Genetic Diversity among and within Genome Groups of Banana Cultivars Based on ISSR Markers
Didik Wahyudi1*,
Dwi Candra Nursita1 and Lia Hapsari2
1Biology Department, Science and Technology
Faculty, Universitas Islam Negeri Maulana Malik Ibrahim Malang, Jl. Gajayana
No. 50 Malang, East Java, 65144, Indonesia
2Research Center for Plant Conservation, Botanic
Gardens and Forestry, National Research and Innovation Agency, Kusnoto Building
Jl. Ir. H. Juanda No. 18, Bogor, West Java, 16122, Indonesia
*For correspondence:
didik_wahyudi@bio.uin-malang.ac.id; didik.s211@gmail.com
Received 14 December 2021; Accepted 14 November 2022; Published 12 December 2022
Abstract
East
Java was considered one of Indonesia's banana production
centres. More than 90
cultivars have been described, with diverse morphological characteristics and a
variety of local languages, making them an intriguing object to research. This
research aimed to examine both the genetic diversity and the
clustering among and within genome groups of banana cultivars in East Java
using ISSR markers. A total of 12 banana cultivars expressing different genome groups were
analyzed using five primers i.e.,
UBC834, UBC835, UBC843, UBC848 and UBC855. UBC-835 primer was considered the best ISSR primer
for amplification
in terms of PIC, EMR, MI and RP. Clustering
analysis resulted in 4
groups of banana cultivars based on their genome. As a result, the ISSR is a
powerful marker for identifying banana cultivars at the intraspecific level. Genetic diversity analysis among genome groups showed high genetic richness with Shannon index 0.587
and polymorphic loci 96.97%. Meanwhile, the AA genome group has the highest genetic variation within genome
groups, with Shannon index and polymorphic loci of 0.289 and 42.42%, respectively, followed
by ABB, AAB, and AAA genome groups. In addition, 50.43% of the
molecular variation was present within genome groups and
49.57% of variation lies among genome groups. The
genetic variation was considered slightly more conserved within the genome
groups of bananas. The
findings of this study provide the foundation for sustainable management of
East Java's local banana, both in situ and ex situ. © 2022 Friends Science Publishers
Keywords: Genetic diversity; Molecular marker; Musa; Polymorphism, PCR
Introduction
Banana
(genus Musa; family Musaceae) is a
popular horticultural crop that has grown since agriculture began (Langhe et al. 2009). Bananas are commonly
cultivated because they
are easy to grow and adapt to various
environmental situations. Hundreds of millions of people
in tropical and subtropical countries rely on bananas as a daily staple meal (Varma and
Bebber 2019). In addition,
bananas are also considered one of popular export commodity products in the world. In
2017, the global production of bananas was up to 144
million tons, and Indonesia reached 7.1 million tons (Ministry of Agriculture RI
2016).
The
Indo-Malesia region is the primary origin of wild and cultivar bananas, which
eventually spread throughout Asia, America, and Africa's tropics and subtropics (Perrier et al. 2011). At least 325 banana cultivars
are recorded in Indonesia (Valmayor et
al. 2000), distributed across the Indonesian
archipelago. In particular, the diversity of bananas in East Java
Province is considered high, with more than 90 cultivars reported. It has a
wide range of morphological features and is recognized in many local languages (Hapsari et al. 2015), which has
become an interesting object to study. East Java Province is also listed as a
center for banana production in Indonesia, with the highest production volume
of up to 2.6 tonnes in 2020 (Central Bureau of Statistics and Directorate
General of Horticulture 2021).
The majority of today's banana cultivars are the result of intraspecific
and interspecific hybridization between two diploid wild bananas, Musa acuminata
Colla (donate A genome) and Musa balbisiana Colla (donate B
genome) (Bakry et al.
2009; Perrier et al. 2011). As a result, the hybridization generated diploid, triploid, and
tetraploid bananas with varied A and B genomic configurations, including AA,
AAA, AB, AAB, ABB, AABB, AAAB and ABBB (Davey et al. 2013; Jesus et al. 2013). The conventional classification of genome groups
in bananas was developed by Simmonds and
Shepherd in 1955, using a scoring method based on 15 distinguishing morphological features of the two ancestral
parents. The final score will determine the
proportional contribution of this ancestral parent to the genomic formation of
banana cultivars today. However, research using more advanced molecular markers
is needed to confirm the genome classification's validity to overcome the
subjectivity weakness of the morphological approach in bananas.
Random amplified polymorphic DNA (RAPD) is the most
commonly used molecular marker for assessing genomic formation and genetic variability of banana
cultivars (Probojati et al. 2019; Wahyudi et al. 2020a). In addition, inter simple sequence repeats (ISSR) (Silva et al. 2017; Babu et al.
2018; Wahyudi et al. 2020b), sequence-related amplified polymorphism (SRAP) (Zozimo et al.
2018; Boonsrangsom et al. 2020) and amplified fragment length polymorphism (AFLP) (Youssef et al. 2011; Vroh-Bi et al. 2011) were also used for genomic
determination of banana cultivars. However, ISSR is a frequently used marker in
banana cultivars since it is one of the
semi-arbitrary markers that use
repeating primers orientated in opposing directions to create segments between
two identical microsatellite repeat regions (Reddy et al. 2002). ISSR markers have several advantages, including not
requiring initial genome sequence information, being effective in
differentiating individuals at intraspecies level and individuals with high
morphological similarities, relatively low costs with simple techniques, and
producing high polymorphisms (Sarwat 2012; Tesfaye et al. 2014; Gajera et al.
2014). It has been proven powerful to classify the different genome
constitutions and evolutionary patterns at intraspecific and interspecific
levels of banana cultivars (Poerba and Ahmad 2010; Jesus et al. 2013; Babu et al. 2018; Poerba et al.
2018; Wahyudi et al. 2020b).
Understanding
genetic diversity and
population dynamics are required as a foundation for sustainable conservation
management of genetic resources (Jesus et al. 2013; Rachmat et al. 2016; Resmi et al. 2016; Babu et al. 2018; Hapsari et al. 2018). However, the use of ISSR markers
to gather insight into the molecular diversity, clustering, and organization of
banana cultivars, particularly in East Java, is currently limited. Therefore, this study attempts to analyze the genetic diversity and the clustering among and within genome groups of
twelve selected banana cultivars from East Java using ISSR marker. The
information on the genetic diversity and clustering analysis of local banana cultivars would assist in
further conservation and breeding strategies.
Materials and Methods
Plant materials
This study used twelve (12) banana cultivars, a collection of Purwodadi Botanic Garden/PBG, located in
Pasuruan, East Java, as an ingroup (un-rooted). The banana cultivars were
previously collected from populations of several regions in East Java. The used banana cultivars
represent four genome groups i.e., AA, AAA, AAB and ABB (Table 1 and Fig. 1).
Collection data
DNA extraction:The
fresh young banana leaf of each sample was crushed into powder by using
liquid nitrogen. DNA extraction was performed using the Promega Wizard® DNA Isolation Kit. The DNA
isolation steps follow the guidelines for plants. The isolated DNA was then
confirmed quantitatively using the NanoDrop® Spectrophotometer ND-1000 at 260
and 280 nm wavelengths.
PCR ISSR: The PCR-ISSR
assays were conducted using five selected primers from the previous study (Wahyudi et al. 2020b). The
list of primers as well as the information on
their sequence are shown in Table 2. The total PCR reaction mixture was 10 µL consisting of 1 µL DNA
sample, 3 µL nuclease-free water, 1 µL 10 pmol primer, and 5 µL DreamTaq PCR Master Mix (2X). DNA
amplification was performed in Bio-RAD thermal cycler with 40 amplification cycles
consisting of denaturation at 94°C for 1 min, annealing with temperature according
to the used primer (Table 2) for 45 sec and extension at 72°C for 2 min. The amplification products were separated by electrophoresis in 1,5% agarose gel and TBE (1/2)x buffer at a voltage
of 80 V for 30 min. The bands were observed under
UV-transilluminator and visualized by Biorad Gel-Documentation system.
Data Analysis
The presence
of a band of individual cultivars was scored as 1 and 0 for
absent band. The fragment size of the DNA band
was estimated using a 1 Kb DNA ladder. The scoring of binary data
was then analyzed to determine the most suitable
primer for amplification, using four parameters i.e., polymorphic information
content (PIC), effective multiplex ratio (EMR), markers index (MI), and resolving power (RP). The PIC
value for each ISSR marker was calculated as proposed by Roldan-Ruiz et al. (2000), as , where PICi
is the polymorphic information content of marker i, fi is the frequency of the
marker bands present, and 1-fi is the frequency of absent marker bands. PIC was
averaged over all the bands for each primer. The EMR was estimated based on
Medhi et al. (2014) as ; which
n is defined as the product of the total number of the present band of each
primer and the number of polymorphic bands (np). The MI was calculated by using
the formulae described by Varshney et al. (2007), as MI = PIC × EMR. The RP value was calculated according to Prevost and
Wilkinson (1999) as RP = 1-[2×(0.5-P)], where P is the proportion of genotypes
containing bands.
Subsequently, multivariate distance indices and
clustering analyses were performed using Palaeontological Statistics (PAST) 3.0
software based on Ward's method of Table 1: List of banana cultivars examined in this study
No. |
Cultivar name (Pisang) |
Genome group |
Sub-group |
Population
source |
1 |
Mas Kripik |
AA |
Sucrier |
Senduro,
Lumajang |
2 |
Mas Jambe |
AA |
Sucrier |
Tulungagung,
Tulungagung |
3 |
Lilin |
AA |
Pisang Lilin |
Krucil,
Probolinggo |
4 |
Cebol |
AAA |
Dwarf
Cavendish |
Pasrujambe,
Lumajang |
5 |
Kongkong |
AAA |
Gros Michel |
Lawang,
Malang |
6 |
Kidang |
AAA |
Red |
Kalisat,
Jember |
7 |
Candi |
AAB |
Plantain |
Ambulu,
Jember |
8 |
Raja Ketan |
AAB |
Pisang Raja |
Siman,
Ponorogo |
9 |
Raja Temen |
AAB |
Pisang Raja |
Lawang,
Malang |
10 |
Tlekung |
ABB |
Saba |
Tlekung,
Batu |
11 |
Tajinan |
ABB |
Saba |
Glagah,
Banyuwangi |
12 |
Sabeh Biru |
ABB |
Bluggoe |
Camplong,
Sampang, Madura Island |
Table
2: List of ISSR primers used in
this study (Wahyudi et al. 2020b)
No. |
Primer name |
Sequences (5’-3’) |
MT (°C) |
AT (°C) |
1 |
UBC834 |
AGA GAG AGA GAG AGA GYT |
51.6 |
46.6 |
2 |
UBC835 |
AGA GAG AGA GAG AGA GYC |
53.9 |
48.9 |
3 |
UBC843 |
CTC TCT CTC TCT CTC TRA |
51.6 |
46.6 |
4 |
UBC848 |
CAC ACA CAC ACA CAC ARG |
53.9 |
48.9 |
5 |
UBC855 |
ACA CAC ACA CAC ACA CYT |
51.6 |
46.6 |
Remarks: R= A/G; Y= T/C; MT= Melting Temperature; AT= Annealing
Temperature
Fig. 1: Map population source of 12 banana cultivars examined:
1. Ponorogo, 2. Tulungagung, 3. Batu, 4. Malang, 5. Lumajang, 6. Probolinggo,
7. Jember, 8. Banyuwangi and 9. Sampang
hierarchical
clustering (minimum variance method) with Euclidean dissimilarity index,
bootstraps 1000 (Hammer et al. 2001).
The basic parameters of genetic diversity was also analyzed using GenAlEx 6.5
software (Peakall and Smouse
2012). The parameters include the number of alleles observed (na), the number
of effective alleles (ne), the average expected heterozygosity (He) and the
Shannon information index (I) as a measure of gene diversity and the percentage
of polymorphic loci (P%). This genetic diversity analysis was carried out both
among and within genome groups of bananas. Furthermore, the data of distance matrix was also subjected to analysis of molecular
variance (AMOVA) using GenAlEx6.5 (Peakall and Smouse 2012). The AMOVA estimated and partitioned the
total molecular variance among and within genome groups of the populations and then tested the significance of partitioned
variance components using non-parametric testing procedures with 999
permutations (Excoffier et al. 1992).
Results
ISSR polymorphisms and marker informativeness
All twelve banana cultivars were successfully amplified using the
five ISSR primers employed in this investigation. Thirty-three bands ranging from 250-2000 bp were produced (Fig. 2 and Table 3). In
this study, UBC-834 primer produced seven bands ranging from 600-2000 bp,
UBC-835 primer produced nine bands ranging from 250-1500 bp, UBC-843 primer
produced five bands ranging from 300-1000 bp, and UBC-848 primer produced five
bands ranging from 400-1000 bp. Furthermore, each primer had an average band of 6.6 and an average number of polymorphic bands of 6.4.
Primer UBC-835 produced the most polymorphic bands (9),
while UBC-843 and UBC-848 produced the least polymorphic bands (5). The
percentage of polymorphic
Fig. 2: ISSR amplification profiles of 12 banana cultivars (4
primers = UBC-834, UBC-835, UBC-843, and UBC-848)
Table 3: Polymophisms analysis result of 12 banana cultivars
based on ISSR markers
No. |
Primer |
TNB |
NPB |
PB (%) |
PIC |
EMR |
MI |
RP |
1 |
UBC-834 |
7 |
7 |
100 |
0.48 |
49 |
23.54 |
8.67 |
2 |
UBC-835 |
9 |
9 |
100 |
0.48 |
81 |
38.52 |
22.50 |
3 |
UBC-843 |
5 |
5 |
100 |
0.40 |
25 |
10.12 |
7.83 |
4 |
UBC-848 |
5 |
4 |
80 |
0.38 |
25 |
9.49 |
5.83 |
5 |
UBC-855 |
7 |
7 |
100 |
0.45 |
49 |
21.93 |
8.83 |
Total |
33 |
32 |
480 |
2.19 |
229 |
103.60 |
53.67 |
|
Average |
6.60 |
6.40 |
96 |
0.44 |
45.80 |
20.72 |
10.73 |
Remarks: TNB = Total
Number of Bands, NPB = Number
of Polymorphic Bands, PB = Polymorphic
Band Percentage, PIC = Polymorphic
Information Content, EMR = Effective
Multiplex Ratio, MI = Marker
Index, and RP = Resolving Power
bands varied from 80% for UBC-848 primers to 100% for UBC-834,
UBC-835, UBC-843 and UBC-855 primers with an average polymorphism of 96% per
primer (Fig. 2 and Table 3).
Analysis of polymorphisms showed that ISSR primers which produced the highest
PIC value of 0.48 were UBC-834 and UBC-835 primers, while the lowest PIC value
of 0.38 was produced by UBC-848 primer, with an average PIC value of 0.44 per
primer.
Clustering of banana cultivars in East Java
Twelve banana cultivars from East Java were clustered into four groups following their genome group, with
distance values ranging from 1.00 to 4.90 (Fig. 3 and Table 4).
Bananas with AA genome (Mas Jambe, Mas Kripik and Lilin) were served as an
outgroup at a genetic distance 3.16, and supported by strong bootstrap values
(100). Bananas with AAA genome (Kidang, Cebol and Kongkong) were separated at a
genetic distance of 1.73 and supported by moderate bootstrap value (70).
Furthermore, bananas with AAB genomes (Candi, Raja Ketan and Raja Temen) were
clustered with a genetic distance value of 2.65, whilst, bananas with ABB genomes (Tlekung, Tajinan and
Sabeh Biru) were grouped at a genetic
distance of 2.83. Both genome groups separation was supported by low bootstrap
values i.e., 32 and 46,
respectively. Nevertheless, from this study, the ISSR markers are proven
powerful in classifying banana cultivars at
the intraspecific level of bananas, particularly among and within genome groups
of bananas.
Genetic variation and structure of banana cultivars
Estimating genetic diversity, like the gene
diversity index and percentage of polymorphic loci, provides a measure of the
taxa's genetic richness. This study
detected high genetic richness across populations of 12 banana cultivars from East
Java, with an average Shannon index value of 0.587 and a percentage of
polymorphic loci of 96.97 percen (Table 5).
Molecular variance
analysis of banana cultivar populations
Analysis of molecular variance (AMOVA) of 12 banana
cultivar populations from East Java revealed that 50.43% of the variation is present within the genome
groups and 49.57% of variation lies among the genome groups (Table 6). The
results of AMOVA were also found comparable to percentage of gene
differentiation in this study,
depicting that
Fig. 3: Dendogram clustering based on ISSR markers and
morphological appearance of 12 banana cultivars
Table
4:
Euclidean genetic distance of 12 banana cultivars
No. |
Cultivar name |
Genome group |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
11 |
2 |
Mas Jambe |
AA |
3.74 |
||||||||||
3 |
Lilin |
AA |
2.00 |
3.16 |
|||||||||
4 |
Cebol |
AAA |
3.87 |
4.58 |
3.32 |
||||||||
5 |
Kongkong |
AAA |
4.00 |
4.69 |
3.46 |
1.00 |
|||||||
6 |
Kidang |
AAA |
3.61 |
4.36 |
3.00 |
2.00 |
1.73 |
||||||
7 |
Candi |
AAB |
3.61 |
4.12 |
3.00 |
3.16 |
3.00 |
2.45 |
|||||
8 |
Raja Ketan |
AAB |
3.46 |
4.24 |
2.83 |
3.32 |
3.16 |
2.65 |
1.73 |
||||
9 |
Raja Temen |
AAB |
3.32 |
3.32 |
2.65 |
3.74 |
3.87 |
3.46 |
2.83 |
2.65 |
|||
10 |
Tlekung |
ABB |
3.74 |
4.47 |
3.16 |
3.32 |
3.16 |
3.00 |
2.65 |
2.45 |
3.00 |
||
11 |
Tajinan |
ABB |
4.24 |
4.90 |
3.74 |
3.00 |
2.83 |
3.00 |
3.32 |
3.16 |
3.61 |
2.00 |
|
12 |
Sabeh Biru |
ABB |
4.47 |
3.46 |
4.00 |
4.36 |
4.24 |
4.12 |
3.61 |
3.74 |
4.12 |
2.83 |
3.46 |
Table 5:
Genetic diversity parameters of 12 banana cultivars among and within genome
groups
Parameter |
Across
populations |
AA group |
AAA group |
AAB group |
ABB group |
N |
12 |
3 |
3 |
3 |
3 |
Na (mean ±
SE) |
1.970 ±
0.030 |
1.121 ± 0.149 |
0.848 ±
0.108 |
1.182 ±
0.102 |
1.182 ±
0.127 |
Ne (mean ±
SE) |
1.741 ±
0.030 |
1.404 ±
0.083 |
1.068 ±
0.035 |
1.228 ±
0.069 |
1.347 ±
0.081 |
I (mean ±
SE) |
0.587 ±
0.048 |
0.289 ±
0.060 |
0.064 ±
0.031 |
0.173 ±
0.051 |
0.248 ±
0.058 |
He (mean ±
SE) |
0.407 ±
0.021 |
0.207 ±
0.043 |
0.042 ±
0.021 |
0.122 ±
0.036 |
0.177 ±
0.041 |
uHe (mean ±
SE) |
0.425 ±
0.022 |
0.248 ±
0.051 |
0.050 ±
0.025 |
0.146 ±
0.043 |
0.213 ±
0.050 |
P (%) |
96.97 |
42.42 |
12.12 |
27.27 |
36.36 |
Remarks: N = number of samples; na = Observed number of
alleles; ne = Effective number of alleles; I = Shannon's Information index; He
= Expected heterozygosity; uHe = Unbiased Expected Heterozygosity; P =
Percentage of polymorphic loci.
Table 6:
Analysis of molecular variance of 12 banana cultivars populations
Variation
source |
df |
SS |
MS |
Est. Var. |
% |
PhiPT |
Prob. |
Among populations/genome groups |
3 |
38.50 |
12.833 |
3.194 |
49.57 |
0.496 |
0.001 |
Within populations/genome groups |
8 |
26.00 |
3.25 |
3.250 |
50.43 |
|
|
Total |
11 |
64.50 |
|
|
100 |
|
|
Remarks: df = degrees of freedom, SS = sum of squares,
MS = mean squares, Est. Var. = estimated of variation, % = percentage of
variation, PhiPT = genetic
differentiation among populations, Prob. = probability
Fig. 4: ISSR band
patterns across populations of 12 banana cultivars from East Java
that the variation was slightly
more conserved within the genome groups of bananas from East Java. The PhiPT value has inferred the
significant level of genetic differentiation of populations. The
PhiPT > 0.2
means populations are significantly different. This present
study resulted PhiPT value of 0.496 (P < 0.001), which
indicated a significant level of genetic differentiation among 12 banana cultivar populations (Table 6).
Discussion
ISSR is the most common marker,
capable of amplifying DNA segments ranging in size from 100 to 3000 bp between
the two microsatellites (Ng and Tan 2015). In
order to evaluate which primer is valuable to used, some evaluation including
total polymorphic band, polymorphic information criteria (PIC), effective
multiplex ratio (EMR), markers index (MI), and resolving power (RP) were
performed. The results of this study are in
accordance with previous research by Lamare and Rao
(2015) on the genetic diversity and population structure of the wild banana Musa acuminata Colla where the UBC-835
primer was the primer which produced the highest number of polymorphic bands
and the highest PIC value.
The maximum
value of PIC is 0.5; the closer PIC value to 0.5, the more informative the
primer is to be used in the analysis of genetic diversity (Chesnokov and Artemyeva 2015). The highest EMR value was produced by
UBC-835 primer (49) and the lowest value was produced by UBC-843 and UBC-848
primers, with an average of 45.80 per primer. The higher EMR value of a primer,
the more effective the primer is in producing polymorphic bands (Laurentin and
Karlovsky 2006). Meanwhile, the highest MI and RP values were
produced by UBC-835 primer and the lowest value was produced by UBC-848 primer
(Table 3). Marker Index (MI) is used to determine which marker is most
efficient in analyzing a number of bands simultaneously (Laurentin and Karlovsky 2006), while resolving power is used to
measure the strength of a primer in producing polymorphic bands (Chesnokov and Artem’eva 2015). Thus, based on all the polymorphism
parameters that have been analyzed, the ISSR primer selected and recommended
for amplifying the DNA of banana cultivars is UBC-835.
The level of
genetic diversity of a population can be estimated from the value of the
genetic distance among the individual members of the population (Babu et al. 2018). If the value of the
genetic distance between individuals in a population is getting smaller, the
more uniform the population is and the higher the percentage of similarity of
the observed accessions. This statement is in accordance with the result of
this study where the highest genetic distance (4.90) was found between Pisang
Mas Jambe and Pisang Tajinan which have different genomes, i.e., AA and ABB, respectively. Genetic distance may indicate
variations between individuals in the population due to genetic hybridization
from ancestral parents (Poerba et al. 2018). Meanwhile,
the lowest genetic distance value (1.00) was found between Pisang Kongkong
(AAA) and Pisang Cebol (AAA); they are considered very closely related and come
from the same genome group but differ in sub-group. A previous study using RAPD markers also showed that
intraspecific levels within AAA genome group, particularly Pisang Ambon
cultivars were low in the genetic distance (Wahyudi et al. 2020a). Likewise,
Pisang Tajinan and Pisang Tlekung were close related under the same ABB group
and Bluggoe sub-group with a genetic distance of 2.00 (Fig. 3 and Table 4).
Compared to
another study to survey the genomes of 30 banana cultivars from Hainan in South
China, only 85.10% of loci generated using ISSR were polymorphic (Lu et al. 2011). Whilst, Babu et al. (2018) reported the ISSR
polymorphic loci of 8 banana cultivars from Karnataka in Southwest India was
61.30%.
Furthermore, the diploid AA is considered the most diverse genome
group within the genome groups of bananas. It can be seen by the high values of genetic diversity parameters and
band patterns accross populations (Table 5 and Fig. 4). Whilst. the triploid AAA genome
group was considered the least diverse, then followed by AAB and ABB genome groups. Resmi et al. (2016) also reported similar
results on banana cultivars in South India, where the diploid AA genome group
was the most diverse. On the contrary, another study by Hariyanto et al. (2021) using matK sequences showed that the genetic diversity within the genomic
group AAA is slightly higher than AA. However, due to continued genetic diversity and mutations, both
genomic groupings (AA and AAA) are unable to be reliably distinguished.
The high degree of genetic diversity in AA diploid cultivars in this study may be due to the isolation and speciation that drives the evolution of
particular traits. In addition, differences in
genetic composition, geographical conditions or diverse environments will lead to
various adaptation patterns and other genetic traits that support a plant's
survival. Selection and vegetative propagation are also
important factors that may cause high variation in banana cultivars. Species with a lot of genetic variation can withstand
environmental strain for a long time (Langhe et al.
2009; Hapsari et al. 2018).
The AMOVA is a
molecular marker-based approach for detecting population divergence. The
percentage of gene divergence is a reliable indicator of the proportion of
diversity among populations and is proportional to the amount of variation
between them (Govindaraj et al.
2015). The variation within the genome
group in this study is higher than among group. This result in this study is
inversely proportional to what was found by Resmi et al. (2016) where among 38
South Indian bananas, a higher proportion of genetic variation was found among
the genome groups (68%) than within the genome groups (31%).
The low gene flow may cause a high degree of variation among populations. Gene
flow between genetically distant populations can
decrease genetic variations between populations, whereas gene flow within a
population can enhance genetic variation. Further, natural population fragmentation or extinction can result
in reduced gene flow across populations, increasing genetic differentiation and
structure (Slatkin 1987; Hatmaker et al.
2018).
This study's analysis of genetic diversity parameters using ISSR markers
showed that the genetic variation of 12 banana cultivars in East
Java was considered high among and within genome groups. The detail information from this study can provide the
basic data for further conservation efforts and breeding of local banana
genetic resources from East Java. Populations with high genetic diversity have
a higher chance of survival because they have better environmental adaptability
(Varma and Bebber 2019). Therefore, for conservation, banana cultivars with high genetic variability and far
genetic distance are prioritized.
Farmers are
encouraged to plant varied banana native varieties to minimize climatic risks,
enhance the resilience of pest and disease outbreaks, and secure food sources
for in-situ/on-farm conservation (Sthapit et al. 2009). Thus, all those 12 banana
cultivars should be cultivated to keep them conserved on farm. Since, genetic
erosion of local bananas may occur through the genetic uniformity of
commercially cultivated cultivars in general which replaces and reduces the
cultivation of potential local cultivars (Hapsari et al. 2017). Furthermore, genetically homogeneous populations are
more susceptible to diseases and viruses, and are more likely to become extinct
as a result of the spread of a single fatal disease on the farm (Resmi et al.
2016).
Ex situ
conservation is required as a final
line of defence to protect germplasm in the event of catastrophic events
threatening their limited natural environment. Further, ex situ conservation also preserves the results of certain genes
and genotypes sampled at a specific moment (Jesus et al. 2013; Rachmat et al.
2016; Hapsari et al. 2017). Upon this
study, the diploid AA group bananas
(Mas Kripik, Mas Jambe, Lilin) as the most genetically diverse group were
prioritized for conservation. Further, they have viable pollens, potentially as
male parents for further breeding (Damaiyani and
Hapsari 2018). Meanwhile, more ex situ conservation efforts are needed for the least diverse
group, i.e.,
the AAA group followed by
AAB and ABB groups, through exploration activities
and collecting missions to several areas in East Java. However, for
long-term strategy, if ex situ
conservation resources are limited, any banana cultivars which are very closely
related (low genetic diversity, low genetic distance) should be chosen with one
of them as representative, such as Pisang Cebol x Pisang Kongkong and Pisang
Raja Ketan x Pisang Candi.
Conclusion
Genetic variation of 12 banana cultivars in East Java were considered high both among
and within genome groups. Diploid AA group bananas
(Mas Kripik, Mas Jambe, Lilin) as the most genetically diverse group were
prioritized for conservation. Ex situ conservation is also needed for the least diverse group i.e.,
the AAA group followed by
AAB and ABB groups, through exploration activities
and collecting missions to several areas in East Java.
Acknowledgements
None to
declare
Author Contributions
All authors (DCN, DW, LH)
contributed equally in this manuscript from conceptualization, labworks, data
analysis, writing the manuscript, review and editing of the final manuscript.
Conflicts
of Interest
The authors declare no conflict of interest
Data Availability
Data is available with the corresponding author
Ethics Approvals
No applicable to this study
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