Introduction
Genetic
diversity in plants is important for breeding of elite genotypes and
conservation of novel germplasm (Iqbal et
al. 2018). Genetic diversity possibly occurs due to selection process,
genetic drift, interaction of climatic conditions and geographical features
(Malik et al. 2018). In date palm,
genetic diversity is greatly influenced by selection process, clonal
propagation and germplasm exchange. It is thought that genotypes are developed
from continuous selection process by farmers on the basis of fruit traits
(Haider et al. 2015). In date palm,
identification of germplasm/ specific genotypes is a hectic job for farmers as
well as researchers due to use of different names for the same genotype by the
people of different geographical regions (Purayil et al. 2018). Specific language of a region is also a major cause
of misnaming in date palm nomenclature. Secondly, seed and offshoot propagation
are factors leading to the mixing of date palm germplasm within the country
(Chaluvadi et al. 2014). Hence, plant
researchers developed different molecular tools for accurate characterization
of date palm germplasm.
Most consistent tools used for evaluation of genetic
diversity are morphological, physical, biochemical and molecular markers (Ahmad
and Anjum 2018). However, morphological, physical and biochemical markers are
not much reliable for fingerprinting because these are highly influenced by
environmental conditions and growth stages (Maina et al. 2019). Introduction of molecular markers brings a great
revolution in phylogenetic relationships and evaluation of genetic variation
(Hazzouri et al. 2015). Among
molecular markers, SSRs and ISSRs are frequently used for evaluation of genetic
diversity of date palm genotypes (Yusuf et
al. 2015; Mirbahar et al. 2016).
ISSRs have high genome abundance, dominant nature, high polymorphism, high
reproducibility and less developmental cost. So, these are appropriate markers
for DNA fingerprinting of date palm genotypes (Karim et al. 2010). SSRs have moderate genome abundance, co-dominant
nature, crop specific, moderate developmental cost and very high
reproducibility (Naeem et al. 2018).
Cluster and structure analyses based on SSRs and ISSRs are effective tools used
for evaluation of genetic relationship and genetic structure of huge set of
genotypes (Ashraf et al. 2016).
Markers discriminating indices i.e., polymorphic information content (PIC), confusion probability (Cj)
and discriminating power (Dj) are
reliable parameters and have been used for determination of markers potential
in fingerprinting of pistachio genotypes (Belaskri et al. 2018). The highest PIC
and Dj of molecular markers
indicate that these have excellent potential to determine genetic diversity
among the studied genotypes. However, the highest Cj of molecular markers exhibit that these markers have poor
reliability for evaluation of genetic variation among the studied genotypes
(Ahmad et al. 2019). Direct
relationship exists between PIC and Dj, while these have inverse relation
with Cj (Ahmad et al. 2019). Hence, selection of molecular markers could be
fruitful for different genetic analyses based on these markers indices i.e., PIC, Cj and Dj.
In Pakistan, different research organizations/stations i.e., Date palm Research Sub-Station,
Jhang, Horticultural Research Station, Bahawalpur, Date Palm Research Station,
Khairpur and District Government Orchard, Layyah are working on selection and
breeding of date palm genotypes (Markhand et
al. 2010; Naqvi et al. 2015).
Mostly, they are focusing on morphological markers for identification of date
palm genotypes. In Pakistan, there are 325 date palm genotypes that need to be
secured scientifically focusing on molecular aspects (Jamil et al. 2010; Haider et al. 2015). In the world, there is extensive use of molecular
markers for different genetic analyses i.e.,
DNA fingerprinting, phylogenetic studies, genotyping-by-sequencing, genome
sequencing and re-sequencing and genome wide association (Gros-Balthazard et al. 2018). Hussein et al. (2004) used RAPDs and ISSRs
(dominant markers system) for DNA fingerprinting of seven date palm genotypes
collected from Egypt. Younis et al. (2008) used RAPDs and ISSRs for identification of male
plants grown in Egypt region. Phylogenetic relationship was determined among
date palm genotypes using RAPDs and ISSRs (Abdulla and Gamal 2010; Kumar et al. 2010). RAPDs and chloroplast
ribosomal protein gene were used for determination of genetic similarity among
Pakistani date palm genotypes (Akhtar et
al. 2014; Mirbahar et al. 2014).
In Pakistan, application of different molecular markers systems like dominant
and co-dominant for different genetic analyses of date palm genotypes is very
negligible. However, few researches were conducted on genetic similarity among
date palm genotypes. Accurate information of genotypes is a basic need for
better utilization of germplasm in the country. Knowledge of genetic variation,
population structure and its linkage within or among the populations is important to better understand the
available genetic inconsistency for further exploration in potential breeding
programs. In this scenario, current study encourages the comparison of dominant
(ISSRs) and co-dominant (SSRs) molecular markers for evaluation of genetic
similarity among indigenous date palm genotypes.
Methods and Methods
Plant materials and DNA isolation
Fifty date
palm genotypes were collected from two different research stations of Punjab,
Pakistan (Table 1). Mature leaves were collected from selected date palm trees
and stored at -80°C for DNA extraction. DNA was isolated according to CTAB
method as described by Doyle (1987). Spectro nanophotometer (Implen
Nano-photometer, Germany) was used to calculate concentration and purity of
extracted DNA.
Amplification of ISSRs and SSRs
PCR reaction
of 20 ΅L volume
was performed using 30 ng/΅L of
genomic DNA as template, 10Χ PCR buffer and 1 unit of Taq DNA polymerase (Fermentas, USA). PCR reactions were carried out in a
thermal cycler (MyCycler, BioRad,
USA). Detailed description of ISSRs sequences and annealing temperatures are
listed in Table 2. The SSRs sequences and annealing temperatures are given in
Table 3 & 4. Amplified PCR products were visualized using 1% agarose gel
after electrophoresis at 80 voltage for 3 h and
photographed with gel documentation system (Photonyx,
USA). The binary data were collected as presence of bands (1) and absence of
bands (0) for each locus.
Genetic diversity analyses
Two
separate dendrograms of SSRs and ISSRs were constructed under un-weighted pair
group method of arithmetic means (UPGMA) with statistical software NTSYS-pc
Version 2.10 (Rohlf 2002).
Population structure analyses
A
statistical software STRUCTURE program ver. 2.3.4. was used for evaluation of
genetic structure and neighbor joining tree of fifty date palm genotypes. The
appropriate K value was calculated through Structure Harvester as described
(Earl 2012). The number of sub-populations (ΔK) was calculated through
ad-hoc statistic method (Evanno et al.
2005). K value graph was developed through Microsoft Excel program, 2016.
Markers discriminating catalog
Polymorphic
information content (PIC), confusion probability
(Cj), discriminating power (Dj) of each primer pair were calculated as described earlier (Ahmad
et al. 2019).
Comparison of ISSRs and SSRs markers systems
Table 1: Date palm genotypes collected from different research
stations of Punjab, Pakistan
Genotype name |
Collection site |
Latitude |
Longitude |
Elevation |
Akhrot |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Dhakki |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Aseel |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Hilawi-1 |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Hilawi-2 |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Kantar |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Makran |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Chohara |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Zahidi |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Burhami |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Neelum |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Zarin |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Haleeni |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Jaman |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Kohraba |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Koznabad |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Karbalaen |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Jan Sahr |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Gokhna |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Danda |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Begum Jangi |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Deglet Noor |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Peela Dhora |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Shamran-1 |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Shamran-2 |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Rachna |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Seib |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Zardo |
Date palm Research
Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Shado |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Peeli Sundar |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Khudrawi-1 |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Khudrawi-2 |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Wahn Wali |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Angoor |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Champa Kali |
Date palm
Research Sub-Station, Jhang |
31, 15.557 |
72, 19.960 |
492 |
Baidhar |
Horticultural
Research Station, Bahawalpur |
29, 22.796 |
71, 38.787 |
335 |
Dedhi |
Horticultural
Research Station, Bahawalpur |
29, 22.796 |
71, 38.787 |
335 |
Sundari |
Horticultural
Research Station, Bahawalpur |
29, 22.796 |
71, 38.787 |
335 |
Kupra |
Horticultural
Research Station, Bahawalpur |
29, 22.796 |
71, 38.787 |
335 |
Shakri |
Horticultural
Research Station, Bahawalpur |
29, 22.796 |
71, 38.787 |
335 |
Eedel Shah |
Horticultural
Research Station, Bahawalpur |
29, 22.796 |
71, 38.787 |
335 |
Pathri |
Horticultural
Research Station, Bahawalpur |
29, 22.796 |
71, 38.787 |
335 |
Kur |
Horticultural
Research Station, Bahawalpur |
29, 22.796 |
71, 38.787 |
335 |
Tarmali |
Horticultural
Research Station, Bahawalpur |
29, 22.796 |
71, 38.787 |
335 |
Fasli |
Horticultural
Research Station, Bahawalpur |
29, 22.796 |
71, 38.787 |
335 |
Sufaida |
Horticultural
Research Station, Bahawalpur |
29, 22.796 |
71, 38.787 |
335 |
Hamin Wali |
Horticultural
Research Station, Bahawalpur |
29, 22.796 |
71, 38.787 |
335 |
Gajar |
Horticultural
Research Station, Bahawalpur |
29, 22.796 |
71, 38.787 |
335 |
Halmain |
Horticultural
Research Station, Bahawalpur |
29, 22.796 |
71, 38.787 |
335 |
Makhi |
Horticultural
Research Station, Bahawalpur |
29, 22.796 |
71, 38.787 |
335 |
Naqvi et al. (2015)
Comparison
between two markers systems ISSRs and SSRs was conducted by calculating
different indices (Maras et al.
2008).
Results
Cluster analysis and similarity matrix
Table 2: Markers sequences and annealing temperatures of ISSRs
Marker name |
Marker sequence (5ʹ
-3ʹ) |
Annealing temperature (°C) |
UBC-808 |
AGAGAGAGAGAGAGA GC |
52 |
UBC-809 |
AGAGAGAGAGAG AGA GG |
52 |
UBC-810 |
GAGAGAGAGAGAGAG AT |
52 |
UBC-811 |
GAGAGAGAGAGAGAG AC |
52 |
UBC-812 |
GAGAGAGAGAGAGAGAA |
52 |
UBC-813 |
CTCTCTCTCTCTCTCTT |
52 |
UBC-814 |
CTCTCTCTCTCTCTCTA |
52 |
UBC-815 |
CTCTCTCTCTCTCTCTG |
52 |
UBC-816 |
CACACACACACACACAT |
52 |
UBC-817 |
CACACACACACACACAA |
52 |
UBC-818 |
CACACACACACACACAG |
52 |
UBC-819 |
GTGTGTGTGTGTGTGTA |
54 |
UBC-820 |
GTGTGTGTGTGTGTGTC |
54 |
UBC-822 |
TCTCTCTCTCTCTCTCA |
52 |
UBC-823 |
TCTCTCTCTCTCTCTCC |
50 |
UBC-825 |
ACACACACACACACACT |
52 |
UBC-826 |
ACACACACACACACACC |
52 |
UBC-827 |
ACACACACACACACACG |
48 |
UBC-828 |
TGTGTGTGTGTGTGTGA |
52 |
UBC-829 |
TGTGTGTGTGTGTGTGC |
52 |
UBC-834 |
AGAGAGAGAGAGAGAGYT |
54 |
UBC-836 |
AGA GAG AGA GAG AGA GYA |
52 |
UBC-840 |
ACAATGGCTACCACCAGC |
52 |
UBC-841 |
GAGAGAGAGAGAGAGACTC |
52 |
UBC-842 |
ACAATGGCTACCACTACC |
48 |
UBC-845 |
CTCTCTCTCTCTCTCTRG |
50 |
UBC-846 |
CACACACACACACACART |
50 |
UBC-847 |
CACACACACACACACARC |
52 |
UBC-848 |
CAACAATGGCTACCACCG |
52 |
UBC-850 |
GTGTGTGTGTGTGTGTYC |
52 |
UBC = University of British Colombia
Dendrograms were
generated on the basis of these two markers systems for fingerprinting of date
pam genotypes. This ISSRs based dendrogram was
truncated at similarity coefficient 0.75 and grouped fifty date palm genotypes
into seven main clusters (cluster AG). Cluster G was sub-divided into two
sub-clusters i.e., G1
& G2 (Fig. 1). Two genotypes Begum Jangi and Burhami of Jhang
region remained independent and did not group with any other genotypes. Cluster
G comprised of twenty-six genotypes, being the largest as compared to other
clusters (Fig. 1). Cluster G is admixtures of genotypes collected from
Bahawalpur and Jhang regions. Genotype Halmain shared (93%) genetic similarity
with genotype Makhi which is the highest than among other genotypes. These two
genotypes were collected from same region Bahawalpur. Sub cluster G1
exhibited the highest genetic similarity between Zardo and Shado (91%)
collected from Jhang region. The greater genetic similarity existed in Kupra
and Shakri (91%) in sub cluster G2 collected from Bahawalpur region.
Cluster F comprised of five genotypes i.e.,
Dhakki, Makran, Aseel, Hilawi-1 and Kantar. The highest genetic similarity was
found between Hilawi-1 and Kantar (88%) as compared to other genotypes of
cluster F. Cluster E contained only two genotypes Chohara and Zahidi having
same origin of collection as Jhang region. Four genotypes i.e., Neelum, Zarin, Haleeni and Koznabad were grouped into cluster
D. Jaman, Jan Sahr, Gokhna and Danda were clustered into cluster C. Cluster B
comprised of five genotypes Deglet Noor, Peela Dhora, Shamran-1, Shamran-2 and
Rachna. Kohraba and Karbalaen were grouped into cluster A. Cluster A, B, C, D,
E and F genotypes were collected from Jhang region. However, cluster G showed
the mixing of genotypes collected from two different regions i.e. Jhang and Bahawalpur.
Cluster analysis based on SSRs grouped fifty date palm
genotypes into three major clusters (cluster AC) truncated at similarity
coefficient 0.95 (95%) (Fig. 2). Five genotypes from
Jhang region showed the highest genetic similarity with one genotype Dedhi from
Bahawalpur region. Therefore, these genotypes grouped together in cluster A.
Genotype Koznabad from Jhang region shared 96% genetic similarity with genotype
Dedhi from Bahawalpur region. Cluster B comprised of 17 mixed genotypes i.e., Makran, Kupra, Shakri, Eedel Shah,
Sufaida, Burhami, Neelum, Jaman, Kohraba, Karbalaen, Shamran-1, Shamran-2,
Rachna, Seib, Zardo, Sundari and Halmain of Jhang and Bahawalpur regions. Four
genotypes i.e., Kupra, Shakri, Eedel
Shah and Sufaida were collected from Bahawalpur region among 17 genotypes of
cluster B. Cluster C contained 21 mixed genotypes i.e., Akhrot, Dhakki, Aseel, Hilawi-1, Kantar, Chohara, Zahidi,
Zarin, Danda, Deglet Noor, Peela Dhora, Peeli Sundar, Hilawi-2, Pathri, Kur,
Tarmali, Fasli, Hamin Wali, Gajar, Makhi and Haleeni of Bahawalpur and Jhang
regions. Pathri, Kur, Tarmali, Fasli, Hamin Wali, Gajar and Makhi genotypes
from Bahawalpur region exhibited genetic similarity with Jhang region genotypes
as in cluster C (Fig. 2).
Population structure analysis
ISSRs
and SSRs results were used to perform population structure analysis for fifty
date palm genotypes under an admixed Bayesian model. Bar plot, best K value and
neighbor joining tree were developed using results of ISSRs and ISSRs to
determine the sub-population of fifty genotypes collected from two different
regions (Fig. 3AC and Fig. 4AC). Population structure analysis using SSRs
results exhibited that the Logarithm of the Data likelihood Table 3: SSRs sequences for evaluation
of genetic diversity in date palm germplasm
Marker name |
Marker sequence (5ʹ
-3ʹ) |
Reference |
PDAAG 1001-Forward |
TGCCGAGTGGTTTAATTGTG |
Arabnezhad et al.
(2012) |
PDAAG 1001-Reverse |
TGAAGCAGAGAATCCAACAGAG |
Arabnezhad et al.
(2012) |
PDAAG 1002-Forward |
GGACATAGTTTTGGCTGGCTAC |
Arabnezhad et al.
(2012) |
PDAAG 1002-Reverse |
ACCAGTTTACCACTTGCTCCA |
Arabnezhad et al.
(2012) |
PDAAG 1003-Forward |
GACTGGGAATATAAAGCGATGTC |
Arabnezhad et al.
(2012) |
PDAAG 1003-Reverse |
CCATCTCCCCTAACTCTCCTC |
Arabnezhad et al.
(2012) |
PDAAG 1005-Forward |
GTATGTTCCATGCCGTTCTAC |
Arabnezhad et al.
(2012) |
PDAAG 1005-Reverse |
AGCCACATCACTTGGTTCA |
Arabnezhad et al.
(2012) |
PDAAG 1008-Forward |
GATGCTGAACTCGGACAAAG |
Arabnezhad et al.
(2012) |
PDAAG 1008-Reverse |
TGGGTAGAGATGGTTGGTTG |
Arabnezhad et al.
(2012) |
PDAAG 1010-Forward |
TGAAGCAGTGAGTTCCATTG |
Arabnezhad et al.
(2012) |
PDAAG 1010-Reverse |
GATGTGCTTTGTGCCATTC |
Arabnezhad et al.
(2012) |
PDAAG 1011-Forward |
TCGATCGCTCCTCCTACAGT |
Arabnezhad et al.
(2012) |
PDAAG 1011-Reverse |
GTCACGCCTTTCATTCCTTC |
Arabnezhad et al.
(2012) |
PDAAG 1013-Forward |
CCAAAACTCTGTTTTCTCTTTGG |
Arabnezhad et al.
(2012) |
PDAAG 1013-Reverse |
CCTGCATGAACTGAACTAGCC |
Arabnezhad et al.
(2012) |
PDAAG 1014-Forward |
TCGTGCATTTAGAACGTTGA |
Arabnezhad et al.
(2012) |
PDAAG 1014-Reverse |
GAGCACGACTTACGAGTTC |
Arabnezhad et al.
(2012) |
PDAAG 1015-Forward |
CTTGGTCGCTGCTTAAAATG |
Arabnezhad et al.
(2012) |
PDAAG 1015-Reverse |
TGGGAACAGGAGACCATCA |
Arabnezhad et al.
(2012) |
PDAAG 1016-Forward |
TCTCAAGCCTCTCAGGTTGC |
Arabnezhad et al.
(2012) |
PDAAG 1016-Reverse |
CCTAGTCGATGCTGTTGTTCC |
Arabnezhad et al.
(2012) |
PDAAG 1017-Forward |
GCTGCGAGGAGAGATTTCAT |
Arabnezhad et al.
(2012) |
PDAAG 1017-Reverse |
GGGAAAAATCTAAATGAACAGGTG |
Arabnezhad et al.
(2012) |
PDAAG 1018-Forward |
TGTCTGCTGCCATTCTGTTC |
Arabnezhad et al.
(2012) |
PDAAG 1018-Reverse |
CTGACCATGGACCACCTACC |
Arabnezhad et al.
(2012) |
PDAAG 1019-Forward |
ATTTCTTTCCCCCACGTTTC |
Arabnezhad et al.
(2012) |
PDAAG 1019-Reverse |
CCAGGTGACACTGCATTCC |
Arabnezhad et al.
(2012) |
PDAAG 1020-Forward |
CGCTCATAAATTAGGGCATTG |
Arabnezhad et al.
(2012) |
PDAAG 1020-Reverse |
CCCTAGGTGATGAAGGACCAC |
Arabnezhad et al.
(2012) |
PDAAG 1021-Forward |
GGAGAGAAACGGAACAAGAAG |
Arabnezhad et al.
(2012) |
PDAAG 1021-Reverse |
AGCGTCCAAGAACAAGGTATG |
Arabnezhad et al.
(2012) |
PDAAG 1022-Forward |
TTCGGAGAATTGGATCCTTG |
Arabnezhad et al.
(2012) |
PDAAG 1022-Reverse |
GTTTGGTCGGCTGAGATGTG |
Arabnezhad et al.
(2012) |
PDAAG 1023-Forward |
AGACGCTCACCTTGGAACTT |
Arabnezhad et al.
(2012) |
PDAAG 1023-Reverse |
ACCCCGCTCATGAATTAGG |
Arabnezhad et al.
(2012) |
PDAAG 1024-Forward |
CTTCTCCACTGGCATCTTCC |
Arabnezhad et al.
(2012) |
PDAAG 1024-Reverse |
CACCCGTTGGGCATCTTA |
Arabnezhad et al.
(2012) |
PDAAG 1025-Forward |
ATCCCGTCCTCTCTTTCCA |
Arabnezhad et al.
(2012) |
PDAAG 1025-Reverse |
CATGCATACATATACGCAAAGAA |
Arabnezhad et al.
(2012) |
KSU-PDL 2-Forward |
TTGGAGTAGGAGACGACAATA |
Al-Faifi et al. (2016) |
KSU-PDL 2-Reverse |
GGGAGTGAGAGGGATATGTAG |
Al-Faifi et al. (2016) |
KSU-PDL 4-Forward |
CAACATAAGGAAAAATGATGC |
Al-Faifi et al. (2016) |
KSU-PDL 4-Reverse |
TGCATCACTCTGGGTATAAAT |
Al-Faifi et al. (2016) |
KSU-PDL 6-Forward |
GCTTTTGCAAATAACAACATC |
Al-Faifi et al. (2016) |
KSU-PDL 6-Reverse |
CATGGAAAAGGCTCCTATC |
Al-Faifi et al. (2016) |
KSU-PDL 18-Forward |
TGTGGTCTATCCATTTTGTGT |
Al-Faifi et al. (2016) |
KSU-PDL 18-Reverse |
GTCATGCAGTTCTCAAAGAAA |
Al-Faifi et al. (2016) |
KSU-PDL 21-Forward |
GCTACTCCTTCTTCTTCTCCTT |
Al-Faifi et al. (2016) |
KSU-PDL 21-Reverse |
TGATGATTGGTTGAGATTAAGA |
Al-Faifi et al. (2016) |
KSU-PDL 29-Forward |
AGCACATGGCAGTTACTCTAC |
Al-Faifi et al. (2016) |
KSU-PDL 29-Reverse |
AACAACAACAATCAGTCCAAA |
Al-Faifi et al. (2016) |
KSU-PDL 42-Forward |
GACCGTACAGTCACATGATTT |
Al-Faifi et al. (2016) |
KSU-PDL 42-Reverse |
TAGGAGAGAGAGAGGGTTTTG |
Al-Faifi et al. (2016) |
KSU-PDL 58-Forward |
GAGAAGAGAAAGGGAGAGAGA |
Al-Faifi et al. (2016) |
KSU-PDL 58-Reverse |
GCCCTTCTTAATCAACAAAAT |
Al-Faifi et al. (2016) |
KSU-PDL 64-Forward |
ACTCTTGTGGGACTCCTTTAC |
Al-Faifi et al. (2016) |
KSU-PDL 64-Reverse |
CCTAAATGTGCTTTCCTTCTT |
Al-Faifi et al. (2016) |
KSU-PDL 76-Forward |
TTGGAGTAGGAGACGACAATA |
Al-Faifi et al. (2016) |
KSU-PDL 76-Reverse |
AGAGAGAGATGGGGAAGAAG |
Al-Faifi et al. (2016) |
[Ln (PD)] on average continued to increase with
increasing the numbers of assumed sub-populations (K) from 2 to 10. The adhoc quantity based on the second order rate of
change in the log probability (∆K) exhibited a clear peak at K = 3. So,
Ln (PD) suggested that a K value of three was the most probable prediction for
the number of sub-populations for both ISSRs and SSRs (Fig. 3A and Fig. 4A).
ISSRs based structure analysis depicted that bar plot has been configured into
three different colors i.e. red, blue and green (Fig. 3C). The highest
contribution was recorded from red color. So, similar depiction was found in
neighbor joining tree (Fig. 3B). Structure analysis on
Fig. 1: Dendrogram showing genetic
relationship among fifty date palm genotypes based on ISSR markers
the basis of SSRs
exhibited that bar plot has been separated into three different colors i.e.
red, blue and green (Fig. 4C). The highest contribution was recorded from green
color. So, similar depiction was found in neighbor joining tree (Fig. 4B).
Markers discriminating catalog
A total of
30 SSRs and 30 ISSRs were used for fingerprinting in collected date palm
genotypes. From 30 ISSRs, two ISSRs (UBC-811 and UBC-840) were monomorphic and
the other 28 were polymorphic and polymorphism was shown (Fig. 5). From 30
SSRs, only primer PDAAG-1010 was polymorphic, 21 were monomorphic and eight
were non-amplified (Table 4). The range of allele size for ISSRs varied from 260
to 1600 bps. The highest PIC (0.394)
and Dj (0.722) was obtained through
UBC-808, while the lowest PIC (0.113)
and Dj (0.559) was obtained through
UBC-817 as compared to all other primers. Moreover, the highest Cj (0.882) was calculated in UBC-817,
while the lowest Cj (0.598) as
compared to all other ISSRs primers (Table 5). PIC, Dj and Cj for PDAAG-1010 are listed in Table 5.
Comparison of ISSRs and SSR markers systems
ISSRs
showed the highest number of assay unit (30) than SSRs (22). The maximum number
of polymorphic bands (141) and number of polymorphic bands/ assay (4.7) were
revealed from ISSRs; while the minimum polymorphic bands (4.00) and number of
polymorphic bands/ assay (0.13) were revealed from SSRs. Number of monomorphic
bands were lower in ISSRs (12) than SSRs (22). Greater number of loci (153),
number of loci/ assay unit (51), effective multiplex ration (4.7) and markers
index (1.32) were revealed by ISSRs as compared to SSRs. Expected
heterozygosity was greater for SSRs (0.51) than ISSRs (0.28) as listed in Table
6.
Discussion
Fig. 2: Dendrogram showing genetic
relationship among fifty date palm genotypes based on SSR markers
Fig. 3: Population structure analysis showing
genetic relationship among fifty date palm genotypes based on ISSR markers; A =
best K value graph, B = neighbor joinng tree and C = bar plot
The
addition of new genotypes in the gene pool can cause complication to
distinguish the difference among germplasm only using morphological and
biochemical markers. Morphological characteristics, biochemical properties and
pedigree information are traditional ways of germplasm identification. These
identification resources are greatly influenced through environmental
fluctuations, cultural practices, nutritional aspects and numerous other
management practices (Teng et al.
2002; Anjum et al. 2018). In
addition, farmers name their genotypes on the basis of genotypes location,
fruit color, taste and shape since the ancient time (Sharif et al. 2019). Hence, misnaming of
genotypes is a big problem in classification of date palm genotypes. Therefore,
present study Table 4: Amplification of SSRs for
evaluation of genetic diversity in date palm genotypes
Marker name |
Annealing temperature (°C) |
Range of allele size |
Amplification of SSRs |
PDAG 1001 |
54 |
800 |
Monomorphic |
PDAG 1002 |
52 |
80 |
Monomorphic |
PDAG 1003 |
55 |
250 |
Monomorphic |
PDAG 1005 |
54 |
300 |
Monomorphic |
PDAG 1008 |
56 |
280 |
Monomorphic |
PDAG 1010 |
54 |
200-250 |
Polymorphic |
PDAG 1011 |
58 |
- |
Non-amplified |
PDAG 1013 |
55 |
250 |
Monomorphic |
PDAG 1014 |
52 |
200 |
Monomorphic |
PDAG 1015 |
55 |
150 |
Monomorphic |
PDAG 1016 |
55 |
400 |
Monomorphic |
PDAG 1017 |
54 |
- |
Non-amplified |
PDAG 1018 |
52 |
60 |
Monomorphic |
PDAG 1019 |
55 |
200 |
Monomorphic |
PDAG 1020 |
56 |
150 |
Monomorphic |
PDAG 1021 |
54 |
170 |
Monomorphic |
PDAG 1022 |
58 |
200 |
Monomorphic |
PDAG 1023 |
54 |
- |
Non-amplified |
PDAG 1024 |
56 |
- |
Non-amplified |
PDAG 1025 |
56 |
230 |
Monomorphic |
KSU-PDL 2 |
50 |
- |
Non-amplified |
KSU-PDL 4 |
54 |
150 |
Monomorphic |
KSU-PDL 6 |
54 |
100 |
Monomorphic |
KSU-PDL 18 |
54 |
70 |
Monomorphic |
KSU-PDL 21 |
54 |
- |
Non-amplified |
KSU-PDL 29 |
52 |
400 |
Monomorphic |
KSU-PDL 42 |
53 |
0 |
Non-amplified |
KSU-PDL 58 |
50 |
0 |
Non-amplified |
KSU-PDL 64 |
54 |
150 |
Monomorphic |
KSU-PDL 76 |
52 |
150 |
Monomorphic |
Fig. 4: Structure analysis showing genetic
relationship among fifty date palm genotypes based on SSR markers; A = best K value graph; B = neighbor joinng tree and C = bar plot
encourages the use of
different molecular markers for identification and authentication of date palm
genotypes, as genetic make-up of genotypes is not influenced due to climatic
conditions and external impact (Ahmad et
al. 2019). Among molecular markers, SSRs and ISSRs are reliable for DNA
fingerprinting. The current study successfully evaluated the genetic diversity/
fingerprinting and population structure of fifty date palm genotypes and tried
to resolve the misnaming of genotypes in nomenclature.
Table 5: Markers discriminating indices of ISSRs and SSRS
Marker name |
Range of allele
size (bp) |
Number of loci |
Polymorphic
bands |
PIC |
Cj |
Dj |
UBC-808 |
300 - 1050 |
7 |
7 |
0.394 |
0.598 |
0.722 |
UBC-809 |
400 - 650 |
4 |
3 |
0.329 |
0.664 |
0.668 |
UBC-810 |
350 - 1200 |
8 |
8 |
0.329 |
0.664 |
0.696 |
UBC-812 |
300 - 1100 |
4 |
4 |
0.384 |
0.609 |
0.697 |
UBC-813 |
500 - 1000 |
4 |
4 |
0.387 |
0.606 |
0.607 |
UBC-814 |
550 - 900 |
2 |
2 |
0.210 |
0.786 |
0.604 |
UBC-815 |
300 - 1500 |
7 |
7 |
0.168 |
0.829 |
0.586 |
UBC-816 |
700 - 1450 |
6 |
6 |
0.203 |
0.792 |
0.683 |
UBC-817 |
1100 - 1150 |
2 |
1 |
0.113 |
0.882 |
0.559 |
UBC-818 |
370 - 1200 |
10 |
9 |
0.359 |
0.634 |
0.610 |
UBC-819 |
800 - 1500 |
3 |
2 |
0.228 |
0.767 |
0.606 |
UBC-820 |
400 - 1000 |
8 |
8 |
0.215 |
0.781 |
0.574 |
UBC-822 |
550 - 750 |
3 |
2 |
0.221 |
0.775 |
0.605 |
UBC-823 |
550 - 770 |
4 |
3 |
0.145 |
0.852 |
0.570 |
UBC-825 |
300 - 1200 |
5 |
5 |
0.265 |
0.730 |
0.656 |
UBC-826 |
770 - 1350 |
6 |
6 |
0.353 |
0.640 |
0.646 |
UBC-827 |
400 - 1600 |
8 |
7 |
0.371 |
0.621 |
0.675 |
UBC-828 |
450 - 1250 |
6 |
6 |
0.314 |
0.649 |
0.666 |
UBC-829 |
550 - 1300 |
5 |
5 |
0.325 |
0.669 |
0.655 |
UBC-834 |
450 - 1200 |
5 |
5 |
0.304 |
0.690 |
0.649 |
UBC-836 |
300 - 900 |
4 |
4 |
0.292 |
0.702 |
0.675 |
UBC-841 |
450 - 1100 |
6 |
5 |
0.321 |
0.672 |
0.664 |
UBC-842 |
450 - 1400 |
3 |
2 |
0.319 |
0.775 |
0.613 |
UBC-845 |
350 - 1000 |
9 |
9 |
0.306 |
0.688 |
0.624 |
UBC-846 |
260 - 800 |
4 |
3 |
0.243 |
0.752 |
0.624 |
UBC-847 |
600 - 1500 |
6 |
5 |
0.372 |
0.620 |
0.624 |
UBC-848 |
300 - 700 |
6 |
5 |
0.205 |
0.791 |
0.624 |
UBC-850 |
400 - 1100 |
4 |
3 |
0.208 |
0.788 |
0.624 |
PDAAG-1010 |
200-250 |
4 |
4 |
0.510 |
0.746 |
0.677 |
PIC= Polymorphic information
contents, Cj = Confusion probability, Dj=
Discriminating power, bp= Base
pair
Table 6: Indices for the comparison of ISSRs and SSRs
Indices |
Abbreviations |
Markers system |
|
ISSRs |
SSRs |
||
Number of assay
unit |
U |
30.00 |
22.00 |
Number of
polymorphic bands |
np |
141.00 |
4.00 |
Number of
monomorphic bands |
nnp |
12.00 |
22.00 |
Number of
polymorphic bands/ assay |
np/ U |
4.70 |
0.13 |
Number of loci |
L |
153.00 |
26.00 |
Number of loci/
assay unit |
Nu |
5.10 |
1.18 |
Expected heterozygosity of polymorphic loci |
Hep |
0.28 |
0.51 |
Fraction of
polymorphic bands |
β |
0.92 |
0.15 |
Effective
multiplex ratio |
E |
4.70 |
0.18 |
Markers index |
MI |
1.32 |
0.09 |
ISSRs and SSRs based dendrograms exhibited variation in
total number of main clusters, sub clusters and location of genotypes within
clusters. Hence, current differences might be due to different markers behavior
because different markers identify different distinctive regions of DNA
variation within the genome (Ashraf et
al. 2016). Regarding the ISSRs, cluster analysis and similarity matrix
determined the highest genetic similarity between Halmain and Makhi (93%) than
all other genotypes. Halmain and Makhi, Zardo and Shado, Peeli Sundar and
Khudrawi-2, Tarmali and Fasli, and Kupra and Shakri genotypes were close to
each other showing similar genetic make-up. Similarly, the highest genetic
similarity through ISSRs was recoded in previous findings (Karim
Fig. 5: ISSR and SSRs amplification of 50 date palm genotypes
et al. 2010; Mirbahar et al. 2016). Cluster G is admixture of
genotypes of two different regions which is due to germplasm exchange,
ecological differences and distinctive adoptive behavior of genotypes (Hamza et al. 2012; Naeem et al. 2018). Cluster analysis of ISSRs revealed that two genotypes
Begum Jangi and Burhami remain independent and did not cluster with any other
genotypes in the current study. These two genotypes are highly divergent due to
different and unique genetic background. The highest polymorphism and genetic
diversity was found in these two genotypes. The greater genetic variation in
these genotypes revealed that these were diverse clones and introduced long
years ago as a cultivar (Ahmad et al.
2019). Regarding the SSRs, cluster analysis and similarity matrix revealed the
highest genetic similarity among the genotypes of Jhang and Bahawalpur regions.
All clusters (A, B and C) showed the mixture of genotypes of two different
locations. So, this similarity among these genotypes was due to exchange of
germplasm, different adaptive conditions of environment (Elshibli and
Korpelainen 2008). Moreover, the highest genetic similarity has already been
reported among date palm genotypes collected from different geographical
regions (Elmeer et al. 2011; Azouzi et al. 2015). Current study is under
conformity of earlier work because they examined that cluster analysis
significantly discriminated the genotypes of different countries i.e., North African and Middle Eastern
through SSRs (Arabnezhad et al.
2012).
Genetic divergence, allelic admixture and evolutionary
relationship can be evaluated through population structure analysis developed
from different molecular markers (Naeem et
al. 2018). Population structure analysis of ISSRs showed the existence of
three main groups i.e., red, blue and
green in the studied population. Red color group had the highest allelic
admixture as compared to other two groups. Bar plot and neighbor joining tree
indicated the presence of three main groups i.e.,
red, blue and green in the studied population. Green color group shared the
maximum allelic admixture than other two groups. Structure analyses proved
complex genetic structures and strong relationship within some genotypes
present in the studied genotypes. Allelic admixture is because of local
adaptation of foreign genotypes. The introduction of exotic germplasm within
the country is very common (Naeem et al.
2018). Allelic mixtures resulting in the introduction of new genetic linkages
into a population increase heterozygosity (Azouzi et al. 2015). The results of structure analysis confirmed the
results of genotype clustering on the basis of similarity matrix. Recently,
Chaluvadi et al. (2014) evaluated
allelic admixture and close affinity among date palm genotypes using structure
analysis.
Different markers indices i.e., PIC, Cj and Dj are suitable tools for determination of efficiency of a
molecular marker. All these indices vary and depend on application nature of molecular
markers (Naeem et al. 2018). The
highest polymorphism was recorded in ISSRs due to dominant nature and higher
number of loci as compared to SSRs (Hamza et
al. 2013). Application of primers for ISSRs and SSRs was same; however, 28
ISSRs and only one SSR showed polymorphism. So, SSRs give less polymorphism
because of its conserved nature and continuous selection of genotypes. ISSRs
revealed higher level of genetic diversity in date palm genotypes than SSRs.
Previous studies confirmed that ISSRs revealed the highest polymorphism due to
many loci which is effective for evaluation of genetic diversity in date palm
genotypes (Karim et al. 2010; Ashraf et al. 2016). Concerning the ISSRs,
UBC-808 had the highest PIC and Dj, while lower Cj among all the studied primers. Therefore, UBC-808 had excellent
potential for discrimination among studied germplasm. UBC-817 had poor
potential to evaluate genetic diversity among the studied genotypes because of
higher Cj and lower PIC and Dj values. PIC and Dj are directly proportional to each
other, while inversely proportional with Cj.
Previous finding confirmed that excellent primer for allelic variation is that
which had higher PIC and Dj and lower Cj (Naeem et al. 2018;
Ahmad et al. 2019).
Comparison of two markers systems on the basis of
discriminating efficiency revealed that expected heterozygosity of SSRs was
higher than ISSRs markers system, indicating higher allelic variability among
date palm genotypes (Belaj et al.
2003). The highest markers index and effective multiplex ratio showed the
distinctive nature of ISSRs markers system (Ashraf et al. 2016).
Conclusion
The studied
date palm germplasm has very high genetic similarity. The population structure
analysis indicated the complex genetic structures of date palm genotypes with
high level of allelic admixture. Therefore, selection of suitable markers and
markers system is imperative for characterization of germplasm. Selection of a
molecular marker or set of markers with in a markers system by considering PIC, Dj and Cj values could yield encouraging results for genotypic
characterization. While comparing the two markers systems i.e. ISSRs and SSRs regarding their efficiency to reveal the difference among date palm
genotypes, ISSRs could be more suitable markers due to higher value of
effective multiplex ration (E) and
markers index (MI).
Acknowledgements
The authors are highly grateful to the Assistant
Horticulturist, Date palm Research Sub-Station, Jhang, and the Horticulturist,
Horticultural Research Station, Bahawalpur for providing the fruit samples, and
Bahauddin Zakariya University, Multan for financial support to conduct the
study.
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