Genetic variability of dromedary camel populations based onmicrosatellite markers

M. Piro1, F. E. Mabsoute2, N. El Khattaby2, H. Laghouaouta2 and I. Boujenane2†

1Department of Medicine, Surgery and Reproduction, Institut Agronomique et Vétérinaire Hassan II, Rabat, Morocco; 2Department of Animal Production andBiotechnology, Institut Agronomique et Vétérinaire Hassan II, Rabat, Morocco

(Received 19 February 2020; Accepted 29 May 2020; First published online 25 June 2020)

Understanding existing levels of genetic variability of camel populations is capital for conservation activities. This study aims toprovide information on the genetic diversity of four dromedary populations, including Guerzni, Harcha, Khouari and Marmouri.Blood samples from 227 individuals belonging to the aforementioned populations were obtained and genotyped by 16microsatellite markers. A total of 215 alleles were observed, with the mean number of alleles per locus being 13.4 ± 6.26. All lociwere polymorphic in the studied populations. The average expected heterozygosity varied from a maximum of 0.748 ± 0.122 inGuerzni population to a minimum of 0.702 ± 0.128 in Harcha population; Guerzni population showed the highest value ofobserved heterozygosity (0.699 ± 0.088), whereas Harcha population the lowest (0.646 ± 0.130). Mean estimates of F-statisticsobtained over loci were FIS= 0.0726, FIT= 0.0876 and FST= 0.0162. The lowest genetic distance was obtained between Guerzniand Khouari (0.023), and the highest genetic distance between Harcha and Marmouri (0.251). The neighbour-joining phylogenetictree showed two groups of populations indicating a cluster of Guerzni, Khouari and Marmouri, and a clear isolation of Harcha.The genetic distances, the factorial correspondence analysis, the analysis of genetic structure and the phylogenetic tree betweenpopulations revealed significant differences between Harcha and other populations, and a high similarity between Guerzni,Khouari and Marmouri. It is concluded from this study that the camel genetic resources studied are well diversified. However, theherd management, especially the random selection of breeding animals, can increase the level of genetic mixing betweendifferent populations, mainly among Guerzni, Khouari and Marmouri, that live in the same habitat and grazing area.

Keywords: genetic diversity, heterozygosity, genetic differentiation, population structure, Morocco

Implications

Camel populations studied have a high genetic variation,with large number of private alleles. They may be used toincrease the genetic variability of other camel populations.Results evidenced that the studied populations were not welldifferentiated and an admixture process between them hadoccurred, indicating the absence of clear genetic differencesbetween them. Such information is essential for the estab-lishment of a strategy for the preservation, utilization andgenetic improvement.

Introduction

In Morocco, camels are single-humped type or dromedary(Camelus dromedarius). Their number is around 200 000heads, and >80% are located in southern and south-eastern

Morocco, where they are raisedmainly for meat andmilk pro-ductions. Camel’s milk and meat constitute an importantcomponent of human diets in these dry desert regions, sincethey reached 13 975 and 3600 tons, respectively, in 2017(Ministry of Agriculture, 2018). Camel classification inMorocco is mainly based on phenotypic and morphologicalcharacteristics. Thus, three populations (Marmouri, Khouariand Guerzni) were identified on this basis in the southernregion (Ezzahiri, 1988; Achaaban et al., 1997). Never-theless, using multivariate analyses of morphological mea-surements, Boujenane et al. (2019) found that the GuerzniandMarmouri populations were similar, and slightly differentfrom the Khouari population. However, no information isavailable for the production rate of Moroccan camel popula-tions. Nevertheless, some surveys conducted in the south ofthe country indicated that the Marmouri population is appre-ciated by breeders for its suitable milk yield, and the Guerznipopulation is preferred for its satisfactory meat production.Thus, the Moroccan dromedaries were generally identified† E-mail: ismail.boujenane@gmail.com

Animal (2020), 14:12, pp 2452–2462 © The Author(s), 2020. Published by Cambridge University Press on behalf ofThe Animal Consortiumdoi:10.1017/S1751731120001573

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on the basis of their morphological characteristics, but theyare poorly differentiated based on genetic analyses (Piroet al., 2011).

Microsatellites are a powerful tool for tracking alleles in apopulation and for estimating genetic variability within andamong breeds. They are numerous, polymorphic and distrib-uted randomly in the genome, as well as codominantlyinherited and selectively neutral (Cheng et al., 1995).Moreover, genetic distance analyses could help to distinguishbetween different populations more objectively than by purephenotypic description. Microsatellites have been used todetermine genetic diversity within and among camel popu-lations. Ould Ahmed et al. (2010) used eight microsatellites,reporting high genetic variability within three Tunisian drom-edaries. Mahmoud et al. (2012), investigating 15 microsatel-lite markers, deduced a low genetic variability among fourSaudi Arabian dromedary camels. In Morocco, there has onlybeen one genetic study (Piro et al., 2011), which detected lowgenetic differentiation among Moroccan dromedary camels.Although this study was carried out on five camel popula-tions, it was restricted to one camel-raising region andhad used seven microsatellite markers only. Therefore,whether these dromedary camels are indeed differentiatedand established breeds or a single admixed group is to bechecked.

Therefore, this study was planned to investigate thegenetic variation using 16 microsatellite markers and severalanimals from southern and south-eastern regions for thegenetic characterization of dromedary populations inMorocco, with the indication that a dromedary populationof the latter region was never studied previously.

Material and methods

Animals and genotypingFresh blood samples were randomly collected from 227healthy dromedaries. The animals were chosen as unrelatedas possible from the following four populations: Guerzni(102), Harcha (26), Khouari (43) and Marmouri (56). Theywere reared in 52 herds of three administrative regions insouth and south-east of Morocco (Draa–Tafilalet region,including provinces of Ouarzazate and Errachidia;Guelmim–Oued Noun region, including provinces ofGuelmim, Tan-Tan, Sidi Ifni and Assa-Zag; and Laâyoune–Sakia Al Hamara region, including provinces of Laâyoune,Es-Smara, Boujdour and Tarfaya) (Figure 1). Briefly, theGuerzni is small with a thin neck, a small udder, a pointedhump located in the middle of the back and a dark pilosityin the ears, head, neck and around the hump. TheMarmouri is high, with a fine skin, a thin neck, a roundedand symmetric hump, a developed udder and no long hairon its body. The Khouari is intermediate between the twoprevious populations. The Harcha is small, with a thin neck,a flat forehead, a fade hump located in the middle of the backand a long dark hair on its body (Figure 2). Herds were

kept by migratory pastoralists under extensive low-input-management conditions without any selective pressure.They weremainly composed by several females of various pop-ulations with one or very few bulls. In each herd, samplingwascarried out randomly among camels. Thus, in front of a herdthat is composed of two or three populations, especially in theabsence of pedigree and any information about the related-ness of the individuals, we started by sampling one animalfrom each population based on phenotypic appearance andmorphological characteristics of each population as describedby Ezzahiri (1988) and Achaaban et al. (1997). Then, if wewished to add some other animals to the sample, we askedthe farmer for those that were not related to animals alreadysampled. Using this approach, two animals of different ages(from herds including one population) to five animals of differ-ent ages and distinct populations (from herds including two orthree populations) were sampled from each herd in order tohave a large variability and tominimize bias sampling betweenthe animals sampled.

Blood was collected from the jugular vein in EDTA tubesand kept refrigerated at 4°C until the time of DNA extraction.Genomic DNA was extracted from whole blood using thealkaline lysis method (Miller et al., 1988) and stored at−20°C until the analysis was performed. A total of 16 micro-satellite markers, selected among those recommended by theInternational Society of Animal Genetics/Food andAgriculture Organization work group (Hoffman et al.,2004), were used for genotyping (Supplementary TableS1): CMS121, CVRL05, LCA66, LCA63, VOLP03, CMS50,VOLP08, VOLP10, VOLP32, YWLL38, VOLP67, CMS13,YWLL08, CMS15, CVRL07 and CVRL01. Microsatellites weredivided into two multiplex (multiplex M1: CVRL05, CMS121,LCA63, LCA66 and VOLP03; and multiplex M2: CMS50,VOLP08, VOLP10, VOLP32 and YWLL38) and six simplex(CRL01, CMS13, YWLL08, VOLP67, CVRL07 and CMS15)according to the dye used, annealing temperature and allelicrange. Polymerase chain reaction was carried out in a totalvolume of 25 μl containing 1.0 μl genomic DNA, 0.25 to1.5 μl of forward and reverse primers separately, 12.5 μlof PCR Master Mix (Promega, Charbonnieres Les Bains,France), which was completed with nuclease-free water.The PCR amplification protocol contained an initial denatu-ration at 95°C for 3 min, followed by 40 cycles of denatura-tion at 95°C for 30 s, annealing for 30 s at 55°C or 60°Cdepending on the primer, elongation at 72°C for 1 minand a final extension at 72°C for 12 min with subsequentcooling to 4°C. The PCR reaction was performed using aGenAmp 2700 (Applied Biosystems, Thermofisher Scientific,Waltham, MA, USA) thermal cycler. The PCR fragments wereresolved on an ABI Prism 3500 (Applied Biosystems)fragment analyser, and data were analysed using theGENEMAPPER 4.1 software (Applied Biosystems). In orderto avoid any uncertainty about the size of amplified frag-ments and to correctly identify the different alleles for eachindividual, three operators validated the fluorescence peakobtained with GENEMAPPER software.

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Statistical analysesAllele frequencies, mean number of alleles per locus,observed heterozygosity (Ho) and expected heterozygosity(He) were calculated using GENETIX (Laboratoire Génome,Populations, Interactions; CNRS UMR 5000; UniversitéMontpellier II, Montpellier, France) software package(version 4.05) (Belkhir et al., 2004). Deviations fromHardy–Weinberg expectations were tested using MarkovChain Monte Carlo simulation (100 batches, 5000 iterationsper batch and a dememorization number of 10 000) imple-mented in the GENEPOP (Laboratiore de Génétique etEnvironment, Montpellier, France) statistical package,version 4.5.1 (Raymond and Rousset, 1995). Wright’sF-statistics (FIS, FIT and F ST) and number of migrants (Nm)according to Weir and Cockerham (1984) and Nei’s geneticdistance (Nei, 1972) were also calculated using GENETIXsoftware. Factorial correspondence analysis (FCA) wasapplied using individual genotypes to produce 3D graphicalrepresentation using GENETIX software. The phylogenetictree was reconstructed using the PHYLIP (Department ofGenome Sciences and the Department of Biology,University of Washington, Seattle, WA, USA) 3.695 software

(Felsentein, 2013), based on the Nei’s genetic distance,applying the neighbour-joining method. Identification of thetrue number of populations (clusters) and assignment of indi-viduals to each cluster were performed by the full Bayesianapproach using the software package STRUCTURE (PritchardLab, Department of Genetic, Stanford University, Stanford,CA, USA), version 2.3.4 (Pritchard et al., 2000). Themodel usedwas based on the assumption of ‘admixture model’ and‘allele frequencies correlated’. In order to choose the appro-priate number of inferred clusters (K ), we performed 10 runs,fitting K from 2 to 10 (the real number of populations plussix). All runs used a ‘burn-in period’ of 100 000 iterationsand a ‘period of data collection’ of 100 000 iterations. Thetrue K was determined using STRUCTURE HARVESTERWEB (Center for Biomolecular Science and Engineering,Biomolecular Engineering Department, University ofCalifornia, Santa Cruz, CA, USA), version 0.6.94 (Earl andvonHoldt, 2012). The assignment of individuals to the refer-ence population was carried out using partial Bayesianapproach (Rannala and Mountain, 1997) with a thresholdof 0.05 through GENECLASS (INRA – CIRAD, Montpellier,France) software package, version 2.0 (Piry et al., 2004).

Figure 1 Map showing the regions of south and south-east of Morocco (8, Draa–Tafilalet, including provinces of Ouarzazate and Errachidia; 10, Guelmim–Oued Noun, including provinces of Guelmim, Tan-Tan, Sidi Ifni and Assa-Zag; and 11, Laâyoune–Sakia Al Hamara, including provinces of Laâyoune, Es-Smara,Boujdour and Tarfaya) where Harcha, Guerzni, Khouari and Marmouri dromedary camels were sampled.

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Results and discussion

Population variability and differentiationAll the considered loci amplified successfully and used in fur-ther analyses. A total of 215 alleles were observed in the totalsample at 16 microsatellite loci, with an average value of13.4 ± 6.26 alleles per locus. Guerzni had 188 alleles,Harcha had 118, Khouari had 151 and Marmouri had 160,averaging 11.7 ± 5.76, 7.37 ± 3.14, 9.44 ± 4.65 and10.0 ± 5.10 alleles, respectively (Table 1). The high geneticdiversity in the studied populations could be explained bythe lack of selective pressure. Additionally, the differencesamong populations might be due to the unequally distributedpopulation samples since generally, as the sample sizeincreases, the alleles’ number increases too. The presentmean number of alleles is similar to the average of 13.3alleles per locus for six Saudi Arabian dromedary populations(Mahmoud et al., 2019). However, it is greater than thosefound within three Tunisian dromedary populations (OuldAhmed et al., 2010), five Moroccan dromedary populations

(Piro et al., 2011), four Saudi Arabian dromedary populations(9.27) (Mahmoud et al., 2012), some dromedary types andsubtypes from Sudan, Qatar, Somalia and Chad (10.0)(Hashim et al., 2014), and four Egyptian populations (9.3)(Al-Soudy, 2018). All the investigated loci were highly poly-morphic, respecting what FAO (1998) suggested about theuse of only loci with a minimum number of four alleles forgenetic distance studies. Themost polymorphic microsatellitewas VOLP67 with 26 alleles, while the least polymorphic wasVOLP32 with five alleles. Mahmoud et al. (2019) found thatYWLL08 was the most polymorphic locus with 23 alleles inSaudi Arabian camel populations. Additionally, the observednumber of alleles per locus varied from 5 (VOLP32 andYWLL38) to 23 (VOLP67) in Guerzni, from 2 (VOLP08) to12 (VOLP67) in Harcha, from 2 (VOLP32) to 18 (VOLP67)in Khouari, and from 3 (VOLP32 and YWLL38) to 21(VOLP67) in Marmouri populations. The allelic frequency var-ied at all loci from 0.005 to 0.657 in Guerzni, from 0.019 to0.750 in Harcha, from 0.012 to 0.679 in Khouari, and from

Figure 2 Photos of dromedary camels from different populations analysed.

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0.009 to 0.705 in Marmouri populations. The medium to highvariability of these populations could be attributed to lowselection pressure since animals are usually subject to tradi-tional husbandry management and reared by breeders fol-lowing their own traditional breeding schemes and usuallyusing their own bulls. When the 16 microsatellites wereexamined for breed-specific alleles, a total of 44 allelesout of 215 total alleles (20.5%) were found across popula-tions. A total of 23 alleles at loci CMS121, VOLP03,CMS50, VOLP08, VOLP10, VOLP32, YWLL38, VOLP67,CMS13, YWLL08, CVRL07 and CVRL01 were found to be spe-cific for Guerzni; three alleles at loci CVRL05, VOLP03 andCMS13 were found to be specific for Harcha; six alleles at lociCMS121, VOLP03, VOLP10, YWLL38 and YWLL08 werefound to be specific for Khouari; and 12 alleles at lociLCA66, LCA63, VOLP03, VOLP10, VOLP67 and CVRL01 werefound to be specific for Marmouri population. The combinedfrequency of private alleles found at each locus varied from0.005 to 0.058, with the highest frequency found in theHarcha population, and the mean frequency of private alleleswas 0.0108, which indicates that these alleles cannot be usedas genetic markers. Studying the dromedary camel popula-tions in Tunisia, Nouairia et al. (2015) found only two allelesthat were private and only observed in the Merzougui group.

In total, 12 of the 16 microsatellites showed significant(P< 0.05) departures from Hardy–Weinberg equilibrium inthe entire population (Supplementary Table S2). Loci show-ing deviations were VOLP32, VOLP67 and CVRL07 in fourpopulations; CMS121, VOLP08 and CVRL01 in three popula-tions; and CMS50, VOLP10 and YWLL38 in two populations.The number of markers that were not in equilibrium was4, 7, 9 and 11 in Harcha, Khouari, Marmouri and Guerznipopulations, respectively. Moreover, when considering all

loci, the four studied populations revealed a significantdeparture (P< 0.001) from Hardy–Weinberg equilibrium.This deviation was mainly due to heterozygote deficiency,especially for markers CVRL07 and VOLP67, which mightresult from inbreeding mating between populations or nullalleles. In this regard, null allele frequencies were estimatedusing FreeNA software (INRA, Montpellier, France; Chapuisand Estoup, 2007), and were found to vary from 0.00002to 0.15819. The presence of null alleles creates false homo-zygous leading to heterozygote deficiency. It has been shownthat the number of loci that deviated from the Hardy–Weinberg equilibrium varied from 12 to 17 among 19 inSaudi Arabian (Mahmoud et al., 2019) and 11 out of 19 inthe total sample of six Algerian and Egyptian camel popula-tions (Cherifi et al., 2017).

The He for the 16 loci ranged from 0.402 at VOLP32 inHarcha, to 0.917 at VOLP67 in Guerzni population, whilethe Ho varied from 0.346 at VOLP32 in Harcha, to 0.846at CMS50 in the same population (Table 2). This indicatesthat the measurement of genetic diversity based on 16 micro-satellite markers is reliable. In this regard, Takezaki and Nei(1996) reported that when average heterozygosity is low, it ismore important to examine a large number of loci rather thana large number of genes per locus. Although varying amongpopulations, mean Ho was lower than mean He for the fourpopulations, confirming the departure from the equilibriumin the studied populations. This could suggest that individ-uals within each of these populations are more likely to beunder inbreedingmating. The average He varied from amaxi-mum of 0.748 ± 0.122 in the Guerzni population to a mini-mum of 0.702 ± 0.128 in the Harcha population; the Guerznipopulation showed the highest value of Ho (0.699 ± 0.088),whereas the Harcha population showed the lowest

Table 1 Genetic parameters measured in the Moroccan camel populations with 16 microsatellite loci

Locus Number of alleles

Population

Allele size interval (bp) Allele frequency intervalGuerzni Harcha Khouari Marmouri

CMS121 11 10 9 10 8 148 to 170 0.012 to 0.437CVRL05 14 12 9 11 12 158 to 184 0.005 to 0.423LCA66 9 6 6 6 8 222 to 246 0.005 to 0.402LCA63 9 7 5 5 8 206 to 224 0.005 to 0.423VOLP03 16 13 8 10 10 145 to 181 0.005 to 0.663CMS50 15 15 10 11 10 148 to 192 0.005 to 0.287VOLP08 6 6 2 4 4 144 to 266 0.005 to 0. 577VOLP10 14 9 5 9 12 148 to 266 0.009 to 0.377VOLP32 5 5 3 2 3 174 to 264 0.005 to 0.750YWLL38 7 5 3 5 3 146 to 190 0.005 to 0.657VOLP67 26 23 12 18 21 148 to 262 0.005 to 0.192CMS13 12 11 9 7 6 166 to 256 0.005 to 0.509YWLL08 21 20 11 15 15 135 to 177 0.005 to 0.385CMS15 10 10 6 8 9 120 to 148 0.005 to 0.404CVRL07 15 15 9 13 13 272 to 302 0.005 to 0.346CVRL01 25 21 11 17 18 198 to 246 0.005 to 0.312Total 215 188 118 151 160Mean ± SD 13.4 ± 6.26 11.7 ± 5.76 7.37 ± 3.14 9.44 ± 4.65 10.0 ± 5.10

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(0.646 ± 0.130). The mean He of the present study is inagreement with that of Hashim et al. (2014) (0.738), higherthan those reported by Ould Ahmed et al. (2010) (0.60) andPiro et al. (2011) (0.65), but lower than those observed byNouairia et al. (2015) (0.78) and Al-Soudy (2018) (0.76).The mean Ho was similar to those found by Mahmoud et al.(2012) (0.665) and Cherifi et al. (2017) (0.647), lower thanthose reported by Hashim et al. (2014) (0.74), Hedayat-Evrigh et al. (2018) (0.748), Al-Soudy (2018) (0.846) andMahmoud et al. (2019) (0.713 to 0.929), but higher than thatobtained by Ould Ahmed et al. (2010) (0.46). The within-population deficit in heterozygosity, as evaluated by theFIS parameter, varied from −0.275 (VOLP32) to 0.259(CVRL07). FIT values ranged from −0.259 (VOLP32) to 0.287(CVRL07), and FST values varied between 0 (LCA66) and0.086 (VOLP08). Mean estimates of F-statistics obtainedover loci were FIS= 0.073 ± 0.025, FIT= 0.088 ± 0.027 andFST= 0.016 ± 0.005 (Table 3). All the three estimates were sig-nificantly different from zero (P< 0.05). The positive totalmean of FIS found in all populations is an indicator of inbreed-ing, even if it cannot be excluded in the presence of null alleles,locus under selection or the presence of population substruc-ture within population (Wahlund effect). Nevertheless, sincecamel breeders in general select their bulls from their ownherds and use them for several years, it is likely that these bullsmate their female relatives (dams, paternal half-sisters anddaughters), leading to inbreeding that could be consideredthe major factor causing the observed heterozygote deficiencyin the analysed populations. The present deficit in hetero-zygosity is greater than that found across 14 microsatelliteswithin two Sudanese camel ecotypes (0.034) (Eltanany et al.,2015). Al-Soudy (2018) reported a negative FIS value(−0.07284) between four Egyptian camel breeds. He explained

this by the random mating and the absence of inbreedingwithin the breeds under study. The significant deficit of heter-ozygotes of 8.8% is partly due to a low degree of differentia-tion among the four Moroccan populations (FST= 0.016), butmost of the total genetic diversity is attributed to the differen-tiation among individuals (98.4%). Our results are lower thanmean estimates of F-statistics reported by Ould Ahmed et al.(2010) for Tunisian camel population (FIS= 0.19, FIT= 0.27

Table 2 Expected (E) and observed (O) heterozygosity per locus in Guerzni, Harcha, Khouari and Marmouri camels

Locus

Guerzni Harcha Khouari Marmouri

E O E O E O E O

CMS121 0.779 0.676 0.765 0.692 0.767 0.628 0.706 0.625CVRL05 0.763 0.733 0.758 0.692 0.744 0.767 0.733 0.696LCA66 0.705 0.755 0.720 0.731 0.736 0.698 0.719 0.643LCA63 0.742 0.782 0.720 0.731 0.725 0.674 0.780 0.714VOLP03 0.544 0.569 0.586 0.654 0.535 0.581 0.486 0.500CMS50 0.875 0.804 0.817 0.846 0.847 0.820 0.848 0.778VOLP08 0.639 0.588 0.488 0.461 0.591 0.512 0.602 0.554VOLP10 0.808 0.758 0.725 0.731 0.823 0.744 0.780 0.736VOLP32 0.511 0.634 0.402 0.346 0.436 0.643 0.494 0.691YWLL38 0.580 0.529 0.544 0.461 0.610 0.615 0.478 0.463VOLP67 0.917 0.735 0.775 0.731 0.911 0.658 0.901 0.764CMS13 0.768 0.667 0.777 0.731 0.692 0.651 0.656 0.661YWLL08 0.813 0.755 0.774 0.692 0.857 0.837 0.842 0.821CMS15 0.794 0.823 0.728 0.654 0.717 0.698 0.780 0.750CVRL07 0.869 0.634 0.781 0.538 0.857 0.558 0.848 0.759CVRL01 0.861 0.745 0.866 0.640 0.859 0.767 0.849 0.821Mean ± SD 0.748 ± 0.122 0.699 ± 0.088 0.702 ± 0.128 0.646 ± 0.130 0.732 ± 0.133 0.678 ± 0.092 0.719 ± 0.139 0.686 ± 0.107

Table 3 F-statistics analysis of each of the 16 microsatellite markers ofMoroccan camel populations. Numbers in parentheses indicatestandard deviation

FIS FIT FST

CMS121 0.142 (0.012) 0.160 (0.021) 0.022 (0.021)CVRL05 0.043 (0.015) 0.050 (0.021) 0.007 (0.009)LCA66 0.012 (0.062) 0.008 (0.061) −0.005 (0.002)LCA63 0.018 (0.053) 0.014 (0.054) −0.003 (0.002)VOLP03 −0.050 (0.013) −0.053 (0.014) −0.003 (0.003)CMS50 0.069 (0.018) 0.073 (0.011) 0.005 (0.010)VOLP08 0.096 (0.014) 0.174 (0.080) 0.086 (0.080)VOLP10 0.069 (0.010) 0.098 (0.033) 0.030 (0.041)VOLP32 −0.275 (0.070) −0.259 (0.079) 0.013 (0.017)YWLL38 0.073 (0.025) 0.076 (0.021) 0.003 (0.010)VOLP67 0.196 (0.024) 0.212 (0.021) 0.020 (0.023)CMS13 0.088 (0.044) 0.091 (0.047) 0.003 (0.006)YWLL08 0.063 (0.015) 0.083 (0.033) 0.021 (0.026)CMS15 0.017 (0.039) 0.022 (0.042) 0.005 (0.004)CVRL07 0.259 (0.047) 0.287 (0.043) 0.038 (0.037)CVRL01 0.127 (0.031) 0.136 (0.035) 0.010 (0.014)Mean 0.073 (0.025) 0.088 (0.027) 0.016 (0.005)

FIS, FST and FIT are F-statistics, also known as fixation indices, from the individual(I) to the subpopulation (S), from the subpopulation to the total (T), and from theindividual to the total, respectively.

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and FST= 0.09). They are also different from mean estimatesfound by Mahmoud et al. (2012) (FIS=−0.043, FIT=−0.025and FST= 0.018) and by Nouairia et al. (2015) (FIS=−0.295,FIT=−0.226 and FST= 0.052).

Pair-wise FST values between each pair of four dromedarypopulations were very low, reflecting a poor genetic differ-entiation between them (Table 4). The smallest distancewas between Guerzni and Khouari populations (0.0)(P> 0.05), whereas the largest FST value was betweenHarcha and Marmouri populations (0.069) (P< 0.001).These values showed no genetic differentiation betweenKhouari and Guerzni, poor genetic differentiation betweenMarmouri and Khouari, and between Marmouri andGuerzni populations, while the highest differentiation wasrecorded between the Harcha population, on one hand,and the three other populations, on the other hand, espe-cially with the Marmouri population. The low degree ofgenetic differentiation could be mainly due to crossbreedingbetween the three populations (Guerzni, Khouari andMarmouri) that share the same grazing area (southernregion) during the transhumance periods. Also, the unequalnumber of animals sampled from each population (Guerzni,102; Harcha, 26; Khouari, 43; andMarmouri, 56) might affectthe results found. Moreover, since null alleles are present, FSTfor each pair of populations was estimated both with andwithout using the excluding null alleles (correction throughthe FreeNA software), and the results were almost similar.The FST values varied from 0.006 to 0.017 betweenSaudi camel populations (Mahmoud et al., 2012) and from0.008 to 0.011 between Iranian dromedary populations(Hedayat-Evrigh et al., 2018).

The number of migrants per generation (Nm) among thefour camel populations averaged 15.3. The values of geneflow observed between Harcha and Guerzni, Harcha and

Khouari, Harcha and Marmouri, Guerzni and Marmouri,and Khouari and Marmouri were 6.47, 6.09, 3.38, 42.9and 82.2, respectively, indicating that the gene flow betweenHarcha and other populations was very low, whereas thatbetween Guerzni and Khouari was negative because its cor-responding FST value was also negative, but put equal to zeroby the software. Ould Ahmed et al. (2010) showed that theNm values among Tunisian camel populations were 1.65between Kebili and Medenine, 2.06 between Kebili andTataouine, and 6.65 between Medenine and Tataouine pop-ulations. The lowest gene flow (Nm= 14.5) was observedbetween Magaheem and Maghateer populations, whereasthe highest (Nm= 39.7) was observed between Sofr andShual populations of Saudi Arabia (Mahmoud et al., 2012).

The results of FCA are graphically presented for the firstthree factors (Figure 3). The first axis explains 61.61% ofthe total variation, whereas the other two axes explains21.69% and 16.70%, respectively. The results of analysisshowed that the four populations formed two groups of dots.The first group, clustered to the right, constituted mainly ofHarcha individuals mixed with few Guerzni and Khouari indi-viduals, whereas the second group, positioned to the left,composed of Marmouri and the majority of Guerzni andKhouari individuals, indicating clear admixture among them.These results were also confirmed by the phylogenetic treethat was constructed using microsatellite marker informa-tion. The neighbour-joining phylogenetic tree showed twogroups of populations, indicating a cluster of Guerzni,Khouari and Marmouri, and a clear isolation of Harcha fromthe centre of the radial tree (Figure 4). The close associationbetween Guerzni, Khouari and Marmouri was probably dueto the effects of admixture. Additionally, Nei’s genetic distan-ces between the four populations were small among Guerzni,Khouari and Marmouri, but large between Harcha and three

Figure 3 Factorial correspondence analysis (FCA) results showing the relationship between all of the individuals among the four camel populations analysed inthe study (percentage of inertia explained by each axis in parentheses).

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other populations. They varied from 0.023 between Guerzniand Khouari to 0.251 between Harcha and Marmouri(Table 4). These values are lower than those reported byPiro et al. (2011) on Guerzni, Khouari and Marmouri popu-lations. The analysis of genetic distances between popula-tions indicated again that the Harcha was the moredistanced population, a result that was confirmed by the pop-ulations’ dendrogram and the FCA. This result was expectedgiven that Harcha is a population that is reared in easternMorocco, near the Algerian frontier, whereas the three otherpopulations are reared together in the southern part of thecountry. Moreover, the similarity between Guerzni, Khouariand Marmouri populations could be explained by similarfounding populations and by the increased gene flow bycrossing between them. In fact, herds found in the southare generally a mixture of females of these three populationswith one or two bulls usually selected by the breeder from hisown herd on some productive criteria regardless to itspopulation.

Population structureThe structure of the populations was analysed using aBayesian clustering analysis, and results of this approachare shown in Figure 5 for K ranging from 2 to 6. Also, usingthe STRUCTURE HARVESTER software, it appears that overthe 10 independent runs for each K, the most appropriatenumber of clusters was five as shown in Supplementary

Figure S1. For K= 5, Ln Pr(X|K ) showed the highest value(−10 386.33) and the lowest standard deviation (133.8).Thus, it can be noticed that at K= 2, the Harcha populationclustered separately; Khouari and Marmouri did not show ahigh degree of admixture between them because they havetraces of ‘red’ background, whereas Guerzni exhibited a mix-ture of the previous three populations. The ‘red’ background,based on K= 3, could be from a separate population not rep-resented in the study. Moreover, setting K= 3 or 4 resulted inpartitioning Guerzni, Khouari, Marmouri and, in someinstances, Harcha into heterogeneous groups composed bydifferent individuals, indicating that there is a level of admix-ture in the populations studied. At K= 5 or 6, this structurewas stressed, thus supporting the evidence of a higheradmixture in Guerzni, Khouari and Marmouri. Noteworthy,the Harcha samples were collected exclusively in the eastof Morocco, where this population is solely raised, whereasthe three other types were sampled from the south andsouth-east of the country. Maybe the Guerzni and Khouariindividuals sampled in the latter region, which is close tothe Harcha’s geographic area, were those that are closerto the Harcha population and found in the FCA analysis.In fact, the level of genomic admixture in Guerzni, Khouariand Marmouri populations can be seen at a higher extenton K= 3 to K= 6 than in the Harcha population and theGuerzni and Marmouri samples closer to Harcha. This struc-ture confirms the gene flow occurred in the past among allthese populations, and affirms their probable common origin.Additionally, since the STRUCTURE software assumes Hardy–Weinberg equilibrium, consistency of the reported resultswas checked by re-running the programme a second timeusing only the four microsatellite markers that were inHardy–Weinberg equilibrium (LCA66, LCA63, VOLP03 andCMS15) with the same model and parameters as for the firstrun. However, results obtained did not change considerably,that is, the optimum number of clusters using STRUCTUREHARVESTER software was similar to the first run (K= 5),and the membership proportion of each of the four currentcamel populations in each of the five inferred clusters wasalmost the same as that reported for the complete set ofmarkers, indicating that microsatellite loci influenced by nullalleles would not modify the overall result of assignment test-ing. In an influential work on dromedary genetics, which ana-lysed 1083 dromedaries from five defined geographicalregions (eastern Africa, western and northern Africa, northArabian Peninsula, south Arabian Peninsula and southernAsia including Australia), Almathen et al. (2016) observedlittle phylogeographic signal in the modern population,indicative of extensive gene flow and virtually affecting allregions except East Africa, where dromedary populationshave remained relatively isolated. Piro et al. (2011) alsoreported a low genetic differentiation between MoroccanMarmouri, Guerzni and Khouari camels and concluded thatthey formed probably the same group. Very low geneticdifferentiation among South African, Saudi Arabian andtwo non-contiguous North African (Algeria and Egypt)camel populations was detected by Nolte et al. (2005),

Figure 4 Neighbour-joining phylogenetic tree showing the genetic rela-tionship among camel populations using the Nei’s distance from 16 micro-satellite loci.

Table 4 Nei’s standard genetic distance matrix (below diagonal) andpair-wise FST distance (above diagonal) between Guerzni, Harcha,Khouari and Marmouri camel populations

Guerzni Harcha Khouari Marmouri

Guerzni 0.037*** 0.000NS 0.006*Harcha 0.147 0.039*** 0.069***Khouari 0.023 0.161 0.003NS

Marmouri 0.036 0.251 0.038

Non-significant (NS), P> 0.05; *P< 0.05; ***P< 0.001.

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Mahmoud et al. (2012) and Cherifi et al. (2017), respectively.Using genome admixture and principle component analysesto determine the genomic relationship between ArabianPeninsula and Sudanese camels, Bahbahani et al. (2019)indicated a clear geographic separation between theSudanese and the Arabian Peninsula camels, but with nopopulation-specific genetic distinction within populations.However, a plausible genetic substructure among fourEgyptian camel populations (Baladi, Soudani, Magrebi andSomali) was found (Al-Soudy, 2018). As previously stated,the most appropriate number of clusters according to theSTRUCTURE analysis was five, which is greater that the realnumber of populations analysed. In this regard, Pritchard

et al. (2000) suggested that the inferred populations donot necessarily correspond to real ancestral populations.This situation may occur when populations are not well dif-ferentiated and a large proportion of individuals have somedegree of admixture, which was the case in the present study.The genetic structure observed here could be a consequenceof both the crossbreeding between Guerzni, Khouari andMarmouri and the geographic isolation of Harcha population.

The partial Bayesian method using GENECLASS softwareindicated that out of the 227 dromedaries used in this study,only 91 were correctly assigned to their reference population.Furthermore, 84.0%, 50.0%, 36.8% and 9.30% of Harcha,Marmouri, Guerzni and Khouari dromedaries, respectively,

Figure 5 Estimated population structure of the four camel populations for K ranging from 2 to 6. Black vertical lines separate the four camel populations(Harcha, Guerzni, Khouari and Marmouri).

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were correctly assigned, indicating a more heterogeneousstructure, especially for the latter three populations. Thelow proportions of correctly assigned individuals to their like-lihood population reflect the high gene flow and intermixingof gene pool between the populations, and suggest that theyare genetically very close. For 17 camel types and subtypesfrom Sudan, Qatar, Somalia and Chad, 46.62% individualswere correctly assigned with a quality index of 46.87%(Hashim et al., 2014), and for the Kenyan dromedaries,39% to 48% individuals were correctly assigned (Mburuet al., 2003).

Table 5 shows the assignment proportion of each of theanalysed camel populations to the five most likely clustersinferred, choosing the iteration with minimum variance.Cluster 4 included the Harcha individuals with 71.6%, show-ing a significant proportion of assignment for this population.Clusters 1 and 4 included the Guerzni individuals with pro-portions of assignment of 23.7% and 23.1%, respectively,and the Khouari individuals with proportion of assignmentof 26.8% and 21.4%, respectively. Marmouri showed a pro-portion of membership split almost equally into four clusters(1, 2, 3 and 5) with proportions of assignment ranging from22.6% to 26.7%. Thus, the Harcha individuals were mainlyassembled in one cluster, whereas the Guerzni, Khouari andMarmouri populations shared a similar clustering structure.Thus, the structure results showed a complex substructurewith a proportion of assignment split into more than onecluster, at least for K= 5. These results evidenced that thesepopulations were not very well differentiated and an admix-ture process between them had occurred, indicating theabsence of clear genetic differences between populations.As mentioned previously, camel herds in these regions aregenerally composed of a mixture of females belonging toGuerzni, Khouari and Marmouri populations because breed-ers do not have preference for one particular population.They are interested in animals that are able to give birthto calves every 1.5 or 2 years and have a satisfactory weaningweight. Males are also selected from their own herds on thebasis of their conformation, weight and, in very few cases, onmilk yield of their dams. Therefore, crosses between thesethree populations are a common practice. This is why propor-tions of correctly assigned Guerzni, Khouari and Marmouriindividuals to their reference population are very low.Moreover, these three populations share the same geo-graphic area, whereas the Harcha is living alone in the

eastern region of Morocco with rare contacts with otherpopulations.

Conclusions

The results obtained from this study show a high geneticvariation among the Moroccan dromedaries, which may bedue to a lack of artificial breeding strategies and to increasedgene flow due to crossing between them. They revealed alsothat individuals within each of these populations are morelikely to be under inbreeding mating. The results showedthat, although the Harcha population was specificallyassigned, they indicated the existence of individuals relatedto other populations. In addition, the results suggest thatGuerzni, Khouari and Marmouri populations are less differ-entiated and genetically closely related because of high levelsof crossbreeding between them. These results will be usefulfor defining adequate breeding and genetic managementstrategies.

AcknowledgementsThis study has been achieved within the CARAVAN project(ARIMNet2). The authors thank all staff of DRA ofLaâyoune-Sakia Al Hamra, DRA of Guelmim-Oued Noun,ONSSA of south regions of Morocco, ORMVA of Tafilalet,and ORMVA of Ouarzazate for their support and assistanceduring the collection of blood samples. They also thank alldromedary owners and shepherds who allowed blood sam-ples to be collected from their animals.

I. Boujenane 0000-0001-8405-7810

Declaration of interestThe authors declare that they have no potential conflict ofinterest.

Ethics statementBlood samples from the animals were collected under standardtechniques upon breeder’s approval. This material has not beenpublished elsewhere, and the manuscript is not currently beingconsidered for publication in another journal.

Software and data repository resourcesNone of the data were deposited in an official repository.

Table 5 Number of individuals per population and proportion of membership of each dromedary camel population in each of the five inferred clustersusing STRUCTURE software

Population

Inferred populations1

Sample size1 2 3 4 5

Harcha 0.022 0.092 0.076 0.716 0.094 26Guerzni 0.237 0.176 0.178 0.231 0.177 102Khouari 0.268 0.175 0.167 0.214 0.176 43Marmouri 0.267 0.226 0.228 0.053 0.227 56

1Contributions >0.20 are in bold.

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Supplementary materialTo view supplementary material for this article, please visithttps://doi.org/10.1017/S1751731120001573

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