high admixture levels.

Table 4 Hardy Weinberg equilibrium test by breed. 

* Significant deviation from Hardy Weinberg equilibrium (p<0.05). OPC: ovino de pelo colombiano. CRL: criollo de lana.

Figure 1 Phylogenetic tree (UPGMA) representing Nei’s standard genetic distances between CRL (criollo de lana), MORA and OPC (ovino de pelo colombiano) breeds. 

Figure 2 Population structure estimated with STRUCTURE in CRL (criollo de lana), MORA and OPC (ovino de pelo colombiano) breeds for values of K = 2 and K = 3. 

Discussion

We studied the genetic diversity of three Colombian indigenous sheep breeds by using microsatellite molecular markers. According with reference values reported by ISAG/FAO (2011) for the minimum number of alleles using this panel of microsatellites, all loci were highly polymorphic. The average NA found in this study (13.4) is higher than that obtained by Nanekarani et al. (2010) using 15 microsatellites in a population of 360 sheep of four breeds in Iran. The EH, best estimator of the genetic diversity present in a population (Kim et al., 2002), had a value of 0.63, indicating that the indigenous sheep population in Colombia has a high genetic variability. Except for SRCRSP 9 and ILSTS 28 loci, the OH was always lower than the EH. Similar results were found by Bozzi et al., (2009), Arora et al., (2010), Zhong et al. (2010), and Gornas et al., (2011) in sheep populations of Sudan, India, China, and Italy, respectively.

Polymorphic information content (PIC), a parameter indicative of the degree of informativeness of a marker, ranged from 0.647 (MAF214) to 0.844 (OarCB2256). In the present study all markers were highly informative (PIC>0.5; Arora et al., 2006). These observations suggested the additional utility of these markers for population assignment (Arora et al., 2010) in indigenous sheep and gene mapping (Kayang et al., 2002).

On the other hand, it is important to note the low level of differentiation observed among breeds (FST = 0.054). Similar results were found by Bozzi et al. (2009), Zhong et al. (2010), Álvarez et al. (2012), and Ben Sassi et al. (2014), who reported FST ranging between 0.09 and 0.3. Genetic similarity between Colombian sheep breeds could be explained by a high flow of genes between farms that borrow or lease rams and also because of the poor control in breeding programs within sheep farms.

All three breeds showed high MNA. The OPC breed had the highest MNA (12.40), which in turn is higher than the value reported in Mexican indigenous sheep (7.8 alleles/locus; Quiroz et al. (2007), Paraguayan indigenous sheep (7.25 alleles/locus; Ochipinti et al. (2012), American indigenous sheep (7.71 alleles/locus; Blackburn et al. (2011), Kenyan indigenous sheep (6.16 alleles/locus; Muigai et al. (2009), and Indian indigenous sheep (5.48 alleles/locus; Arora et al. (2010). It is important to note that OPC individuals represented 80.66% of the total population sampled, however, this percentage is similar to the proportion of this breed in the sheep national inventory (Martinez et al., 2009).

The significant deviations found in the HW tests and the high values of FIS found in each breed indicate a general deficit of heterozygote individuals. This could have been caused by nonrandom mating (Arora et al., 2010), selection (Álvarez et al., 2012) and the Wahlund effect which means the presence of substructures in the sheep populations (Nei, 1987).

Nevertheless, it is highly probable that the main origin of this heterozygosity deficit is the high levels of endogamy in the flocks, which is caused by mating individuals with closely related ancestors, which in Colombia is related with poor animal identification, lack of mating control (Martínez et al., 2009), and the lack of clear breeding objectives. Moreover, most sheep farms in Colombia only have one or two rams, which must be mated with all the females of the flock, thus increasing endogamy and reducing genetic diversity (Tolone et al., 2012).

The standard genetic distances allowed grouping CRL and MORA breeds in a same node. It is essential to highlight that MORA breed was developed 50 years ago by ICA by crossing CRL (50%), Hampshire (23%), Romney Marsh (19%), and Corriedale individuals (8%) to obtain animals for meat production but also recessive homozygotes for black coloured wool (Pastrana et al., 1996). On the other hand, these are wool sheep breeds with a common geographical origin, since they are descendent of Churra and Manchega Spanish sheep breeds. In addition to this, CRL and MORA breeds are closely bred in the high tropics of Colombia, and the crossing between individuals of these breeds is frequent. Therefore, the results of the distance matrix and the phylogenetic tree can be explained by the common geographical location, the origin of these breeds and the breeding practices to obtain genetically improved individuals through crossbreeding strategies.

The Bayesian analysis using STRUCTURE program assumed a value of K = 3 as the most likely number of ancestral populations to explain the genetic diversity and structure of the Colombian sheep populations. As Figure 2 showed, none of the clusters had a clear differentiation, which suggests the presence of high admixture levels in these sheep breeds. This could be considered as a phenomenon of introgressive hybridization in which there is a gene flow from one population into the gene pool of another, but in this case, this introgression would occur between different proportions of the genetic material of three ancestral breeds, as showed by the most likely K value. The group of wool sheep imported from Europe 500 years ago (Churra and Manchega breeds, mainly) would make up the first ancestral population, from which the current Colombian sheep are descendants (Pastrana and Calderon, 1996). African sheep brought to America after the colonization would make up the second ancestral population, and from which breeds like OPC, Black Belly, and Pelibuey would be descendants. European breeds introduced to the region long after the conquest times with the aim of genetically improving wool sheep could make up the third ancestral group.

In conclusion, all three Colombian sheep breeds showed high genetic variability, evidenced by high polymorphism and number of alleles per locus for the molecular markers used for genotyping. However, a heterozygosity deficit was present to some extent in all breeds, something mainly attributed to endogamy within sheep flocks. In order to maintain the existing genetic diversity, breeding strategies (i.e. seed stock exchange oriented) aiming to maintain effective population size while minimizing inbreeding and genetic drift, should be implemented, especially for MORA and CRL. Besides, a conservation program is recommended for MORA and CRL breeds, including in vitro (e.g. germplasm bank) and in situ (e.g. maintenance of flocks) approaches.

Acknowledgements

The authors thank the committee for research development CODI, Universidad de Antioquia (Project code 2012-5019), the Grupo de Investigación GaMMA from the Universidad de Antioquia (Project code E01808), and CORPOICA (Colombia) for financial support of this research. We also thank all the farmers who facilitated the sampling process necessary for conducting this study.

Conflicts of interest

The authors declare they have no conflicts of interest with regard to the work presented in this report

References

Arora R, Bhatia S. Genetic diversity of Magra sheep from India using microsatellite analysis. Asian Australasian J Anim Scienc 2006; 19 (7):938-942. [ Links ]

Arora R, Bhatia S, Jain A. Morphological and genetic characterisation of Ganjam sheep. Anim Gen Resources 2010; 46:1-9. [ Links ]

Awobajo OK, Salako AE, Osaiyuwu OH. Analysis of genetic structure of Nigerian West African Dwarf goats by microsatellite markers. Small Rumin Res 2015: In press. [ Links ]

Álvarez I, Capote J, Traoré A, Fonseca N, Perez K, Cuervo M, Fernández I, Goayche F. Genetic relationships of the Cuban hair sheep inferred from microsatellite polymorphism. Small Rumin Res 2012; 104:89-93. [ Links ]

Barrios C. Guía práctica de ovinocultura enfocada hacia la producción de carne. Finagro 2005. [Access date: August 9th, 2016]. URL: URL: http:// http://www.academia.edu/14189463Links ]

Ben SZ, Maretto F, Charfi-Cheikrouha F, Cassandro M. Genetic diversity, structure, and breed relationships in Tunisian sheep. Small Rumin Res 2014; 119:52-56. [ Links ]

Blackburn HD, Toishibekov Y, Toishibekov M, Welsh CS, Spiller SF, Brown M, Paiva SR.Genetic diversity of Ovis aries populations near domestication centers and in the new world. Springer genetic 2011; 139:1169-1178. [ Links ]

Bozzi R, Degl’Innocenti P, Rivera Diaz P. Genetic characterization and breed assignment in five Italian sheep breeds using microsatellite markers. Small Rumin Res 2009; 85(1):50-57. [ Links ]

Ciani E, Ciampolini R, D’Andrea MS, Castellana E, Cecchi F, Incoronato C, D’Angelo F, Albenzio M, Pilla F, Matassino D, Cianci D. Analysis of genetic variability within and among Italian sheep breeds reveals population stratification and suggests the presence of a phylogeographic gradient. Small Rumin Res 2013; 112:21-27. [ Links ]

Delgado JV, León JM, Gómez, M, Nogales S, Camacho ME. Las razas ovinas ibéricas y su participación en la colonización de Iberoamérica. Biodiversidad ovina Iberoamericana. Caracterización y uso sustentable 2009; 14:18-40. [ Links ]

Dixit SP, Verma NK, Aggarwal RAK. Genetic diversity and relationship among Indian goat breeds based on microsatellite markers. Small Rumin Res 2012; 105:38-45. [ Links ]

Dodgson JB, Cheng HH, Okimoto R. DNA marker technology: a revolution in animal genetics. Poult Sci 1997; 76:1108-1113. [ Links ]

Egito AA, Mariante AS, Albuquerque MSM. Programa brasileiro de conservacão de recursos genéticos animais. Arch Zootec 2012; 51:193-194. [ Links ]

Evanno G, Regnaut S, Goudet J. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 2005; 14:2611-2620. [ Links ]

FAO. Global project for the maintenance of domestic animal genetic diversity (MoDAD). 1996. [ Links ]

FAO. Molecular genetic characterization of animal genetic resources. FAO Animal Production and Health Guidelines. Roma; 2011. [ Links ]

Gornas N, Weimann C, El Hussien A. Genetic characterization of local Sudanese sheep breeds using DNA markers. Small Rumin Res 2011; 95:27-33. [ Links ]

Goudet J. FSTAT (version 2.9.3.2): a program to estimate and test gene diversities and fixation indices. F-statistics. J Hered 2002; 86:485-486. [ Links ]

Jiang W, Wang Y, Xing J, Jiang Y. Evaluation of the genetic diversity of Laiwu pigs using twenty-seven microsatellite markers. Biochem Sys Ecol 2015; 62:1-5. [ Links ]

Kayang BB, Inoue-Murayama M, Hoshi T. Microsatellite loci in Japanese quail and cross-species amplification in chicken and guinea fowl. Genet Select Evol 2002; 34:233-253. [ Links ]

Kim KS, Yeo JS, Choi CB. Genetic diversity of North-East Asian cattle based on microsatellite data.Anim Genet 2002; 33(3):201-204. [ Links ]

Kugonza DR, Jianlin H, Nabasirye M. Genetic diversity and differentiation of Ankole cattle populations in Uganda inferred from microsatellite data. Lives Sci 2011; 135:140-147. [ Links ]

Martínez R, Vásquez R, Ballesteros H. El ovino criollo en Colombia, conservación. Caracterización y evaluación de la variabilidad genética. Biodiversidad ovina Iberoamericana. Caracterización y uso sustentable 2009; 18(33):235-261. [ Links ]

Muigai AWT, Okeyo AM, Kwallah AK, Mburu D, Hanotte O. Characterization of sheep populations of Kenya using microsatellite markers: Implications for conservation and management of indigenous sheep populations. South African J Anim Scienc 2009; 39(1):93-96. [ Links ]

Nanekarani S, Amirinia C, Amirmozafari N, Torshizi RV, Gharahdaghi A. Genetic variation among pelt sheep population using microsatellite markers. Afr J Biotechnol 2010; 9(44):7437-7445. [ Links ]

Nei M. Molecular evolutionary genetics. New York: Columbia University Press; 1987. [ Links ]

Ochipinti G, Núñez L, Cazal C, Samudio A, Castro L, Ramírez L, León D, Martínez A, Oka A, Landi V, Delgado JV, Martínez O. Diversidad genética en ovejas de los humedades de la región Oriental del Paragüay. Actas Iberoamericanas de conservación animal 2012; 2:227-230. [ Links ]

Park SDE. Trypanotolerance in West African cattle and the population genetic effects of selection. Ph.D. thesis, University of Dublin; 2001. [ Links ]

Pastrana R, Calderón C. El ovino criollo colombiano. Los animales domésticos criollos y colombianos en la producción pecuaria nacional 1996; 1:65-71. [ Links ]

Peakall R, Smouse P.E. GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics 2012; 28:2537-2539. [ Links ]

Pritchard JK, Stephens M, Donnelly P. Inference of population structure using multilocus genotype data. Genetics 2000; 155:945-959. [ Links ]

Quiroz J, Martínez A, Landi V, Zaragoza L, Martínez R, Perezgrovas G, Vega-Pla J.L. Relación genética de la raza ovina de Chiapas con algunas razas ovinas españolas. Arch Zootec 2007; 56(1):441-447. [ Links ]

Radhika G, Raghavan KC, Aravindakshan TV, Thirupathy V. Genetic diversity and population structure analysis of native and crossbred goat gentic groups of Kerala, India. Small Rumin Res 2015: In press. [ Links ]

Rousset F. Genepop’007: a complete reimplementation of the Genepop software for Windows and Linux. Mol Ecol Resour 2008; 8:103-106. [ Links ]

Sodhi M, Mukesh M, Bhatia S. Characterizing Nali and Chokla sheep differentiation with microsatellite markers. Small Rumin Res 2006; 65:185-192. [ Links ]

Souza CA, Paiva SR, McManus CM. Genetic diversity and assessment of 23 microsatellite markers for parentage testing of Santa Ines hair sheep in Brazil. Genet Mol Res 2012; 8:1217-1229. [ Links ]

Tamura K, Stecher G, Peterson D, Filipski A, Kumar S. MEGA6: Molecular evolutionary genetics analysis, Version 6.0. Mol Biol Evol 2013; 30:2725-2729. [ Links ]

Tolone M, Mastrangelo S, Rosa AJM. Genetic diversity and population structure of Sicilian sheep breeds using microsatellite markers. Small Rumin Res 2012; 102:18-25. [ Links ]

Weir BS, Cockerham C. Estimating F-statistics for the analysis of population structure. Evolution 1984; 38:1358-1370. [ Links ]

Zhong T, Han J, Guo J. Genetic diversity of Chinese indigenous sheep breeds inferred from microsatellite markers. Small Rumin Res 2010; 90:88-94. [ Links ]

Zuccaro A, Bordonaro S, Criscione A, Guastella M, Perrotta G, Blasi M, D’Urso G, Marletta D. Genetic diversity and admixture analysis of Sanfratellano and three other Italian horse breeds assessed by microsatellite markers. Animal 2008; 2(7):991-998 [ Links ]

1To cite this article: Ocampo RJ, Martínez RA, Rocha JF, Cardona H. Genetic characterization of Colombian indigenous sheep. Rev Colomb Cienc Pecu 2017; 30:116-125.

Received: December 15, 2015; Accepted: September 12, 2016

* Corresponding author: Ricardo J Ocampo. Facultad de Ciencias Agrarias, Universidad de Antioquia. Carrera 75 # 65-87, Bloque 47, oficina 231, Ciudadela Robledo. AA 1226, Medellín, Colombia. Tel.: +57 3006261228. E-mail: ricardo.ocampo23@gmail.com

Creative Commons License This is an open-access article distributed under the terms of the Creative Commons Attribution License