ORIGINAL PAPER
Diversity of wild and cultivated pearl millet accessions
(Pennisetum glaucum [L.] R. Br.) in Niger assessed
by microsatellite markers
Cedric Mariac Æ Viviane Luong Æ Issoufou Kapran Æ Aı
¨
ssata Mamadou Æ
Fabrice Sagnard Æ Monique Deu Æ Jacques Chantereau Æ Bruno Gerard Æ
Jupiter Ndjeunga Æ Gilles Bezanc¸on Æ Jean-Louis Pham Æ Yves Vigouroux
Received: 14 March 2006 / Accepted: 6 September 2006 / Published online: 18 October 2006
Springer-Verlag 2006
Abstract Genetic diversity of crop species in sub-
Sahelian Africa is still poorly documented. Among
such crops, pearl millet is one of the most important
staple species. In Niger, pearl millet covers more than
65% of the total cultivated area. Analyzing pearl millet
genetic diversity, its origin and its dynamics is impor-
tant for in situ and ex situ germplasm conservation and
to increase knowledge useful for breeding programs.
We developed new genetic markers and a high-
throughput technique for the genetic analysis of pearl
millet. Using 25 microsatellite markers, we analyzed
genetic diversity in 46 wild and 421 cultivated acces-
sions of pearl millet in Niger. We showed a significantly
lower number of alleles and lower gene diversity in
cultivated pearl millet accessions than in wild acces-
sions. This result contrasts with a previous study using
iso-enzyme markers showing similar genetic diversity
between cultivated and wild pearl millet populations.
We found a strong differentiation between the culti-
vated and wild groups in Niger. Analyses of intro-
gressions between cultivated and wild accessions
showed modest but statistically supported evidence of
introgressions. Wild accessions in the central region of
Niger showed introgressions of cultivated alleles.
Accessions of cultivated pearl millet showed intro-
gressions of wild alleles in the western, central, and
eastern parts of Niger.
Introduction
In Sahelian Africa, numerous traditional crops con-
tribute to food security. Studies of the crops cultivated
in these regions are relatively rare, particularly in
terms of their genetic diversity. Pearl millet (Pennise-
tum glaucum [L.] R. Br.) is one of the most important
crops in the whole Sahelian region from Senegal to
Sudan. Pearl millet was domesticated in the Sahelian
zone of western Africa (Harlan et al. 1976; Tostain
1992). In Niger, land under pearl millet represents
more than 65% of a total of 7.5 millions ha of culti-
vated land (estimated for the 1995–1999 period,
Guenguant and Banoin 2003). Studying the diversity of
such important crops enables identification of land-
marks for in situ germplasm conservation, the creation
of core collections of accessions for genetic analysis
Cedric Mariac and Viviane Luong have contributed equally to
this work.
Electronic supplementary material Supplementary material is
available in the online version of this article at http://dx.doi.org/
10.1007/s00122-006-0409-9 and is accessible for authorized users.
C. Mariac V. Luong J.-L. Pham Y. Vigouroux (&)
Institut de Recherche pour le De
´
veloppement (IRD),
911, avenue Agropolis, BP 64501, 34394 Montpellier, France
e-mail: yves.vigouroux@mpl.ird.fr
I. Kapran A. Mamadou
Institut National de la Recherche Agronomique du Niger
(INRAN), Niamey, Niger
F. Sagnard M. Deu J. Chantereau
Centre International de la Recherche Agronomique pour le
De
´
veloppement (CIRAD), Montpellier, France
B. Gerard J. Ndjeunga
International Center of Research for the Semi-Arid tropics
(ICRISAT), Niamey, Niger
G. Bezanc¸on
Institut de Recherche pour le De
´
veloppement (IRD),
Niamey, Niger
123
Theor Appl Genet (2006) 114:49–58
DOI 10.1007/s00122-006-0409-9
and the extension of knowledge useful for breeding
programs. To date, the diversity of pearl millet has
been studied using iso-enzyme loci (Tostain et al. 1987;
Tostain and Marchais 1989; Tostain 1992, 1994), AFLP
markers (Vom Brocke et al. 2003), and RFLP markers
(Bhattacharjee et al. 2002). New markers such as
SSCP-SNP (Bertin et al. 2005) and microsatellite loci
(Allouis et al. 2000; Qi et al. 2001, 2004; Budak et al.
2003) have recently been developed. However, they
have not yet been used to assess the genetic diversity of
landraces of pearl millet. Microsatellite markers are a
promising tool for in-depth investigations of genetic
diversity of pearl millet. Consequently, we developed a
new set of microsatellite markers and a high-through-
put methodology for microsatellite genotyping. Using
these new methods, we analyzed the genetic diversity
of a large sample of wild and cultivated accessions.
Our genetic analysis focused on Niger, the second
largest pearl millet producer in Africa after Nigeria.
The morphological diversity of pearl millet in Niger is
the highest in West Africa (Tostain 1994). In particu-
lar, spike morphology exhibits wide variation from a
very short spike in the eastern part of the country to a
very long spike in the South-central part of Niger.
Moreover in Niger, both wild millet (Pennisetum
glaucum ssp. monodii) and cultivated pearl millet
(Pennisetum glaucum ssp. glaucum) are found. Wild
populations grow at latitudes between 12N and 21N
but are found mainly in the northern part of the
country (Tostain 1992) in the Aı
¨
r mountains. However,
some wild populations have also been described in
sympatry with pearl millet landraces. This situation was
documented mainly near the northern limits of culti-
vation of pearl millet.
The objectives of this study were: (1) to develop new
markers and a high-throughput method for genotyping,
(2) to investigate the diversity of wild and cultivated
accessions, and (3) to study introgressions between
cultivated and wild pearl millet.
Materials and methods
Seed collection and DNA extraction
In 2003, samples were collected in 80 different villages.
A total of 421 different cultivated seed accessions were
collected, corresponding to about 140 different land-
race names. An accession consisted of a quantity of
panicles or seeds of a named variety, provided by a
single farmer in one village. Sampling was conducted
throughout the cultivated area of Niger (Fig. 1, S1).
The area in which pearl millet is cultivated is limited by
rainfall, and most of northern and central Niger is not
cultivated, but is used as pasture during the rainy
season. In each sampling location, we collected pani-
cles that farmers identified as their varieties. Our
objective was to sample 30 panicles per variety, but this
number varied depending on local availability. An
average number of 21 panicles per sample was col-
lected. We also analyzed 46 previously sampled
wild accessions of pearl millet from Niger (Fig. 1, S1,
Tostain 1992). For each wild and cultivated accession,
one individual was studied. A total of 467 individuals
was analyzed using 25 microsatellite loci.
Microsatellite isolation
We developed a new set of microsatellite markers
using public EST available in GenBank. Briefly,
genomic DNA sequences were retrieved from Gen-
Bank using the name pearl millet or
Pennisetum
glaucum as query. On September 24, 2003, 2,577
sequences were retrieved. Microsatellite markers
were identified using the software SSRI (http://www.
gramene.org/gramene/searches/ssrtool). We searched
for microsatellites exhibiting repeated motifs from 2
to 10 bases and at least five repeats. A total of 266
microsatelite hits were found. Some of them corre-
sponded to a same sequence containing an interrupted
microsatellite loci. Some sequences were redundant
as they corresponded to the same gene. To analyze
only unique ESTs, we compared each sequence with
the other pearl millet ESTs using Blast software. We
then selected only unique sequences and their unique
microsatellite loci. The diversity of the newly devel-
oped markers was then assessed in ten wild, 12
Fig. 1 Sampling locations of wild and cultivated pearl millet
accessions. The sampling location of the 46 wild accessions (dark
triangles) and 421 cultivated accessions (light gray circles).
Different cultivated accessions were collected from the 80
sampling sites and are represented by a single light gray circle
123
50 Theor Appl Genet (2006) 114:49–58
weedy, and ten cultivated millet samples collected in
Niger.
DNA extraction and PCR conditions
Samples of fresh leaves were harvested and ground in
nitrogen. Approximately 0.2 g of powder were re-sus-
pended with 700 ll extraction buffer (Tris 0.1 M, NaCl
1.25 M, EDTA 0.02 M, MATAB DTT 0.01 mM, PH
8) and incubated at 65C for 4 h. Lysat was then mixed
with chloroform-isoamyl alcohol (24:1), and then cen-
trifuged. DNA was precipitated from the supernatant
using isopropanol and washed with 70% ethanol. Dried
pellets were re-suspended with 200 ll deionized water.
The PCR reaction mixture (11 ll final) consisted of
1· Colorless GoTaq
TM
Reaction Buffer (Promega
M7921, Madison, WI, USA), 0.5 mM MgCl
2
, nucleo-
tides dATP, dGTP, dCGT, dTTP (125 lM each),
0.1 lM primer, 1 unit of taq DNA polymerase, and
20 ng template DNA. The 5¢ end of the forward primer
was labeled with fluorescent dye (Table 2).
The DNA and reaction mixture were dispensed
using a HAMILTON starlab robot in a 384-well mic-
rotitre plate (Abgene, Epsom, UK). Plates were sealed
with thermoseal Easy Peel (ABgene-0745). Silicone
mats were added between plate and lid (110C) to
homogenize pressure and to limit evaporation loss.
Amplifications were performed in a Biometra T1 384-
well thermocycler programed for 35 cycles of 30 s at
94C, 30 s at 55–58C, 45 s at 72C, and ending with
10 min at 72C.
One microliter of 30-fold diluted amplification
product and 11 ll HD formamide were mixed with
0.15 ll GS 500 Liz internal size standard and heated at
94C for 3 min. Migration was performed using an
automatic sequencer ABI Prism
TM
3100 (Applied
Biosystems, Foster City, CA, USA). Microsatellite al-
leles were scored using Genescan and Genotyper
software packages (Applied Biosystems). The scoring
was manually checked by two different persons. Each
384-well PCR plate included eight negative controls
(no DNA).
To develop a set of markers for high-throughput
genotyping, we used some of the microsatellites that
we developed and also some markers developed in
previous publications (Allouis et al. 2000; Qi et al.
2001, 2004; Budak et al. 2003). Our objective was to
developed multiplex PCR associations of microsatellite
loci and multiplex migration on ABI prism. We tested
a total set of 65 microsatellite markers including the
ones we actually developed. We retained only the best
markers showing good yield amplification and with no
surnumary bands. Surnumary bands correspond to loci
showing more than two alleles certainly link to dupli-
cate loci or EST belonging to multigene families. Fi-
nally, we selected the markers, which could be
combined for the development of multiplex PCR and
migration. We ended up with a set of 25 markers
including eight markers developed in this study.
Statistical analysis
Genetic data analysis was performed using Power-
marker (Liu and Muse 2005). We calculated the
number of alleles, observed heterozygosity, gene
diversity, polymorphic information content (PIC) and
differentiation (Fst). The gene diversity was calculated
as n=ðn 1Þð1
P
p
2
i
H
o
=2nÞ; where n is the num-
ber of individuals, p
i
the frequency of the i allele and
H
o
the number of observed heterozygotes (Nei 1987).
The PIC was calculated as 1
P
p
2
i
P
i
P
j[i
2p
2
i
p
2
j
;
where p
i
and p
j
are the frequencies of the i and j alleles,
respectively (Botstein et al. 1980). The differentiation
between the wild and cultivated groups was tested lo-
cus by locus, and overall significance was also tested.
Sample size has a large impact on the estimation of the
number of alleles. We compared the number of alleles
for a same sample size using the parameter allelic
richness (FSTAT software, Goudet 2001). The allelic
richness and gene diversity of two samples (wild and
cultivated) were compared using a Wilcoxon paired
test. A 1,000 bootstraps were performed to calculate
the 95% confidence interval (CI) of the average allelic
richness and gene diversity across loci.
We calculated the Shared Allele Distance between
individuals using Powermarker. We used this matrix
to statistically assess the correlation (1) between ge-
netic distance and landrace name and (2) between
genetic distance and geographical distance. We built a
matrix where the geographical distance between
accessions was calculated using latitude and longitude
data (S1). To test whether geographical distance and
genetic distance were correlated, we performed a
Mantel test (Sokal and Rohlf 1995). To analyze the
correlation between genetic distance and landrace
name, we built a matrix as follows: if two accessions
shared the same landrace name, the distance was 0,
otherwise it was 1. The correlation was also tested by
a Mantel test.
For each individual, we calculated the frequencies of
each allele (0, 0.5, and 1) at each locus, and used this
data to perform a principal component analysis (PCA)
using SYSTAT.
We used a Bayesian method to determine the
presence of hybrids or introgressed wild or culti-
vated individuals. The software Structure Version 2.1
123
Theor Appl Genet (2006) 114:49–58 51
(Pritchard et al. 2000; Falush et al. 2003) was used to
perform this analysis. Parameters were set at K = 2 for
the number of populations, 100,000 for the burn-in
time and 1,000,000 for the number of runs. Five repli-
cates were performed. The output of this analysis is the
ancestry of the two different groups: cultivated and
wild groups. The ancestry value is a statistical estima-
tion of the proportion of the genome of an individual
that originated from a given population. The ancestry
value varies from 0 to 1. An ancestry close to 0 or 1 in
one group suggests no evidence of introgression for the
individual studied. Intermediate values suggest intro-
gression. For each individual we calculated a CI of the
ancestry parameter. We also performed the same
analysis using different numbers of populations (K
varying from 1 to 7). Five repetitions of each assumed
population number were performed. A recent simula-
tion study proposed a methodology to assess the best
K-value supported by the data (Evanno et al. 2005).
Following Evanno et al. (2005), we calculated the
second order change of the likelihood function divided
by the standard deviation of the likelihood (DK).
Results
Isolation of microsatellite loci
A total of 207 unique microsatellite loci were found in
the EST sequences screened. Thus, 8% of the 2,577
sequences analyzed exhibited microsatellite loci of the
minimum size specified. Di-nucleotide microsatellites
are the most abundant, 169 loci were identified. We
also found 32 tri-nucleotide microsatellites, five tetra-
nucleotide microsatellites and only one deca-nucleo-
tide microsatellite. The mean size of the microsatellite
alleles was 9.0 repeats. We designed 58 different pairs
of primers and tested them for the presence of a simple
Table 1 List of EST derived microsatellite loci
Locus GenBank accession Primer sequence 5¢–3¢ Core motif Number of alleles PIC
PGIRD5 CD724362-1 CAACCCAACCCATTATACTTATCTG (GA)
7
––
GCAACTCTTGCCTTTCTTGG
PGIRD7 CD724492-1 CGGAGACGCACTAGACTTGG (GT)
7
4 0.23
CCGGATGCTCACTTCCTTAT
PGIRD12 CD724749-1 ACTCGTTCGGATGCACTTCT (TA)
8
8 0.44
CGGGGAAGAGACAGGCTACT
PGIRD13 CD724750-1 CAGCAGCGAGAAGTTTAGCA (AGC)
8
10 0.58
GCGTAGACGGCGTAGATGAT
PGIRD19 CD724869-1 TGAGGACCGAGAAGAAGCAT (GT)
10
6 0.44
CAACACCCAACAGAAACTGAA
PGIRD21 CD724961.1 GCTATTGCCACTGCTTCACA (ACC)
8
3 0.21
CCACCATGCAACAGCAATAA
PGIRD25 CD725199.1 CGGAGCTCCTATCATTCCAA (GA)
9
9 0.53
GCAAGCCACAAGCCTATCTC
PGIRD43 CD724428.1 GTTCATGCAGCTTGGTTTCC (GAT)
6
10 0.68
AGTGACCTGGGGTACAGACG
PGIRD44 CD725489.1 TCTCTCTCGGATCGCTGTG (GCG)
6
5 0.41
GCTGGTTGGTAGAGGCTGAC
PGIRD46 CD724372.1 GAACAATTGCTTCTGTAATATTGCTT (CTC)
6
3 0.24
GCCGACCAAGAACTTCATACA
PGIRD49 CD725305.1 AGCTCCTCGACGGAGAAAGT (CGG)
6
5 0.48
GACGGTGTCGACGAAGATG
PGIRD50 CD724894.1 CTCTCGGTTTGACGGTTTGT (TGT)
6
7 0.58
GGGGAAAACAAAGTTGCTCA
PGIRD54 CD724361.1 GCCTGGGATGTGTTTCTTCT (GT)
5
2 0.37
GCCTTTCATTTCCACCATGA
PGIRD55 CD725120.1 CTTTACTACGGCCCACGACA (AC)
6
18 0.86
GTGTGTTTGTACCGGTGTGG
PGIRD56 CD725501.1 ATCACTCCTCGATCGGTCAC (TG)
6
2 0.06
ACCAGACACACGTGCCAGT
PGIRD57 CD726121.1 GGCCCCAAGTAACTTCCCTA (AG)
7
11 0.67
TCAAGCTAGGGCCAATGTCT
For each microsatellite locus, its name, the accession number of the EST, the forward and reverse primer sequences, and the core motif
of the microsatellite are presented. The number of alleles and the PIC value was estimated on a sample of 32 individual plants. For
PGIRD5, polymorphism was detected but high slippage was observed at this loci and the number of alleles and PIC value was not
estimated
123
52 Theor Appl Genet (2006) 114:49–58
pattern, reliable amplification and the presence of
polymorphism between pearl millet accessions. A new
set of 16 microsatellites was developed (Table 1). The
diversity of these microsatellite loci varied from 2 to 18
for the number of alleles and 0.06–0.86 for the PIC
values. One of the polymorphic locus genetic diversity
parameters was not estimated because high slippage
rendered diversity estimation difficult (PGIRD5).
We amplified 25 loci with 15 PCR reactions. The
number of amplified microsatellite loci in a single PCR
reaction varied from 4 to 1 (Table 2). The 25 micro-
satellite loci were combined so that an average of six
microsatellite loci migrate together. PCR and migra-
tion multiplexes of microsatellite loci are presented in
Table 2.
Diversity and differentiation between cultivated
and wild pearl millet samples
To compare the number of alleles in the cultivated
sample with the number of alleles in the wild sample,
the effect of the sample size needs to be taken into
account. We corrected the effect of the sample size by
calculating allelic richness, which was calculated on the
smaller size of the two samples (Goudet 2001). We
found significantly lower allelic richness (Table 3)in
the cultivated sampled than in the wild sample (Wil-
coxon test, Z = 3.68, P < 0.001). The average allelic
richness for the cultivated sample was 6.2 compared
with 8.1 for the wild sample. The 95% CI of the mean
value across loci is 4.5–8.1 alleles for the cultivated
sample and 6.1–10.2 alleles for the wild sample. The
cultivated sample had 23% fewer alleles than the wild
sample. The average Fis value was 0.30 for the wild
sample (P < 0.001) and 0.19 for the cultivated sample
(P < 0.001). Gene diversity was significantly lower
(Wilcoxon test, Z = 3.29, P < 0.001) in the cultivated
sample than in the wild sample. The cultivated sample
showed an average gene diversity of 0.49 (CI 0.39–0.59)
compared with 0.67 (CI 0.57–0.75) for the wild sample.
The cultivated sample thus showed a gene diversity
that was 28% lower than in the wild sample.
Overall, the differentiation (Fst) between the wild
and cultivated samples was highly significant
(P < 0.001) with an average value of 0.17. This differ-
entiation varied from 0.019 to 0.49 depending on the
loci studied and was significant for each locus
(P < 0.05). PCA (Fig. 2) enabled us to explain 4.2% of
the overall variation on the first axis and 1.6% on the
second one. The low percentage of explained variance
on the two axes is common in analyses using a high
number of alleles from different microsatellite loci
(Matsuoka et al. 2002). The marked differentiation
between wild and cultivated samples is clear on the first
axis of the PCA. The second axis differentiates dif-
ferent accessions of wild pearl millet.
Landrace names, geographical, and genetic
distances
For cultivated accessions we analyzed the relationship
between genetic distance and geographical distance.
For this purpose, we calculated a matrix of geograph-
ical distance and a matrix of genetic distance between
accessions. The relationship between these two matri-
ces was studied using a Mantel test. There was a low
correlation between genetic distance and geographical
distance (R = 0.11, P < 0.001). We also tested the ge-
netic proximity of accessions belonging to the same
landrace. We found a very weak correlation
(R = 0.026, P < 0.01).
Introgressions
We performed a Bayesian analysis to detect evidence
of introgression between cultivated and wild acces-
sions. For this purpose, we used Structure software
assuming two groups (K = 2): a cultivated and a wild
Table 2 PCR condition and
migration
The 5¢ fluorescent-labels used
with forward primers are
NED
a
, VIC
b
, 6-FAM
c
, and
PET
d
. The temperature of
hybridization is given for each
combination of loci. Loci
from different PCR reactions
were pooled and alleles were
separated using a capillary
ABI Prism 3100 system
Locus combination multiplexed in a single PCR Temperature (C) Migration pool number
PGIRD46
a
, CTM8
b
, PSMP2249
c
, PSMP2247
c
55 1
PSMP2201
d
, PSMP2237
d
55
PSMP2227
a
, PGIRD12
b
55
PSMP2266
c
, PGIRD21
c
55 2
PSMP2208
a
, PSMP2085
a
58
PGIRD44
b
, PGIRD 13
b
58
PSMP73
d
58
PSMP32
b
55 3
CTM10
b
, PGIRD43
c
55
PSMP2214
d
55
PGIRD7
d
55
PGIRD25
d
, PSMP2219
a
, PSMP2220
a
55 4
PSMP2206
c
, PSMP2202
b
55
123
Theor Appl Genet (2006) 114:49–58 53
