West African countries are characterized in general by high variability in farm animal genetic resources (Molina-Flores et al., 2020). Concerning goat species, Benin’s neighboring countries have remarkably diversified indigenous goat breeds, defined by different ecotypes of West African Dwarf goats (WAD, also named Djallonké goats) found in fifteen West and Central African countries including Togo, Burkina Faso, and Nigeria (Wilson, 1991; Awobajo et al., 2015); Red Sokoto goats in Niger and Nigeria, and a large population of Sahelian goat breeds in Mali, Niger, Burkina Faso and Nigeria (Wilson, 1991). In addition, some exotic goat breeds are also introduced into these countries such as the Boer and Kalahari goats imported into Niger (FAO, 2007). This pool of goat breeds from Benin’s neighboring countries certainly influences the genetic diversity of the indigenous Beninese goat population whose genetic diversity has not been documented to date, unlike that of other African countries like Nigeria (Awobajo et al., 2015; Ojo et al., 2018), Ghana (Ofori et al., 2021), and Burkina Faso (Traoré et al., 2009). Indeed, the previous characterization studies conducted on this species in Benin have been limited to documenting the existing between- and within-species morphological variability (Dossa et al., 2007; Kouato et al., 2021; Whannou et al., 2021) and, habitat suitability modeling of the goat population of Benin under climate change scenarios (Whannou et al., 2022). Thus, there remains a need to determine the genetic diversity within and among this indigenous goat population at the molecular level to optimize their management. Such a study is a response to the Food and Agriculture Organization of the United Nations (FAO, 2012) exhortation to document both phenotypic and molecular diversity of animal genetic resources for better knowledge and definition of policies for their sustainable management. Regarding molecular genetic characterization, different tools, including microsatellite markers, and single-nucleotide polymorphism (SNP) chips have been developed with advances in technology for a better exploration or analysis of the genome. However, although SNPs are highly informative and more nowadays recommended for population genetics studies, their accessibility remains limited, especially in developing countries due to the high costs associated with using this high-definition technology (e.g., cost of chips, high-level infrastructure, and equipment required, and continuous energy power) (Laoun et al., 2020). In contrast, microsatellite markers are less expensive, especially if they are multiplexed, and have demonstrated worldwide their ability to assess diversity in animal population genetics (Ben Sassi-Zaidy et al., 2022). This amply justifies their use in numerous genetic diversity studies conducted in the last years on different species including cattle (Msanga et al., 2012; Gororo et al., 2018; Demir and Balcioğlu, 2019), pigs (Djimènou et al., 2021) and small ruminants (Missohou et al., 2011; Mekuriaw, 2016; Ravimurugan, 2017; Ojo et al., 2018; Dayo et al., 2022). Therefore, microsatellite markers are still highly useful for preliminary studies of the diversity of populations that have never been characterized using molecular tools (Laoun et al., 2020). In such a context, the genetic diversity of the indigenous Beninese goat population could be better documented using microsatellite markers as only phenotype-related information has been reported so far. On the one hand, it should be noted that a review of previous knowledge on the diversity of goat breeds present in Benin has reported the cohabitation of a multitude of West African local breeds such as WAD/Djallonké, Red Sokoto or Maradi, Sahelian (Hounzangbe-Adode et al., 2011; Molina-Flores et al., 2020), and exotic breeds like Alpine and Saanen goats (Hounzangbe-Adode et al., 2011). On the other hand, the most recent study (Whannou et al., 2022) that addressed the phenotypic diversity of the local Beninese goat population revealed the existence of high diversity within and among this indigenous goat population. Moreover, two major groups of goats have been reported within the three vegetation zones (i.e., one group of small individuals mainly in the Guinean-Congolese zone in the South and another group of relatively large goats from the Guinean-Sudanese zone in central Benin to the Sudanese zone in northern Benin).

Hence, this study investigated the genetic diversity and structure of the indigenous goat population in Benin using microsatellite markers to allow a clear identification of breed groups or genetic types and to confirm or refute the phenotypic diversity aforementioned.

This study constitutes the first one performed on the genetic diversity within the goat population of Benin. All the microsatellite loci used in this study were informative because they recorded at least 4 alleles (Barker et al., 2001) and most of them obtained high PIC values (PIC>0.50) (Arora et al., 2010; Botstein et al., 1980). Regarding the genetic diversity indices estimated, the mean values of Na (11.25), He (0.69), Ho (0.66), and PIC (0.66) recorded in this study revealed a high genetic diversity within the goat population of Benin (Kumar et al., 2009; Jawasreh et al., 2018; Mihailova, 2021). The average Ho (0.66) obtained is higher than that reported for the Ardi goat from the Saudi Arabia Kingdom (0.55) (Aljumaah et al., 2012), the Nigerian West African Dwarf goat (0.60) (Awobajo et al., 2015), and the Nigerian indigenous goat population (0.61) (Ojo et al., 2018). However, it is lower than the mean Ho value (0.84) reported for four Algerian goat breeds (Tefiel et al., 2018). The mean value of PIC (0.66) obtained in this study was lower than values reported in Indian goat breeds (0.77) (Dixit et al., 2012), in Nigerian West African Dwarf goats (0.69) (Awobajo et al., 2015), and Algerian goat breeds (0.93) (Tefiel et al., 2018). Although the Beninese goat population appeared diverse, the low F_IS (0.035) and F_IT (0.047) values recorded suggest some inbreeding events in this population (Tolone et al., 2012). Indeed, a positive F_IS value is generally considered as an indicator of heterozygosity deficit compared with Hardy-Weinberg equilibrium (Tefiel et al., 2018). Nevertheless, obtained values of F_IS and F_IT were lower than those (F_IS = 0.090, F_IT = 0.180) reported by Awobajo et al. (2015) (F_IS = 0.105, F_IT = 0.129) by Ojo et al. (2018) (F_IS = 0.035, F_IT = 0.063) by Traoré et al. (2009) in Burkina Faso goats, and to (F_IS = 0.057, F_IT = 0.102) reported by Tefiel et al. (2018) in the four Algerian goat breeds. This highlights the diversity of indigenous goat populations in Africa, and probably reflects the difference in the management of goat resources from one country to another.

The mean value of F_ST (0.012) obtained in this study was inferior to 0.05, indicating a very low genetic differentiation in the goat population of Benin. The coefficient of gene differentiation (G_ST) obtained with a mean value of 0.012 confirmed the limited genetic differentiation between vegetation zones. The result of the AMOVA applied to the dataset using vegetation zones as a like-effect of variation also confirmed this limited genetic differentiation. Therefore, the genetic differentiation of the Beninese goat population is intraspecific diversity, thus mainly due to the diversity between individuals within vegetation zones. The lack of genetic differentiation observed between vegetation zones is probably due to different factors including the proximity of production areas, similar extensive breeding practices in the different vegetation zones, but especially the gene flow that occurred between individuals of the main goat groups in the past. A similar finding has been reported by Tolone et al. (2012). The proximity of the breeding areas certainly favors the continuous exchange of breeds through the market system and other mechanisms developed by the different actors of the goat value chain, such as gifts. Moreover, the extensive breeding practices developed by goat breeders (notably the non-control of reproduction in most breeding areas) in all vegetation zones are probably also levers of diversity in the Beninese goat population and therefore favor the low genetic differentiation observed. In comparison to other studies, the average F_ST over loci (0.012) estimated in the Beninese goat population is lower than the value obtained in goat populations of Burkina Faso (0.035) (Traoré et al., 2009), Nigeria (0.10) (Awobajo et al., 2015) and (0.030) (Ojo et al., 2018), and Algeria (0.048) (Tefiel et al., 2018). Therefore, the indigenous goat population of Benin is less differentiated than those of other African countries.

The high mean values of Na, He, Ho, and F_IS obtained in GSZ and SZ goat subpopulations when measuring the genetic diversity existing within and among the vegetation zones, underline that the goats of these vegetation zones are very diverse, but some individuals from these zones are also inbred. In a similar study, Tolone et al. (2012) also recorded high He and Na values within subpopulations or breed groups, with high F_IS, and concluded a high genetic diversity within these subpopulations or breed groups. Furthermore, the highest values of pairwise F_ST and Nei’s genetic distance recorded between GCZ and SZ confirm that goats from these two vegetation zones are genetically different. In contrast, the lowest values of F_ST and Nei’s genetic distance obtained between GSZ and SZ suggest that goats from these zones are genetically close. However, some goats from GSZ would be also genetically closer to GCZ individuals, and their genetic proximity seems similar to that observed between GSZ and SZ, as shown by their near similarity between the indices of genetic differentiation and the genetic distance of Nei’s (Table 3). These results suggest that GSZ is an intermediate subpopulation of goats with a high gene flow. In a recent study of phenotypic diversity, Whannou et al. (2022) stated that GCZ grouped mainly small-size goats, namely, Djallonké, whereas large and intermediate goat types (i.e., Sahelian and crossbreed goats) predominated in SZ and GSZ. Moreover, these authors argued that GSZ may be considered an interbreeding zone. Therefore, the current genetic findings agree to some extent with previous results on phenotypic diversity.

The investigation of the genetic structure of the Beninese goat population using three different methods (STRUCTURE, SOM, and DAPC) confirmed the aforementioned results. First, the STRUCTURE results confirmed the widely accepted existence of two existing ancestral populations of goats in Benin (Meyer, 2002; Dossa et al., 2007; Hounzangbé-Adote et al., 2011) with gene flows between these populations, as suggested by the most probable value of K = 2 groups and proportions of individuals’ assignment. Moreover, the STRUCTURE results showed that goats in GCZ and SZ were genetically more distant than that observed between GSZ and SZ. Indeed, GSZ grouped the two distinct goat genotypes. Second, SOM results supported the lower genetic differentiation existing between individuals from vegetation zones and suggested a distinction between goats from GCZ and those from SZ, but the closeness of individuals from GSZ to those of the two other distinct zones. Finally, the DAPC results that reveal the existence of four goat genetic clusters (C) in Benin according to both vegetation and phytogeographic zones, confirm the geographic distribution of goat types in Benin as previously defined based on morphology (Whannou et al., 2022). These results also show that the two main ancestral goat populations are highly crossed, with a critical purity degree of only 70% for the purest subpopulations (i.e., C1, C3, and C4) (Table 5). Considering these results, there is a risk of losing part of genetic diversity if no breeding policy is defined to maintain some pure individuals of the main goat types. Moreover, there are no reliable updated data on the population size of the different goat genetic types identified due to the lack of organization in the goat farming sector in Benin. As a result, the sustainability of goat resources in Benin would be threatened if crossbreeding practices continue anarchically on farms without measures being taken to conserve the predominant genetic types. New management policies for goat keeping in Benin are therefore essential to ensure their sustainable use and to face the challenges of current and future climate and societal changes. To achieve this, an inventory of goat genetic resources should be organized at the national level together with the elicitation of goat farmers’ preferences for goat breeds and production objectives and will allow the establishment of guidelines for maintaining the existing diversity within the goat population in Benin.

This study provides valuable data on the genetic diversity and structure of the indigenous goat population of Benin and fairly confirms the phenotypic diversity observed within this population. Indeed, the results highlighted the presence of two ancestral genetic groups of goats in Benin with a high level of interbreeding, particularly in GSZ. However, although the indigenous goat population of Benin is highly diverse, the pressure of poorly planned and controlled crossbreeding might threaten the sustainability of goat farming systems. With the current pressure of climate and societal changes, any threat to local goat resources should be prevented more than ever. Measures for the conservation and sustainable management of indigenous goat resources need to be taken involving the farmers who are the owners of these animal genetic resources. For instance, sensitization and training sessions could be organized to raise the awareness of farmers on the need to maintain farm animal genetic resources, to show them the importance and necessity of monitoring and organizing reproduction in their herds, and to remind them or strengthen their knowledge of the qualities of local breeds such as the trypanotolerance and prolificacy of the Djallonké goats with a view to establishing purebred breeding. In addition, the Beninese government should, in the long term, introduce breeding laws and policies to control the movement of animals both at the borders and within Beninese localities. Finally, conservation programs for the local breeds should be urgently set up.