Introduction

Rattans are spiny climbing palms belong to the family Arecaceae and consist of some 600 species in 14 genera. Calamus is the most widespread with 370 species occurring in both tropical and subtropical regions of Africa and south-east Asia (Uhl and Dransfield 1987). In peninsular India, the genus is represented by 22 species (Anto et al. 2001), and recently several nomenclatural changes have been proposed for the Indian species (Sreekumar and Henderson 2014). Over-exploitation of rattan has considerably depleted natural populations, particularly in the southern regions of India, and consequently raw materials are being collected from the unexplored north-eastern states of the country (Raj et al. 2014). [In fact, rattan furniture industry is growing at US$4 billion trade per year in India (Arunachalam 2011).]

To understand genetic variations in natural populations, it is necessary to examine a large number of polymorphisms. Variations between individuals of species have been observed over millennia and are considered as ‘hotspots’ of evolution (Seeni et al. 1998). The study of genetic diversity within species and interspecific or intergeneric relationships among a number of species is carried out with the help of molecular markers (Bandopadhyay et al. 2004). Microsatellites or simple sequence repeats (SSR) occurring in all plant genomes are widely studied for analysing genetic variations in plants. They are abundant in non-coding genomic regions but are also detected in coding regions using SSRs developed from expressed sequence tags (ESTs) (Ranade et al. 2014; Anjali et al. 2015; Sakthipriya and Sabu 2016). Accordingly, SSRs are classified into genomic SSRs and EST-SSRs based on the sequence regions used to identify microsatellite region (Wei et al. 2011).

The genomics of the genus Calamus has been reviewed earlier (Arunachalam 2011). Genetic variability in rattans have been reported using random amplified polymorphic DNA (RAPD) (Sreekumar and Renuka 2006; Sarmah et al. 2007), inter simple sequence repeats (ISSR) (Ramesha et al. 2007), and isozyme markers (Ravikanth et al. 2002). There was one attempt to employ microsatellites in rattans (Nageswara Rao et al. 2007), but the study failed to identify significant variations in the samples. The major disadvantage of RAPD and ISSR markers for characterizing population genetics is that heterozygotes cannot be detected (Ferguson et al. 1998). Therefore, the objectives of this study were: (1) to estimate genetic variation in selected Calamus species from a wide geographic area in the southern Western Ghats; (2) to analyse the distribution of genetic variability within and among the Calamus species; and, (3) to investigate existing patterns of genetic structure in the species.

Materials and methods

Leaf samples from 227 individuals of seven Calamus species, namely, Calamus brandisii Becc., C. gamblei Becc., C. hookerianus Becc., C. metzianus Schltdl., C. nagbettai R.R. Fernald & Dey, C. thwaitesii Becc. and C. travancoricus Bedd.ex.Becc. were collected from different areas of the states of Kerala and Karnataka (Fig. 1). The field trips were carried out in 2012 − 14 in various natural habitats such as protected areas, buffer zones and periphery adjacent to settlements. Young leaf samples from individual plants were collected throughout their natural habitats at maximum distances but no less than 5 m apart to minimize the chance of collecting clones. Samples were rinsed in running tap water followed by distilled water and 70% ethanol and kept at − 20 °C for DNA extraction.

Fig. 1
figure 1

Map of the sampling location. a Calamus brandisii (N = 32), b C. gamblei (N = 30), c C. hookerianus (N = 36), d C. metzianus (N = 35), e C. nagbettai (N = 35), f C. thwaitesii (N = 42), g C. travancoricus (N = 17)

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Microsatellite analysis

DNA was extracted using the DNeasy Plant Mini Kit (Qiagen, India). Forty-two microsatellite or simple sequences repeat (SSR) markers were tested, of which 26 were used to assess genetic variability and amplified in all the species (Table 1). The reaction mixture contained 15 pmol each of the forward and reverse primers, 200 µM of deoxynucleotides, 2.5 µL of MgCl2 buffer, 0.2  µL of 5 U/µL Taq polymerase and 50 ng of DNA template. After 2 min at 94 °C, 35 cycles were performed for 30 s at 94 °C, 1 min annealing at the optimized temperature, a 2 min extension at 72 °C, and a final extension of 7 min at 72 °C. The Polymerase chain reaction (PCR) was carried out using SureCycler 8800 (Agilent Technologies, Malaysia).

Table 1 Details of 26 SSR primers, their annealing temperatures and product sizes in seven Calamus species
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After the PCR, the amplified DNA products were electrophoresed on 3.5% agarose gel with ethidium bromide (10 µg/µL) and visualized under ultraviolet light using a gel documentation system (UVP Bio-Imaging, UK). To determine the precise PCR product size, a 6% acrylamide gel with silver staining was used (Benbouza et al. 2006). Bands were scored as loci and alleles and used for genetic analysis.

Statistical analysis

The bands obtained with each primer were scored, keeping the expected size range of the PCR products as a reference. The microsatellite data were analyzed using POPGENE version 1.32 (Yeh et al. 1999) and FSTAT version 2.9.3.2 (Goudet 2014). The mean observed number of alleles per locus (Na) counts the number of alleles with nonzero frequency. The effective number of alleles per locus (Ne) estimates the reciprocal of homozygosity (Hartl and Clark 1989). The Shannon’s Information Index (I) is a measure of gene diversity (Lewontin 1972). The observed heterozygosity (Ho) is a proportion of observed heterozygotes at a given locus and the expected heterozygosity (He) is a proportion of expected heterozygotes under random mating (Nei 1973). The percentage of loci that were polymorphic (P), regardless of allele frequencies, the observed heterozygosity (Ho) and the expected heterozygosity (He) were calculated using the POPGENE version 1.32.]

Estimates of F-statistics (Weir and Cockerham 1984), average gene diversity within the samples (Ht), in all the samples (Hs), and among the samples (Dst) were obtained using FSTAT software. The unbiased genetic identity and genetic distance were calculated (Nei 1978) as a measure of population structuring. The phylogenetic tree based on Nei (1978) genetic identity estimates was generated in POPGENE version 1.32, following UPGMA (unweighted pair group method with arithmetic average) and visualized using MEGA version 7 (Tamura et al. 2013). STRUCTURE version 2.3.4 (Pritchard et al. 2000) was used to analyze population structure, and the ‘K’ populations were visualized through Structure Harvester (Earl and VonHoldt 2012).

Results

Gene diversity and heterozygosity

Twenty-six SSR primers provided PCR products for the 7 Calamus species of a total of 227 accessions. Summary statistics of the loci were tabulated to reveal the informative loci of the variability (Table 2). Ne (effective number of alleles per locus) ranged from 1.01 to 2.00 with a mean of 1.29 ± 0.30, I (Shannon’s Information Index) from 0.02 to 0.69, and the average Ho (observed heterozygosity) from 0 to 0.78 with a mean value of 0.16. Average gene diversity Ht (within the samples), Hs (in all samples) and Dst (among the samples) were estimated as 0.13, 0.18 and 0.06 respectively.

Table 2 Summary statistics of the 26 microsatellite loci used for genotyping the seven Calamus species
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Genetic diversity

C. metzianus had the lowest Ne value of 1.15; the highest (1.33) was recorded for C. brandisii. Estimates of I (0.11 and 0.26), Ho (0.11 and 0.24), He (0.08 and 0.18), and P (23.08 and 46.15) exhibited similar ranges for C. metzianus and C. brandisii, respectively (Table 3).

Table 3 Species-wise descriptive statistics and extent of inbreeding as evidenced from Fis values obtained using 26 SSR markers in seven Calamus species
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Genetic structure

The multilocus estimator of Fst (theta) (Weir and Cockerham 1984) between all pairs of species (Table 4) was calculated. C. hookerianus and C. travancoricus showed highest genetic differentiation of 44% as revealed through Fst values, whereas the lowest differentiation of 22% was observed between C. gamblei and C. thwaitesii. The Fis estimates were negative (Table 3), indicating low inbreeding, i.e., occurrences of outcrossing were more prevalent than inbreeding).

Table 4 Genetic differentiation (Fst) between pairs of Calamus species
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The mean genetic identity among populations was 0.92 (SD = 0.024; Table 5). The highest genetic identity was between C. metzianus and C. travancoricus (0.95) and the lowest between C. brandisii and C. nagbettai (0.88). The dendrogram using Nei’s genetic distance (Nei 1978) showed two groups: one with C. hookerianus, the other with the remaining 6 species (Fig. 2). The observed clustering does not have a relationship with the habit and systematic position. However, the dendrogram created using Nei’s genetic identity data from the 227 accessions showed them generally into the respective biological species (Fig. 3).

Table 5 Genetic identity (above **** diagonal) and genetic distance (below **** diagonal) estimated using 26 SSR markers in seven Calamus species
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Fig. 2
figure 2

Dendrogram based on Nei’s genetic distance (Nei 1978) using 26 SSR markers in seven Calamus species. Method = UPGMA. Modified from NEIGHBOR procedure of PHYLIP Version 3.5

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Fig. 3
figure 3

Nei’s genetic identity-based dendrogram using 26 SSR markers in 227 accessions belonging to seven Calamus species. Cbr: C. brandisii, Cgm: C. gamblei, Chk: C. hookerianus, Cmt: C. metzianus, Cng: C. nagbettai, Cth: C. thwaitesii, Ctr: C. travancoricus

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STRUCTURE HARVESTER software was used to analyse the population structure in the 227 individuals. The program applies a Bayesian model-based clustering algorithm that identifies subgroups with distinct allele frequencies. This procedure places individuals into K clusters, where K is chosen in advance but may be varied across independent runs of the algorithm. The program visualized the results of the analysis and determined the ‘K’ clusters. Individuals were assigned to populations or multiple populations if their genotype indicated an admixture. The highest-likelihood run for K 7 found distinct structure where the seven species exactly clustered into seven groups with some differentiation or sub-structuring (Fig. 4).

Fig. 4
figure 4

Model-based population structure of 227 individuals of Calamus spp. Numbers indicate the populations formed based on the genetic characteristics which are the same as that of the biological species. 1: C. brandisii, 2: C. gamblei, 3: C. hookerianus, 4: C. metzianus, 5: C. nagbettai, 6: C. thwaitesii, 7: C. travancoricus

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Discussion

Amount of genetic variation

Allelic variation may be detected and estimated using genetic markers; however, the value of genetic markers for detecting population differences depends largely on the differences of the alleles in various individuals of a population (Nei 1987). Different methods have been adopted in the last two decades to reveal the extent of genetic diversity in various Calamus species (Bon 1996; Changtragoon et al. 1996; Ravikanth et al. 1999; Wickneswari et al. 2002; Sudarmonowati et al. 2004; Sarmah 2005; Sreekumar and Renuka 2006; Nageswara Rao et al. 2007; Sarmah et al. 2007; Ramesha et al. 2007; Ambida et al. 2012; Swain and Abhijita 2015; Priya et al. 2016). In a pioneering study carried out in Malaysia during the mid-1990s, allozymes from C. subinermis were characterized and polymorphism was much higher (70.5%) in this species than expected levels of genetic diversity for tropical woody and non-woody species (Bon 1996). RAPD markers have also been employed during this period to study genetic variability of Calamus species of Thailand (Changtragoon et al. 1996). Isozyme analysis in C. manan from Malaysia showed extremely low polymorphism (6.7 to 20.0%) for mature plants from rattan plantations (Wickneswari et al. 2002). On the other hand, natural populations of this species in Indonesia exhibited higher isozyme diversity with respect to polymorphic loci, ranging from 66.7 to 76.7% (Sudarmonowati et al. 2004). In a study of north-eastern Indian Calamus species viz. C. flagellum, C. gracilis, C. khasianus, C. tenuis, C. erectus, C. leptospadix, C. inermis, and C. acanthospathus, average polymorphism of 93.0 and 98.1% were identified using isozymes and RAPDs, respectively (Sarmah 2005), which indicated a better scope for genetic improvement of rattans in this region. Allozyme analysis involving 12 loci over eight enzyme systems detected polymorphic loci in C. thwaitesii from the central Western Ghats in India’s Karnataka state ranging from 75.0 to 91.7% (Ravikanth et al. 1999). In another study, the percentage of polymorphic loci varied from 40.0 to 60.8% in eight populations of C. thwaitesii from the Western Ghats and Sri Lanka using RAPD markers (Sreekumar and Renuka 2006). The genetic distance between these populations ranged from 0.03 to 0.3. However, ISSR (inter simple sequence repeats) analysis of C. thwaitesii in the central Western Ghats showed an average of 45.3 polymorphism. Greater diversity was found in the core protected areas in comparison to the buffer and periphery regions (Ramesha et al. 2007). Molecular analyses of different Indian and Sri Lankan populations of C. rivalis and C. metzianus carried out using RAPD markers revealed that the percentage of polymorphic loci between populations varied from 26.5 to 68.4%, and the genetic distance between populations ranged from 0.1 to 0.3 (Sreekumar et al. 2006). This study helped to resolve the taxonomic ambiguity previously existing in these two species and recommended that C. rivalis be merged with C. metzianus. Preliminary molecular analysis of twelve species of Calamus from The Philippines using modified RAPD and ISSR primers indicated 100% polymorphism in all the loci tested (Ambida et al. 2012). Another study of six Calamus species from Orissa, India using ISSR primers, also exhibited high (94.6%) polymorphism (Swain and Abhijita 2015). Recently, ISSR analysis of C. vattayila, a medium sized rattan endemic to the Western Ghats, showed an average polymorphism of 36.2% in three populations studied (Priya et al. 2016).

In the above studies, either isozymes, RAPD or ISSR markers were used. For the first time, in an attempt to identify microsatellite markers to determine gene flow events and genetic differentiation of populations in rattans, those developed for Cocos nucifera L. (family Arecaceae) were examined for cross-species amplification (Nageswara Rao et al. 2007). Of the six microsatellite primer pairs screened, two yielded good cross-species amplification across different rattan genera and species from South and Southeast Asia. In this study, low levels of genetic variability were recorded which was not surprising for EST-SSR markers. The proportion of polymorphic loci ranged from 23.1 to 46.2 for C. metzianus and C. brandisii respectively. The surprisingly low polymorphism shown by C. metzianus might be that the samples were collected mostly from sacred groves (regions of micro forest, rich in biodiversity and protected by local communities), and the rattan population in these areas are represented by a few individuals, limiting continued evolution. These plants might be introduced to develop different sacred groves in the past from the same habitat. Average polymorphism for the remaining six species was 41.0%.

Distribution of genetic variability

Generally, outcrossing species retain most of their genetic variability within populations (Bartish et al. 1999). This is true for Calamus species as reported from several studies. The levels of population differentiation in C. thwaitesii are low, as indicated by the mean Fst value of 8.8% generated through allozyme analysis, suggesting that nearly 91.0% of the genetic variation is accounted by variation within a population (Ravikanth et al. 2001). In another study using RAPD markers, the majority of the genetic diversity was distributed within populations (70.8%) and only (29.2%) among populations of C. thwaitesii (Sreekumar and Renuka 2006). An analysis of molecular variance (AMOVA) of variations within and between populations of C. rivalis and C. metzianus of populations of the Western Ghats treated as one region and the Sri Lankan populations as another, showed that the percentages of variation attributable to the differences between regions, among populations within regions, and among individuals within populations were 18.8% (p < 0.001), 21.4% (p < 0.001), and 59.9% (p < 0.009), respectively, (Sreekumar et al. 2006). This study revealed a coefficient of gene differentiation (Gst) measures the gene diversity between populations of 24.0%, indicating that 76% of variation resides within populations (Table 2).

Distribution of genetic variability over space is critical in conservation. Generally moderate to high genetic diversity in the core areas results in higher fitness of small populations and is noted in this study in species such as C. brandisii (p = 46.2%; Table 3) which was collected from the Agasthyamalai Biosphere Reserve. This was also observed in a study of C. thwaitesii, where populations sampled from core and buffer regions maintained better population structure as well as higher genetic diversity than populations of the peripheral regions of the protected area (Ramesha et al. 2007).

Genetic structure

Sampling from predefined populations is used mostly for studies of human genetic variation where populations are usually defined on the basis of culture or geography and might not reflect underlying genetic relationships (Foster and Sharp 2002). On the other hand, sampling of plants to analyse genetic structure mostly considers geographical boundaries of the distribution. Analysis of multilocus genotypes allows inference of genetic ancestry without relying on information on sampling locations of individuals (Bowcock et al. 1994; Mountain and Cavalli-Sforza 1997; Pritchard et al. 2000). The 227 individuals of the Calamus species collected from various locations in this study were analysed using STRUCTURE software without considering their biological status. Surprisingly, the seven species separated into seven K groups (Fig. 4). However, separation shows different levels of sub-structuring within each species. The UPGMA-based dendrogram using genetic identity estimates also resulted in a similar profile with varying levels of differentiation (Fig. 3). Generally, the breeding system determines the extent of within-population genetic diversity, whereas other factors, including geographical distribution, have little effect (Bartish et al. 1999). However, this concept does not account for genetic drift due to over exploitation of the mature Calamus species that usually occurs from the periphery of the protected areas. In the long-term, this would affect the continued evolution of the species but an outcrossing mechanism would reconcile some of the loss and help to restore genetic variability to some extent for these dioecious species.

Protected areas, genetic diversity hotspots and conservation implications

The amount of genetic variation within a species in its natural habitat determines the niches or hotspots. The Western Ghats, a 1600 km mountain chain between 8 to 21°N parallel to the west coast of India and older than the Himalayas, is considered one of the eight ‘hottest hot-spots’ of biological diversity in the world (Daniels 1992; Myers et al. 2000), and is listed in the UNESCO World Natural Heritage sites July 2012. Identifying lesser areas of high genetic diversity and endemism, or micro-hotspots within larger hotspots at diverse scales, has been carried out for both flora and fauna (Murray-Smith et al. 2006; Raes et al. 2009; Kraft et al. 2010; Schouten et al. 2010; Lopez-Lopez et al. 2011).

Except for C. metzianus, all the species were collected from various regions of the Western Ghats (Table 6). An attempt was made to identify micro-hotspots for these species. C. brandisii showed the highest heterozygosity (Ho) of 0.40 from the Agasthyamala Biosphere Reserve. High and low altitude provenances of C. brandisii determine the clear ecotypic differentiation among the species. Even though C. gamblei is more widely distributed than C. brandisii due to its occurrence in a narrow elevation range, the species displayed an observed heterozygosity of 0.24 from the Bonacaud region of the Reserve. The occurrence of C. hookerianus from the buffer areas to the periphery maintained an observed heterozygosity of 0.23 from the region. The higher occurrence of C. travancoricus produced a higher heterozygosity of 0.28 compared to C. gamblei and C. hookerianus from the Rosemala area of the Shenduruney Wildlife Sanctuary. Due to the broad pattern of distribution of C. thwaitesii from the southern and central Western Ghats, the species had a significantly higher heterozygosity; the highest of 0.32 was recorded from the Rosemala area. The universally threatened, endemic species, C. nagbettai, showed a heterozygosity of 0.29 from the Subramanya forest of the Pushpagiri Wildlife Sanctuary. The protected areas in the Agasthyamala Biosphere Reserve have higher species density, greater gene flow and higher regeneration due to fewer human interventions and to the intrinsic spatial distribution gradients of the species. Detailed location-wise heterozygocity values are given in Table 6.

Table 6 Observed heterozygosity in seven Calamus species using 26 microsatellite markers
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The genetic diversity hotspots of rattans in the southern and central Western Ghats were found in the micro-hotspots of the Agasthyamala Biosphere Reserve and the Pushpagiri Wildlife Sanctuary (Table 7). The intra-specific genetic variation was found below the Achenkovil gap in the Agasthyamala, Bonacaud and Rosemala regions and above the Palghat gap in the Subramanya forest. In the Western Ghats, protected areas are well-managed and conserved. However, they are surrounded by large numbers of villages and the boundaries are permeable, leading to the illegal harvesting of rattans. Three of the four micro-hotspots were identified in the southern part of the Western Ghats and one from the central Western Ghats. The four hotspots are at low, mid-to high elevations in the southern Western Ghats, and low-to mid-elevations in the central Western Ghats. These protected areas may be possible for future reintroduction and species recovery programs.

Table 7 Seven Calamus species of the Western Ghats with conservation status and region of genetic diversity micro-hotspots
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Conclusions

Varying levels of genetic diversity were found for different Calamus species depending on their areas of distribution, their exploitation for commercial use, and level of protection status. The findings of this study provide a strong foundation for further strengthening protected area networks as well as the enrichment of man-made micro habitats such as sacred groves, especially areas of intermediate levels of disturbances. The dioecious nature of Calamus species may reconcile some of the genetic loss and help to restore genetic variability over a period of time. The present study provides useful information for genetic conservation and will aid in further understanding of species phylogeography on the Indian subcontinent.