Livestock Research for Rural Development 31 (4) 2019 Guide for preparation of papers LRRD Newsletter

Citation of this paper

Genetic differentiation and population structure of four Mozambican indigenous cattle populations

M A Madilindi1,2, C B Banga2, E Bhebhe1, Y P Sanarana2, K S Nxumalo2, M G Taela3 and N O Mapholi4

1 Department of Animal Science, University of Venda, Private Bag X5050, Thohoyandou, 0950, South Africa
matomemadilindi@gmail.com
2 ARC-Animal Production, Private Bag X2, Irene, 0062, South Africa
3 Directorate of Animal Science, Agrarian Research Institute of Mozambique, Av. Namaacha Km 11.5 P O Box 1410, Maputo, Mozambique
4 Department of Life and Consumer Sciences, University of South Africa, Private Bag X6, Florida, 1710, South Africa

Abstract

Knowledge of genetic diversity and population structure among livestock populations plays an important role in the design of genetic improvement programmes, as well as sustainable utilization and conservation of genetic resources. Genetic differentiation and population structure among four Mozambican indigenous cattle populations were investigated using 25 bovine-specific microsatellite markers, recommended for genetic diversity studies by the Food and Agriculture Organization. The analysis of unrelated autosomal DNA was performed on 120 animals (Angone n=30, Bovine de Tete n=30, Landim n=30 and Namaacha Nguni n=30), which presented sufficient genetic diversity across all populations.

Most microsatellites showed high levels of polymorphism, with an overall PIC mean of 0.665. A total of 255 alleles were detected, ranging from 6 to 20 alleles per locus. Estimates of mean number of alleles, and observed and expected heterozygosity were 6.92 ± 0.20, 0.68 ± 0.02 and 0.71 ± 0.01, respectively. Global F-statistics FIT, FIS, and FST had mean values of 0.111 ± 0.021, 0.027 ± 0.020, and 0.086 ± 0.013, respectively. Genetic differentiation among the populations accounted for 8.02% of total genetic variability. Negative (-0.025 ± 0.029) to low positive (0.073 ± 0.050) levels of inbreeding were observed within the four populations. Genetic distance, as PCoA and FCA revealed a close relationship between the Bovine de Tete and Landim as opposed to the Angone and Namaacha Nguni. STRUCTURE analysis assigned the four Mozambican populations independently; however, Bovine de Tete and Landim showed relatively higher levels of admixture with each other than Angone and Namaacha Nguni. It can be concluded that Mozambican indigenous cattle populations have a high level of genetic diversity; and Bovine de Tete and Landim are genetically closer than the Angone and Namaacha Nguni. These results may be useful for determining current and future breeding programmes, management and conservation strategies for Mozambican indigenous animal genetic resources.

Keywords: animal genetic resources, conservation, genetic variation, inbreeding, microsatellite markers


Introduction

The agriculture sector in Mozambique is dominated by smallholders who farm in a risky environment that is vulnerable to weather variability, climate threats such as droughts, floods and cyclones, and climate change. To cope with these threats, farmers have been taking up various low-input and cost-effective Climate-Smart Agriculture measures, such as small livestock rearing, crop residue management, intercropping and animal waste management. In harsh environments, where crops will not flourish, livestock keeping is often the main or only livelihood option. Livestock production plays a significant role in the inclusive agricultural production and livelihood system of most smallholder farming households in Southern African countries, including Mozambique (Assan 2012; Nyamushamba et al 2017). Mozambican indigenous cattle are beneficial resource to the human population, as they supply food in the form of meat and milk, income from sale of live animals and their products, manure for soil fertility improvement, and transport and draft power (Rege and Tawah 1999; Morgado 2000).

Historically, humped cattle breeds of Southern Africa were categorized into Sanga (cervico-thoracic hump) and Zebu (thoracic hump) types (Epstein 1971; Marshall 2000). Four indigenous cattle populations exist in Mozambique, namely the Angone, Bovine de Tete, Landim and Namaacha Nguni. Morphologically, the Angone is classified as a Zebu type, while the Landim is categorized as a Sanga type (Epstein 1971). The Bovino de Tete has been commonly categorized as a Sanga type but its origin is uncertain. Decades ago it was reported that Bovino de Tete was derived from crossbreeding between the Landim and the Angone breeds (Rege and Tawah 1999); however, it has also been suggested that Bovino de Tete was derived from the Mashona breed (Sanga type), which inhabits the border of Zimbabwe with Mozambique (Morgado 2000). Namaacha Nguni is a Nguni ecotype from KwaZulu-Natal province, South Africa, that belongs to the Sanga class.

Mozambican indigenous cattle are adapted to the harsh local environmental conditions, characterized by poor quality grazing, a need to walk long distances, parasite infestation and challenges of tick-borne diseases (Mapiye et al 2007; Ramsay 2010; Matjuda et al 2014; Nyamushamba et al 2017). Such adaptation is of significance to the poorly resourced local farmers who cannot afford the high production inputs required by exotic cattle breeds. However, indiscriminate crossbreeding is resulting in the replacement and dilution of locally adapted breeds with the exotic ones (Scholtz and Ramsay 2007). These indigenous bovines are thus under threat and may become extinct if their conservation is not prioritized. Additionally, it has been reported that a huge loss of Mozambican indigenous animals occurred between 1987 and 1992 during the countrywide civil war (Maciel et al 2013). After the civil war, Mozambique embarked on a Livestock Restocking Programme, which involved importing indigenous cattle breeds from neighbouring countries, especially South Africa, to re-establish the national cattle populations and industry. In 1996, Nguni cattle were re-introduced into Mozambique, to establish an “ ex-situ” conservation programme and increase cattle numbers, in order to meet the national demands for indigenous cattle and their products (Hanks and Pereira 1998; Maciel et al 2013).

A major requirement for formulating and implementing a sound conservation programme is information on the genetic structure of the available populations (FAO 2007; Sharma et al 2013). Previous studies on the genetic diversity of Mozambican indigenous cattle have been limited to only three populations (Angone, Bovine de Tete and Landim) (Kotze et al 2000; Bessa et al 2009). The Namaacha Nguni has, however, not been studied at the genetic level; hence necessitated the need to assess the genetic diversity of all existing Mozambican indigenous cattle. Molecular technologies allow the detection of variation or polymorphism among individuals in a population for specific regions of DNA; thus, they enhance an understanding of the genetic basis of biodiversity (Baumung et al 2004; FAO 2007; Sulandari et al 2008). Microsatellite markers has been quite useful in the past to study genetic diversity, calculation of genetic distance, detection of bottlenecks and admixture because of their high degree of polymorphism, random distribution across the genome, codominance and neutrality with respect to selection (FAO 2007; Putman and Carbone 2014). Their effectiveness has been demonstrated in numerous genetic diversity studies of farm animal genetic resources (e.g. Chaudhari et al 2009; Acosta et al 2013; Pham et al 2014; Mollah et al 2015; Sharma et al 2015; Sanarana et al 2016; Yilmaz et al 2016; Gororo et al 2018).

The current study was carried out to investigate the genetic differentiation and population structure among four Mozambican indigenous cattle populations using bovine microsatellite markers, recommended by both the Food and Agriculture Organization of the United Nations (FAO-UN) and the International Society of Animal Genetics (ISAG) advisory board (FAO 2011). This is important in developing an insight into the genetic diversity of the Mozambican indigenous cattle populations within the country, in order to develop strategies for their effective management at national level. It is anticipated that such knowledge will not only help to develop the value of the Mozambican indigenous cattle populations as an indigenous animal genetic resource, but will also contribute towards informed livestock production improvement strategies, to ensure national food security and enhance economic growth.


Materials and methods

A total of 120 unrelated animals were randomly selected from four different indigenous cattle populations, from research stations and stud herds in Mozambique. These comprised of Angone (n=30), Bovine de Tete (n=30), Landim (n=30) and Namaacha Nguni (n=30). In order to exploit genetic diversity within each population sampled, pedigree records of each farm were used to select unrelated individuals (against full and half sibs). Animal ethics approval to conduct the study was obtained from the Animal Ethics Committee (AEC) of the University of Venda, South Africa (SARDF/16/ANS/03/1404).

Hair samples with visible roots were collected from the end of the tail of each selected animal. Samples from different animals were kept in separate LIDCAT bags to prevent contamination. Each bag was sealed and labelled with detailed information (animal identity number, location, owner, sex and colour) of the particular animal. The samples were then taken to the laboratory (Animal Genetics Unit, Agricultural Research Council (ARC) – Animal Production (AP), Irene, Pretoria, South Africa). When samples arrived at the laboratory, they were stored at room temperature until the commencement of laboratory work.

Deoxyribonucleic acid (DNA) was extracted from hair samples using phenol-chloroform extraction, following the protocol of Sambrook et al (1989) as modified by the ARC-Animal Genetics laboratory. DNA concentration was measured using a 2000c Nanodrop Spectrophotometer machine (Thermo Fisher Scientific Inc., Waltham, MA, USA), following the manufacturer’s protocol. DNA extracts were amplified by the GeneAmp PCR System 9700 machine (Applied Biosystems, CA, USA), following the manufacturer’s protocol. Twenty-five microsatellite markers (Table 1) which are recommended for genetic diversity studies by the Food and Agriculture Organisation (FAO) and the International Society of Animal Genetics (ISAG) (FAO 2011) were used. The amplified DNA fragments were separated by capillary electrophoresis using an ABI PRISM 3130 Genetic Analyser (Applied Biosystems, Foster city, CA, USA), following the manufacturer’s protocol. Allele sizes of each microsatellite marker were analysed using GeneMapper version (ver.) 4.0 software (Applied Biosystems). The generated allele data (integer values in base-pairs) were used for statistical analyses.

Descriptive statistics such as total number of alleles (TNA), mean number of alleles (MNA), private alleles, observed heterozygosity (Ho) and expected heterozygosity (He) and polymorphic information content (PIC) values per marker and population were computed using the Microsatellite toolkit software (Park 2001) and GenAlex ver. 6.4.1 software (Peakall and Smouse 2006). The exact test for Hardy-Weinberg equilibrium (HWE) deviation for individual loci (p <0.05) was conducted using the GenePop ver. 4.0 software (Raymond and Rousset 1995).

The distribution of genetic variability within and among populations was determined by estimating the Wright’s F-statistics (FIS, F IT, and FST) and gene flow (Nm) per locus and across the studied populations using GenAlex ver. 6.4.1 software (Peakall and Smouse 2006). Analysis of molecular variance (AMOVA) on a locus-by-locus basis was performed using the Arlequin ver. 4.0 software (Excoffier et al 2005). Pairwise estimates of genetic differentiation (FST) across populations were determined using GenAlex ver. 6.4.1 software (Peakall and Smouse 2006).

Nei’s genetic distances (DA) (Nei 1987) across the studied populations were computed using GenAlex ver. 6.4.1 software (Peakall and Smouse 2006). A Principal Coordinate Analysis (PCoA) via multivariate analysis of microsatellite allele frequencies was performed using the GenAlex ver. 6.4.1 software (Peakall and Smouse 2006). Factorial Correspondence Analysis (FCA) was also computed using DARwin ver. 6 software (Perrier and Jacquemoud-Collet 2006).

The genetic structure and degree of admixture of the studied populations were investigated using the Bayesian clustering assignments procedure utilizing the STRUCTURE ver. 2.3.4 software (Prichard et al 2000). The software was set to run using the correlated allele frequencies and an admixture model. Simulations were performed using a burn-in period of 50,000 in length followed by 100,000 Markov Chain Monte Carlo (MCVM) iterations. Independent runs were performed for each K between 2 and 9 clusters, replicated 10 times for Mozambican indigenous cattle populations. The most probable K value which reasonably describes the substructure of the populations under study was determined from the log probability of the data (Ln Pr (X|K)) using the STRUCTURE Harvester software (Earl and von Holdt 2012) which implements Evanno’s method (Evanno et al 2005).


Results

Total number of alleles (TNA), heterozygosities and polymorphic information content (PIC) per locus are summarized in Table 1. A total of 255 alleles of 25 microsatellite markers were detected across the four Mozambican indigenous cattle populations. The TNA per locus ranged from 6 (BM1824 and INRA63) to 20 (TGLA53), with a mean of 10.20 alleles. The expected heterozygosity (He) varied from 0.553 (BM1824) to 0.835 (BM2113), with a mean of 0.714; whereas the observed heterozygosity (Ho) varied from 0.504 (CSSM60) to 0.795 (TGLA122), with a mean of 0.681. Most of the microsatellite markers showed high PIC values with an overall mean of 0.665 (>0.5), except BM1824 (0.496).

Table 1. Microsatellite loci, chromosomal location, allele range, total number of alleles per marker, heterozygosities
(expected and observed), polymorphic information content in four Mozambican indigenous cattle populations

Locus

Chr

Allele range

TNA

He

Ho

PIC

BM1818

23

256-272

9

0.801

0.763

0.758

BM1824

1

178-196

6

0.553

0.578

0.496

BM2113

2

121-145

10

0.835

0.828

0.799

CSRM60

10

92-120

12

0.654

0.725

0.604

CSSM66

14

179-205

12

0.615

0.504

0.581

ETH10

5

207-225

9

0.806

0.682

0.761

ETH225

9

138-162

10

0.799

0.773

0.755

HAUT27

26

138-156

8

0.765

0.650

0.713

ILSTS006

7

284-304

10

0.773

0.769

0.723

INRA23

3

184-218

10

0.784

0.817

0.742

TGLA122

21

131-183

16

0.771

0.795

0.722

TGLA126

20

113-129

7

0.790

0.649

0.745

TGLA227

18

73-101

13

0.725

0.775

0.677

ETH3

19

107-127

12

0.653

0.682

0.604

SPS115

15

244-260

8

0.581

0.511

0.522

TGLA53

16

154-190

20

0.760

0.770

0.730

HEL13

11

181-195

8

0.716

0.679

0.658

HEL9

8

146-170

12

0.740

0.362

0.700

ILSTS11

14

263-275

7

0.696

0.634

0.632

INRA32

11

163-189

8

0.731

0.595

0.674

INRA37

10

118-146

9

0.722

0.667

0.676

INRA5

12

136-150

9

0.585

0.676

0.536

INRA63

18

167-185

6

0.640

0.621

0.581

MM12

9

112-138

14

0.629

0.536

0.565

MM8

11

136-150

10

0.721

0.713

0.672

Mean

10.20

0.714

0.681

0.665

Chromosomal position (Chr); Total number of alleles per locus (TNA); Expected heterozygosity (He);
Observed heterozygosity (Ho); Polymorphic information content (PIC).

Results of Wright’s F-statistics indices for each of the 25 microsatellite markers within the four populations are presented in Table 2. The global heterozygote loss across populations (FIT) ranged from -0.018 (INRA23) to 0.404 (CSSM66) per locus, with an overall mean of 0.111 ± 0.021. The lowest and highest deficit of heterozygotes (FIS) values were -0.175 (INRA5) and 0.171 (INRA32) per locus respectively, with an overall mean of 0.027 ± 0.020. All markers contributed to genetic differentiation (FST) with the highest estimate being observed on ETH3 marker (0.245). The overall FST mean was 8.6%, indicating moderate genetic variation amongst the populations, with the remaining 91.4% representing variation among individuals within the populations. The overall estimate of mean number of migrants per generation (Nm) was 4.37 ± 0.725, signifying a moderate gene flow among the populations.

Table 2. Global F-statistics and estimates of Nm for each of 25 microsatellite markers in four Mozambican indigenous cattle populations

Locus

FIS

FIT

FST

Nm

BM1818

0.030

0.062

0.033

7.40

BM1824

-0.064

-0.002

0.058

4.07

BM2113

-0.009

0.036

0.044

5.46

CSRM60

-0.130

0.036

0.147

1.45

CSSM66

0.165

0.404

0.286

0.62

ETH10

0.136

0.188

0.060

3.90

ETH225

0.015

0.042

0.027

8.99

HAUT27

0.133

0.202

0.079

2.90

ILSTS006

-0.013

0.034

0.046

5.15

INRA23

-0.060

-0.018

0.039

6.15

TGLA122

-0.049

0.030

0.076

3.04

TGLA126

0.164

0.211

0.056

4.20

TGLA227

-0.089

0.021

0.100

2.25

ETH3

-0.063

0.102

0.155

1.36

SPS115

0.105

0.202

0.108

2.06

TGLA53

-0.030

0.020

0.049

4.86

HEL13

0.035

0.084

0.050

4.72

HEL9

0.130

0.236

0.121

1.81

ILSTS11

0.071

0.104

0.035

6.83

INRA32

0.171

0.240

0.084

2.74

INRA37

0.061

0.159

0.104

2.16

INRA5

-0.175

0.106

0.239

0.796

INRA63

0.014

0.027

0.013

18.3

MM12

0.132

0.216

0.097

2.33

MM8

-0.006

0.037

0.043

5.63

Mean

0.027

0.111

0.086

4.37

SE

0.020

0.021

0.013

0.725

Inbreeding coefficient of individuals within a subpopulation level (FIS); Inbreeding coefficient of individuals within the total population (FIT); The amount of genetic differentiation within the total population (FST); Mean number of migrants per generation (Nm); Standard error (SE).

A summary of descriptive statistics for genetic diversity parameters of the four Mozambican indigenous cattle populations is presented in Table 3. The mean number of alleles (MNA) per locus ranged from 6.28 ± 0.37 to 7.76 ± 0.39 in Angone and Bovine de Tete, respectively. The average expected heterozigosity (He) ranged from 0.69 ± 0.02 in Angone and 0.69 ± 0.03 in Namaacha Nguni to 0.77 ± 0.01 in Bovine de Tete. The average observed heterozigosity (Ho) ranged from 0.63 ± 0.04 to 0.71 ± 0.03, with the lowest value being found in the Angone and the highest in the Bovine de Tete population. The average Ho was lower than the He in Angone, Bovine de Tete and Landim, but not for Namaacha Nguni. Out of the twenty-five microsatellite markers used in this study, three loci in the Namaacha Nguni and six in the other populations (Angone, Bovine de Tete and Landim) significantly (p <0.05) deviated from Hardy-Weinberg equilibrium. A total of 67 private alleles across Mozambican indigenous cattle populations were found; where 16, 18, 21 and 12 private alleles were specifically detected within Angone, Bovine de Tete, Landim and Namaacha Nguni populations, respectively. The level of inbreeding (FIS) ranged from negative (-0.025 ± 0.029) in the Namaacha Nguni to low positive (0.073 ± 0.050) in the Angone, with an overall mean estimate of 0.033 ± 0.020.

Table 3. Descriptive statistics of genetic diversity parameters in four Mozambican indigenous cattle populations

Population

N

MNA (SE)

He (SE)

Ho (SE)

FIS (SE)

#HWE

Angone

30

6.28 (0.37)

0.69 (0.02)

0.63 (0.04)

0.073 (0.050)

6

Bovine de Tete

30

7.76 (0.39)

0.77 (0.01)

0.71 (0.03)

0.059 (0.034)

6

Landim

30

7.20 (0.45)

0.71 (0.02)

0.69 (0.04)

0.027 (0.045)

6

Namaacha Nguni

30

6.44 (0.35)

0.69 (0.03)

0.70 (0.03)

-0.025 (0.029)

3

Mean

6.92 (0.20)

0.71 (0.01)

0.68 (0.02)

0.033 (0.020)

5.25

Sample size (N); Mean number of alleles (MNA); Expected heterozygosity (He); Observed heterozygosity (Ho); Inbreeding coefficient (FIS); Number of Hardy-Weinberg equilibrium deviated loci at p <0.05 (#HWE); Standard error (SE).

Analysis of molecular variance (AMOVA) revealed that 8.02% of the total genetic variation resulted from differences among the populations, while 91.98% could be attributed to differences among individuals within the populations. The genetic differentiation (FST values) and Nei’s genetic distances (DA) pairwise estimates between Mozambican indigenous cattle populations are presented in Table 4. The FST values ranged from 0.038 (Landim-Bovine de Tete pair) to 0.095 (Namaacha Nguni-Angone pair). The Namaacha Nguni, when paired with Bovine de Tete or Landim, was genetically differentiated by a similar magnitude (0.052). The shortest DA was observed between the Landim and Bovine de Tete (0.178) followed by Bovine de Tete and Angone (0.219). The Namaacha Nguni was the most distant population, displaying the largest DA (0.540) when compared with the Angone population.

Table 4. Pairwise estimates of genetic differentiation (FST) and Nei’s genetic distances (DA) between Mozambican indigenous cattle populations. The FST estimates are above the diagonal, and Nei’sgenetic distances (DA) estimates are below diagonal

Angone

Bovine de Tete

Landim

Namaacha Nguni

Angone

-

0.045

0.073

0.095

Bovine de Tete

0.219

-

0.038

0.052

Landim

0.383

0.178

-

0.052

Namaacha Nguni

0.540

0.270

0.251

-

All FST values are significant at p < 0.05.

Principal Coordinates Analysis (PCoA) was perfomed to futher investigate genetic relationships among the four Mozambican indigenous cattle populations (Figure 1). The first three dimension of the PCoA revealed that PC1 (61.54%); PC2 (24.43%) and PC3 (14.03%) accounted for 100 % of the total variation. In the multivariate space defined by PCoA, Angone and Namaacha Nguni were relatively distant populations compared to Landim and Bovine de Tete. These results were further confirmed by Factorial Correspondence Analysis (Figure 2).

Figure 1. Principal coordinates analysis (PCoA) via covariance matrix with data standardization for four Mozambican indigenous cattle populations.

Factorial Correspondence Analysis (FCA) was carried out to further examine the genetic relationships among the four Mozambican indigenous cattle populations (Figure 2). FCA analysis showed very clear separation between Angone and Namaacha Nguni populations, suggesting a divergent relationship between them. The FCA results also showed an overlap of some individuals between Landim and Bovine de Tete populations, suggesting a genetic relationship between the two.

Figure 2. Factorial correspondence analysis (FCA) of individuals of four Mozambican indigenous cattle populations computed using DARwin software.

The proportion of membership of the four Mozambican indigenous cattle populations are presented in Table 5. A membership with a proportion of >90% was observed in each of the four Mozambican indigenous cattle populations, with some genetic materials from Landim (6.7%) and Bovine de Tete (5.5%) dispersed to cluster two and three, respectively.

Table 5. Proportion of membership of the analysed four Mozambican indigenous
cattle populations in each of the four clusters (K = 4)

Predefined populations

Inferred clusters

N

1

2

3

4

Angone

0.948

0.028

0.015

0.009

30

Bovine de Tete

0.027

0.903

0.055

0.015

30

Landim

0.009

0.067

0.912

0.012

30

Namaacha Nguni

0.009

0.040

0.024

0.927

30

A structure analysis using a Bayesian model-based clustering approach was performed with an assumed inferred number of clusters (K) which ranged from 2 to 9 (Figure 3). Change in inferred clusters (ΔK) values peaked at K = 4, indicating strong support for four independent populations. Each population independently assigned to its inferred cluster despite some evidence of admixture. The Landim and Bovine de Tete showed relatively more admixture with each other than Angone and Namaacha Nguni.

Figure 3. Estimated population structure of four Mozambican indigenous cattle populations (K = 4).


Discussion

Information of genetic diversity and population structure among livestock populations plays an important role in the design of genetic improvement programmes, as well as sustainable utilization and conservation of genetic resources (Groeneveld et al 2010; Sharma et al 2015). Furthermore, genetic information is fundamental for maintaining genetic diversity as well as preventing undesirable loss of alleles. In this study, genetic differentiation and population structure of Mozambican indigenous cattle populations were investigated using bovine microsatellite markers.

The majority of microsatellite markers used presented a high degree of polymorphism (PIC >0.5) and a significant number of alleles, confirming that they are appropriate and sufficiently informative for genetic diversity studies. The overall mean for PIC values is comparable to those reported by Suh et al (2014) and Sanarana et al (2016). According to Botstein et al (1980), PIC values >0.5 indicate that the markers are highly informative for the assessment of genetic diversity. All markers surpassed the Food and Agriculture Organization’s (FAO) recommended minimum threshold of five alleles per locus, which is required for the estimation of genetic differentiation among animal populations (FAO 2011; Sanarana et al 2016). The mean heterozygosity values (He = 0.714 and Ho = 0.681) across all markers, indicate wide genetic variation within the studied populations. High genetic variation in Mozambican indigenous cattle populations could be important for adaptability to the different agro-ecological areas of Mozambique. Genetic variation within populations is necessary to allow individuals to adapt to ever changing environments (Kunene 2007; Hlophe 2011). The heterozygosity values obtained were comparable to those reported by Suh et al (2014) (He = 0.667and Ho = 0.733) and Sanarana et al (2016) (He = 0.700 and Ho = 0.694); however, higher values were reported by Acosta et al (2013) (He = 0.751 and Ho = 0.728). This discrepancy could be attributable to the higher number of markers used in the latter study.

The four Mozambican indigenous cattle populations studied revealed a moderate and statistically significant genetic differentiation (FST = 0.086 ± 0.013), implying that within-population genetic variation (91.4%) was greater than that between-populations (8.6%). This variation could be a key tool for implementing genetic improvement and effective conservation strategies of these cattle populations. An overall significant shortfall of heterozygotes (FIS) of 2.7% detected in the analysed markers could be due to limited inbreeding within the populations. Eleven of the markers (BM1824, BM2113, CSRM60, ILSTS006, INRA23, TGLA122, TGLA227, ETH3, TGLA53, INRA5 and MM8) did not contribute to loss of heterozygotes. The general shortfall of heterozygotes across populations (FIT) was 11.1%. The overall mean values of Wright’s fixation indices (FST, FIS, and FIT) obtained within populations in this study were comparable with those reported by Acosta et al (2013) for Cuban cattle breeds; and higher than those reported in South African Nguni ecotypes (Sanarana 2015) and Zimbabwean Sanga breeds (Gororo et al 2018). Sharma et al (2015) reported higher Wright’s fixation indices in Indian cattle than in the current study. However, Bessa et al (2009) reported higher FIT and FIS values than in this study. Some discrepancies of these Wright’s fixation indices could be due to variation in the number of animals and microsatellite markers analysed. The mean number of migrants per generation (Nm) resulted in a moderate rate of gene flow (Nm = 4.37) among the populations. The results opposed the effects of genetic drift and inbreeding (Nm > 1), and revealed that the populations were mating at random (Nm > 4) (Frankham et al 2002; Groeneveld et al 2010). This could be attributed to the fact that the studied populations are confined in their respective conversation habitats, under controlled breeding system. However, low and high rates of gene flow have been reported in Indian cattle breeds (Sharma et al 2015) and East Indian cattle population (Sharma et al 2013), respectively. The chance of uncontrolled crossbreeding between some East Indian cattle populations (local and two established cattle breeds) could have contributed to the high rate of gene flow, especially in free grazing systems and villages, as compared to the conserved and controlled breeding of Indian cattle breeds and the populations in the current study.

The mean number of alleles (MNA) per locus ranged from 6.28 (Angone) to 7.76 (Bovine de Tete). The expected heterozygosity (He) varied from 69% (both Angone and Namaacha Nguni) to 77% (Bovine de Tete). Comparable results from studies using microsatellite markers in genetic diversity studies on indigenous cattle have also been reported (Bessa et al 2009; Suh et al 2014; Sanarana et al 2016, Gororo et al 2018). They were, however, relatively higher than the gene diversity reported in the Afrikaner cattle population (Pienaar et al 2014) and lower than those obtained in Cuban cattle breeds (Acosta et al 2013). The high He and MNA observed in this study indicate that Mozambican indigenous cattle populations represent an important reservoir of genetic variation, which is valuable for the conservation of indigenous animal genetic resources (AnGR). The private alleles detected in the populations could also be important for future plans towards long-term conservation of these populations. Mozambican cattle populations are spread in different parts of the country, with different environmental conditions. Ojango et al (2011) noted that high He levels are associated with long-term natural selection for adaptation and the historic mixing of different populations. Average observed heterozygosity (Ho) was lower than expected in all the Mozambican populations studied, excluding the Namaacha Nguni. Several studies have reported similar observations (Bessa et al 2009; Acosta et al 2013; Suh et al, 2014). This could be attributed to factors such as scoring bias (heterozygotes scored incorrectly), segregation of nonamplifying (null) alleles, recent mixing of distinct subgroups resulting in a Wahlund effect or inbreeding (Garrine 2007). The Ho was relatively higher than He in the Namaacha Nguni, with a low number of HWE (3) which concurred with the negative levels of inbreeding in that population. Similar observations have been reported in Zimbabwean Sanga cattle breeds (Nkone and Tuli) (Gororo et al 2018). The positive level of inbreeding detected in Angone, Landim and Bovine de Tete, in this study, was relatively lower than the values reported in a previous study by Bessa et al (2009). The high diversity levels detected in the current study, and limited inbreeding, shows that there is an opportunity for proper selection and conservation of the Mozambican cattle populations.

About 8.02% of the total variation was found between the populations and 91.98% was within the populations. Interestingly, these findings were higher than values reported by Bessa et al (2009) in a previous study with the same populations. However, the results for molecular variance were comparable to the values reported on Zimbabwean Sanga cattle breeds (Gororo et al 2018). The significant variation among these Mozambican populations could be attributed to their geographic isolation, natural process of mutation and adaptation to the different ecological zones of Mozambique.

Both genetic differentiations (FST) and unbiased Nei’s genetic distance (DA) estimates established some genetic relationships among the Mozambican indigenous cattle populations. The Landim and Bovine de Tete were the most closely related populations, followed by Bovine de Tete and Angone. These results concur with a previous study by Bessa et al (2009). The Namaacha Nguni, when paired with Bovine de Tete or Landim, was genetically distant by a similar magnitude. This is most likely due to different ancestral histories of origin for these populations (breeds). It has been reported that, based on their morphology, the Angone is classified as a Zebu type whereas the Landim and Namaacha Nguni are classified as Sanga type breeds (Epstein 1971; Scholtz et al 2011; Tada et al 2013).

Some individuals from Landim and Bovine de Tete were mixed on the Factorial Correspondence Analysis (FCA), suggesting a close relationship between them. On the other hand, the Angone and Namaacha Nguni’s individuals clearly clustered away from each other, disclosing a divergent relationship between these two populations. The Principal Components Analysis (PCoA) maintained a close relationship between Landim and Bovine de Tete, as opposed to a distant relationship between the Angone and Namaacha. A similar pattern of genetic relationships was reported in a previous study (Bessa et al 2009). In general, genetic differentiation, genetic distance, PCoA and FCA analyses together provided precise genetic evidence for the differentiation of the four Mozambican indigenous cattle populations. The scientific information pertaining to genetic relationships could effectively assist with proper planning on management of the populations to improve and/or maintain genetic diversity for their survival within the country.

Mozambican indigenous cattle populations assigned independently on the structure analysis, despite some evidence of admixture. Each population constituted >90% of its membership being assigned to the rightful population, indicating that Mozambican cattle populations still maintain most of their unique genetic identity. However, the Landim and Bovine de Tete populations shared more signals of admixture to each other than Angone and Namaacha Nguni populations. This could be explained by the suggestion that Bovine de Tete was developed through cross breeding of the Landim and Angone, notwithstanding the fact that it is generally considered as a Sanga breed similar to Landim (Rege and Tawah 1999; Bessa et al 2009). The findings in the current study point origins of Bovine de Tete towards Landim derivation and their close relationship has been supported in this study. Namaacha Nguni cattle were re-introduced into Mozambique after the huge loss of the national herd during the years of civil war between 1975 and 1994 (Hanks and Pereira 1998). It is a Nguni ecotype from KwaZulu-Natal province, South Africa, that belongs to the Sanga class. On the other hand, Angone is classified as a Zebu type. These points suggest a distant relationship between the two populations, with minimal appearance of shared genetic materials between the two, hence indicating that there have been very low levels of gene flow between the two populations.


Conclusions

The present study carried out within-country genetic characterization of Mozambican indigenous cattle populations. Previous studies had been limited to only three of these breeds (Angone, Bovine de Tete and Landim). The panel of microsatellite markers used in the current study proved to be sufficiently informative in quantifying genetic diversity, establishing genetic relationships and determining the population structure of the studied populations. Genetic diversity is high for Mozambican indigenous cattle populations, as shown by the mean number of alleles and expected heterozygosities observed. The AMOVA results indicated that most of the genetic variation existed within and not among the populations studied. A low level of inbreeding was observed in the Mozambican indigenous cattle populations, especially in Namaacha Nguni, indicating sound breeding management within these populations. Landim and Bovine de Tete disclosed a closer relationship as opposed to Angone and Namaacha Nguni populations. Population structure clearly indicated that most of the individuals analysed were correctly assigned to their populations, despite some evidence of admixture detected. It is thus concluded that sufficient genetic variation has been maintained within the Mozambican indigenous cattle populations, with populations retaining most of their genetic identity. Thus, the studied populations constitute an important reservior of genetic diversity; and therefore present valuable animal genetic resources for Mozambique and the Southern African region. There is a need to conserve these resources in order to cope with unpredictable future enviromental conditions. Future studies may be warranted, to investigate the association between genetic markers and phenotypic parameters to enable exploitation of these valuable genetic resources. Science has moved on from microsatellites to Single Nucleotide Polymorhism (SNP) markers and all future work should use SNPs, especially given their low cost today.


Acknowledgements

We sincerely thank the financial support provided by Technology Innovation Agency, National Research Foundation (Grant Number: 103042), University of Venda: Research and Publication Committee grant (SARDF/16/ANS/03) and Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) - Council for Scientific and Industrial Research (CSIR) of South Africa to carry out this study. The collaboration and contribution of Directorate of Animal Science, Agrarian Research Institute of Mozambique, Mozambique is duly acknowledged.


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Received 20 February 2019; Accepted 22 February 2019; Published 1 April 2019

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