Genetic diversity of some Ghanaian pigs based on microsatellite markers

R A Ayizanga^1,2, B B Kayang¹, K Adomako², C Adenyo^3,4, M Inoue-Murayama⁴ and L Asamoah⁵

¹ Department of Animal Science, University of Ghana, P. O. Box LG 226, Legon - Accra, Ghana
rayizanaga@ug.edu.gh   or   raphayi2003@yahoo.com
² Department of Animal Science, Kwame Nkrumah University of Science and Technology, University Post Office, Kumasi, Ghana
³ Livestock and Poultry Research Centre, University of Ghana, P. O. Box LG 38, Legon – Accra, Ghana
⁴ Wildlife Research Center, Kyoto University, Sakyo, Kyoto 606 – 8203, Japan
⁵ International Institute of Tropical Agriculture, P. O. Box TL6, Tamale, Ghana

Abstract

A knowledge of the level of genetic diversity is very important in ensuring the sustainable utilisation of animal genetic resources. To this end, the genetic diversity of some local pigswas assessed by genotyping 86 unrelated pigs in four regions of Ghana namely Northern (Tingoli = 9), Upper West (Papu = 31 and Babile = 32) and Upper East (Gia = 14) using 12 microsatellite markers.The number of alleles (N_a), number of effective alleles (N_e), observed heterozygosity (H_o), expected heterozygosity (H_e) and inbreeding coefficient (F_IS) were used to assess the level of genetic differentiation among the five populations in this study.

All loci studied were polymorphic and the mean number of alleles ranged from 4.58 (Yorkshire) to 10.58 (Papu) with an overall average of 7.65 alleles. At all the 12 loci studied, inbreeding coefficient (F_IS) deviated significantly from zero with a mean of 0.32. When the Nei’s standard genetic distance based on the proportions of shared alleles was used to construct a neighbour joining tree, pigs from the different communities sampled in the Upper West region emerged with the highest bootstrap value of 90%. Generally, the sampled pigs represent distinct populations with a moderate amount (12%) of genetic differentiation but considerable amount of inbreeding (29%) has taken place within these populations over the years. This is the first report of the genetic diversity of Ghanaian local pigs using microsatellite markers.

Keywords: Ashanti Black pig, genetic differentiation, inbreeding, sustainable utilisation

Introduction

The role of indigenous domestic animal genetic resources in safeguarding human life and wellbeing can be felt in one way or the other by millions of the earth’s inhabitants. According to the Food and Agriculture Organisation (FAO) of the United Nations (UN),“animal genetic resources (AnGR) for food and agriculture are an essential component of the biological basis for world food security. Hundreds of millions of poor rural people keep livestock and often rely on their animals to provide multiple products and services. In harsh environments where crops will not flourish, livestock keeping is often the main or only livelihood option available. Livestock currently contribute about 30 percent of agricultural gross domestic product in developing countries, with a projected increase to about 40 percent by 2030”(FAO 2011).

It is also worth stating that the world now believes that climate change is real and reckoned to be the most serious environmental challenge humanity faces today. In the face of climate change and its consequent threats to man’s continued existence on earth, the role of indigenous domestic animal genetic resources in safeguarding human life and wellbeing becomes even more evident. Indigenous domestic animal genetic resources are believed to be the most adapted to their respective natural and human induced production environment. Therefore, to state that indigenous animal genetic resources will evolve over time to withstand the effects of climate change is not farfetched.

The local pig of Ghana, often called the Ashanti Black pig or Ashanti Dwarf pig (Jollans 1959) is an adapted and very valuable breed considering the prevailing climatic and management conditions. It is not very fecund, have slow growth rates, smaller matured size and are considered by some authorities (Epstein 1971 as cited by Payne 1990) to be of the Iberian ancestry but a very hardy breed, very well adapted to feed and/or water shortage and trypano tolerant (Jollans 1959). There is however dearth of information on the genetics and management of this breed. Therefore any effort towards the proper understanding of its utilisation and conservation will lead to a sustainable increase in small holder farm incomes and consequently raise the living standard of the poor segment of our society.

Fleischer et al (1995) stated that “the greatest threat to hardy local breeds of domesticated animals in Ghana is the indiscriminate crossbreeding with imported breeds particularly those of the LargeWhite, the Landrace and Hampshire, ostensibly to increase the production potential of the local breed”. Indiscriminate crossbreeding of indigenous breeds with exotic blood is not peculiar to Ghana alone. It has also been established that of the several hundred breeds of pigs in the world, many are in danger of extinction and others are threatened by inefficient use or loss due to crossbreeding (Nidup and Moran 2011). It is now common place knowledge that the world has evolved towards more of commerce than any other consideration. Driven by profit motive, preference for high yielding breeds of animals and/or crops has resulted unfortunately in the want on neglect of local breeds which adapt well to local conditions, particularly poor management systems and diseases/pests. The improvedexotic breeds of pigs are perceived by farmers to be fast growing, prolific and give better returns on investment, however, exotic breeds do perform poorly under tropical and sub-optimal conditions. Many pigfarmers in Ghana are not able to provide optimal conditions for the exotic breeds, but rather resort to indiscriminate crossbreeding with local breeds in order to make their animals more adaptable to tropical and sub-optimal conditions without taking cognisance of the genetic identityand potential of thelocal breed.

According to FAO (2012), information provided by genetic diversity studies is essential for planning the management of indigenous animal genetic resources at local, national, regional and global levels. Another opinion expressed is that the first step for the sustainable use of domestic animal genetic resources is gathering information about the genetic variability in the populations (Grigalinait et al 2003). To date, generally, not much scientific studies have been conducted at the molecular level of the local pig of Ghana and so very little is known about the genetic structure of the pig populations scattered all over Ghana. Furthermore, this is the first use of microsatellite markers for genetic diversity studies in the Ghanaian pig populations. Osei-Amponsahet al (2010) also conducted genetic diversity studies using microsatellite markers but their work was on forest and savannah chicken populations of Ghana. The closest study to the present genetic diversity study was conducted by Osei-Amponsahet al (2015) who worked on the origin and phylogenetic status of the local pig of Ghana but they relied on evidence from mitochondrial DNA analysis and the Y-chromosome haplotypes.

Microsatellite markers have become very useful and very reliable for assessing genetic diversity in populations of farm animals. Groenen et al (2003) cited Archibald et al (1995) and Rohrer et al (1994, 1996) as having stated that microsatellite markers are used based on their good quality, size, polymorphism and being widely distributed on the porcine genome. Luetkemeier et al (2010) in their study of the origin of some Asian pig breeds, reiterated the above stated attributes of microsatellite markers and added the absence of null alleles as one of the good characteristics of microsatellite markers that make them suitable for genetic diversity studies.

It still remains unclear whether or not the local pig populations, particularly in the three regions of northern Ghana represent genetically identical or genetically distinct populations. Whatever the case may be, it has been established that the genetic potential of such local breeds and planning for their sustainable utilisation requires a prior knowledge of their prevailing genetic diversity (Bordas et al 2004 as cited by Keambou et al 2014).

The FAO Global Plan of Action for Animal Genetic Resources also recognises that a good understanding of breed characteristics is necessary to guide decision making in livestock development and breeding programmes (FAO 2007). This study will also contribute towards Ghana fulfilling the first of 23 strategic priority areas of the FAO led Global Plan of Action which is devoted to characterisation, inventory and monitoring of trends and associated risks of indigenous animal genetic resources. The plan aims at combating the erosion of animal genetic diversity and using animal genetic resources sustainably.

The aim of this study therefore was to assess the genetic diversity of pig populations in Ghana with particular reference to the pig populations in the three regions of northern Ghana in order to clarify their phylogenetic relationships and to possibly identify genetically distinct populations for sustainable utilisation.

Materials and methods

Sample collection and DNA extraction

A total of 54 blood samples were obtained from randomly sampled local pigs at Tingoli in the Northern region, Papu in the Upper West region and Gia in the Upper East region. These communities were purposively sampled for the present study to coincide with the USAID/IITA research for development project intervention communities whereas all participating farmers were randomly sampled from the farmers on the research for development (R4D) platform. Only nine blood samples could be obtained from Tingoli because it is a Moslem dominated community and hence not many farmers keep pigs. In addition, blood samples were taken from 32 unrelated pigs at the national pig breeding station at Babile and seven DNA samples from the Yorkshire pig breed from the DNA repository of the Wildlife Research Center (WRC) of Kyoto University for use as a reference population. In order to minimise the probability of taking blood samples from related pigs, only one pig was sampled per farmer. Figure 1 is a map of Ghana depicting the sampling sites. Blood samples were taken from the jugular vein using sterile vacutainer needles into 1.5 ml vacutainer tubes containing EDTA as an anti-coagulant agent as prescribed by FAO guidelines for molecular genetic characterisation (FAO 2011). The blood samples were transported on ice using a vaccine carrier and stored at – 20°C until ready for DNA extraction.

Fig 1. Map of Ghana showing sampling sites. The sampling sites are indicated with the pig symbol

Genomic DNA was extracted using the QIAGEN®DN easy Blood Kit (QIAGEN, Valencia, CA, USA) according to the protocol provided by the manufacturer and stored at – 20°C until it was ready for subsequent laboratory analyses. The concentration and purity of all DNA samples was measured using a Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific) and stored at – 30°C until ready for use.

Microsatellite markers and genotyping

Polymerase chain reaction (PCR) was carried out with a multiplex of three primer pairs with each reaction volume of 5µl mixture comprising 20 ng of template DNA, 0.125µl of forward primer, 0.25 µl of reverse primer, 0.25 µl of M13 tag (FAM or HEX or NED) and 2.5 µl of multiplex PCR mastermix. The amplification protocol involved an initial denaturation of DNA and enzyme activation at 94°C for five minutes followed by 35 cycles of denaturation at 94°C for 30 seconds, primer annealing at temperatures varying between 55°C and 60°C for 45 seconds and extension at 72°C for 45 seconds. There was a second stage of eight cycles of denaturation at 94°C for 30 seconds, annealing at 53°C for 45 seconds and extension at 72°C for 45 seconds before a final round of extension at 72°C for ten minutes and the resulting PCR product stored at 10°C using the GeneAmp PCR System 9700 automated thermal cycler (Applied Biosystems). Subsequently, the PCR products were diluted 100 times with distilled water and electrophoresed on a 3130 xl Genetic Analyser (Applied Biosystems) and the sizes of the fragments were estimated using the GeneMapper computer programme (Applied Biosystems). Genotyping of all the samples was performed across all 12 loci.

The twelve microsatellites were selected from the list of microsatellite markers recommended by the International Society of Animal Genetics (ISAG)-Food and Agriculture Organisation (FAO) (http://www.fao.org/docrep/014/i2413e/i2413e00.htm) for evaluating genetic diversity in pigs as part oftheir global strategy for the sustainable management of animal genetic resources. The primers for the 12 microsatellite markers used in the present study were synthesised by Sigma-Aldrich Co. LLC, Tokyo, Japan.

Data analyses

Population genetic diversity indices such as the number of alleles per locus (Na), the number of effective alleles per locus (Ne), the observed heterozygosity (H_o), expected heterozygosity (H_e) and inbreeding coefficient (F_IS) were computed using the GenAlEx computer programme (Peakall and Smouse 2006, 2012). Genepop on the web (Rousset 2008; Raymond and Rousset 1995) was used to conduct the Hardy-Weinberg exact test following the Markov chain (MC) algorithm using 5000 iteration stepsand followed by 1000 batches of 5000 iterations per batchas per the Guo and Thompson (1992) procedure. The Bonferroni correction factor was applied to arrive at critical limits for making multiple comparisons at the 5% probability level. In order to investigate the extent of genetic differentiation between all pairs of populations in the present study, pairwise F_ST values were evaluated using GenAlEx (Peakall and Smouse 2006, 2012) to calculate pairwise distance values from inter individual genetic distances based on the proportion of alleles shared for two individuals averaged over all 12 loci.To evaluate the geometric relationships among the pig populations studied, a Principal Coordinate Analysis (PCA) was done using GenAlEx. For the exact phylogenetic relationships, genetic distances were computed between populations (Nei et al 1983) using Populations computer software (Langella 1999) and then visualised using TreeView (Page 2001). Bootstrap resampling of 1000 runs was performed to test the robustness of the phylogenetic tree.

Results

Genetic variation within populations

All loci studied were polymorphic. The mean number of alleles per locus (N_a) found for the 12 microsatellite markers in the four local pig populations and one reference population (Yorkshire) in the present study amounted to 7.65with a mean number of effective alleles per locus (N_e) of 4.18. The mean highest number of alleles of 10.0was obtained at the Sw72 while the least mean number of alleles recorded was 5.20 at the S0002 locus.

On statistical parameters pertaining to genetic differentiation, the three hierarchical measures of genetic diversity (F_IS, F_ST and F_IT), commonly called the F-statistics, among the pig populations sampled were estimated. A mean observed heterozygosity (H_o) of 0.467, expected heterozygosity (H_e) averaged 0.710 and a mean inbreeding coefficient (F_IS) of 0.320 was recorded among the 93 pigs sampled. Inbreeding coefficient (F_IS) ranged from – 0.090 (S0178) to 0.560 (Sw632 and Sw1067). At all the 12 loci studied, F_IS deviated significantly from zero. Fixation index (F_ST), a measure of the extent of genetic differentiation among subpopulations due to genetic drift averaged 0.120with a range of 0.04 (S0226) to 0.310 recorded at the S0155 locus. Overall fixation index (FIT) averaged 0.410and ranged between–0.040 at locus S0178 to as high as 0.610 at loci S0090 and Sw1067. A summary of the genetic diversity parameters of the microsatellite markers used are outlined in Table 1.

Inter population genetic diversity

To investigate the level of genetic differentiation between the pigs sampled from the various locations, genetic diversity indices were computed for these pig populations across all the 12 microsatellite markers. Table 2 shows the mean number of alleles (N_a), number of effective alleles (N_e), observed heterozygosity (H_o), expected heterozygosity (H_e) and inbreeding coefficient (F_IS) of all 12 microsatellite markers across all the five populations in this study. The mean number of alleles per population ranged from 4.58 for the Yorkshire population to 10.6 recorded for the pigs sampled from Papu with an overall mean of 7.65 alleles. The mean number of effective alleles recorded in this study amounted to 4.18 with a range of 3.54 (Yorkshire) to 5.06 (Papu). Observed heterozygosity (H_o) averaged 0.470 whilst for expected heterozygosity (H_e), a mean of 0.710 was obtained in this study. At all 12 loci studied, observed heterozygosity (H_o) fell short of expected heterozygosity (H_e) and the level of inbreeding (F_IS) within the four pig populations sampled from Ghana ranged from 32% (Papu) to as high as 43% (Gia) but no inbreeding was found in the Yorkshire population.

One of the genetic indices of interest in the present study was the number of private alleles. The number of private alleles recorded ranged from four in Yorkshire pigs to 29 for the pigs sampled from Papu in the Upper West region of Ghana. The observed mean heterozygosity for the sampled pig populations ranged from 0.390 (Gia) to 0.560 (Yorkshire) whereas the expected mean heterozygosity ranged from 0.610 (Yorkshire) to 0.770 (Papu).

Pairwise comparisons and principal coordinate analysis (PCA)

Results from the pairwise comparison of all the populations studied based on the proportion of common alleles averaged over all 12 loci revealed that among the local pigs, the highest pairwise F_ST of 6% was recorded between the pigs at Papu and those at Tingoli. The same F_ST  value of 6% was obtained for Papu/Gia and Tingoli/Gia whilst the least pairwise population differentiation value of 4% was recorded for both between Papu/Babile pigs and Babile/Tingoli.

The assignment of individual pigs to populations by the PCA plot showed poor clustering of individuals. The clusters that stood out clearly are Gia and Papu pigs. The pigs from Babile and Tingoli were however seen quite dispersed in all the coordinates. The first three axis of the PCA plot cumulatively accounted for 57.67% of all the variations in the pig populations studied. Figure 2 is an illustration of the outcome of the PCA conducted among the five pig populations in this study.

Figure 2. A scatter plot of principal coordinate analyses of some pig populations based on 12 microsatellite markers

Phylogenetic relationships between populations

In order to visualise the exact phylogenetic relationships between the pigs sampled from the various communities, a neighbour joining tree was constructed based on the Nei’s standard genetic distances calculated between populations and using the Yorkshire pigs as an outgroup to root the tree. Consistent with the PCA analysis, the dendrogram revealed a tight relationship between the pigs sampled from the Upper West region with the highest bootstrap value of 90% (Figure 3). The dendrogram also separates all the pigs sampled from the Upper West and Northern regions from those sampled from the Upper East region of Ghana.

Figure 3. Neighbour joining phylogenetic tree of some Ghanaian pigs using 12 microsatellites. Number in the branch nodes indicates the percentage occurrence in 1000 bootstrap resampling and the branch lengths are proportional to genetic distances

Discussion

Genetic variation within populations

The mean number of alleles per locus of 7.65 recorded in the present study is more than twice the mean number of alleles of 2.50 recorded for the black Slavonian pig (Bradic et al 2007), indicating more genetic diversity in the local pigs of Ghana but falls within mean 3.20 – 5.80 microsatellite alleles recorded in other European breeds of pigs (Martinez et al 2000; Laval et al 2000), 4.30 – 6.10 for some Chinese breeds (Fan et al 2003; Li et al 2000) but falls short of 7.00 – 7.70 reported by Behlet al (2002) for two Indian pig breeds. This indicates that there is nearly as much genetic variability in Chinese pigs as in the local pigs of Ghana but much more genetic variability is recorded in the Indian pig breeds as compared to the Ghanaian and Chinese breeds. However, differences in the reported number of alleles and other genetic diversity parameters may be caused by differences in the types of microsatellites used since some microsatellites are highly polymorphic whilst others exhibit less polymorphism (San Cristobal et al 2003). Factors such as the level of inbreeding, population size, the history or origin of the breeding population, the level of selection pressure and the rate of mutation and husbandry practices affect the genetic diversity of populations.

There was a significant level of inbreeding recorded at all loci studied. At S0155 and S0178, excess heterozygosity was recorded whilst at the remaining ten loci, observed heterozygosity fell short of expected heterozygosity. This indicates some amount of inbreeding as a result of the mating of individuals (sometimes accidentally) that are more closely related than the average in the population. Excess heterozygosity can be due to deliberate management interventions aimed at reducing inbreeding as sometimes implemented in small populations (San Cristobal et al 2003). The trend noticed at S0155 and S0178) indicates an excess of homozygosity which may arise at any particular locus from technical artefacts such as the presence of null alleles since the expected heterozygotes for the null alleles appear as false homozygotes (San Cristobal et al 2003). Ollivier (2009) made similar suggestions when he cited Chakraborty et al (1992) who reported occasional failure of amplification leading to null alleles that tend to enhance spurious heterozygote deficits as a known difficulty with microsatellite markers. Observed heterozygosity values obtained in the present study were generally higher as compared to values reported by Bradic et al (2007) for the black Slavonian pig but lower than that reported by Shu-Lin et al (2003) for some Chinese pig breeds and Nidup and Moran (2011) for European, Asian and Latin American pig breeds. Luetkemeier et al (2010) also reported higher observed heterozygosity values in their study of some Asian pig breeds. It is likely that the Ghanaian breeds studied have larger effective population sizes as compared to the black Slavonian pig which is reported to be bred in small numbers in extensive production systems and thus represented by smaller populations. As a matter of fact, only 46 sows and 6 boars were reportedly registered in 10 farms in Croatia in 1996 (Croatian Livestock Centre 2005) as cited by Bradic et al (2007).

Pairwise comparisons and principal coordinate analysis

For the local pigs, the highest pairwise F_ST of 6% was recorded between the pigs at Papu and those at Tingoli, same F_ST value was obtained for Papu/Gia and Tingoli/Gia whilst the least pairwise population differentiation value of 4% was recorded for both between Papu/Babile pigs and Babile/Tingoli. The pigs from Babile can be found in all coordinates in the PCA. This is expected because the station operates an open nucleus breeding scheme and also sells some breeders to farmers. It is interesting to note that the Yorkshire recorded the highestpairwise F_ST (as expected) when compared with all the other populations since the Yorkshireis an exotic breed. A mean F_ST of 0.12 indicates that 12% of total genetic variability occurs among the subpopulations and this is indicative of moderate genetic differentiation between the pig populations sampled as per guidelines proposed by Wright (1978) (http://www.library.auckland.ac.nz/subject-guides/bio/pdfs/733Pop-g-stats2.pdf). This is comparable with results of Nidup and Moran (2011) who reported a significant F_ST value of 27% among European pigs.  The mean overall fixation index (F_IT) of 41% recorded in the present study shows a great deal of genetic differentiation in individual animals relative to the total population. This index combines the genetic effects of non-random mating within populations together with the effects of genetic drift among populations.

Phylogenetic relationships between populations

The neighbour joining tree established in this study showed that the pigs from Babile/Tingoli and Papuhad the highest bootstrap value of 90% followed by a value of 72% for Babile and Tingolipigs. These bootstrap values show significant relationships among the pig populations in this study considering the fact that Shu-Lin et al (2003) reported that the accuracy of the dendrogram obtained from genetic distances is only confirmed for nodes with bootstrap values above 70% and that nodes with bootstrap values below 50% were not significant. Nevertheless, the dendrogram established a clear trend of relationship as all the populations from the Upper West region were separated from the populations in the Northern, Upper East and the Greater Accra regions. The phylogenetic relationship between the Babile and Tingoli pigs established in this study confirms the fact that some pigs from Babile were introduced to Tingoli, a Moslem dominated community (Mr. Benjamin Alenyorege, Former Manager, Babile pig breeding station, personal communication).

The populations generally exhibit a close genetic relationship which also indicates the possibility of originating from a common ancestor. An examination of the phenotypic characteristics of the populations studied indicates similarities such as mature size, generally black body colour, prolonged snouts and so on. It has been established that genetic distances may be used for purposes of clustering of populations or for studying their evolutionary relationship (Nei 1987). Nei (1987) also indicated that when dealing with breeds of farm animals, the interpretation of trees in terms of phylogeny can be misleading. If at all,there is very little selection pressure in the pigs kept at the village level in Ghana, besides, most farmers resort to obtaining starter stocks from neighbours and others tend to use same boars for crossing their gilts/sows and therefore there is considerable admixing of the pig populations in the villages. Hence the observed relatedness among the pigs is not strange.

Conclusions

• We firmly believe that having used the ISAG-FAO recommended microsatellites for pig diversity studies, the results of this study constitute a fairly accurate report on the genetic variation and the relationships between the sampled local pig populations of Ghana. Consequently, within the range of experimental error, it can be concluded that the pig populations found in the Upper West, Upper East and Northern regions of Ghana represent distinct populations with a moderate (12%) amount of genetic diversity between them with considerable amount of inbreeding (29%) within these populations. However, with the fast advances in molecular genetic tools, we concede that the use of microsatellite markers has become outdated and less accurate as a method of measuring genetic diversity. Where possible, more modern molecular genetic methods such as the use of SNPs will produce more accurate results.

Acknowledgements

Special gratitude is due to the University of Ghana for funding the major part of this study. We also acknowledge support from the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) grant (number 25290082 to MI-M) for science research, the A.G. Leventis Foundation, the USAID funded Africa RISING project led by the International Institute for Tropical Agriculture (IITA) and also express gratitude to the Manager (Mr. Ali Martin) and Staff (Messrs William Pollu-Baare, Sylvio Depaalo, Christopher Nwinzie and Richard Vuo) of the Babile Pig Breeding Station for granting us access to their records and pigs. Finally, we recognise the support of all the farmers who willingly answered our numerous questions and granted us free access to their pigs for blood sampling.

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Received 2 December 2015; Accepted 8 January 2016; Published 1 February 2016

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