SSR and SRAP Markers-based Genetic Diversity in Sorghum (Sorghum bicolor (L.) Moench) Accessions of Sudan
Adil A. El Hussein,
Marmar A. El Siddig,
Abdel Wahab H. Abdalla,
To evaluate the genetic diversity among the 33 sorghum accessions of Sudan, 70 Simple Sequence Repeats (SSR) and 23 Sequence Related Amplified Polymorphism (SRAP) primer sets were utilized. Results indicated that, of the SSR markers used, 50 (71.4%) were polymorphic, producing 88 (53.0%) polymorphic alleles of PIC value ranging from 0.06 to 0.96 with an average of 0.58. Among the SRAP markers, 8 (34.8%) produced 33 alleles with 48.5% marker polymorphism and PIC value ranging from 0.23 to 0.93. The similarity coefficients based on SSRs were in the range of 0.15 to 0.78 with an average of 0.45, while those based on SRAP markers were in the range of 0.13 to 0.80 with an average of 0.50. Coefficients of similarity generated with SSRs grouped the sorghum accessions into five clusters. In contrast, grouping according to the similarity coefficients of the SRAPs resulted in another completely different five clusters. When data obtained from both SSRs and SRAPs were combined and utilized to generate a dendrogram in which the 33 sorghum accessions were again grouped into five clusters. Cluster 1 and 5 were typical to those of the SSR-based grouping. The present study indicates that fast, accurate and high throughput fingerprinting could be obtained using those markers, from the combined analysis, which revealed the existence of significant variation among the 33 accessions. The most distant accessions can be used by breeders to develop improved sorghum genotypes.
to cite this article:
Adil A. El Hussein, Marmar A. El Siddig, Abdel Wahab H. Abdalla, Ismael Dweikat and Stephen Baenziger, 2014. SSR and SRAP Markers-based Genetic Diversity in Sorghum (Sorghum bicolor (L.) Moench) Accessions of Sudan. International Journal of Plant Breeding and Genetics, 8: 89-99.
Received: December 21, 2013;
Accepted: February 08, 2014;
Published: April 26, 2014
Sorghum (Sorghum bicolor (L.) Moench) is the fifth most important cereal
crop worldwide and together with maize and pearl millet, form the most important
dry land cereal crops for the semi-arid tropics. It is grown worldwide on a
total area of 47 million ha (FAOSTAT, 2010). Sudan is
within the geographical range where sorghum is believed to be domesticated and
where the largest genetic variation for both cultivated and wild sorghum is
found (Dawelbeit et al., 2010). Sorghum is the
main staple food in the Sudan and it ranks first among other crops in allocated
area and production. Sudans average annual production is estimated as
3.7x105 MT (FAOSTAT, 2010). However, 90% of
the cultivated sorghum is grown under rainfed conditions mainly in Gadarif,
Damazin, Kordufan, Darfur and Nuba mountains. Gadarif State (Eastern Sudan)
is the most important region for sorghum production where about 2.1-2.5 million
ha are annually cultivated. Large mechanized schemes, of about 600 ha, characterize
this region where average yield accounts 2.4 MT ha-1 (FAOSTAT,
Sorghum yield is limited by inadequate and/or erratic rainfall, poor soil fertility,
pest and disease invasions and high temperatures (FAOSTAT,
2005). It is important to increase sorghum yield to meet the worldwide increasing
demand due to expanding population (Prakash et al.,
2006). Information on various aspects of sorghum diversity will result in
the formation of a sorghum core collection that contains a maximum amount of
variation (Maqbool et al., 2001). This information
can be used as a tool for mining germplasm collections for genomic regions associated
with adaptive or agronomically important traits (Casa et
al., 2005). In addition, assessment of genetic variation among sorghum
accessions is a gateway to the study of evolutionary forces that influence the
domestication process and has strong impact on conservation and breeding.
DNA molecular markers such as Restriction Fragment Length Polymorphism (RFLP)
(Vierling et al., 1994; Ahnert
et al., 1996), Random Amplified Polymorphic DNA (RAPD) (Uptmoor
et al., 2003; Huang, 2004), Simple Sequence
Repeats (SSRs) (Ghebru et al., 2002; Menz
et al., 2004) and Sequence-Related Amplified Polymorphism (SRAP)
(Li and Quiros, 2001) have been successfully used to
estimate genetic diversity in sorghum. SSR markers have been found to be very
efficient in sorghum diversity studies as they revealed more diversity in sorghum
compared with other markers (Kudadjie, 2006). SRAP markers
were considered as new and useful molecular markers that target coding sequences
in the plant genome (Li and Quiros, 2001). They are based
on two primer amplifications that preferentially amplify Open Reading Frames
(ORFs) or coding regions resulting in a number of dominant and codominant markers.
The forward primer amplifies the exon regions while the reverse primer amplifies
the intron and promoter regions. Their polymorphisms result from the variation
in length of these exons, introns, promoters and spacers both among individuals
as well as species (Li and Quiros, 2001; Zhao
et al., 2009). SRAP markers have been used in a wide range of plant
species such as Medicago sativa (Ariss and Vandemark,
2007), Buchloe dactyloides (Budak et al.,
2004), Gossypium (Lin et al., 2004),
Cucurbita (Ferriol et al., 2003), Paeonia
suffruticosa (Han et al., 2008) and Triticum
spp. (Fufa et al., 2005; Zaefizadeh
and Goliev, 2009).
The objective of this study was to examine the genetic variability within some
sorghum accessions from different regions of Sudan and to group them based on
SSR and/or SRAP markers fingerprinting.
MATERIALS AND METHODS
Plant material: Seeds of 33 sorghum accessions collected from different
regions of Sudan were used in this study (Table 1). In the
33 accessions, 10 are landraces (from Eastern Sudan, Gadarif area), 13 are inbred
lines (Central Sudan), 6 are local cultivars (1 from Eastern Sudan and 5 from
Western Sudan) and 4 are standard commercial cultivars from Central Sudan.
DNA extraction: Genomic DNA was extracted following a sap-extraction
method from 100 mg of fresh tissue. Leaves of 2-week-old seedlings were placed
between the two rollers of a sap-extraction apparatus (Ravenel Specialities,
Seneca, S.C.) and 1 mL of extraction buffer (50 mM Tris-HCl, 25 mM EDTA, 1 M
NaCl, 1% CTAB, 1 mM 1, 10-phenathroline and 0.15% 2-mercaptoethanol) was slowly
added to the rollers, immediately mixing with the sap for collection in 1.5
mL microcentrifuge tubes. The extract was incubated at 60°C for 1 h, then
mixed with equal volume of chloroform-isoamyl alcohol (24:1).
|| Sorghum accessions used in the study, their collection codes,
types and collection location
After centrifugation at 12,000 rpm, the supernatant was transferred to a new
tube. To precipitate the DNA, isopropanol was added and the contents were incubated
for 30 min. The pellet was dried, resuspended in 200 mL of TE buffer (10 mM
Tris-HCl, 0.1 mM EDTA, pH 8.0) plus 20 μg of RNase and then incubated overnight
at room temperature. The DNA solution was mixed with 20 μL of 8 M ammonium
acetate and 400 μL of cold absolute ethanol for 30 min, centrifuged for
10 min and air dried at room temperature. The DNA was then resuspended in 200
μL of TE buffer and DNA concentration was quantified by spectrophotometry
(TKO100 Fluorometer, Hoefer Scientific Instruments, San Francisco).
Markers analysis: A total of 93 oligonucleotide primer pairs that included
70 sorghum SSRs (Schloss et al., 2002) and 23
SRAP combinations (Li and Quiros, 2001) were used. The
marker assays were conducted following the procedure of Kuleung
et al. (2004). A 25 μL total volume/reaction was used, consisting
of 75 ng genomic DNA, 100 ng primer pair, 125 μM dNTPs, 50 mM KCl and 10
mM Tris-HCl, 25 mM MgCl2 and 1 unit Taq polymerase. The amplification
procedure consisted of one cycle at 94°C for 3 min, followed by 35 cycles
of 1 min at 94°C, 1 min at 55°C for SSRs but 47°C for SRAPs, 1 min
at 72°C and final extension step at 72°C for 5 min. The reaction was
then cooled to a resting temperature of 4°C and resolved by electrophoresis
in a 12% non-denatured polyacrylamide gel (37:1 acrylamide:bis-acrylamide).
The gel was stained in 1 μg mL-1 ethidium bromide for 10 min,
destained in deionized water for 15 min and photographed using the Gel Doc2000
(Bio-Rad, Hercules, CA.).
Data analysis: Each DNA fragment obtained by both marker types was scored
as present (1) or absent (0), each of which was treated as an independent character.
Similarity between the accessions was analyzed on the basis of the scores. Data
were then used to create a matrix to analyze genetic relationship using the
R software package (R Development Core Team, 2011). A
dendrogram was constructed based on Jaccards similarity coefficient (Jaccard,
1908) using the markers data for all sorghum accessions following the Unweighted
Pair Group Method Analysis (UPGMA) as described by Sokal
and Michener (1958). Polymorphism Information Content (PIC) values were
calculated as in Anderson et al. (1993), who
assumed homologous alleles. PIC for a locus is calculated as:
where, Pij is the relative frequency of the jth allele of the ith
locus, summed over all the alleles for individual marker locus over all lines.
A marker with a PIC value of more than 0.5 is considered as highly informative,
between 0.25 and 0.5 as informative and less than 0.25 as slightly informative
(Botstein et al., 1980). The genetic diversity
was estimated by similarity indices calculated from band sharing data of each
pair of DNA fingerprints.
RESULTS AND DISCUSSION
Molecular markers analysis: A total of 70 SSRs and 23 SRAPs markers
were used to characterize and evaluate the genetic diversity of 33 sorghum accessions.
Out of the screened SSRs, 50 (71.4%) were polymorphic. The markers produced
166 alleles, 88 of them (53.0%) were polymorphic displying PIC values ranging
from 0.06 to 0.96 with an average of 0.58. These values were higher than those
of 0.40, 0.44 and 0.52 observed, for sorghum accessions, by Ali
et al. (2008), Folkertsma et al. (2005)
and Lekgari (2010), respectively. The differences may
be attributed to the number of bands/alleles scored and the type of SSR markers
used. For example, Ali et al. (2008) used only
one type of SSR marker (xcup) while in this study four different SSR marker
types (Xcup, Sam, Xsb and Drenhsbm) were used. In addition, the number of alleles/bands
scored per marker differs between individual studies. The mean PIC value of
0.58 reported here indicates that the markers used were highly informative (Botstein
et al., 1980).
Similarity indices based on the polymorphic data obtained were used to estimate
the genetic relatedness among the sorghum accessions. Results (Table
2) indicate that the genetic similarity coefficients for all accessions
based on SSR markers ranged from 0.15-0.78 with an average of 0.45. It is also
evident that accessions ShSc871 and ShSc875 are the most closely related genotypes
as they showed the highest similarity index, while the genotypes ShSc879 and
L15-08, with the lowest index, are the most distantly related.
||Genetic similarity matrix for sorghum accessions as assessed
by SSR (lower) and SRAP (upper) markers
||Dendrogram of 33 sorghum accessions from Sudan based on SSR
markers. Values along x-axis correspond to Jaccards coefficients of
A dendrogram based on the similarity values produced from the SSRs was constructed
using the UPGMA cluster analysis (Fig. 1). Five major clusters
were obtained; cluster 1 contained three accessions which were all collected
from the Central Region of Sudan. Cluster 2 included accessions from Central
(3), Eastern (2) and Western (1) regions. The largest group, cluster 3, has
13 members. Of these, five were from Central Sudan, five from Eastern Sudan
and the remaining were from the Western region. The 67% of the accessions in
cluster 4 and 80% of the accessions in cluster 5 are from Eastern and Central
Sudan, respectively. It could also be noted in Fig. 1 that
accession Bot.4, from Western Sudan, is distant from the other four accessions
of the same region. The four standard cultivars of the Central Sudan were distributed
in three different clusters, indicating that they are genetically different.
This highlights the possibility of using these cultivars in breeding activities
for introgression of desirable traits.
In SRAP analysis, the markers produced 33 alleles, the percentage of marker
polymorphism is 48.5 and the PIC values ranged from 0.23 to 0.93. The similarity
coefficients based on SRAP markers ranged from 0.13, in L15-08 and ShSc5, to
0.80, between L20-08 and L13-08 (Table 2). Grouping according
to the coefficients of the SRAPs have also resulted in five clusters (Fig.
2) but they were completely different from those of SSRs. Of these, cluster
1 included four accessions, two from Central Sudan and two from Western Sudan.
Three of these accessions are known cultivars, while the fourth is an inbred
line. Cluster 2 included seven accessions five of them belong to the Central
region, one from East while the other is from the West. In cluster 3 which contained
six accessions, there was an equal number of accessions from Central and Eastern
Sudan. The fourth cluster had accessions (n = 4) representing each of the regions
studied. Being the largest group (12 accessions), cluster 5 contained six accessions
from the centre, five from East and only one accession from the West.
||Dendrogram of 33 sorghum accessions from Sudan based on SRAP
markers. Values along x-axis correspond to Jaccards coefficients of
This cluster included only two cultivars, one from Western Sudan (Bot.1) and
the other from Eastern Sudan (ShSc881), the remaining were lines and landraces.
With the exception of cluster 4, each of the other clusters contained at least
one of the accessions collected from Western Sudan. This may indicate the diverse
nature of the sorghum genotypes grown in that region.
Data obtained from both SSRs and SRAPs were combined and utilized to generate
the diversity grouping. Based on the obtained results (Fig. 3),
the 33 accessions were again grouped into five clusters. Cluster 1 and 5 were
typical to those in the SSR-based grouping. In cluster 2 which had eight accessions,
six were found in cluster 3 of the SSRs groups. Cluster 3 was the largest one,
containing 11 accessions; six of them were local cultivars from all of the regions
studied. Four of the six members of cluster 4 were similar to the members of
cluster 3 in SRAPs based grouping.
Both marker types were efficient in elucidating the genetic diversity present
in the tested sorghum accessions. Furthermore, clustering based on the combined
data was found to be more informative than those derived from individual type
of analysis. The results presented in this study reveal that the sorghum accessions
grown in the potential parts in Sudan have wide genetic background and they
are highly diverse.
||Dendrogram of 33 sorghum accessions from Sudan based on both
SSR and SRAP markers. Values along x-axis correspond to Jaccards coefficients
The present study indicates that fast, accurate and high throughput fingerprinting
could be obtained using those markers, from the combined analysis, which revealed
the existence of significant variation among the 33 accessions. The most distant
accessions can be used by breeders to develop improved sorghum genotypes.
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