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SIMPLE SEQUENCE REPEATS (SSR) ANALYSIS OF GENETIC INTRASPECIFIC RELATIONSHIPS OF MORINGA OLEIFERA POPULATIONS FROM NIGERIA.

Byline: Popoola Jacob O., O.A. Bello, J.A. Olugbuyiro and O.O. Obembe

ABSTRACT: Moringa oleifera Lam. (Moringaceae) is a multi-purpose economic plant whose commercial demand is on the increase in Africa. To meet this demand, it is significant to step up collections and diversity studies adaptable to higher productivity and utilization. The present study focuses on recently collected landraces/accessions of six populations of M. oleifera from different eco-geographical locations within Nigeria. A total of 70 accessions were evaluated for genetic intraspecific diversity using 20 SSR markers. Among the 20 SSR markers screened, 10 primer pairs (forward and reverse) were selected based on clear amplification products and reproducible scorable bands. Analysis of Molecular Variance (AMOVA), Principal Coordinates Analysis (PCoA) and cluster analysis (CA) were used to evaluate the genetic intraspecific diversity. A total number of 74 alleles with a range of 4 to 15 were detected among the 70 accessions.

On the average, 7.4 alleles per locus were amplified in each accession. Allele frequency varied from 0.214 to 0.671 with a mean of 0.477; gene diversity from 0.487 to 0.885 with a mean of 0.669 while the average PIC value was 0.633. The observed and expected heterozygosity varied from 0.00 to 0.50 with a mean of 0.972 and from 0.00 to 0.250 with a mean of 0.567, respectively. AMOVA shows that 8 % of the genetic diversity was attributed to differences among the populations while 92 % of the variation (significant at p = 0.001) was due to differences within populations. Allelic patterns across the six populations aligned with the AMOVA result. The results of PCoA and CA identified high intraspecific similarities with few exceptions. Similarity coefficients (SC) of CA ranged from 0.53 to 1.00 and delineated the 70 accessions into seven groups. All accessions are distinguishable from each other at SC 1.00 except (soN066 and taN085) and (anN045 and anN047).

The genetic relationships highlighted are significant for conservation, cultivation and genetic improvement of M. oleifera in view of the species socio-economic relevance to the people of Nigeria and Africa in general.

Key word: Moringa oleifera; SSR; genetic intraspecific diversity; similarity coefficient (SC); Nigeria.

INTRODUCTION

Moringa oleifera Lam. is one of the most economic and cultivated species in the single genus Moringa of the (Moringaceae) family [1, 2]. It is a tree crop with enormous potential capable of contributing to improved food security and nutrition, medicine and health care, incomes and environment in Africa [3]. In recent time, various products including health care products such as Moringa organic powder, capsules, leaf tea, oil extracts among others have been prepared from the leaves, pods and seeds of M. oleifera. These confirms the significance of its medicinal, nutritional, food, phytochemicals and various economic values to the socio-economic lives of the people particularly in the Sub-Sahara Africa (SSA). Several authors have also reported the nutritional, food, medicinal, commercial and agricultural uses of the crop [3, 4, 5, 6].

Anwar et al. [7] reviewed detailed phytochemical composition, medicinal uses as well as pharmacological properties to include antitumor, antipyretic, antiepileptic, anti-inflammatory, antiulcer, antihypertensive, cholesterol lowering, antioxidant, antibacterial among others.

In Nigeria, the increasing awareness on the economic values and usefulness of M. oleifera has led to the distribution or spread of landraces/ecotypes to different locations [3] even though there are little or no conservation management strategies for the present and future use. Recent database search by Leone et al. [5] also specified that there are no records of active germplasm banks worldwide on M. oleifera to represent 'core collections' of the taxa. The concept of 'core collections' represents the genetic diversity with a minimum duplication of accessions was introduced to effect a good and robust management of genetic resources for conservation and breeding purposes [8, 9]. In view of this, it is pertinent to step up genetic studies via germplasm collections and characterizations to possibly create core collections of M. oleifera in the near future.

Also, to meet a stable and commercial demand for Moringa products and other economic values derivable from the crop, it is significant to intensify diversity studies to create variants adaptable to local needs. This is justifiable since genetic diversity is the key determinant of germplasm utilization in crop improvement [10]. Presently, the existing germplasms in Nigeria can be regarded as landraces/accessions with no elite varieties adapted to local conditions.

M. oleifera is a geitonogamous and xenogamous diploid species (2n = 28; n = 14 chromosomes) whose gene pool and genetic base are expected to be wide with higher productivity [11, 12, 13, 14]. Reports, however, are contrary to the above as gene pool/ genetic base is narrow/weak with unknown gene pool among cultivated and wild species [13, 15]. The genetic bases and relationships among the different ecotypes/landraces in Nigeria are still limited and very unclear though few genetic characterizations have been investigated based on phenotypic and molecular markers [15, 16, 17]. Hence, it is significant to further evaluate the genetic relationships and provide useful information for the management and conservation of the genetic resources of the taxa towards breeding and improvement.

DNA based characterizations could provide additional information on the degree of diversity, genetic / eco-geographical relatedness of the collected landraces/accessions, avoid duplication of germplasms and maximize diversities. Globally, different DNA techniques including random amplified polymorphic DNA (RAPD), amplified fragment length polymorphisms (AFLPs), simple sequence repeats (SSR), chloroplast gene rcbL among others have been used to assess the genetic diversities among the populations / some accessions of M. oleifera. Muluvi et al. [18] and Ulloa [19] used AFLPs to evaluate diversity among and within populations of M. oleifera from Kenya. High degree of genetic variations between cultivated and non-cultivated populations of M. oleifera from Tanzania was reported by Mgendi et al. [20] using RAPD. Da Silva et al. [21] also used RAPD markers to assess the genetic diversity of 16 Moringa accessions from Brazil.

So far, very few studies are available where SSR markers have been used to assess genetic diversity of M. oleifera [22, 23, 24]. However, such studies did not cover West Africa nor include accessions from Nigeria. The studies of Shahzad et al. [22] combined SSR with a partial sequence of the chloroplast gene atpB to investigate genetic diversity and population structure of M. oleifera which covered a wide range of collections from Asia, Africa, North and South America and the Caribbean. Such studies have not been carried out on populations of M. oleifera in Nigeria. In the studies of Ganesan et al. [23] and Natarajan and Aslin-Joshi [24] both morphological and molecular markers were combined to assess genetic diversity among M. oleifera accessions restricted to Indian populations. SSR markers specific to M. oleifera were first developed by Wu et al. [25] which have been recommended as useful markers for detail genetic population studies and pollen-mediated gene flow within populations.

SSR is used as a primer to amplify regions between microsatellites. The analyses of SSRs are highly polymorphic and reproducible with small quantities of template DNA, inherited co-dominantly, and particularly for the abundance distribution of repeat sequences throughout genomes [26, 27, 28]. SSRs over the years have found practical applications for evaluation of molecular diversity and germplasm classification of underutilized crops [28]. Assessment of genetic diversity is crucial for efficient in situ and ex situ conservation of the taxa to which SSRs have been proven to be most suitable because of ability to detect hyper variable allelic variations [29, 30, 25]. Therefore, the study was aimed at using SSR to analyze levels of genetic diversity within and among six populations of 70 accessions of M. oleifera collected from different locations in Nigeria.

The study was also undertaken to provide information on genetic relationships based on differentiation of populations and clusters; and come up with strategies to adopt for conservation, management, breeding and genetic improvement of the species.

MATERIALS AND METHODS

Plant samples and Areas of Collection

A total of 70 accessions of Moringa oleifera were pooled from the survey and geographical distribution [3] and phenotypic intraspecific variability studies of M. oleifera in Nigeria [6]. Information about study sites, acquisition and passport data of plant materials/accessions are as described by Popoola and Obembe [3] and Popoola et al. [6]. The detail of accessions, codes and geographic source of the Moringa oleifera accessions used for this study are as listed in Table 1. Figure 1 shows the map of collection areas of the M. oleifera samples used for this study.

Table 1. List Of Accessions, Codes, Area Of Collection And State Within Nigeria Where Samples Were Collected.

###Accession###Area of

S/N###Code###Collection###L/G###State

1###abN057###Okpanku###Umuonoji###Abia

2###abN059###Umudike###Umudike###Abia

3###anN049###Enu Ifite###Awka###Anambra

4###anN051###Ihiala###Ihiala###Anambra

5###anN046###Unizik###Awka###Anambra

6###beN081###Otukpo###Otukpo###Benue

###Oshimili

7###deN041###Asaba###South###Delta

###Ehanlen-###Esan

8###edN035###Ewu###Central###Edo

###Ovia

9###edN040###Ugbokwi###South###Edo

###Benedicta###Esan

10###edN037###Monastry###Central###Edo

###Enugu

11###enN055###Ugwuomu###South###Enugu

12###enN053###Orba1###Nsukka###Enugu

13###goN068###Nafada###Nafada###Gombe

###Ahiazu

14###imN064###Mbaise###Mbaise###Imo

###Tudan

15###kaN033###Wada###Zaria###Kaduna

###Kofar###Kano

16###knN078###kudu###Municipal###Kano

###Army

17###knN077###Barracks###Kano###Kano

18###kwN016###Igosun###Oyun###Kwara

###Ilorin

19###kwN015###Ilorin###West###Kwara

20###niN018###Bida###Bida###Niger

###Abeokuta

21###ogN025###Abeokuta###South###Ogun

###Covenant

22###ogN028###Univ###Ado-Odo###Ogun

23###ogN076###Kila###Odeda###Ogun

24###ogN026###Olodo###Odeda###Ogun

###Owena

25###onN070###road###Ondo

###Ondo -

26###onN074###Ore road###Ondo

27###onN072###OsusTech###Okitipupa###Ondo

###Ife North

28###osN019###Ipetumodu###Central###Osun

###Ife North

29###osN020###OAU###Central###Osun

30###osN024###Owode###Ede###Osun

31###oyN003###Aroje###Atisbo###Oyo

###Oke-oro /

32###oyN001###Saki###Saki West###Oyo

###Aba

###Oremeta /

33###oyN005###Irawo###Atisbo###Oyo

###Sango,

34###oyN004###Ago Are###Atisbo###Oyo

###Alariwo

###Village /

35###oyN009###Igboho###Oorelope###Oyo

36###oyN010###Okaka###Itesiwaju###Oyo

37###plN030###UniJos###Jos###Plateau

38###soN066###Sokoto###Sokoto###Sokoto

###Wukari

###(Fed.

39###taN085###Univ)###Taraba

###Bukarti /

40###yoN031###Karasuwa###Karasuwa###Yobe

41###kaN032###Kafanchan###Kafanchan###Kaduna

42###kaN034###Sabongari###Kaduna

43###niN017###Mokwa###Mokwa###Niger

44###soN067###Shagari###Shagari###Sokoto

45###goN069###Gombe###Gombe

46###kwN075###Unilorin###Ilorin East###Kwara

###Ilorin

47###kwN014###Sobi###West###Kwara

48###abN079###Wuse###Wuse###Abuja

49###oyN004###Agoare###Atisbo###Oyo

50###oyN007###Alakuko###Oorelope###Oyo

51###oyN012###Iseyin###Iseyin###Oyo

52###oyN029###Araromi###Oyo###Oyo

52###imN063###Obowo###Imo

53###imN065###Obowo###Imo

54###osN021###Iwo###Iwo###Osun

55###osN022###Ejigbo###Ejigbo###Osun

56###osN027###Owode###Osun

###Etsako

57###edN036###Agbede###West###Edo

###Benin

58###edN038###Uniben###City###Edo

59###edN039###Uselu###Egor###Edo

###Oshimili

60###deN042###Parkinson###South###Delta

61###deN044###Agbor###Delta

62###anN045###Onitsha###Onitsha###Anambra

63###anN047###Infite###Awka###Anambra

64###anN048###Aniocha###Aniocha###Anambra

###Enugu

65###enN052###UNN###South###Enugu

66###enN054###Orba2###Awka###Enugu

67###onN071###Idepe###Okitipupa###Ondo

68###onN073###Owo###Owo###Ondo

69###oyN080###Irawo-ile###Atisbo###Oyo

70###oyN011###Alagutan###Oorelope###Oyo

49###oyN004###Agoare###Atisbo###Oyo

50###oyN007###Alakuko###Oorelope###Oyo

51###oyN012###Iseyin###Iseyin###Oyo

52###oyN029###Araromi###Oyo###Oyo

52###imN063###Obowo###Imo

53###imN065###Obowo###Imo

54###osN021###Iwo###Iwo###Osun

55###osN022###Ejigbo###Ejigbo###Osun

56###osN027###Owode###Osun

###Etsako

57###edN036###Agbede###West###Edo

###Benin

58###edN038###Uniben###City###Edo

59###edN039###Uselu###Egor###Edo

###Oshimili

60###deN042###Parkinson###South###Delta

61###deN044###Agbor###Delta

62###anN045###Onitsha###Onitsha###Anambra

63###anN047###Infite###Awka###Anambra

64###anN048###Aniocha###Aniocha###Anambra

###Enugu

65###enN052###UNN###South###Enugu

66###enN054###Orba2###Awka###Enugu

67###onN071###Idepe###Okitipupa###Ondo

68###onN073###Owo###Owo###Ondo

69###oyN080###Irawo-ile###Atisbo###Oyo

70###oyN011###Alagutan###Oorelope###Oyo

SAMPLE PREPARATION

Young fresh leaf samples of the 70 accessions were harvested and lyophilized for three days and stored at - 20degC at Bioscience Laboratory of the International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria.

DNA extraction and Quantification

The native DNA was extracted using Cetyl Trimethyl Ammonium Bromide (CTAB) procedure described by FAO/IAEA [31]. The DNA was visually quantified using NanoDrop Spectrophotometer (Nanodrop Technologies, Inc. Wilmington, DE, U.S.A) at 230, 260 and 280 nm, on 1.5 % agarose gel. DNA samples were stored at - 20degC until use.

Source of SSR Primers

Twenty SSR polymorphic microsatellite markers specific to M. oleifera [25] were adopted and used for this study. The 40 oligonucleotides (20 bases F/R) with code number (IBOL0001) were synthesized and supplied by Inqaba biotechnical Industries (Pty) Ltd, South Africa.

PCR amplification reaction

The PCR reactions of 10 l contained 3.0 l of native DNA (100 ng / l), 1.0 l of 10 X PCR buffer, 0.4 l of MgCl2 (50 mM), 0.5 l each of SSR primer mix (Forward and Reverse primers, 5 M), 0.8 l of DNTPs (2.5 mM), 0.8 l of DMSO, 0.1 l of taq polymerase (5 u/ul) and 2.9 l of sterile double distilled water. The amplification reaction was performed using te Applied Biosystems thermal cycler (GeneAmp PCR system 9700, USA) with the following programs; initial denaturation at 94.0degC for 5 minutes, final denaturation at 94.0 degC for 15 seconds, annealing at 65.0degC for 20 seconds and extension at 72.0degC for 30 seconds (9 cycles). The reactions also followed another 35 cycles of 94.0degC for 15 seconds, 55.0degC for 20 seconds, 72.0degC for 30 seconds and a final extension at 72.0degC for 7 minutes. The PCR products were resolved on 1.5 % agarose gel and visualized using the automated trans-illuminator (ENDURO GDS) with digital camera compatible with Window/Vista.

A 1000 bp ladder plus generuler (Thermo Scientific) was used to determine band sizes.

SSR PAGE Analysis

The amplified products were resolved on 6 % (w/v) polyacrylamide gel electrophoresis (PAGE) for 2.5 hours in 1 X Tris/borate/EDTA buffer with 7.5 M urea at 70 W according to the manufacturer's protocol. The gels were stained with silver nitrate [32, 33]. The size of DNA bands in base pairs was estimated using 1000-bp ladder (Thermo Scientific(r)). Gels output files were saved as TIFF format for scoring and analysis.

Statistical Analysis

Each SSR fragment was scored for their presence (1)/absence (0), size and polymorphisms. PowerMarker software program [34] was used to determine Nei [35] gene diversity, Shannon information index [36], number of alleles (Na), expected heterozygosity (HE) and observed heterozygosity (Ho). Allelic Polymorphic Information Content (PIC) and fixation index were estimated. Genetic similarity and genetic distance estimated by Nei's coefficient between pairs were analyzed using Popgene software version 3.5 [37]. The total numbers of alleles, number of alleles with a frequency of < 5 %, the number of private alleles, number of alleles found in more than 25 % and 50 % of the accessions from sub-groups according to source of samples, mean diversity and expected and unbiased expected heterozygosity were evaluated using GenAlEx 6.501 [38].

Analysis of Molecular Variance (AMOVA) using data matrix to partition the genetic variation into, within and among the populations' components was also determined using GenAlEx software [38]. Principal coordinate analysis (PCoA) and scores for the first and second components were plotted using Minitab software. Genetic similarity between different accessions were estimated based on Jaccard's similarity (J) coefficient using a SIMQUAL programme of NTSYSpc v. 2.20 [39]. Jaccard's similarity coefficients of different accessions were also used to construct UPGMA dendrograms for SSR markers using SAHN programme of NTSYSpc v. 2.20 [39].

RESULTS

SSR Primers Genetic Information/Polymorphisms

In this study, twenty polymorphic microsatellites [25] were used to analyze the intraspecific diversity among 70 accessions of Moringa oleifera. Ten SSR primers did not satisfactorily reflect/show clear polymorphisms among the accessions, and as such were not included in the analysis. The sequences and repeat motifs of the primers used are shown in Table 2 while Table 3 shows the summary of genetic estimates of the SSR primers used for this study. The primers generated polymorphic bands, which varied in size from 100 bp to 460 bp. A total of 74 alleles was detected in all the 70 accessions of M. oleifera with a mean value of 7.4 alleles per locus for each accession. Among these 74 alleles, 5 % were considered as rare (showed an allele frequency of < 5 %) (Table 3 and 4). The numbers of alleles per locus ranged from 4 in locus MO18 and locus MO61, to 15 in locus MO15 with an average of 7.4.

Major allele frequencies observed varied and ranged from 0.214 for locus MO15 to 0.671 for locus MO13 and locus MO58, with a mean value of 0.477. Generally, the genetc diversity was high ranging from 0.487 for locus MO13 to 0.885 for locus MO15 with a mean value of 0.669. The polymorphic information content (PIC), which represents the allele diversity for a specific locus ranged from 0.430 for MO13 to 0.875 for MO15 with an average mean value of 0.633. The most informative markers were primers MO6, MO8, MO12, MO15 and MO46 with PIC values of 0.676, 0.782, 0.820, 0.875 and 0.701, respectively. For markers with higher PIC values, frequent alleles occurred in [?] 45 % of the accessions. The observed heterozygosity per primer ranged from 0.00 in MO18, MO16 and MO48, to 0.500 in MO12 with an average of 0.972.

The expected heterozygosity per primer ranged from 0.000 to 0.250 with an average of 0.567 while Shannon information index (I) ranged from 0.000 in locus MO13 to 0.347 in locus MO12 with a mean value of 0.048 (Table 3). The markers were more informative than the others with respect to allelic patterns across the populations in the assessment of the genetic diversity among the 70 accessions. For instance, locus MO6 and MO8 recognized 3 more private alleles each with frequencies of 0.083 and 0.250 for North-central and South-west accessions, while locus MO12 identified 5 private alleles with a frequency of 0.50 for South-south accessions. However, marker with locus MO15 detected a higher number of private alleles (10) and recorded the frequency of 0.834 for South-west accessions.

Allelic Pattern Across the Sub-groups/populations

Mean allelic patterns across the sub-groups/populations, according to the source of samples were also estimated to determine allele's variability among the populations. The numbers of different alleles (Na) were similar for North-central, Northeast, North-west, South-south and South-east subgroups with 0.80, 0.70, 0.90, 0.80 and 0.90, respectively, while South-west sub group/population was higher with 1.50 (Table 5). The analysis showed that only the South-west collections detected a higher number of different alleles (Na = 1.50), effective alleles (Ne = 1.32) and private alleles (0.40). For Shannon Information Index (I), 0.02 was recorded for North-central; Northeast 0.00, North-west, South-east and South-south recorded 0.07 each while South-west recorded 0.27. There were no unique (private) alleles among the Northeast, North-west and Southeast subpopulations, North-central and South-south recorded 0.10 each while South-west recorded 0.40.

Also, there were no locally common alleles (frequent [greater than or equal to] 5 %) found in 25 % or fewer population across the six subgroup/populations. However, at 50 %, North-west and Southeast recorded 0.20 each, South-south 0.10 while South-west recorded 0.27. The expected heterozygosity (He) was low across board, with North-east (0.00), North-central (0.02), North-west (0.05), South-east (0.05), South-south (0.05) and South-west (0.07). The unbiased expected heterozygosity (uHe) was also low and ranged from 0.00 for northeast to 0.11 to southwest. This indicates that among the subgroups/populations, intraspecific diversity is low. The percentage of polymorphic loci across the populations shows the following; North-central 10.00 %, Northeast 0.00 %, North-west 10.00 %, South-south 10.00 %, Southeast 10.00 % and South west 40.00 %.

With respect to accessions with number of one or more private alleles, one accession each was identified for North-central (KaN034) and South-south (edN039), while five accessions were recognized for the South-west population (onN070, onN074, onN072 and oyN005) by the markers.

Table 2. The Sequences And Repeat Motif Of The Primers Used For This Study.

Locus###Forward Sequence (5' - 3')###Repeat Motif

###Reverse (5' - 3')

MO6###FGCATAGCCACCTTTACTCCT###(AG)T(AG)6

###RGACTTTTGAACTCCACCACC

MO8###FGTAGATGGTGCAGCTACTCA###(CT)13

###RTGGGGTTCTTGTTCTTTATT

MO12###FACCGAAGATGATAAGGTGGG###(CT)11

###RCAAAAGGAAGAACGCAAGAG

MO13###FTTTCGGGTTTTCTTTCACGG###(CT)15

###RAGCTCACTTTCCATCTCCAT

MO15###FCCCCTCTATTTCCATTTTCC###(TC)10CCT(TC)

###RGCTCCATAAACCCTCTTGCT###6

MO18###FTTTTCCTCCCTTATTGTGCC###(GA)6A(AG)16

###RCCGTTGCCCTTTGTGGTTCA

MO46###FACCAAGGGTTTCAACTGCTG###(AG)5-(GA)6

###RCATTTTGCGACGGTCTCACG

MO48###FAGAAGAACCCAACAGAGGAT###(TC)8C(CT)15A(

###RCTTTTCACTAACCACCACCC###AC)7

MO58###FTGGATTTCTTCTCCTGCTAT###(CT)6T(TC)9

###RCACAGTTCTTATTGTATTGG

MO61###FTGTGGGTCCTGCCTTTTCTC###(TC)11

###RCTTCTGTCTTTCTTCCTGCT

Table 3. Summary Of Genetic Parameters Estimates Of The Ssr Markers Used For This Study

Locus###MAF###NA###GD###PIC###Ho###He###I

MO6###0.414###7###0.719###0.676###0.028###0.025###0.048

MO8###0.343###9###0.782###0.753###0.083###0.063###0.094

MO12###0.271###13###0.838###0.820###0.500###0.250###0.347

MO13###0.671###5###0.487###0.430###0.000###0.000###0.000

MO15###0.214###15###0.885###0.875###0.111###0.083###0.145

MO18###0.571###4###0.587###0.529###0.000###0.000###0.000

MO46###0.371###5###0.743###0.701###0.000###0.000###0.000

MO48###0.629###5###0.564###0.530###0.000###0.000###0.000

MO58###0.671###7###0.520###0.493###0.250###0.146###0.209

MO61###0.614###4###0.565###0.520###0.000###0.000###0.000

Total###0.477###7.4###0.669###0.633###0.972###0.567###0.048

Percentages of Molecular Variance among and within Populations (AMOVA)

The result of analysis of molecular variance (AMOVA) among and within populations of M. oleifera is shown in Table 4. Based on this, 8 % of the genetic diversity was attributed to differences among the populations while 92 % of the variation (significant at p = 0.001; after 999 permutations) were due to differences within populations. This indicates higher intraspecific diversity within the populations and less among the populations. Figure 3 shows the percentages of molecular variance among and within populations of M. oleifera.

Table 4. Amova Among And Within Populations Variations

###TV###p-

Source###df###SS###MS###EV###%###value*

Among###<0.001

Pops###5###61.733###12.347###0.551###8%

Within###=###0.80###0.70###0.90###0.90###0.80###1.50

5%

Ne###0.72###0.70###0.90###0.90###0.80###1.32

I###0.023###0.00###0.07###0.07###0.07###0.27

No. private###0.10###0.00###0.00###0.00###0.10###0.40

alleles

No. frequent###0.00###0.00###0.00###0.00###0.00###0.00

alleles

(<=25%)

No. frequent###0.00###0.00###0.20###0.20###0.10###0.40

alleles

( 75 % genetic similarity coefficient (Fig. 5). Some of the main cluster groups obtained from the UPGMA tree and PCoA were correlated with the geographic regions/areas of collection of the accessions. For instance, cluster group A in Fig. 4 and Fig. 5 consists of accessions from all the sub regions/populations and corresponds to their geographical regions of collection. This is in agreement with the studies of Matus and Hayes [47] on Barley (Hordeum vulgare L.), which coincided with geographic origin. Several other researchers have also reported correlation between germplasms collections and geographical distribution [43, 48, 49].

In addition, the grouping of 68.57 % of the accessions in cluster A of PCoA (Fig. 4) and the intermixing of colors across the coordinate further support the allelic connectivity earlier observed among the subpopulations. The accessions from the North-west were the most distinct and centrally placed within the scatter group A which suggest the North-west as the primary point of spread of M. oleifera to other regions (Fig. 4). Also the closeness of North-central accessions to the North-west presupposes that M. oleifera accessions may have been introduced to Southern Nigeria from North-west via North-central and then to all south regions of Nigeria.

The clustering system of CA indicated that cluster groups shared a large number of alleles hence resulting into overlap/random distribution of accessions across the cluster groups except sub cluster A3. The widespread distribution of accessions particularly in cluster group A and C showed the ability of the Moringa oleifera accessions to adapt to varying/diverse climatic conditions across Nigeria. M. oleifera is highly adaptable to varying ecological conditions both in its native and introduced ranges in temperate, semi-arid and arid regions [3, 50, 51]. Similarly, accessions collected from the same source were grouped in the same cluster group indicating close affinity between accessions while accessions with different genetic background were clustered in single cluster (Figure 5).

Clustering of over 50 % (47) accessions in cluster group A (Fig. 5) buttressed the view that geographical distribution and genetic divergence do not follow the same pattern as many accessions from differing locations were clustered together [52]. Similar observations have been reported in many tree species including M. oleifera [22, 44, 53]. The cluster analysis with low genetic distances indicated that the accessions are closely related and could have a recent common ancestor. For instance, in cluster group A sub cluster A1 with 8 accessions, beN081 collected from Benue (North-central) Nigeria, where M. oleifera is apparently endemic may probably be the ancestor accession/source for other accessions. Likewise, for sub cluster A2 with greater number of collections and hence wide ancestral relationship may likely be traced to either plN030 from Plateau State or KaN034 from Kaduna State and alternatively from yoN031 (Yobe State) through exchange of planting materials and trade routes.

The closeness of accessions abN057 and anN049 in sub cluster A1and the similarities of accessions (soN066 and taN085) in sub cluster A2 and accessions (anN045 and anN045) in cluster C also reinforced the possibility of similar ancestral relationship. These two pairs of accessions (soN066 and taN085) and (anN045 and anN045) appeared to be 100 % identical; however, accessions anN045 and anN045 collected from the same locations (Anambra state) might be regarded as duplicates while other accessions were distinguishable at similarity coefficient of 1.0. Two accessions (soN066 and taN085), were geographically divergence (Sokoto and Taraba) but genetically identical indicating possibility of same ancestral relationship. Similar reports have suggested same ancestors for genetically closely connected accessions/species in other plants including M. oleifera [45, 52, 54].

The spread of planting materials in form of cuttings, seeds and seedling via exchange may have also enhanced rates of gene flow between adjacent populations and thereby contributing to the distribution of accessions in cluster groups and intraspecific relationship among the accessions. The clustering of accessions in cluster group B and D, however, was quite different without any connection with accessions from any of endemic areas of M. oleifera in Nigeria. Cluster group B contained only two accessions (onN074 from Ondo and oyN029 from Oyo) and cluster group D had four accessions (enN052 and enN054 from Edo State; onN071 and onN073 from Ondo Sate) indicating that the accessions have potential inherent diversity that can be exploited for genetic improvement and breeding purposes. Therefore crossing between accessions of cluster A and cluster B or D might possibly create more variability for increased yield and utilization of the species.

Implication for conservation and utilization

The use of SSR markers have apparently enriched our understanding of the level of genetic relationship existing among the accessions of M. oleifera, which can be exploited for future Moringa breeding program. The collections are of great significance as major landraces in Nigeria with valuable agronomic traits [6], which can be cultivated as Moringa plantation for utilization as leafy vegetables, food and medicine, oil from seeds and also for other product development. Since there was no clear genetic differentiation among the populations and duplications among the accessions other than 100 % resemblance of two pairs of accessions (soN066 and taN085) and (anN045 and anN045) observed; all other accessions were independent at similarity level of 1.00, these accessions could, therefore, be given high priority in situ conservation.

Likewise, there was no suspicion of loss of genetic intraspecific variation among the accessions studied; combining the in situ and ex situ conservation as management strategies will practically enhance utilization for breeding program and other socio-economic uses of M. oleifera in Nigeria and elsewhere. The allelic patterns plot, which highlighted the possibility of genetically homogenous accessions could be mitigated by systematic increase in collection of accessions, which can also enhance the creation of core collection of M. oleifera for conservation and utilization to meet the increasing demand for Moringa products.

CONCLUSION

The present study significantly contributes basic information towards the implementation of appropriate conservation and utilization plans as well as potential breeding trial programs for Moringa oleifera genetic resources in Nigeria. Simple sequences repeats (SSRs) markers are indeed very efficient in the genetic intraspecific diversity study of M. oleifera in Nigeria. Relatively high genetic diversity within population and low among populations are useful as accessions/planting materials for continuous use for cultivation, breeding and utilization purposes. As a result of weak gene pool arising from exchange of same planting materials and increased gene flow among the accessions, there is need to further broaden the genetic diversity of the species via germplasm collections particularly from the endemic Northern regions for systematic characterizations.

On the whole, this study is a timely contribution considering the multi-purpose economic importance of the species, its wide distribution, adaptation and ease of integration into commercial agricultural production.

ACKNOWLEDGEMENTS

The authors acknowledge the management of Covenant University and Centre for Research, Innovation and Development of the University for project funding (Grant No. CUCRID RG 003.10.14/FS) granted to Moringa Research Cluster Group (MRCC) under the supervision of Prof. Olawole O. Obembe. We also extends thanks to Dr. Agre Paterne of Bioscience, International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria for his assistance while working in the Lab.

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Table (Appendix 1): Pairwise Population Matrix of Nei Unbiased Genetic Distance

###North Central###North East###North West###South East###South South###South West

North Central###0.000

North East###0.360###0.000

North West###0.308###0.304###0.000

South East###0.326###0.322###0.269###0.000

South South###0.450###0.458H###0.365###0.424###0.000

South West###0.251###0.247###0.123L###0.141###0.312###0.000

Appendix 2: Pairwise Population Matrix of Nei Unbiased Genetic Identity

###North Central###North East###North West###South East###South South###South West

North Central###1.000

North East###0.698###1.000

North West###0.735###0.738###1.000

South East###0.722###0.725###0.764###1.000

South South###0.638###0.632L###0.694###0.655###1.000

South West###0.778###0.781###0.884H###0.868###0.732###1.000
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Author:Popoola, Jacob O.; Bello, O.A.; Olugbuyiro, J.A.; Obembe, O.O.
Publication:Science International
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Geographic Code:6NIGR
Date:Jun 30, 2017
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