Characterizations of Ganoderma species causing basal stem rot disease in coconut tree

Abstract

The basal stem rot disease incidence ranged from 0 to 5% in Karnataka India during the year 2019–20. Twenty pathogenic isolates of Ganoderma sp varied with cultural characteristics and virulence on coconut seedlings of the variety Tipatur Tall. The identity of each isolate was confirmed through morphological characters and through ITS sequencing. Two isolates viz., G₄ and G₅ were identified as Ganoderma applanatum and remaining all isolates were identified as G. lucidum. The genetic diversity analysis of Ganoderma isolates was done using ten Random Amplified Polymorphic DNA (RAPD) and fifteen Inter Simple Sequence Repeat (ISSR) primers. Among the ten RAPD primers, only eight primers recorded polymorphism (33.30–66.70%). The primer SBS-Q3 exhibited the highest polymorphism of 66.70%. In case of ISSR primers, all primers recorded polymorphism (33.30–60.00%). The primer UBC866 was the most polymorphic primer with 60.0% polymorphism. RAPD and ISSR markers were compared for their efficacy in assessing the genetic diversity by taking the band frequency, Shannon’s index, polymorphic information content, resolving power, and mean resolving power into consideration, and it was concluded that ISSR was marker of choice over RAPD.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03872-w.

Introduction

The coconut tree (Cocos nucifera L.) belongs to the palm tree family, Arecaceae. The unique feature of this crop is that each and every part of the plant has multiple usage along with huge commercial value. Coconut, besides serving as a primary source of food components, provides a considerable amount of foreign exchange through export of coconut-based products. Looking to the multifarious usage and health benefits the tree is regarded as ‘Heavenly Tree’ (Sudarshan et al. 2017). It is now cultivated throughout the humid tropics in an area of 12 mha with production of 63.68 MT (Beveridge et al. 2022). India being the second largest producer accounts for 31.45% of the total production with an area of 2.10 mha (CDB 2022). It supports the livelihood of 12 million people and also provides an employment opportunity to 6 million people in India (Arumugam and Hatta 2022).

Coconut palm is affected by number of biotic and abiotic stresses resulting in drastic yield reduction (Palanna et al. 2016; Salum et al. 2020). Among the biotic stresses, basal stem rot (BSR) incited by species of Ganoderma is an important disease and is reported in many parts of the world viz., India, Sri Lanka, West Indies, Indonesia, Bangladesh etc. (Ariffin et al. 2000; Bhaskaran et al. 1994). In India, the most serious disease inflicting significant yield loss, i.e., 50–60% in coconut is basal stem rot disease (BSR) (Vinjusha and Arun Kumar 2022). In India, the disease was reported from Andhra Pradesh, Maharashtra, Gujarat, Kerala, Tamil Nadu, and Orissa (Bhaskaran and Karthikeyan 1994).

The various species of Ganoderma viz., G. lucidum, G. boninense, G. applanatum, etc. are reported to be associated with BSR of coconut (Wong et al. 2012; Thamban et al. 2016; Cooper et al. 2011). There has been a little attention diverted in the past to identify the species existing in different parts of the country. Identification of species is most crucial to devise the sustainable management practices. In general, a holistic approach comprising both morphological and molecular means are used to characterize the species (Kandan et al. 2009). Ganoderma is morphologically most complex genus of family Ganodermataceae of Aphyllophorales order (Park et al. 2012; Gottlieb and Wright 1999; Miller et al.1999). The color and shape of the fruiting body produced the specificity with the host and the origin are usually used to identify the species in Ganoderma (Govindu et al. 1983). Studies on cultural characteristics are most useful in species identification of some groups of higher basidiomycetes (Dyakov et al. 2011). However, useful studies on cultural characteristics of Ganoderma for species identification are rare, owing to their reliability (Smith and Sivasithamparam 2000). The development in sciences has led to advanced PCR-based techniques for resolving the conflicts developed out of morphological data and aided in identification of fungal species accurately without ambiguity (Singh et al. 2003; Rakib et al. 2014; Ghazala et al. 2010; Sun et al. 2006; Pilotti et al. 2004; Rolim et al. 2011). Rakib et al. (2014) reported the use of cultural characters in developing the taxonomy of Ganodermataceae that deals with the relationships and phylogeny. Similarly, Ryvarden (1994) used morphological characteristics such as pileus surface used for grouping of Ganoderma sp. associated with coconut. Further, it has been reported that the combined use of specific primers and restriction enzyme analysis was helpful in differentiating the species of Ganoderma infecting oil palm (Utomo et al. 2005). Thus, a combined approach of morphological and molecular means is advised for characterizing the species of Ganoderma. In this study, attempt has been made to characterize pathogens associated with coconut BSR disease and also study the diversity among them using various molecular markers.

Materials and methods

Distribution of BSR

The seven major coconut growing districts of Karnataka viz., Hassan, Shivamogga, Tumkur, Chamarajanagar, Mandya, Mysuru, and Ramanagar were selected for assessing the spatial distribution of BSR during 2019–2020. The random survey was conducted in each district with three taluka per district and in each taluka, three villages were selected randomly. The sample size was 100 palms in each plot and five plots per village were selected. The per cent incidence was calculated for each plot and mean disease incidence in each district was calculated. Disease incidence (%) = [NI/TP] × 100, where, NI is the number of palms infected and TP is the total number of palms observed (AICRP Palms 2020).

Pathogen

The coconut palms exhibiting the characteristic symptoms were selected and the 10 sporocarp of Ganoderma, and 10 root bits from such plants were collected and brought to laboratory and kept in refrigerator for future use. The pathogen associated with BSR disease was isolated by tissue segment method using Potato Dextrose Agar (PDA) medium (Hi Media, Mumbai, India) with streptomycin (50 µg/ml) (Ayliffe et al. 2013). The hyphal tip method was used for purifying the fungus (Meyer et al. 1976). Identification of culture was done based on colony morphology and mycelia characteristics (Bhaskaran et al. 1991). The pathogen cultures obtained from various geographical locations were designated as G₁ to G₂₀.The cultures of each isolate were stored separately on agar slant in a refrigerator at 4 °C for future studies. The association of the fungus was proved through repeated isolation for at least thrice for each sample.

Pathogenicity of Ganoderma isolates

The pot culture experiment to prove the pathogenicity of Ganoderma isolates on coconut seedlings variety Tipatur Tall was conducted at Horticulture Research and Extension Centre, Arsikere, Karnataka. The Ganoderma isolates were mass multiplied individually on sorghum seeds as suggested by Palanna et al. (2020). The six-month-old Tipatur tall variety coconut seedlings were raised in iron ports of 33 × 85 cm size. The farm yard manure, soil and sand in equal portion were filled in the pot. Each pot was inoculated with 200 g of inoculum. The control pots were also maintained without inoculation. The seedlings were kept in green house with 85% relative humidity and day temperature of 30 °C and night temperature of 20 °C. Three replications were maintained in each isolate. Severity of the disease was assessed as per Abdullah et al. (2003). The experiment was repeated under the same conditions.

Pathogen identification through molecular characterization

DNA isolation and PCR amplification

The total DNA was extracted from the twenty isolates of Ganoderma, separately using CTAB method (Nagappan et al. 2018). The primer pairs viz., ITS1 (5′ -TCCGTAGGTGAACCTGCGG -3′) and ITS4 (5′ -TCCTCCGCTTATTGATATGC -3′) were employed to in order to amplify the ITS1-5.8S-ITS4 region of each isolate (Utomo et al. 2005). PCR reaction was performed using 20 μl reaction containing 1 µL DNA, 1 µL primers(5 pmol) forward and reverse, 2 µL DNTP'S (2 mM), 2 µL Taq buffer A (10 ×), 0.3 µL Taq DNA polymerase, and 13.7 µL sterile water. PCR conditions of reaction mixtures were as follows: 91 °C for 1 min followed by 94 °C for 35 s and then amplified for 30 cycles (35 s at 94 °C, 1 min. at 54 °C, and 1 min. at 72 °C) with the final step at 72 °C for 10 min (Utmo et al. 2005). The100 bp molecular markers (Bangalore Genei Pvt. Ltd., India) were used to determine the size of amplicon obtained through electrophoresis.

Sequencing of ITS region and sequence analysis

The PCR products having the expected amplicons were sent to sequencing at Bio serve Biotechnologies Pvt. Ltd, Genome Valley, Hyderabad, India. The sequences obtained after sequencing were searched for the homology with already existing sequences in NCBI using BLAST program (Altschul et al. 1990). The sequences and accession number for the predeposited sequences at NCBI sharing maximum homology with query sequences were retrieved from GenBank. Sequence pair distances among related and different fungi of the isolate were scored with the Clustal X (1.8) program and phylogenetic tree analysis was performed with the Mega version 1.15. All 20 sequences of isolates were submitted in the GenBank database, USA.

Variability among collected Ganoderma isolates

Phenotypic variability

Mycelial disc of 5 mm from 20-day-old culture was transferred onto the center of the Petri plate having PDA and incubated at 28 ± 2 °C for 10 days. Three replications were maintained for each isolate. The colony color, days taken for covering full plate, concentric rings, type of colony margin, mycelial texture, and mycelial density were recorded after the full growth of fungus in Petri plates (Palanna et al. 2020). The characters and the corresponding codes used for grouping are presented in Table 1. The cultural characteristics recorded on PDA medium were transformed into different codes. Similarity matrices were developed using the simple matching coefficient and a dendrogram was generated using the unweighted pair group method of arithmetic averages (UPGMA) (Palanna et al. 2020).The cultural characters and their corresponding codes used to group Ganoderma isolates are as follows days for full plate (Code 1, < 8 days; 2, 8–9 days; 3, 10–11 days; 4, > 11 days; and 5, > 11–25 days), colony color (6—white and 7—creamy color), mycelial texture (8—Smooth, 9—Leathery, and 10—Fluffy), concentric rings (11— present and 12—absent), mycelial density (13—Thin, 14—Dense, 15—Thin at center and dense at corner, and 16—Dense at center), and margin of colony (17—filamentous, 18—even, 19—undulate, 20—erose, and 21—lobate).

Table 1.

Details of isolates of Ganoderma sp. from coconut and their cultural characteristics

Isolate	Location	GPRS coordinates	Part used for isolation	GenBank accession No	Sequence bp
G1	Kesthur	12.09N,77.02 E	Sporocarp	OQ303636	642
G2	Alathur	11.87N,76.60E	Root	OQ303637	643
G3	Mahadeshwar	12.03N,77.59E	Sporocarp	OQ303638	643
G4	Nanjangudu	12.10N,76.54E	Root	OQ303641	677
G5	Koppa	12.32N,76.05E	Sporocarp	OQ303654	627
G6	Madapura	12.22N, 76.84E	Root	OQ303639	643
G7	Marasinghanahalli	12.64N,77.04E	Sporocarp	OQ303642	678
G8	Kyatanahalli	12.31N, 77.02E	Root	OQ303643	678
G9	Billenahalli	12.64N, 76.30E	Root	OQ303644	678
G10	Aralalu	12.51N, 77.42E	Root	OQ303645	637
G11	Vaderahalli	12.73N, 77.29E	Sporocarp	OQ303646	631
G12	Bommanahalli	12.65N, 77.24E	Root	OQ303647	632
G13	Mududi	13.20N, 76.27E	Sporocarp	OQ303648	643
G14	Boovanahalli	13.00N, 76.13E	Root	OQ303649	627
G15	Bagur	12.93N, 77.28E	Sporocarp	OQ303650	627
G16	Konehalli	13.18N, 76.56E	Root	OQ303651	637
G17	Mallasandra	13.30N, 77.03E	Root	OQ303652	643
G18	Kuppur	13.36N, 77.06E	Sporocarp	OQ303653	643
G19	Vadiyur	13.70N, 75.69E	Sporocarp	OQ303640	637
G20	Gajanur	13.85N, 75.53E	Sporocarp	OQ303655	626

DAI days after inoculation

Genetic variability

Random amplified polymorphic DNA (RAPD)

Ten RAPD primers viz., SBS-A5 (5′-AGGGGTCTTG-3′), SBS-A15(5′-TTCCGAACCC-3′), SBS-I1(5′-ACCTGGACAC-3′),SBS-I9(5′-TGGAGAGCAG-3′),SBS-I20(5′-AAAGTGCGGG-′), SBS-M7(5′-CCGTGACTCA-3′), SBS-M17(5′-TCAGTCCGGG-3′), SBS-4(5′GACCGACCCA-3′), SBS-N9(5′-TGCCGGCTTG-3′), SBS-Q3(5′-GGTCACCTCA-3′), and SBS-A15(5′-TTCCGAACCC-3′) were employed for the study. The PCR reactions were done with 25 µl of reaction mix with conditions suggested by Fu et al. (2013). One per cent agarose was used to visualize the amplicons. To confirm the reproducibility of the profile, the experiment was repeated two times with selected primers exhibiting polymorphism and only primers exhibiting polymorphism were taken into consideration. Each identifiable amplicon showing constancy was scored one for the presence and zero for the absence and binary data were developed. The similarity matrices were developed out of the binary data using NTSYS-pc and also cluster analysis was done using UPGMA method (Rohlf 2002).

Inter-simple sequence repeats (ISSR)

A set of 15 ISSR primers viz., UBC807(5′-AGAGAGAGAGAGAGAGT 3′),UBC827(5′ACACACACACACACA-3′),UBC847(5′-CACACACACACACACARC-3′),UBC851(5′-GTGTGTGTGTGTGTGTYG-3′),UBC856(5′-CACA CACACACACACYA-3′),UBC86(5′-GAAGAAGAAGAAGAAGAA-3′),UBC880(5′-GGAGAGGAGAGGAGA-3′), UBC887(5′-TTATCTCTCTCTCTCTC-3′),UBC899(5′-ATGGTGTTGGTCATTGTTCCA-3′),UBC810(5'GAGAGA GAGAGAGAGAT-3′),UBC846(5′-CACACACACACACACART-3′),UBC848(5′-CACACACACACACACARG3′), UBC855(5′-ACACACACACACACACYT-3′),UBC866(5′-CTCCTCCTCCTCTCCTC-3′), and UBC873(5′-ACAGA CAGACAGACA -3′) were used for the study and the details are given in Table (Mei et al. 2014). PCR reactions were performed with 25 µl reaction mix and the conditions were followed according to (Fu et al. 2013). The visualization of amplicons, scoring and development of binary data, similarity matrices and cluster analysis was done as explained earlier.

Principal component analysis (PCA)

The data generated out of RAPD and ISSR were subjected to principal components analysis using GENalex software. The first two principal components extracted were plotted in possible combination to produce biplots.

Comparison of RAPD and ISSR markers for the genetic diversity of Ganoderma isolates

Two marker systems, namely RAPD and ISSR were compared for their potentiality in figuring the genetic diversity of Ganoderma isolates. Various parameters viz., band frequency, observed number of alleles, effective number of alleles, Shannon's information index, Nei’s gene diversity, unbiased heterozygosity, polymorphic information content, resolving power, mean resolving power, fraction of polymorphic loci, effective multiplication ratio, and assay efficiency index were calculated using GENalex software. Further, total number of bands, the number of monomorphic and polymorphic bands per primer, per cent polymorphism, per cent monomorphism, and assay efficiency index (AEI = polymorphic bands/total number of primers) were documented. In addition, polymorphism information content (PIC) values were calculated using the expression described by Botstein et al. (1980).PIC =$1-\sum \begin{array}{c}n\\ ij\end{array}\sum \begin{array}{c}2\\ ij\end{array},$ where ij p is the frequency of the jth allele for the ith marker, summed over n alleles. The resolving power for each primer was calculated as sum of band informativeness and effective multiplex ratio as product of fraction of polymorphic loci and number of polymorphic bands.

Results

Disease incidence

The roving survey was conducted in major coconut growing tracts of Karnataka revealed that Tumkur and Arsikere Talukas recorded maximum incidence of BSR (5.00%); whereas, 0.5% of incidence of BSR was recorded at Kollegal taluk. Yalandur, Gundalupete, Nanjangudu, Periyapattana, T. N. Pura, Malavalli, and Channapattana Talukas were completely free from disease. In general, highest disease incidence was observed in sandy soils and where canal source of irrigation prevails when compared to red soils and bore well irrigated and rainfed conditions (Figs. 1 and 2).

Fig. 1.

Incidence of basal stem rot disease in Karnataka (Vertical line in each bar represents standard error)

Fig. 2.

Geographical locations of Ganoderma isolates

Pathogen isolation, identification, and pathogenicity

From the twenty infected coconut plant samples collected from different growing places, twenty Ganoderma isolates were isolated and purified. All the isolates exhibited the white-colored colony and fluffy texture (Table 1). These isolates invariably produced a clamp connection with a white septate mycelium (Fig. 3A). All the twenty isolates produced the characteristic symptoms after six months of inoculation in coconut seedlings indicating their pathogenic potential. However, the degree of infection varied across the isolates. The lowest disease incidence of 16.50 DSI was observed in coconut palm inoculated with G7 as against 38.70 DSI in palms inoculated with G16. The disease severity index also varied significantly among the isolates even at nine months after inoculation and the trend was same as in seven months (Table 2).

Fig. 3.

Cultural characteristics (A); A1-Pure culture A2-Clamp Connection A3-Polypores and PCR amplification of ITS region of Ganoderma isolates (B)

Table 2.

Virulence of Ganoderma isolates to coconut

Isolate	*DSI at different months after inoculation
	3 months	6 months	9 months
G1	0.00 ± 0.00	26.00 ± 4.59	33.30 ± 6.10
G2	0.00 ± 0.00	32.70 ± 4.28	35.50 ± 1.43
G3	0.00 ± 0.00	26.50 ± 4.37	37.00 ± 6.65
G4	0.00 ± 0.00	28.50 ± 3.49	35.50 ± 1.43
G5	0.00 ± 0.00	23.00 ± 2.05	30.50 ± 1.84
G6	0.00 ± 0.00	22.00 ± 0.94	30.00 ± 1.63
G7	0.00 ± 0.00	16.50 ± 1.08	41.10 ± 6.18
G8	0.00 ± 0.00	22.00 ± 0.94	28.00 ± 0.94
G9	0.00 ± 0.00	31.50 ± 2.27	33.00 ± 2.94
G10	0.00 ± 0.00	19.50 ± 2.27	20.25 ± 2.61
G11	0.00 ± 0.00	20.00 ± 0.94	30.00 ± 4.32
G12	0.00 ± 0.00	18.50 ± 3.27	28.50 ± 2.27
G13	0.00 ± 0.00	17.50 ± 3.12	24.50 ± 4.09
G14	0.00 ± 0.00	20.00 ± 4.11	28.00 ± 2.49
G15	0.00 ± 0.00	20.60 ± 5.05	30.90 ± 1.53
G16	0.00 ± 0.00	38.70 ± 2.27	43.30 ± 1.48
G17	0.00 ± 0.00	19.50 ± 2.27	22.50 ± 3.34
G18	0.00 ± 0.00	25.50 ± 2.86	27.00 ± 3.49
G19	0.00 ± 0.00	26.50 ± 2.32	30.20 ± 1.64
G20	0.00 ± 0.00	31.50 ± 2.27	39.50 ± 1.65
SEm ±	NS	2.13	2.38
CD (5%)		6.08	6.80

^*Disease Severity Index ± Standard Deviation (n = 3) NS Non Significant

PCR amplification of genomic DNA of these isolates with universal ITS primers yielded an expected amplicon of 680 bp (Fig. 3B). Further, the amplified PCR product was sequenced and all the sequences were submitted in NCBI, USA under accession numbers OQ 303636–OQ 303655. The sequences of all twenty isolates along with four reference sequence from GenBank were used construct Elucidian matrics using Mega software. The analysis revealed that two isolates viz., G₄ and G₅ were sharing maximum similarity of 95% with reference isolates of G. applanatum (MN435135.1—Ganoderma applanatum from Betula pendula and MN435146.1—Ganoderma applanatum from Salix alba). The remaining isolates exhibited the similarity of 87–95% with that of G. lucidum (Fig. 4A and B). From the study, it was clearly evident that isolates G₄ and G₅ were identified as G. applanatum and remaining all isolates were G. lucidum. Further, these isolates produced the symptom of BSR on coconut seedlings after 7 months after inoculation indicating the association of the pathogen with host. Based on the results obtained, it was confirmed that two major species responsible for the infection was be G. applanatum and G. lucidum.

Fig. 4.

Phylogenetic tree of Ganoderma isolates based on 18S rDNA ITS sequence data with GenBank reference isolates (a) and heat map depicting values in the Euclidian distance metrics generated out of ITS sequences (b) (M -Marker 100 bp, Lane 1-20 are isolates of Ganoderma)

Phenotypic variations among Ganoderma isolates

The isolates of Ganoderma cultured on PDA medium showed variations with respect to texture, concentric rings, margin of the colony and growth. However, the colony color was uniform across the isolates exhibiting white color. The colony texture of the isolates G₄, G₁₇, G₁₈, and G₁₉was thin and the rest all isolates had the floppy growth on PDA. Further, the concentric rings in the colony were also varied among the isolates. The isolates G₂, G₆ and G₁₉ showed the presence of concentric rings on PDA medium whereas rings were absent in the remaining isolates. The other cultural characters viz., colony margin was also varied as either filamentous or even across the isolates. The colony margin was filamentous in G₁, G₃, G₄, G₅, G₇, G₈, G₉, G₁₀, G₁₁, G₁₂, G₁₃, G₁₄, G₁₅, G₁₆, G₁₈, and G₂₀ isolates whereas the isolates G₂, G₆, G₁₀, G₁₇, and G₁₉ exhibited the even margin. The growth of isolate was uniform among the isolates as all isolates took 7 days for the complete growth on PDA (Fig. 5).

Fig. 5.

Grouping of isolates based on cultural variations

The dendrogram constructed based on the cultural variations divided the isolates into two major groups. The 15 isolates (G₁, G₃, G₄, G₅, G₇, G₈, G₉, G₁₁, G₁₂, G₁₃, G₁₄, G₁₅, G₁₆, G₁₈, and G₂₀) were placed in one group I and remaining five isolates (G₂, G₆, G₁₀, G₁₇, and G₁₉) were placed in group II. Group I was again subdivided into A and B. In case of A, there were five isolates viz., G₃, G₁₄, G₁₆, G₁₈, G₂₀ and incase of B, 10 isolates (G₄, G₅, G₇, G₈, G₉, G₁₁, G₁₂, G₁₃, and G₁₅) were placed (Fig. 5). From the dendrogram, it was clearly inferred that though all the isolates used under the study showed high variability with respect to cultural characteristics, grouping based on cultural characteristics was not in accordance with geographical origin of the isolates. Further, the categorization was not even agreed with molecular data obtained in the study. Hence, isolates showing similar cultural characters were still found to be genetically different and also isolates exhibiting differences in genotype in Ganoderma may show similar cultural characters and vice versa. Thus, a deeper insight into molecular means is necessary to categorize different species in Ganoderma sp.

Molecular variability among Ganoderma isolates

RAPD

Out of ten RAPD primers employed to understand the diversity among the twenty isolates of Ganoderma sp., only eight were exhibiting the polymorphism. The total number of amplicons produced by primer varied from 5 to 12 with size ranging from 300 to 900 bp. In general, the per cent polymorphism ranged from 33.30 to 66.70. The primer SBS-Q3 was the most polymorphic primer with 66.70% polymorphism (Fig. 6; Table 3). The genetic relationship was presented in dendrogram constructed using UPGMA. The groups A and B shared all the isolates under study and each group was further divided into clusters (Fig. 6). G₂, G₃, G₄, G₅, and G₁₁ isolates were placed in group A with 64 per cent similarity among them and remaining all isolates are placed in group B sharing 77% similarity among them. Group B was subdivided into clusters a and b with similarity of 77%. Cluster A had only one isolate G₁ whereas in the cluster b, 14 isolates were grouped with 91.0%. On the other, group A was further, divided into cluster C and cluster D. The cluster c had 3 isolates with 85.00%, whereas cluster d had two isolates with 87.00% similarity among them. The results clearly implied that, the RAPD analysis of Ganoderma isolates could differentiate the isolates effectively and there exist a great diversity among the isolates across coconut growing areas.

Fig. 6.

Genetic distance tree based on Jaccards Coefficient using RAPD and ISSR data

Table 3.

Polymorphism Ganoderma sp. detected by RAPD and ISSR primers

	Primer	TB	MB	PB	PM	PP	Size range (bp)
RAPD	SBS-A5	10.00	6.00	4.00	60.00	40.00	300–700
	SBS-A15	6.00	3.00	3.00	50.00	50.00	300–800
	SBS-I1	10.00	6.00	4.00	60.00	40.00	300–800
	SBS-I9	5.00	5.00	0.00	100.00	0.00	400–500
	SBS-I20	12.00	12.00	0.00	100.00	0.00	300–600
	SBS-M7	6.00	4.00	2.00	66.70	33.30	500–700
	SBS-M17	8.00	5.00	3.00	62.50	37.50	00
	SBS-N4	5.00	3.00	2.00	60.00	40.00	300–500
	SBS-N9	10.00	4.00	6.00	40.00	60.00	300–900
	SBS-Q3	9.00	3.00	6.00	33.30	66.70	300–900
	Total	81.00	44.00	37.00
	Mean	08.10	04.40	03.70
ISSR	Primer	TB	MB	PB	PM	PP	Size range
	UBC807	5.00	3.00	2.00	60.00	40.00	450–700
	UBC827	4.00	2.00	2.00	50.00	50.00	300–600
	UBC847	8.00	4.00	4.00	50.00	50.00	400–600
	UBC851	6.00	4.00	2.00	66.67	33.33	450–550
	UBC856	2.00	1.00	1.00	50.00	50.00	600–700
	UBC868	7.00	5.00	2.00	71.43	28.57	600–700
	UBC880	5.00	3.00	2.00	60.00	40.00	300–600
	UBC887	3.00	2.00	1.00	66.67	33.33	300–600
	UBC899	5.00	3.00	2.00	60.00	40.00	300–600
	UBC810	4.00	2.00	2.00	50.00	50.00	300–600
	UBC846	9.00	5.00	4.00	55.56	44.44	450–550
	UBC848	10.00	8.00	2.00	80.00	20.00	450–550
	UBC855	2.00	1.00	1.00	50.00	50.00	450–550
	UBC866	10.00	4.00	6.00	40.00	60.00	600–700
	UBC873	8.00	4.00	4.00	50.00	50.00	600–700
	Total	88.00	51.00	37.00
	Mean	6.29	3.64	2.64

TB Total Bands, MB Monomorphism bands, PB Polymorphic bands, PM Per cent monomorphism, PP Per cent polymorphism

ISSR

The genetic diversity prevailing among Ganoderma isolates representing Karnataka state was assessed through 15 ISSR primers. All primers recorded polymorphism of varying degree. The total number of amplicons produced by primer varied from 2 to 10 with size ranging from 300 to 700 bp. In general, the per cent polymorphism ranged from 33.3% to 60.0%. The primer UBC866 was the most polymorphic primer with 66.70% polymorphism (Supplementary Fig. 2; Table 3). The relationships among the isolates were represented as a dendrogram using UPGMA. Total two groups viz., A and B were formed within 20 isolates sharing 84.0% similarity with A and B. The group B had only four isolates viz., G₂, G₃, G₄ and G₅ and the rest of the isolates were placed in group A. Group A was further divided into cluster a with 10 isolates and cluster b with one isolate sharing 88.0% similarity. Group B had two clusters viz., c and d. The cluster c had three isolates and cluster d had one isolate. In summary, the results implied there exist genetic diversity among isolates of Ganoderma sp. infecting coconut in Karnataka. Further, the grouping of isolate G₄ and G₅ as separate cluster also supported the identification of these two isolates separate species based on ITS data.

Comparison of RAPD and ISSR markers for assessing the genetic variability of Ganoderma isolates

Using the binary data out of RAPD and ISSR different parameters viz., band frequency, observed number of alleles, effective number of alleles, Shannon's information index, Nei’s gene diversity, unbiased heterozygosity, polymorphic information content, resolving power, mean resolving power, fraction of polymorphic loci, effective multiplication ratio, and assay efficiency index were calculated. It was observed that average band frequency was 0.83 in case of ISSR as compared to RAPD with 0.78. The observed and effective number of alleles was 1.46 and 1.40, respectively in RAPD whereas it was slightly lesser in ISSR documenting 1.43 (observed number of allele) and 1.38 (effective number of alleles). The Shannon’s index was 0.29 in case of ISSR when compared to 0.28 in RAPD. The other parameters such as Nei's gene diversity, and unbiased heterozygosity were same in both cases (Table 4). The polymorphic information content was more in ISSR documenting 0.22 as against 0.16 in case of RAPD. Further, the resolving power and mean resolving power were also more in ISSR when compared to RAPD. The two other parameters viz., fraction of polymorphic loci and effective multiplication ratio were also more in RAPD compared to ISSR. Further, assay efficiency index was also more in RAPD compared to ISSR. Overall, the band frequency, Shannon’s index, polymorphic information content, resolving power, mean resolving power were higher in ISSR marker when compared to RAPD. Hence, ISSR marker would be better choice for genetic diversity assessment compared to RAPD.

Table 4.

Genetic parameters computed for comparison of ISSR with RAPD marker

	Primer	BF	na	ne	I	h	uh	PIC	RP	MRP	Β	EMR	AEI
RAPD	SBS-A5	0.80	1.33	1.30	0.22	0.16	0.17	0.1588	10.65	1.18	0.40	1.60	4.62
	SBS-A15	0.71	1.50	1.37	0.30	0.21	0.22	0.209	6.625	1.10	0.50	1.50
	SBS-I1	0.75	1.42	1.37	0.28	0.20	0.21	0.1958	13.67	1.14	0.40	1.60
	SBS-M7	0.93	1.57	1.54	0.27	0.19	0.20	0.16	6.90	1.15	0.33	0.66
	SBS-M17	0.88	1.29	1.24	0.19	0.13	0.14	0.13	8.15	1.16	0.37	1.12
	SBS-N4	0.72	1.40	1.28	0.23	0.16	0.17	0.163	5.625	1.12	0.40	0.80
	SBS-N9	0.70	1.60	1.58	0.41	0.30	0.31	0	11.275	1.12	0.60	3.60
	SBS-Q3	0.75	1.60	1.52	0.39	0.27	0.29	0.276	11.95	1.08	0.67	4.00
	Average	0.78	1.46	1.40	0.28	0.20	0.21	0.16	9.36	1.13	0.46	1.86
ISSR	Primer	BF	na	ne	I	h	uh	PIC	RP	MRP	Β	EMR	AEI
	UBC807	0.830	1.400	1.341	0.260	0.183	0.193	0.38	11.20	1.60	0.40	0.80	2.46
	UBC827	0.775	1.500	1.481	0.342	0.245	0.258	0.15	9.40	1.57	0.50	1.00
	UBC847	0.838	1.500	1.385	0.312	0.216	0.228	0.23	2.70	1.35	0.50	2.00
	UBC851	0.883	1.333	1.278	0.216	0.152	0.160	0.14	12.20	1.74	0.33	0.67
	UBC856	0.825	1.500	1.417	0.324	0.228	0.239	0.20	8.10	1.62	0.50	0.50
	UBC868	0.871	1.286	1.280	0.197	0.141	0.149	0.18	8.00	2.00	0.29	0.57
	UBC880	0.790	1.400	1.396	0.276	0.199	0.209	0.23	7.70	1.54	0.40	0.80
	UBC887	0.833	1.333	1.333	0.231	0.167	0.175	0.19	5.50	1.38	0.33	0.33
	UBC899	0.830	1.400	1.367	0.268	0.191	0.201	0.09	12.60	1.40	0.40	0.80
	UBC810	0.825	1.500	1.412	0.321	0.225	0.237	0.23	17.50	1.75	0.50	1.00
	UBC846	0.844	1.444	1.361	0.283	0.198	0.208	0.29	16.20	1.25	0.44	1.78
	UBC848	0.920	1.200	1.182	0.134	0.095	0.100	0.24	11.30	1.41	0.20	0.40
	UBC855	0.825	1.500	1.417	0.324	0.228	0.239	0.38	4.20	1.05	0.50	0.50
	UBC866	0.765	1.600	1.514	0.390	0.275	0.289	0.15	10.20	1.02	0.60	3.60
	UBC873	0.769	1.500	1.474	0.340	0.243	0.256	0.23	8.50	1.062	0.50	2.00
	Average	0.83	1.43	1.38	0.29	0.20	0.21	0.22	9.69	1.45	0.43	1.12

BF Band frequency, na Observed number of alleles, ne Effective number of alleles, I Shannon's information index, h Nei's gene diversity, uh Unbiased heterozygosity, PIC Polymorphic information content, RP Resolving power, MRP Mean resolving power, β Fraction of polymorphic, EMR Effective Multiplication Ratio, AEI Assay efficiency index

Principal component analysis of genetic diversity of Ganoderma isolates

The binary data obtained from ISSR and RAPD were subjected to PCA using Jaccard's coefficients of similarity. In case of RAPD, the PCA was done using 81 bands generated by 10 decamer primers. The first three components explained the total cumulative variation of 55.86% which is an indication of low genetic diversity at various RAPD loci in analyzed isolates. It is evident that over topology obtained in PCA was slightly different from UPGMA dendrogram. To conclude, results of PCA were not in agreement with UPGMA and hence, the efficiency of RAPD primers in assessing the diversity of Ganoderma isolates was lesser compared to ISSR. In case of ISSR, overall topology of the PCA plot was compatible with that of the UPGMA dendrogram. The cumulative variation explained by first three PCA components was approximately 60.19% variation (Fig. 7). All the isolates formed four clusters in two dimensions. Hence, the results obtained from PCA were in agreement with dendrogram by UPGMA method, which is a further confirmation of genetic relationships delineated by cluster analysis. Further, in both cases, the isolates G₄ and G₅ were grouped together and separated from rest isolates indicating the existence of diversity between these two isolates and rest of the isolates in the study.

Fig. 7.

PCA using RAPD and ISSR data of Ganoderma isolates

Discussion

The survey conducted during December 2019 in seven major districts of Karnataka where coconut is grown extensively showed that the disease incidence across the district varied greatly and even within the district and taluk the incidence varied significantly. The incidence of disease ranged from 0 to 5.00%. Tumkur and Arsikere talukas recorded maximum incidence of 5.0%, whereas Kollegal taluk recorded the least incidence of 0.5%. The disease was not existing in Yalandur, Gundalupete, Nanjangudu, Periyapattana, T. N. Pura, Malavalli, and Channapattana talukas. The results obtained in the study agreed in line with the findings of Naik et al. (2000) who reported the varied disease incidence of BSR in Karnataka with 6.06–36.15% in Arsikere taluk of Hassan district of Karnataka. In the present study, less disease incidence was reported compared to Naik et al. (2000); however, our report was not significantly different with the study of Bhaskaran et al. (1994) in Tamil Nadu who reported 3.30–10.80 per cent in Thanjavur district of Tamil Nadu. Further, Ramadoss (1991) also observed the disease incidence from 10.8% to 80% in Thanjavur district of Tamil Nadu. The variation in disease incidence might be due to response of coconut tree to pathogen in different environmental conditions. The varied incidence of disease also due to soil factors, varieties cultivated irrigation status and also the management practices being undertaken by coconut growers. In general, the sandy soil favors the disease development when compared to other soils. Srinivasalu et al. (2003) reported that, the incidence was more in sandy soil and negligible or no incidence in black soil. Similarly, Papa Rao and Govinda Rao (1966) reported that, the incidence of BSR disease was low in heavy soils compared to light soils. Further, flood irrigation helps in development of disease. The disease was more severe during summer months which were due to lack of soil moisture (Vijayan and Natarajan et al. 1972). They also reported that rainfall and rainy days have a negative relation with the spread of Ganoderma disease indicating the flood irrigation has role in disease spread. Hence, incidence of disease varied even within the taluka.

The isolation of pathogen associated with disease constitutes the most important step in identification and management of any disease. In general tissue segment method is used for isolation of many plant pathogens around the world. Most plant pathogens can be easily isolated on the basic PDA medium without any amendments. In the present study, infected stems, roots and also sporocarps collected and the pathogen was isolated. Isolation of pathogen was made on PDA and sporocarp was most convenient means of isolation as it contains many spores in it. A total of 20 isolates were isolated and purified on PDA and used for further study. The results obtained in the study are in corroboration with findings of Bhaskaran et al. (1991) who reported advantage of use of sporocarp over the other infected materials for isolation of Ganoderma from coconut. Similarly, Manjunath et al. (2019) reported the isolation of pathogen on PDA medium. The reason for the ease of isolation using sporocarp was owing to less contamination compared to stem bits and roots bits.

Establishing the etiology of pathogen is an important aspect to prove its association with host. In the present study all the twenty isolates proved to be pathogenic to coconut seedlings after six months of inoculation. The degree of infection varied across the isolates as demonstrated by disease severity index. The results are in accordance with findings of Palanna et al. (2020) and Bhaskaran et al. (1991). Further the correct identification of pathogen is important in diagnosis of disease. The coconut BSR disease has been known to be incited by different species of Ganodermaviz., G. lucidum, G. applanantum, and G. boninense. (Vinjusha and Arun Kumar 2022) The pathogen was identified based on morphology and cultural characters. In the present study, twenty isolates exhibited white-colored colony with varying degree of zonation. Further, clamp connection and mycelial characters were taken as base to identify. The results agreed with findings of earlier researchers (Khairudin 1990; Smith and Sivasithamparam 2003; Singh et al. 2003). However, exact identification of Ganoderma sp. based on morphology and cultural characteristics is difficult as these characters are greatly influenced by environmental factors (Vinayaka and Prathiba 2013). Hence, in the present study, molecular means have been employed for correct identification.

Precise identification of pathogen up to species level has been a challenge in many diseases even today. The traditional identification tools encompassing morphological and cultural criteria had an inherent problem of being subjective as well as are greatly influenced by environmental conditions. It is with this backdrop; identification of pathogen has now completely relied on molecular means. A range of molecular methods comprising ITS region, species-specific primers, SCAR markers, housekeeping genes etc., have been developed and are in use (Kałużna et al. 2016; Kok et al. 2020). In this context, in the present study, twenty isolates of Ganoderma sp. representing varied geographical locations were subjected to DNA isolation and PCR amplification of ITS region using ITS1 and ITS4 primers. It was observed that all the isolates in the study could yield 680 bp confirming the isolates under study belong to Ganoderma sp. Further, sequencing of all isolates concluded that G4 and G5 isolates were G. lucidum and remaining isolates were G. applanatum. The findings of this study were in agreement with Karthikeyan et al. (2006) who used ITS region for identification of G. lucidum associated with coconut. Further, they confirmed the identification using species-specific primers. Similarly, Utomo et al. (2005) and Thawthong et al. (2017) also employed ITS region of Ganodermasp for identification.

Ganoderma being most complex genus among the Polyporaceae of basidiomycetes has been distributed widely both in temperate and tropical areas (Cao and Yuan 2013). A considerable amount of variation in the genetic makeup of Ganoderma sp has been attributed to out crossing over multiple generations and different geographical origins (Miller et al. 1999). Hence, the species of Ganoderma occurring across the globe exhibit a great diversity of morphological and cultural characteristics (Douanla-Meli and Langerm 2009). In the foregoing study, twenty isolates of Ganoderma sp. infecting coconut were assessed for their cultural and morphological variability among them. It was observed that, isolates exhibited great variations with respect to texture, colony margin and concentric rings whereas the colony color did not vary among the isolates. Further, based on the variations exhibited a dendrogram was constructed using DARwin 6 software to group the isolates. The dendrogram clearly grouped twenty isolates into two main groups with five isolates in one group (G₂, G₆, G_10, G₁₇, G₁₉) and remaining isolates into another group. However, this grouping had neither congregated with geographical locations from where pathogen was isolated nor with any diversity assessment based on molecular markers. Thus, grouping was only arbitrary. The existence of variability of cultural and morphological characteristics among the isolates suggested to an association of more than one species of Ganoderma with BSR disease in coconut.

In this study, variations among the twenty isolates of Ganoderma with respect virulence has been documented. This is in accordance with previous reports of Kok et al. (2013) and Goh et al. (2014) who reported variation in aggressiveness of 12 different G. boninense isolates infecting oil palm from West Malaysia. The possible reason for the change in virulence pattern of the isolates would be due to adaptability of a pathogen to new place as these isolates were drawn from the diverse places. Further, the environmental conditions prevailing in the place from where the samples have been drawn was different from the place where the experiments were conducted. In addition to this, the age of the host would also have contributed for the virulence variation (Lo et al. 2023). Apart from these, the genetic makeup of the isolate would have contributed for the variation in virulence among the isolates. Owing to its specific inter-hybridization, genetic composition of Ganoderma sp. is relatively not clear. This has become an impediment in identification of many closely related species of Ganoderma infecting many crops as well as the Ganoderma sp. employed for medicinal purpose (Zheng et al. 2009). The variations in Ganoderma sp. could be due to out crossings of isolates over generations (Miller et al. 1999). The existence of variations has been proven phenomenon in Ganoderma sp. as suggested by many authors (Wang et al. 2003; Zheng et al. 2009). There is humpty number of methods developed for studying genetic diversity of Ganoderma sp. right from traditional isozyme analysis to most advanced molecular markers (Jin et al. 1998; Qi et al. 2003). In this study, two important molecular marker system viz., ISSR and RAPD were employed to assess the genetic diversity of twenty isolates of Ganoderma sp.

Advances in genomic science have contributed many new tools for assessing the population structure of many plant pathogens. One of the most widely used tool is DNA fingerprinting techniques. Among the finger printing techniques, RFLP, RAPD, AFLP, SSR ISSR, and SRAP are employed for studying the genetic diversity of Ganoderma isolates. RAPD utilizes the short oligonucleotide of random nucleotides as primers to amplify the nanograms of total DNA under low annealing temperature (Williams et al. 1990). This technology has been recognized to be in usage for genetic diversity assessment of Ganoderma sp as reported by many earlier workers (Wang et al. 2003; Zakaria et al. (2005). Based on findings of this study it was observed that, out of ten RAPD primers used only eight primers could exhibit polymorphism. The polymorphism exhibited RAPD ranged from 33.30 to 66.70%. Further, based on RAPD pattern obtained the grouping of isolates was done. The isolates of Ganoderma were categorized in two main groups, A and B with 5 and 15 isolates, respectively. These groups were further divided into clusters. The grouping of isolates was not in accordance with geographical locations from where isolates were collected. On the other hand, the RAPD pattern could differentiate G₄ and G₅ isolates form rest of isolates in the study as they formed a separate cluster. This supported the identification of species based on ITS region sequencing. The findings corroborated with outcomes of Zhao et al. (2003) who reported high rate of genetic diversity among Ganoderma species in China using RAPD. The polymorphism reported to be 80%. Similarly, Rolim et al. (2011) reported around 22–80% polymorphism among the several strains of G. lucidum collected from Brazil and China. Further, Park et al. (2012) reported the use of RAPD marker to develop a particular marker for G. lucidum however, the genetic diversity existing between this species and other species of Ganoderma remained unresolved in their study.

ISSRs are small DNA fragments of 100–3000 bp size found in microsatellite regions which are oppositely oriented. These ISSRs are typically amplified through PCR with help of microsatellite core sequences in the form of primers. ISSRs are becoming more popular markers over the others owing to the reason that no sequence information is required for primer designing (Godwin et al. 1997). In this study, 15 ISSR primers were employed to assess the genetic makeup of Ganoderma isolates. Based on the data obtained UPGMA grouping was done. The twenty isolates were categorized in two groups A and B sharing 84.00% similarity. The polymorphism exhibited by ISSR primers ranged 33.30 to 60.00%. Like RAPD, ISSSR marker also differentiated two isolates G4 and G5 from rest of isolates under study as evidenced by UPGMA clustering. This also supported the identification of these two isolates as G. applanatum. The results are in line with findings of with Suet al. (2008) who used ISSR marker technique for the development of G. lucidum strain specific sequence-characterized amplified region (SCAR) markers. Further, Chao et al. (2018) used ISSR markers to differentiate various species of Ganoderma and, in the study, they developed a stable SCAR primer pair GLH5F/GLH5R to identify the Ganoderma lucidumHunong 5 cultivar.

However, there exists a gray area in comparing marker systems for assessing diversity of pathogens. There are many issues pertaining to markers suitability, number of marker combinations to be employed and relevance of appropriate marker utility parameters, which need to be addressed in every pathogenic species prior to large-scale use of molecular markers in plant pathogen characterization and race identification. Though there exist a vast number of studies in case of plant diversity studies in this direction but in case of fungi this type of studies are limited. In the foregoing study, effort was made to compare the RAPD marker with ISSR for their efficiency in assessing genetic diversity of Ganoderma isolates. The result clearly implied that the band frequency, Shannon’s index, Polymorphic information content, resolving power, mean resolving power was higher in ISSR marker when compared to RAPD. The findings of this study are in accordance with Renu et al. (2015) who reported the existence high genetic variability among the Ganoderma isolates under Indian subcontinent. Further, Phong et al. (2011) reported the superiority of ISSR markers over RAPD in assessing the genetic diversity of Dalbergia oliveri. Hence, ISSR marker would be better choice for genetic diversity assessment of Ganoderma sp. compared to RAPD. Further, principal component analysis of the isolates using both RAPD and ISSR data was also done. The results of PCA were not in agreement with UPGMA in case of RAPD whereas in case of ISSR it agreed with UPGMA and hence, RAPD primers were lesser efficient when compared to ISSR in assessing diversity of Ganoderma sp.

The genetic diversity existing among the isolates of Ganoderma would be attributed to the wide host ranges of the pathogen and the existence of hybridization or gene duplication or low concerted evolution as reported by Midot et al. (2019). Further, the existence of genetic diversity among isolates is supported by high morphological plasticity. Thus, the genetic diversity prevailing among the isolates would have impact on the management practices adopted across the growing areas.

Conclusion

The species of Ganoderma were associated with BSR disease of coconut in major growing tracks of Karnataka as revealed by morphological characteristics and ITS sequencing. Further, the isolates of Ganoderma exhibited wide genetic diversity among them and to assess the genetic diversity, ISSR-based markers are the choice of markers as revealed from this study.

Supplementary Information

Below is the link to the electronic supplementary material.

Data availability

Data will be available based on the special request.