Genetic Diversity and Relationship Among Algerian, Nigerian, and Turkish Goat Breeds Using Microsatellite Markers

Abstract

Background:

This study was conducted to identify genetic diversity among goat breeds in Algeria, Türkiye, and Nigeria, which is believed to have arisen due to historical influences, trade networks, and environmental adaptations, using 12 microsatellite markers. Additionally, the study provided insights into the population structure and kinship relationships among the breeds.

Methods:

The animal material of the study consisted of 514 goats from eight breeds: four Algerian (n = 224), two Turkish (n = 140), and two Nigerian (n = 150) native goat breeds. The quality and quantity control of DNA obtained from blood samples was determined using the Nanodrop 2000 device. In the study, 12 microsatellite markers were used. Capillary electrophoresis was used to separate polymerase chain reaction (PCR) fragments labeled with fluorescent dye in the Beckman Coulter GeXP Genetic Analyzer. Statistical analyses were used to calculate molecular genetic parameters, F-statistics, and genetic distances. Factorial correspondence analysis, structure analysis, and dendrogram construction were used to explore population structure.

Results:

The study used microsatellite markers to analyze genetic diversity in various breeds, revealing 149 alleles with a mean of 12.41 per locus. Positive inbreeding coefficient within subpopulations (F_IS) values indicated a heterozygote deficiency, suggesting potential breeding strategies. Population structure analyses revealed distinct genetic clusters and relationships, providing insights into genetic variation within populations.

Conclusion:

The study provides a detailed analysis of goat populations in Algeria, Türkiye, and Nigeria, revealing the presence of heterozygote deficiency and the need for strategic breeding interventions to preserve genetic diversity. The findings also reveal distinct genetic clusters and relationships with historical influences, particularly the role of the Mediterranean Sea, adding depth to our understanding. The research offers practical guidance for the sustainable management of these valuable genetic resources, emphasizing adaptive strategies to ensure the resilience and adaptability of goat populations. The findings are crucial for informed decision-making in conserving and utilizing diverse livestock breeds, urging further exploration of goat populations’ genetic landscapes.

Graphical abstract

Keywords

genetic diversity / Algerian goat breeds / Turkish goat breeds / Nigerian goat breeds / microsatellites / population genetic structure

1. Introduction

Goats are essential for rural life in developing economies, contributing to food security and poverty alleviation. Climate change, market dynamics, and the movement of people and animals influence the genetic diversity of goat populations. The Mediterranean Sea has been a significant conduit for trade between Africa, Europe, and Asia, influencing the genetic makeup of goat breeds. However, there is a gap in understanding regarding the genetic relationships between goat breeds from Algeria, Türkiye, and Nigeria. This study aimed to explore the genetic diversity, population structure, and interbreed relationships among these breeds using twelve microsatellite markers to investigate the genetic tapestry woven by centuries of trade, travel, and environmental adaptations.

Preserving biological diversity is essential for future breeding options and livestock genetic resources, which are crucial for adapting to changing climates and markets [1]. A previous study by Cañón et al. [2] highlighted the importance of the Mediterranean Sea as a pathway for the movement of people and animals within a vibrant web of commerce. The transcontinental commerce of products, plants, and animals between Africa, Europe, and Asia is typically associated with Africans; however, Arabs also experienced significant population shifts and were frequent travelers due to their role as extensive traders. Over the Mediterranean region, these movements relocated both people and their animals [3]. Microsatellite markers exhibit a high degree of polymorphism, random distribution throughout the genome, co-dominance, automated genotype scoring capabilities, and selection neutrality, making them extremely significant and useful tools in previous diversification study [4]. A thorough understanding of the current genetic diversity in domestic animals and how that variability is distributed among breeds is a prerequisite for both the conservation and use of that biodiversity [5]. However, no prior analysis exists of the link between Algerian, Turkish, and Nigerian breeds.

Meanwhile, microsatellite marker studies on these breeds have revealed significant genetic variability within and between them [6, 7, 8, 9, 10, 11]. However, most of this research concentrated on the variety and relationships between goat breeds at the national level, with relatively little data available at the regional level. Therefore, this current study was designed to examine the genetic diversity, population structure, and genetic relationships among four breeds of goats in Algeria (M’zabite, Naine of Kabylie, Mekatia, and Arbia), two Turkish goat breeds (Damascus and Hair goat), and three Nigerian goat breeds (West African Dwarf, Red Sokoto, and Sahel) using twelve microsatellite markers.

2. Materials and Methods

2.1 DNA Extraction of Samples

The animal material used in the study consisted of 514 goats from eight breeds: four Algerian (n = 224), two Turkish (n = 140), and two Nigerian (n = 150) native goat breeds (Table 1). Blood samples were collected into a vacutainer tube filled with K3EDTA (Fisher Scientific, Arendalsvägen, Göteborg, Sweden) from the jugular vein of each animal. Next, DNA quantification and qualification of all samples were performed using a NanoDrop 2000 (Thermo Scientific, Waltham, MA, USA). The protocol was approved by the University of Abou Bekr Belkaid, Tlemcen Ethics Committee (approval number: 32/2022), and the type approval number was 16/10/2022 EDCTU.

2.2 PCR, Fragment Analysis

This study used 12 microsatellite markers recommended by the Food and Agriculture Organization (FAO) of the United Nations [12]. Three multiplex groups were formed using the microsatellites (Table 2, Ref. [12]). Approximately 50 ng of DNA was utilized for the polymerase chain reaction (PCR). A PCR master mix was prepared, consisting of 0.10 µM primers, 0.20 mM dNTPs, 2.0 mM MgCl₂, 1\times PCR buffer, and 1 unit of Taq DNA polymerase (Thermo Scientific, Waltham, MA, USA), resulting in a total volume of 25 µL (Table 3). Capillary electrophoresis was used to separate PCR fragments labeled with fluorescent dye in the Beckman Coulter GeXP Genetic Analyzer (Beckman Coulter, Inc., Pasadena, CA, USA).

2.3 Statistical Analysis

The following values were calculated using GenAlEx 6.5.01 (https://biology-assets.anu.edu.au/GenAlEx/Welcome.html) [13], POPGENE 1.32 (Molecular Biology and Biotechnology Center, University of Alberta, Edmonton, Canada) [14], and CERVUS 3.0.3 (www.fieldgenetics.com) [15, 16]: the number of alleles per locus (Na), the mean number of alleles (MNa), effective number of alleles (Ne), polymorphic information content (PIC), observed heterozygosity (Ho), expected heterozygosity (He), average heterozygosity (Ĥ), Hardy–Weinberg equilibrium (HWE), Wright’s F-statistics (total inbreeding coefficient (F_IT), inbreeding coefficient within subpopulations (F_IS), fixation index (F_ST)) [17, 18], and null allele frequencies. The robustness of the dendrogram topology was tested using the bootstrap resampling methodology (1000 replicates) and Nei’s minimum genetic distance matrix [19]. FSTAT 2.9.3 (Institute of Ecology, University of Lausanne, Lausanne, Switzerland) [20] was used to calculate Nei’s gene diversity (H_T), diversity between breeds (D_ST), and coefficient of gene differentiation (G_ST) values. Factorial correspondence analysis was carried out using the GENETIX V4.0.5 (CNRS UMR 5000, University of Montpellier II, Montpellier, France) [21] software’s “AFC populations” program to test for potential admixtures that may have occurred between the populations. Using this structure, cluster techniques based on the Bayesian approach were employed to analyze the population structures [22, 23, 24, 25]. The analysis used independent allele frequencies and an admixture model with a burn of 20,000 length and 100.000 Markov chain Monte Carlo iterations for each from K = 2 to 10. There were 20 replication runs for each K. Using \mathrm{\Delta }K, the right number of clusters was determined based on the change rate in the log probability of the data, according to Evanno’s method [26]. STRUCTURE HARVESTER was used to determine the ideal K values [27].

3. Results and Discussion

This study uses 12 microsatellite markers to explore the genetic diversity, population structure, and interbreed relationships among Algerian, Turkish, and Nigerian goat breeds. The results (Table 4, Ref. [18, 28]) reveal high variability in alleles, effective alleles, and polymorphic information content, with observed heterozygosity and expected heterozygosity values providing nuanced understanding. Positive F_IS values suggest a heterozygote deficiency, indicating potential implications for breeding strategies and population dynamics. Population structure analyses reveal genetic relationships and distinct clusters among the breeds. These findings contribute to the scientific understanding of goat genetics and offer practical implications for conservation and breeding strategies in changing climates and markets.

The selected microsatellite panel performed well in the diversity study, focusing on loci with at least four alleles based on identified alleles, gene diversity, PIC, and F_IS values [29]. Every locus examined in this study had four or more alleles, proving that every marker was suitable for examining genetic diversity. A total of 149 alleles were identified from the 12 microsatellites utilized in this study. The number of alleles observed was greater than that reported for West African goats (120) [30], West Himalayan goats (135) [31], West Java goats (96) [32], and Benin goats [11]. The allele numbers obtained in the present study were lower than those reported for Retinta Extremena goats in Spain [33], native goats in Türkiye [6, 8], and native goat breeds in Algeria [9, 10]; the average number of alleles per locus in this study was 12.41. This value was higher than reported in several related studies [30, 31, 33, 34]. In studies conducted on various goat breeds, the number of alleles per locus was reported as 14.12, 16.48, and 16.50 for South Indian, Indian, and Indian Kerala goat breeds, respectively [35, 36]. For Turkish goat breeds, the number was 15.65 [6], while Algerian breeds exhibited values of 25 and 28.39 [9, 10]. On the other hand, the number of alleles per locus was reported to be 17.82 in certain goat breeds raised in Türkiye [8], 8 in East Java goats [32], and 11.25 in Benin goats [11]. According to Kumar et al. [37], the genetic diversity found in those populations, as measured by the mean number of alleles across a range of loci in various populations, represents a believable indicator of genetic variation within populations. The average effective number of alleles was 7.53, ranging from 6.385 (ILTS0019) to 9.3 (SRCRSP0008). This value was significantly higher than those reported by Singh et al. [31], Parejo et al. [33], and Dixit et al. [34]. PIC values can be used as a statistical measure of a marker’s informativeness; in population genetic analyses, a genetic marker with a PIC value greater than 0.5 is typically regarded as informative [38]. The current PIC values ranged from 0.87 (ILTS0019) to 0.96 (CSRD0247), with a mean of 0.93. The values obtained for PIC were higher than those reported in several studies conducted on goats [6, 8, 9, 10, 31, 32, 39, 40]. This study demonstrated that the examined microsatellites exhibited a high level of polymorphism in these populations and can be utilized with great confidence for identifying genetic diversity within them. This could be because the population’s heterozygosity and allele richness levels, reliable markers of genetic polymorphism in the Algerian goats under study, were higher than average. The F_IS indicates the heterozygous excess or deficiency deviation between genotypic and panmictic frequencies. Positive F_IS values indicate heterozygote deficiency and negative values indicate heterozygote excess compared to the HWE estimations [41]. Each of the 12 loci used in this investigation had a positive F_IS value. Tefiel et al. [9] reported that only 2 of the 18 loci in their study exhibited negative F_IS values, indicating an excess of heterozygotes. Similar situations have been reported [33]. The average F_IS value obtained in this study (0.087) was higher than the values reported in studies conducted in Switzerland (0.014), Türkiye (0.037), South Africa (0.020), Spain (0.060), and among Algerian goat breeds (0.057 and 0.083) [6, 9, 10, 32, 39, 42]. The general heterozygosity loss, or F_IT value, was between 0.125 (BM1818) and 0.287 (INRA063), with a mean of 0.194. This value exceeded the 0.08 reported by Bosman et al. [39], the 0.077 obtained by Parejo et al. [33], the 0.102 reported by Tefiel et al. [9], and the 0.146 obtained by Tefiel et al. [10]. The F_ST values obtained for each locus in this study indicate population differences (Table 4). While F_ST values ranging from 0.05 to 0.3 are commonly considered normal findings [43], it has also been noted that smaller values can be significant. The average F_ST value obtained (0.118) is a key indicator of genetic divergence between the studied populations, suggesting that gene flow is not entirely interrupted. However, there is still some limited gene flow between these populations. This observed level of genetic divergence is believed to result from geographical barriers, variations in reproductive behaviors, environmental adaptations, or other factors that impede gene flow between populations. In the study of the genetic structure of 45 goat breeds from Europe and the Middle East, Cañón et al. [2] reported that only 7% of all genetic variability could be attributed to breed differences. The mean F_ST value was higher than some values reported in previous research [6, 9, 10, 44, 45, 46, 47, 48] and lower than others [36] for goat breeds raised in various countries. The expected and observed heterozygosity for Ho and He are provided in Table 4, with respective means of 0.75 and 0.82. The He value was greater than Ho, indicating a population heterozygote deficit. The average Ho value (0.75) was higher than those reported for Western Himalayan goat breeds [31], Indian goat breeds [35, 37, 40], Turkish goat breeds [6, 8], and Benin goat breeds. Hence, based on these results, it can be considered that although the populations under investigation had a high level of genetic diversity, there was a slight heterozygote deficit, as shown by slightly lower Ho values. Meanwhile, high levels of genetic variation may be attributed to the admixture of populations or lower selection pressure, as reported by [31, 40]. Heterozygote deficit may be linked to the use of an inadequate number of stud bucks, a small population size, insufficient gene flow, and potential inbreeding. A population has a genotype frequency deviation when the HWE assumptions are devastated. A few possible explanations exist for the variations noticed in some population markers, including selection against heterozygous individuals, non-amplification (null alleles), inbreeding, and group defective alleles. The HWE was examined for each population; the findings are displayed in Table 4. The genetic equilibrium assessment for each examined breed showed highly significant differences (p 0.001) for all loci (Wright’s statistics, according to [14]). Some studies have reported similar situations [9, 10, 39]. Observed null allele frequencies for all microsatellites below the critical value (20%) indicated that these studied markers could confidently identify genetic diversity in these native sheep breeds. The mean value of Nei’s gene diversity (H_T), between-breed diversity value (D_ST), and coefficient of gene differentiation (G_ST) were determined as 0.938, 0.102, and 0.109, respectively. With an average of 2.01 across all populations, the gene flow (Nm, or number of migrants per generation) estimated for this study was high (Table 4). The Nm value obtained was lower than those reported in studies conducted on various goat breeds [4, 9, 40, 49]. This value, along with the F_ST (0.118), suggests a moderate level of genetic differentiation between the populations, indicating that some gene flow still occurs. Table 5 summarizes the genetic diversity results according to the studied population.

The mean number of alleles (MNA) in the breeds varied from 8.00 in the Red Sokoto breed to 16.41 in the Arbia breed. Values between 6.5 and 12.94 have been reported for the MNA across different breeds [1, 5, 6, 9, 10, 35, 39, 44]. The observed heterozygosity ranged from 0.65 (Red Sokoto and West African Dwarf breeds) to 0.87 (Naine of Kabylie breed) and is higher than the results published by Missohou et al. [30]. Algerian native goat breeds exhibited heterozygosity values ranging from 0.82 to 0.89, as reported by Tefiel et al. [9]. In contrast, the heterozygosity observed in Algerian and Turkish goat breeds was between 0.77 and 0.88, according to Tefiel et al. [10]. In the present study, the lowest He value was obtained in Red Sokoto at 0.70, while the highest values were observed in Arbia and Naine of Kabylie at 0.90 (Table 5). The values obtained for the He parameter were higher than those reported for native goat breeds from Egypt and Syria [47] and some Italian breeds [5]. While the He values ranged from 0.67 to 0.74 in Southern Italian breeds [1], values between 0.88 and 0.99 were reported in Algerian breeds [9].

In most populations, the He values were higher than the Ho values. This discrepancy indicates a deficiency in heterozygosity, as previously reported by Missohou et al. [30]. Although 124 unique alleles were detected in the studied populations, only 54 had a frequency greater than 5%. Conversely, the highest number of private alleles with a frequency exceeding 5% was observed in the Damascus breed. Of the total private alleles observed in the studied populations, 43.5% had a frequency greater than 5%. It has been reported that unique alleles observed at frequencies exceeding 20% within a population can be considered a positive indicator for conserving genetic diversity [42].

Table 6 shows that the breeds with the lowest and highest genetic identities are the Red Sokoto and Sahel breeds (0.984) and the Mekatia and Sahel breeds (0.070), respectively.

According to these findings, the genetic distance between the Red Sokoto and Sahel breeds is greater than between Mekatia and Sahel breeds. In the present study, the genetic similarity values obtained between the breeds, based on Nei’s similarity and distance matrix, ranged from 0.123 to 0.984. In contrast, the genetic distance values varied from 0.123 to 2.660. Considering the genetic distance and similarity matrix, the lowest genetic identity value was observed between the Mekatia and Sahel breeds (0.070). In contrast, the highest genetic identity value was obtained between the Red Sokoto and Sahel breeds. The Nigerian, Algerian, and Turkish goat breeds are categorized separately from other breeds based on the FCA test axes; however, the FCA graph indicates that the Algerian and Turkish breeds exhibit a degree of admixture (Fig. 1).

Fig. 2 illustrates the structure analysis results, revealing various genetic clustering scenarios (K = 2–10) within the studied populations. This visual narrative reveals the complex patterns of population stratification and provides a detailed understanding of genomic subdivisions within the analyzed dataset.

Table 7 presents estimates, including posterior probabilities ([Ln Pr(X|K)]) for various clustering numbers (K) and highlighting \mathrm{\Delta }K values.

\mathrm{\Delta }K values were obtained from various clustering scenarios according to Evanno et al. [26]. The genetic distance dendrogram and the FCA graph both reveal a triple genetic landscape. The \mathrm{\Delta }K values indicate three distinct genetic profiles in the studied breeds.

4. Conclusion

This study used twelve microsatellite markers to explore the genetic makeup of goat populations in Algeria, Türkiye, and Nigeria. The results reveal a rich genetic landscape with high diversity and distinctiveness among the breeds. This study highlights the importance of genetic variation, particularly in heterozygote deficiency, which requires careful breeding strategies and population management. Population structure analyses, such as the factorial correspondence analysis and structure analysis, reveal clear genetic clusters and the impact of historical influences, trade networks, and environmental adaptations on the genetic makeup of these goat populations. The historical role of the Mediterranean Sea as a transportation route has significantly impacted the genetic diversity observed today. These findings have practical implications for conservation and breeding efforts, guiding targeted breeding strategies to preserve and enhance desirable traits within each breed. The heterozygote deficiency in some breeds requires careful management to mitigate potential impacts on genetic diversity. This study also contributes valuable knowledge for the sustainable management of these vital livestock genetic resources, particularly in the face of climate change and market dynamics. Moreover, this study enhances our understanding of goat genetics and provides a foundation for informed decision-making in conserving and utilizing these diverse and resilient livestock breeds.

Availability of Data and Materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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