Popoola et al 2020 Parkia paper

ISSN- 2394-5125 VOL 7, ISSUE 11, 2020
ASSESSMENT OF GENETIC DIVERSITY OF
AFRICAN LOCUST BEAN (PARKIA BIGLOBOSA
JACQ.) LANDRACES USING MICROSATELLITE
MARKERS
Jacob Olagbenro Popoola 1, 2* , James Oludare Agbolade 3, 4 , Abiodun Ajiboye 3 , Omotolani Akinola 1 , Francis
Bayo Lewu 5 , Joseph Kioko 6 and Conrad Asotie Omonhinmin 1, 2 .
1 Department of Biological Sciences, College of Science and Technology, Covenant University, PMB 1023,
Canaanland Ota, Ogun State, Nigeria.
2 Biotechnology Cluster Group, Covenant University Centre for Research, Innovation, and Discovery.
3 Department of Plant Science and Biotechnology, Federal University, Oye Ekiti, Ekiti, Nigeria.
4 Department of Biodiversity and Conservation, Cape Peninsula University of Technology, South Africa.
5 Department of Agriculture, Faculty of Applied Sciences, Cape Peninsula University of Technology, South
Africa
Email: jacob.popoola@covenantuniversity.edu.ng.
Received: 14 March 2020 Revised and Accepted: 8 July 2020
ABSTRACT: Parkia biglobosa, commonly called African locust bean, is rich in nutrition and pharmacological
properties that can be explored in the food and drug industry. However, its cultivation and production is
declining and genetically threatened in its natural ranges. This study determined the genetic diversity among 19
landraces of P. biglobosa collected from different agroecological areas (AEAs) in Nigeria using microsatellite
markers. Genomic DNA was extracted using the modified sodium dodecyl sulfate (SDS) protocol, while
amplification was performed using five primer pairs of PbL02, PbL03, PbL04, PbL05, and PbL09. Genetic
diversity was analyzed using descriptive statistics and a dendrogram. The five markers were highly
polymorphic, with a mean of 70.25 %. The polymorphic information content (PIC) was relatively high, ranging
from 0.51 to 0.89, with a mean of 0.72. The allelic richness per locus ranged from 5 to 15, while major allele
frequency ranged from 0.26 to 0.63 with a mean of 0.41. The gene diversity within a population (Hs) was quite
low, with a mean of 0.28 ± 0.01, while the estimate of gene flow among the landraces was relatively high (17.50
– 2.03). The Coefficient of gene differentiation (Gst) of 0.10 indicates that about 10 % of the total genetic
divergence was among populations and 90 % within the populations. The dendrogram based on the UPGMA
method classified the 19 landraces into three distinct genetic clusters that shared quite some alleles and allocated
landraces from different AEAs into the same cluster except cluster II. The study identified four genetically
distinct landraces (Pb18, Pb16, Pb17, and Pb19) that are potentially good as parental lines for heterosis crossing.
In contrast, cluster I with diverse landraces could be exploited for commercial cultivation, and conservation
purposes.
KEYWORDS: African locust beans; Agro-ecological areas (AEAs); cluster analysis; genetic diversity,
microsatellite markers; landraces.
I. INTRODUCTION
Parkia biglobosa (Jacq.), commonly called African locust bean, is an oilseed legume that belongs to the
subfamily Mimosoideae of the family Fabaceae (Hopkins, 1983). It is well-distributed in many African
countries such as Benin Republic, Togo, Nigeria, Ghana, Mali, Niger, and Cameroon. It is one of the indigenous
tree species that produce essential non-timber forest products for people in Sub-Saharan Africa (Houndonougbo
et al., 2020). African locust bean is a good source of woody products and, most importantly, rich in nutrition and
medicine. The pods containing-seeds are highly nutritious and rich in protein (Agbani et al., 2018; Ouédraogo et
al., 2012; Tringali, Spatafora, & Longo, 2000). Locally, the seeds are processed into spicy food/condiments in
soups while the pods and husks are sources of animal feed (Fetuga, Babatunde, & Oyenuga, 1974; Rendu,
Saleun, & Auger, 1993). Different parts of the tree such as seeds, bark, roots, and flowers are used as a source of
herbal remedy to treat illnesses such as malaria, diabetes, hypertension amongst others (Abioye et al., 2013;
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Adetutu, Morgan, & Corcoran, 2011; Kouadio et al., 2000). The African locust bean tree is also a good source
of firewood, charcoal, and timber. The woody timber parts are used to make bows, pestles, hoe handle, mortars,
and seats (Adetutu et al., 2011; Aiyelaagbe, Ajaiyeoba, & Ekundayo, 1996; Traore et al., 2013). Its seeds'
annual production was estimated above 200,000 t while the processed grains were reported to have high market
and socio-economic value in Nigeria (Babalola, 2012; Sina & Traoré, 2002).
Despite the vast economic significance and cultural values of African locust bean for local and regional
economies, its area of cultivation and production is declining without reforestation and breeding strategies
insight. Recent studies have shown that domestication of the species is at the infant stage, while regeneration is
rapidly decreasing (Lompo et al., 2017). Genetic resources are fading away, and improved tree management
practices are lacking while genetic improvement is not sufficiently promoted. In the field survey and sample
collections for this study, we observed possible loss of genetic resources among the neglected but extensively
versatile indigenous species in Nigeria. These genetic resources are vanishing at an alarming rate linked to
political instability, massive unregulated developmental activities, climate change, weak or nonexistent
conservatory programs, and erosion of cultural heritages. The management and conservation of African locust
bean's genetic resources across the major AEAs are lacking, yet there is increased demand for its use and
derivable products. Individual landraces affected by land clearing, bush fire, deforestation, old age, and climatic
change are not replaced through the conscious effort of cultivation, afforestation, and research. To our
knowledge, no active germplasm is available on P. biglobosa, available landraces were old, exposed to the bush
fire burning from time to time, and over-exploitation by users. Thus, there is a need for concerted research
efforts to increase its cultivation and production, improve its conservation and management of its genetic
resources toward sustainable utilization for food and medicinal purposes.
African locust bean is a monoecious and highly outcrossing crop with amphipolyploidy genome chromosome
numbers (2n = 2x = 22, 24, and 26) (Uyoh, Urua, Ntui, & Okpako, 2011), the genetic diversity is expected to be
high. However, there is a lack of adequate and consistent data on its genetic diversity. Also, very few genetic
diversity studies using marker-based analysis are available on the species in Nigeria. Amusa et al. (2014)
studied 23 open-pollinated accessions of the species using RAPD and reported a weak genetic diversity among
the accessions. The studies of Adesoye and Apo (2015) also indicated a high similarity in the polypeptide
profiles of the 34 samples studied using seed protein electrophoresis. However, studies have shown that
microsatellite markers are better and versatile in the determination of genetic diversity, population genetics, and
reproductive biology as well as in demarcation of genetic groupings of many plant species including African
locust bean (Toth, Gaspari & Jurka, 2000; Lassen et al., 2014; Yang et al., 2019). These markers are abundant in
eukaryotic genomes, highly polymorphic with co-dominant inheritance, and fitted for automated allele sizing
and cross-species transferability (Zia et al., 2014). To effectively use the genetic resources of P. biglobosa for
improvement and sustainable utilization, it is pertinent to understand its diversity. Therefore, more genetic
characterizations and seed yield capacity of different populations/landraces from different agroecological areas
are needed to lay a solid foundation for developing sustainable conservation and breeding systems to meet the
increased demands of its products. Hence, the present study was designed to collect some landraces of African
locust bean from different agroecological areas (AEAs) in Nigeria, and determine their genetic diversity using
microsatellite markers to identify unique genotypes for cultivation and breeding purposes.
II. MATERIALS AND METHODS
Areas of collection and Sample Preparation: A total of 19 landraces/open-pollinated P. biglobosa was
selected from the field survey on sample collection of the genetic diversity assessment of under-exploited
African plants for genetic improvement and food security (Omonhinmin et al., 2016). The selected landraces cut
across five major agroecological areas (AEAs) in Nigeria, as shown in Table 1 and Figure 1. Young leaf
samples of the 19 landraces were silica gel dried in well-labeled zip-lock bags. The crystals were removed and
moisture-free samples kept at – 80 °C at the Molecular Biology Laboratory, Bioscience Department, Covenant
University, Ota, Nigeria. The samples were transferred to the Bioscience Laboratory of the International
Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria, and lyophilized for 72 hours before the
DNA extraction.
Sources of Primers and DNA Extraction: Five out of the ten microsatellite primers (SSR) developed for
African locust bean (Lassen et al., 2014) were selected, tested, and used for this study. The primers ten bases
(R/F) were supplied by Ahava Biotechnology and Forensic Services Ltd (Nigeria) with the code number
(NG2018/049). The locus name and sequences were presented in Table 3. Genomic DNA was extracted using
the modified sodium dodecyl sulfate (SDS) method (Dellaportal et al., 1983). The quality and quantity of the
extracted DNA were determined using 1% agarose gel in a NanoDrop spectrophotometer (ND-1000).
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PCR amplification and PAGE analysis: The PCR amplification was performed previously described by
Popoola et al. (2017). Briefly, the 10 μl reaction consisted of 0.4 μl of 50 mM MgCl 2 , 1.0 μl 10 X PCR buffer,
0.5 μl each of reverse and forward primer mix in 0.8 μl of 2.5mM dNTPs, 0.8 μl of dimethyl sulfoxide, 2.9 μl of
sterile double distilled water, 0.1 μl of Taq polymerase (5 u/ul) and 3.0 μl of 100 ng / μl DNA. A total of 10 μl
was reacted in a GeneAmp PCR system 9700 (USA) using a touchdown PCR program for 9 cycles and 30
cycles, as described by Popoola et al. (2017). To resolve the amplified products, 6 % (w/v) non-denaturing
Polyacrylamide gel in 1 X TBE buffer with 7.5 M urea were prepared based on manufacturer’s protocol
(ThermoFisher Scientific, USA) and allowed to stay for 1.5 hours at 70 W. A 1000-bp ladder (ThermoFisher
Scientific, USA) was used to estimate the DNA band size in base pairs.
Data Analysis: Scoring was done using the gel output files under Photo light (UMAX power look, 2100XL).
Bright and scorable bands were traced and scored as discrete numbers (absent = 0, present = 1), and data entered
into an Excel sheet (Microsoft, 2013). The Power Marker v.3.25 software (Liu & Muse, 2005) was used to
estimate genetic parameters such as allele count and frequency, major allele frequency, gene diversity and PIC
values for each of the marker. The Popgene software version 3.5 (Yeh et al., 1999) was used to evaluate the
genetic diversity and population structure parameters, as highlighted in Tables 4 and 5. The unweighted pair
group method average (UPGMA) procedure was followed to generate a dendrogram using NTYSYSpc 2.1
software (Rolf, 20020).
Table 1: Collection of P. biglobosa landraces from different Agroecological areas (AEAs) of Nigeria.
Location State Agroecological areas (AEA) Landrace No
Bunyayi Adamawa Sudan Savannah Pb1
Katsina-Ala Benue Southern Guinea Savannah Pb2
Gurzumo Bauchi Sudan Savannah Pb3
Abaji Abuja Southern Guinea Savannah Pb4
Ture-Balam Gombe Sudan Savannah Pb5
Ehanle-Ewu Edo Wet lowland rain forest Pb6
Ishielu Ebonyi Wet lowland rain forest Pb7
Karshi Kaduna Southern Guinea Savannah Pb8
Besse Kebbi Northern Guinea Savannah Pb9
Gwarmai Kano Sudan Savannah Pb10
Mashjigwari Kaduna Northern Guinea Savannah Pb11
Dada Village Kebbi Northern Guinea Savannah Pb12
Onipako Kaiama Kwara Northern Guinea Savannah Pb13
Wawa/New Bussa Niger Northern Guinea Savannah Pb14
Batagi
Niger
Southern Guinea Savannah
Pb15
Iseyin Road Oyo Southern Guinea Savannah Pb16
Shagari Sokoto Sudan Savannah Pb17
Jol Plateau Jos Plateau Mosaic Pb18
Maru Zamfara Sudan Savannah Pb19
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III. RESULTS AND DISCUSSION
Figure 1: Location of accessions on the Map of Nigeria
Allele frequencies and Genetic characteristics of the markers used in this study.
The frequency of alleles per marker varied greatly. The scorable number of alleles ranged from 1, with a
frequency of 0.05 to 12 with a frequency of 0.63 (Table 2). Marker PbL02 and PbL09 at different allele count
generated 8 alleles, each with a frequency of 0.42, while PbL04 generated 6 alleles with a frequency of 0.32.
Markers PbL03 and PbL04 at different alleles produced 4 alleles, each with a frequency of 0.21 while PbL05
and PbL09 produced 5 and 3 alleles with a frequency of 0.26 and 0.21, respectively. Generally, PbL05
generated the lowest allele count of 1 with a frequency of 0.05, while PbL03 generated the highest allele count
of 12 with a frequency of 0.63 (Table 2). Overall, 40 alleles out of which 28 (70 %) were polymorphic with a
mean of 5.60 alleles per microsatellite primer were obtained from this study. The number of alleles per primer
ranged from 5 alleles in locus PbL03 to 15 alleles in PbL05. Loci PbL03 and PbL09 generated the least
polymorphic number of alleles (4 each), while locus PbL05 generated the highest alleles and the polymorphic
number of alleles (Table 3). The range of alleles recorded in this study (5 – 15 alleles) is comparable to the
studies of Lassen et al. (2014) and higher than previously reported on some tree species (Allal et al., 2011;
Logossa et al., 2011). The major allele frequency (MAF) ranged from 0.26 to 0.63, with a mean of 0.41. The
PbL03 showed the highest MAF (0.63), while PbL05 the lowest (0.26). Gene diversity (GD) values at all loci
were quite high, with a mean of 0.75. The GD was highest in PbL05 while it was lowest in PbL03 (0.55). Locus
PbL05 also showed the highest PIC value (0.89), while PbL03 the lowest (0.51). The five microsatellite markers
are highly polymorphic with a mean of 70.25%, while locus PbL05 appeared to be more effective than the
others. The mean PIC of 0.72 was relatively high, representing allele diversity, which indicates high genetic
polymorphism among the studied landraces of African locust bean. The existence of high polymorphism in this
study aligns with the report of Amusa et al. (2014) on P. biglobosa and that of Kaur et al. (2016) on Tribulus
terrestris. Similarly, the mean percent polymorphism (70.25%) was high and comparable to previous reports on
forest trees including P. biglobosa (Dainou et al., 2016; Kaur, Sharma, Singh, Wani, & Gupta, 2016; Popoola,
Bello, Olugbuyiro, & Obembe, 2017). This finding can be attributed to the adaptation of the species to the
different eco-geographical settings, continuously spreading and possibly the amphipolyploidy nature of P.
biglobosa genome with varying numbers of chromosomes (2n = 2x = 22, 24, and 26) (Uyoh et al., 2011).
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Table 2: Allele count and frequencies at the Microsatellite Loci of the 19 studied P. biglobosa
Marker Allele Allele count Frequency
PBL02 0/0/0 2 0.11
PBL02 0/0/1 8 0.42
PBL02 0/1/0 2 0.11
PBL02 0/1/1 2 0.11
PBL02 1/0/0 1 0.05
PBL02 1/0/1 3 0.16
PBL02 1/1/0 1 0.05
PBL03 0/0/0 12 0.63
PBL03 0/0/1 1 0.05
PBL03 0/1/0 4 0.21
PBL03 1/0/1 1 0.05
PBL03 1/1/1 1 0.05
PBL04 0/0/0/1 4 0.21
PBL04 0/0/1/0 2 0.11
PBL04 0/1/0/0 6 0.32
PBL04 0/1/1/0 4 0.21
PBL04 1/0/0/0 1 0.05
PBL04 1/1/0/0 1 0.05
PBL04 1/1/1/0 1 0.05
PBL05 0/0/0/0/0/0 1 0.05
PBL05 0/0/0/0/1/0 1 0.05
PBL05 0/0/1/0/0/0 1 0.05
PBL05 0/0/1/0/0/1 5 0.26
PBL05 0/0/1/0/1/0 1 0.05
PBL05 0/1/0/0/0/0 1 0.05
PBL05 0/1/0/0/0/1 1 0.05
PBL05 0/1/0/0/1/0 1 0.05
PBL05 0/1/0/1/0/1 1 0.05
PBL05 0/1/1/0/0/0 1 0.05
PBL05 0/1/1/0/0/1 1 0.05
PBL05 0/1/1/0/1/0 1 0.05
PBL05 1/0/0/1/0/1 1 0.05
PBL05 1/0/0/1/1/0 1 0.05
PBL05 1/1/0/1/1/0 1 0.05
PBL09 0/0/0/0 4 0.21
PBL09 0/0/0/1 8 0.42
PBL09 0/0/1/0 2 0.11
PBL09 0/0/1/1 1 0.05
PBL09 0/1/0/0 3 0.16
PBL09 0/1/0/1 1 0.05
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Table 3: List of Microsatellite Primers and Genetic parameters for P. biglobosa studied.
S/
N
Loc
us
Primer (5 ′ –3 ′) Primer reverse (5 ′ –3 ′) Rep
eat
Moti
f
CGAAATAAGAACTCGGA ATGCCGTGTTCTGTTT (GA
CCAAA
CACC
) 17
TTCGATTCAATTCAACTT TCGGTGCTAGCAATA (GA
GCAG
TCAGC
) 17
GAAGCCTTGGAATGAAG GAAAACGGAAGGCAT (CA
TTGA
GGTTA
) 17
GAATCAGAGAAGCCCTT GCCGCTTGTTTTCTTG (AC
1. PbL
02
2. PbL
03
3. PbL
04
4. PbL
05 AGGTT
TGA
5. PbL GACGTATTTGAGTGTCTT
09 TTACACA
Mea
n
Source of primer pairs (Sequences): Lassen et al., 2014.
GCAGAAAATCACAAA
TGCAGA
) 17
(AG
) 18
NA
7.0
0
5.0
0
7.0
0
15.
00
6.0
0
8.0
0
NP
A
5.0
0
4.0
0
5.0
0
10.
00
4.0
0
5.6
0
M
AF
0.4
2
0.6
3
0.3
2
0.2
6
0.4
2
0.4
1
G
D
0.7
6
0.5
5
0.7
9
0.8
9
0.7
4
0.7
5
PI
C
0.7
3
0.5
1
0.7
6
0.8
9
0.7
0
0.7
2
NA = Number of alleles, NPA = Number of Polymorphic alleles, MAF = Major allele frequency, GD = Gene
diversity, PIC = Polymorphic information content.
Genetic diversity and population structure of P. biglobosa landraces studied.
The number of effective alleles was highest (1.87) in landrace Pb17, followed by 1.80 in Pb19 and lowest in Pb2
and Pb6 (1.22) with a mean of 1.48 ± 0.20 (Table 4). Nei’s gene diversity was highest (0.46) in Pb17 and lowest
in Pb2 (0.18) with a mean of 0.31 ± 0.09 while Shannon’s diversity values were relatively moderate with a mean
of 0.49 ± 0.10. Landrace Pb17 had the highest Shannon's information index (0.66), while Pb2 had the lowest at
0.33. The gene diversity within a population was highest (0.41) in landrace Pb17 and lowest (0.14) in Pb6 with a
mean of 0.28 ± 0.01. The estimate of gene flow among the landraces varied greatly. Two landraces (Pb10 and
Pb11) had the highest estimate of gene flow of 17.50, each followed by another two landraces (Pb4 and Pb7)
with 12.50 each while landrace Pb6 had the lowest (2.03). The mean coefficient of gene differentiation of 0.10
indicates that about 10 % of the total genetic divergence was among populations and 90 % within the
populations (Table 4). The results of the estimate of gene flow suggest the exchange of pollen grains between
populations and among landraces since the AEAs are near to each other and thus influenced the mean
coefficient gene differentiation obtained in this study. The analysis revealed that gene diversity was high in four
landraces (Pb18 = 0.39, Pb14 = 0.42, Pb17 = 0.46, and Pb19 = 0.44), indicating that collection areas of these
landraces are centers of high biological diversity and adaptation of P. biglobosa in Nigeria. The areas are Sudan
Savannah (Pb5, Pb17, Pb19), Southern Guinea Savannah (Pb16), Northern Guinea Savannah (Pb14), and Jos
Plateau Mosaic (Pb18). However, two landraces (Pb17 and 19) appear to be unique with higher genetic diversity
values (0.46 and 0.44) than others and therefore, can be adopted as potential parental lines for future cultivation
and breeding strategies. The two landraces were sourced from the same agroecological areas (Sudan Savannah),
one of the endemic and large areas of P. biglobosa in Nigeria.
Analysis of genetic correlations among the landraces of P. biglobosa and AEAs
The mean Nei’s unbiased measure of genetic identity and genetic distance (Nei, 1973; 1978) between the
different AEAs (agroecological areas) showed a high genetic identity and a close genetic distance between the
various AEAs. The analysis showed that the genetic identity among the landraces and AEAs ranged from 0.94
to 1.01 (Table 5). The highest genetic identity (1.013) was between Sudan Savannah (SS) and Northern Guinea
Savannah (NGS) areas and lowest (0.938) between wet lowland rain forests (WLRF) and Southern Guinea
Savannah (SGS) areas. Similarly, the highest genetic distance (0.064) was between landraces collected from
SGS and WLRF. The shortest genetic distance was between Sudan Savannah and wet lowland rain forest
(0.004) (Table 5). Thus, both the Southern Guienea Savannah and wet lowland rain forest agroecological areas
are considered hot spots for germplasm collection of P. biglobosa for commercial cultivation, characterization,
conservation, and exploitation for breeding. The analysis revealed that the genetic distance was generally low
across the AEAs, indicating that the 19 African locust beans landraces are closely related to common ancestry.
Several studies have reported that close natural populations like P. biglobosa exhibit high genetic
identity/similarity and low genetic distance attributed to a high rate of exchange of gene flow (pollen grains)
between populations (Amusa et al., 2014; Ojuederie et al., 2014; Popoola et al., 2017).
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Table 4: Genetic diversity and population structure of 19African locust bean using Microsatellite
markers.
Landraces Ne H I Hs Gst Nm
Pb1 1.38 0.28 0.45 0.26 0.08 5.75
Pb2 1.22 0.18 0.33 0.17 0.07 6.25
Pb3 1.30 0.23 0.39 0.20 0.13 3.21
Pb4 1.30 0.23 0.39 0.22 0.04 12.50
Pb5 1.64 0.39 0.58 0.33 0.15 2.88
Pb6 1.22 0.18 0.33 0.14 0.20 2.03
Pb7 1.30 0.23 0.39 0.22 0.04 12.50
Pb8 1.30 0.23 0.39 0.20 0.13 3.21
Pb9 1.38 0.28 0.45 0.23 0.16 2.63
Pb10 1.47 0.32 0.50 0.31 0.03 17.50
Pb11 1.47 0.32 0.50 0.31 0.03 17.50
Pb12 1.38 0.28 0.45 0.23 0.16 2.63
Pb13 1.47 0.32 0.50 0.29 0.10 4.64
Pb14 1.72 0.42 0.61 0.39 0.07 6.25
Pb15 1.56 0.36 0.54 0.32 0.10 4.53
Pb16 1.64 0.39 0.58 0.36 0.09 5.00
Pb17 1.87 0.46 0.66 0.41 0.11 3.85
Pb18 1.64 0.39 0.58 0.36 0.09 5.00
Pb19 1.80 0.44 0.64 0.38 0.15 2.83
Mean 1.48 0.31 0.49 0.28 0.10 4.41
St. Dev 0.20 0.09 0.10 0.01
Ne = Effective number of alleles, H = Nei’s gene diversity, I = Shannon’s Information Index, Hs = gene
diversity within a population, Gst = Coefficient of gene differentiation - Gst, Nm = estimate of gene flow.
Table 5: Analysis of genetic correlations among the landraces of P. biglobosa and AEAs.
AEA JPM WLRF SS SGS NGS
JPM *** 0.978 1.011 0.969 1.007
WLRF 0.023 *** 0.997 0.938 0.992
SS 0.011 0.004 *** 1.005 1.013
SGS 0.032 0.064 0.005 *** 0.954
NGS 0.007 0.008 0.013 0.047 ***
Nei's genetic identity (above diagonal) and genetic distance (below diagonal). AEA: Agro-Ecological Areas;
JPM: Jos Plateau Mosaic, WLRF: Wet lowland Rain Forest, SGS: Southern Guinea Savannah, SS: Sudan
Savannah, and NGS: Northern Guinea Savannah.
Cluster Analysis
The UPGMA cluster analysis grouped the 19 landraces of African locust bean into three major groups. Cluster I
is the most diverse, with 78.95% (15 landraces) of the total landraces studied. This cluster consisted of three
sub-clusters IA, IB, and IC (Fig. 2). Subcluster IA had 5 landraces (Pb13, Pb8, Pb7, Pb6, and Pb4), sub-cluster
IB had 4 landraces (Pb15, Pb14, Pb12, and Pb5) while sub-cluster IC had 6 landraces (Pb1, Pb2, Pb3, Pb9,
Pb10, and Pb11) (Fig. 2). Cluster II is the most distinct and had one landrace (Pb18), while cluster III had three
landraces (Pb17, Pb18, and Pb19). The clustering pattern showed that cluster groups with the outcome of
random distribution of landraces in clusters I and III shared quite some alleles except distinct cluster II. The
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analysis revealed that landraces were not necessarily classified according to the areas of a collection but were
more or less heterogeneous containing landraces from different AEAs.
Hence, the high gene flow and the random assortment of alleles explain the outcome of the cluster analysis
obtained in this study. African locust bean is an open-pollinated species with a high rate of gene flow from one
population/landrace to another through agents of pollination, and transfer of planting materials within and
among the AEAs, which led to a high genetic identity among the landraces studied. The species is highly
adapted to all the AEAs considered in this study from the northern hemisphere to the derived guinea savanna
and wet lowland rain forest of Nigeria. The analysis showed that four landraces (Pb18, Pb16, Pb17, and Pb19)
are unique and can be used as parental lines in heterosis crossing with landraces from the diverse cluster group I.
Landraces Pb17 and Pb19 were sourced from different locations (Sokoto and Zamfara) both of which fall within
Sudan Savannah AEAs. Landrace Pb18 was sourced from the Jos Plateau Mosaic of Plateau State, while Pb16
was sourced from Oyo State of Southern Guinea Savannah. The diversity in areas of collection of these
landraces and that of cluster I can be explored for cultivation and hence, the establishment of orchards,
conservation, and breeding purposes. Contrarily to the narrow genetic diversity observed in this study, the report
of Lompo et al. (2018) on the phylogeography of African locust bean indicated a high genetic differentiation
and spatially structured populations consisted of 84 populations and 1610 individuals from West and Central
Africa. In another study, high genetic diversity was found on 24 populations of the species (Ouedraogo, 2015).
The limitation of this present study is probably due to fewer landraces/populations evaluated for genetic
diversity.
I
I
I
Figure 2: Dendrogram showing three significant groups and genetic relationships among the 19 African
locust bean landraces studied using five microsatellite markers.
IV. CONCLUSION
This study identified four genetically distinct landraces (Pb18, Pb16, Pb17, and Pb19) that can be adopted as
parental lines for heterosis crossing while the diverse cluster I landraces are recommended for systematic
cultivation, management and conservation purposes. The homogeneity of alleles among the studied landraces
suggests possible loss of intraspecific genetic diversity among the landraces. This loss is a threat to the
environment and consequently, to the well-being of the present and future generations. African locust bean is
threatened in Nigeria, and concerted scientific efforts/strategies are required toward systematic conservation and
management of the taxa's genetic resources using the combination of ex-situ and in-situ techniques. The
weakening gene pool and diversity observed from this study can be enhanced through more germplasm
collections, particularly from the diverse AEAs and endemic centers of the species in Nigeria for better genetic
characterizations using genome-wide association study (GWAS). African locust bean is limited to local uses.
Given its socio-economic importance and cultural value to increase income, enhance food security, and good
health, it is imperative to intensify germplasm collection and genetic characterization towards conservation,
breeding, and sustainable utilization.
AVAILABILITY OF DATA AND MATERIALS:
The data supporting the findings of the article are available in this manuscript.
ETHICS APPROVAL AND CONSENT TO PARTICIPATE:
Not applicable.
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HUMAN AND ANIMAL RIGHTS:
No humans/animals were used in this study.
FUNDING
The sample collection part of this work was financially supported by the Covenant University Centre for
Research, Innovation, and Discovery (CUCRID). Grant No: VC/CRD.05/CUCRID RG 016.12.14/FS.
CONFLICT OF INTEREST: The authors declare no conflict of interest, financial or otherwise.
ACKNOWLEDGMENTS: We wish to thank Dr. David Igwe, Bowie State University, Maryland, USA for his
assistance in the data analysis and Mr. Gideon Adewale, Covenant University for mapping the collection areas.
The authors acknowledge the publication support from the Covenant University Center for Research Innovation
and Discovery (CUCRID).
V. REFERENCES
[1] Abioye, E. O., Akinpelu, D. A., Aiyegoro, O. A., Adegboye, M. F., Oni, M. O., & Okoh, A. I. (2013).
Preliminary phytochemical screening and antibacterial properties of crude stem bark extracts and
fractions of Parkia biglobosa (Jacq.). Molecules, 18(7), 8485-8499. DOI:10.3390/molecules18078485
[2] Adetutu, A., Morgan, W. A., & Corcoran, O. (2011). Ethnopharmacological survey and in vitro
evaluation of wound-healing plants used in South-western Nigeria. J Ethnopharmacol, 137(1), 50-56.
DOI:10.1016/j.jep.2011.03.073
[3] Agbani, P. O., Kafoutchoni, K. M., Salako, K. V., Gbedomon, R. C., Kegbe, A. M., Karen, H., & Sinsin,
B. (2018). Traditional ecological knowledge-based assessment of threatened woody species and their
potential substitutes in the Atakora mountain chain, a threatened hotspot of biodiversity in Northwestern
Benin, West Africa. J Ethnobiol Ethnomed, 14(1), 21. DOI:10.1186/s13002-018-0219-6
[4] Ai, B., Kang, M., & Huang, H. (2014). Assessment of genetic diversity in seed plants based on a uniform
pi criterion. Molecules, 19(12), 20113-20127. DOI:10.3390/molecules191220113
[5] Aiyelaagbe, O. O., Ajaiyeoba, E. O., & Ekundayo, O. (1996). Studies on the seed oils of Parkia
biglobosa and Parkia bicolor. Plant Foods Hum Nutr, 49(3), 229-233.
[6] Allal, F., Sanou, H., Millet, L., Vaillant, A., Camus-Kulandaivelu, L., Logossa, Z. A., . . . Bouvet, J. M.
(2011). Past climate changes explain the phylogeography of Vitellaria paradoxa over Africa. Heredity
(Edinb), 107(2), 174-186. DOI:10.1038/hdy.2011.5
[7] Amusa, O., Adesoye, A., Ogunkanmi, A., Omoche, O., Olowe, O., Akinyosoye, S., & Omodele, T.
(2014). Genetic diversity of Parkia biglobosa from different agroecological zones of Nigeria using
RAPD Markers. International Journal of Biodiversity, 2014, 1 - 9.
[8] Babalola, F. D. (2012). Evaluation of the Marketing Chain of Parkia biglobosa (Jacq. Berth) R. Br. Ex G.
Don in Southwest Nigeria. International Journal of Basic and Applied Sciences, 1(3), 210-213.
[9] Dainou, K., Blanc-Jolivet, C., Degen, B., Kimani, P., Ndiade-Bourobou, D., Donkpegan, A. S., . . .
Hardy, O. J. (2016). Revealing hidden species diversity in closely related species using nuclear SNPs,
SSRs and DNA sequences - a case study in the tree genus Milicia. BMC Evol Biol, 16(1), 259.
DOI:10.1186/s12862-016-0831-9
[10] Dash, S., Campbell, J. D., Cannon, E. K., Cleary, A. M., Huang, W., Kalberer, S. R., . . . Cannon, S. B.
(2016). Legume information system (LegumeInfo.org): a key component of a set of federated data
resources for the legume family. Nucleic Acids Res, 44(D1), D1181-1188. DOI:10.1093/nar/gkv1159
[11] Dellaporta SL, Wood J, Hicks JB. 1983. A plant DNA minipreparation: version II. Plant molecular
biology reporter 1(4):19-21.
[12] Fetuga, B. L., Babatunde, G. M., & Oyenuga, V. A. (1974). Protein quality of some unusual protein
foodstuffs. Studies on the African locust-bean seed (Parkia filicoidea Welw.). Br J Nutr, 32(1), 27-36.
[13] Gaisberger, H., Kindt, R., Loo, J., Schmidt, M., Bognounou, F., Da, S. S., . . . Lykke, A. M. (2017.).
Spatially explicit multi-threat assessment of food tree species in Burkina Faso: A fine-scale approach.
PLoS One, 12(9), p.e0184457.
[14] Hopkins, H. C. (1983). The taxonomy, reproductive biology and economic potential of Parkia
(Leguminosae: Mimosoideae) in Africa and Madagascar. Botanical Journal of the Linnean Society,
87(2), 135-167.
[15] Houndonougbo, J. S. H., Kassa, B., Mensah, S., Salako, V. K., Glèlè Kakaï, R., & Assogbadjo, A. E.
(2020). A global systematic review on conservation and domestication of Parkia biglobosa (Jacq.) R. Br.
ex G. Don, an indigenous fruit tree species in Sub-Sahara African traditional parklands: current
knowledge and future directions. Genetic Resources and Crop Evolution, 67(4), 1051-1066. Retrieved
from https://doi.org/10.1007/s10722-020-00892-w. DOI:10.1007/s10722-020-00892-w
[16] Kaur, K., Sharma, V., Singh, V., Wani, M. S., & Gupta, R. C. (2016). Development of novel SSR
markers for evaluation of genetic diversity and population structure in Tribulus terrestris
L.(Zygophyllaceae). Biotech, 6(2), p.156.
3204

ISSN- 2394-5125 VOL 7, ISSUE 11, 2020
[17] Kouadio, F., Kanko, C., Juge, M., Grimaud, N., Jean, A., N'Guessan, Y. T. & Petit, J. Y. (2000).
Analgesic and antiinflammatory activities of an extract from Parkia biglobosa used in traditional
medicine in the Ivory Coast. Phytother Res, 14(8), 635-637.
[18] Lassen, K. M., Kjær, E. D., Ouédraogo, M., & Nielsen, L. R. (2014). Microsatellite primers for Parkia
biglobosa (Fabaceae: Mimosoideae) reveal that a single plant sires all seeds per pod. Applications in
plant sciences, 2(6), p: 1400024.
[19] Liu, K., & Muse, S. V. (2005). Power marker: Integrated analysis environment for genetic marker data.
Bioinformatics, 21, 2128-2129.
[20] Logossa, Z. A., Camus-Kulandaivelu, L., Allal, F., Vaillant, A., Sanou, H., Kokou, K., & Bouvet, J. M.
(2011). Molecular data reveal isolation by distance and past population expansion for the shea tree
(Vitellaria paradoxa C.F. Gaertn) in West Africa. Mol Ecol, 20(19), 4009-4027. DOI:10.1111/j.1365-
294X.2011.05249.x
[21] Lompo, D., Vinceti, B., Gaisberger, H., Konrad, H., Duminil, J., Ouedraogo, M., . . . Geburek, T. (2017).
Genetic conservation in Parkia biglobosa (Fabaceae: Mimosoideae)-what do we know?. Silvae Genetica,
66(1), 1 - 8.
[22] Nei, M. (1973.). Analyzing of gene diversity in subdivided populations. Proc. Natl. Acad. Sci. USA, 70,
3321-3323.
[23] Nei, M. (1978). Estimation of average heterozygosity and genetic distance from a small number of
individuals. Genetics 89, 583–590.
[24] Ojuederie OB, Balogun MO, Fawole I, Igwe DO, Olowolafe MO. 2014. Assessment of the genetic
diversity of African yam bean (Sphenostylis stenocarpa Hochst ex. A Rich. Harms) accessions using
amplified fragment length polymorphism (AFLP) markers. African Journal of Biotechnology 13(18).
[25] Omonhinmin, A. C., Popoola, J. O., Daramola, F. Y., Ejoh, S. A., Omotosho, O. E., Mordi, R., . . .
Taiwo, O. (2016). Genetic Diversity Assessment of Under-exploited African Plants for genetic
improvement and food security. Progress Report. Covenant University Centre for Research, Innovation,
and Discovery (CUCRID). Nigeria.
[26] Ouedraogo, M. (2015). Improving and conserving Sahelian fruit trees: a case study of Parkia biglobosa
(Jacq.) Benth. (Ph.D. IGN Ph.D.), University of Copenhagen, Frederiksberg. , Frederiksberg.
[27] Ouédraogo, S., Somé, N., Ouattara, S., Kini, F. B., Traore, A., Bucher, B., & Guissou, I. P. (2012). Acute
toxicity and vascular properties of seed of Parkia biglobosa (JACQ) R. Br Gift (Mimosaceae) on rat
aorta. Afr J Tradit Complement Altern Med, 9(2), 260-265. doi:10.4314/ajtcam.v9i2.12
[28] Popoola, J. O., Bello, O. A., Olugbuyiro, J., & Obembe, O. O. (2017). Simple sequence repeats (SSR)
analysis of intraspecific genetic relationships of Moringa oleifera populations from Nigeria. Sci. Int.
(Lahore), 29(3), 645-657.
[29] Rendu, F., Saleun, S., & Auger, J. (1993). Parkia biglobosa seeds possess antiplatelet activity. Thromb
Res, 71(6), 505-508.
[30] Rohlf, F., 2002. NTSYS-pc: numerical taxonomy system ver. 2.1. Setauket, NY: Exeter Publishing Ltd.
[31] Sina, S., & Traoré, S. (2002). Parkia biglobosa (Jacq.) R. Br. ex G. Don. Record from Protabase. Oyen,
LPA & Lemmens, RHMJ (Editors). PROTA (Plant Resources of Tropical Africa/Ressources végétales
de l’Afrique tropicale), Wageningen, the Netherlands. In.
[32] Tóth, G., Gáspári, Z., and Jurka, J. (2000). Microsatellites in different eukaryotic genomes: survey and
analysis. Genome Res. 10:967. DOI: 10.1101/gr.10.7.967.
[33] Traore, M. S., Balde, M. A., Diallo, M. S., Balde, E. S., Diane, S., Camara, A., . . . Balde, A. M. (2013).
Ethnobotanical survey on medicinal plants used by Guinean traditional healers in the treatment of
malaria. J Ethnopharmacol, 150(3), 1145-1153. DOI:10.1016/j.jep.2013.10.048
[34] Tringali, C., Spatafora, C., & Longo, O. D. (2000). Bioactive constituents of the bark of Parkia
biglobosa. Fitoterapia, 71(2), 118-125. doi:10.1016/s0367-326x(99)00137-9
[35] Uyoh, E. A., Urua, I. S., Ntui, V. O., & Okpako, E. C. (2011). Flow cytometric analysis of nuclear DNA
content, mitotic chromosome number and protein separation by SDS-PAGE in three accessions of
African locust bean (Parkia biglobosa Benth.). Journal of Crop Science and Biotechnology, 14(4), 227-
232.
[36] Yang J, Zhang J, Han R, Zhang F, Mao A, Luo J, Dong B, Liu H, Tang H, Zhang J, and Wen C (2019)
Target SSR-Seq: A Novel SSR Genotyping Technology Associate With Perfect SSRs in Genetic
Analysis of Cucumber Varieties. Front. Plant Sci. 10:531. DOI: 10.3389/fpls.2019.00531
[37] Yeh FC, Yang R, Boyle TB, Ye Z, Mao JX. 1999. POPGENE version 1.32, the user-friendly shareware
for population genetic analysis. Molecular Biology and Biotechnology Centre, University of Alberta,
Canada.
[38] Zia, Z. U., Sadaqat, H. A., Tahir, M. H., Sadia, B., Bushman, B. S., Hole, D., . . . Malik, W. (2014).
Estimation of genetic diversity using SSR markers in sunflower. Genetika, 50(5), 570-580.
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