Study on population genetics of Rhododendron mechukae, an endemic species of the Eastern Himalayas

Study on population genetics of Rhododendron mechukae, an endemic species of the Eastern Himalayas | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Study on population genetics of Rhododendron mechukae , an endemic species of the Eastern Himalayas Sabbir Mondal, Shivani Dobhal, Siddhartha Singh, Tisu Tayeng, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9681924/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study presents the first molecular analysis of Rhododendron mechukae , a critically endangered and narrowly distributed species endemic to Arunachal Pradesh in the Eastern Himalayas. Population genetic diversity was assessed using simple sequence repeat (SSR) markers across 50 genotypes sampled from natural populations in Mechuka, Shi Yomi district. Out of 20 SSR primer pairs screened, nine exhibited successful amplification with polymorphic information content (PIC) values ranging from 0.231 to 0.540. The effective number of alleles (Ne) averaged 1.38 ± 0.11, Shannon’s information index (I) was 0.35 ± 0.07, and observed heterozygosity (Ho) was extremely low at 0.032 ± 0.01. STRUCTURE analysis revealed two distinct genetic clusters (K = 2), with Population 1 showing higher genetic diversity (Na = 2.333, He = 0.333) than Population 2 (Na = 1.556, He = 0.103). Analysis of molecular variance (AMOVA) indicated that 63% of the total genetic variance occurred among populations, confirming strong genetic structuring. The mean fixation index (F = 0.731 ± 0.09) indicated severe heterozygote deficiency and a high prevalence of homozygosity. These findings show that although R. mechukae retains moderate genetic diversity at the species level, it faces pronounced vulnerability due to limited gene flow and population isolation, highlighting the need for urgent conservation interventions. Forestry population genetics SSR markers genetic diversity conservation genetics Eastern Himalayas endangered species Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 1 Introduction The Eastern Himalayas are a globally important biodiversity hotspot that supports exceptional floristic diversity but is increasingly threatened by anthropogenic pressures and climate change (Nautiyal and Kaechele, 2007 ).The genus Rhododendron (Ericaceae), with more than 1,200 species worldwide, reaches its highest diversity in this region, and Asian mountains harbour approximately 90% of wild Rhododendron populations (Pradhan et al., 2015 ).These species often function as keystone taxa in fragile high-altitude ecosystems, stabilizing slopes, providing habitat, and supporting complex ecological interactions (Bharali et al., 2013 ). Rhododendron mechukae , recently described from Arunachal Pradesh, India, is a narrowly distributed endemic species restricted to temperate forests in the Mechuka region (Mao et al., 2013 ).It is characterized by rough brownish peeling bark, leaves with rufous-brown indumentum on the abaxial surface, short pedicels up to 1.8 cm long, and early flowering from February to March (Mao et al., 2013 ).Its distribution is highly localized, and populations are under strong pressure from habitat degradation and timber extraction (Mao et al., 2013 ; Bharali et al., 2013 ). Conserving endangered plant species is essential for maintaining biological diversity and ecosystem stability (Torres-Díaz et al., 2021 ). Genetic diversity within and among populations strongly influences long-term survival, adaptability, and resilience to environmental change (Jiajia et al., 2023 ). Populations with reduced genetic variation are more vulnerable to extinction because of inbreeding depression, genetic drift, and limited adaptive potential (Reed and Frankham, 2003 ; Frankham, 2005 ; Johnson and Molano-Flores, 2023 ). Characterizing genetic variation within and between populations is therefore crucial for designing effective conservation strategies for small and fragmented populations (Frankham, 2005 ; Johnson and Molano-Flores, 2023 ). Despite its conservation importance, no molecular or genomic data were previously available for R. mechukae , leaving a major gap in evidence-based conservation planning. The present study addresses this gap by providing the first population-level genetic assessment of R. mechukae using microsatellite markers, with the aims of quantifying genetic diversity, resolving population structure, and generating baseline information for conservation management. 2 Materials and methods 2.1 Study area and sample collection Field surveys were conducted in the natural distribution range of R. mechukae in Mechuka, Shi Yomi district, Arunachal Pradesh, India (28°39′53.70″ N, 93°59′08.70″ E) at elevations of 2,000–3,500 m. A total of 50 individual genotypes were randomly sampled from five populations (Segong, Hanuman Camp, Yorlung, Pogor, and Lamang) using linear transects, and the sampling locations are presented in Fig. 4. GPS coordinates were recorded for each sampled plant, and three healthy leaves per genotype were collected during September-March 2024 following the original taxonomic description. Leaf samples were rapidly desiccated in silica gel and stored at − 80°C until DNA extraction. Figure 4 Sampling locations of R. mechukae populations in Mechuka region, Arunachal Pradesh, India 2.2 DNA extraction and quantification Genomic DNA was extracted using a modified cetyltrimethylammonium bromide (CTAB) method following Doyle and Doyle ( 1993 ). Approximately 2 g of leaf tissue was ground to a fine powder in liquid nitrogen using a pre-cooled mortar and pestle. The powder was mixed with CTAB extraction buffer (100 mM Tris–HCl, pH 8.0; 20 mM EDTA; 1.42 M NaCl; 5 mM ascorbic acid; 3% CTAB; 3% polyvinylpyrrolidone) and incubated at 55°C for 45 min. After extraction with chloroform:isoamyl alcohol (24:1) and precipitation with isopropanol, DNA pellets were dissolved in sterile water and treated with RNase. DNA concentration and purity were measured spectrophotometrically using A260/A280 ratios, with values around 1.8 indicating acceptable purity. DNA quality was further checked on 0.8% agarose gels, which showed intact high-molecular-weight bands with minimal degradation. 2.3 SSR marker analysis Twenty SSR primer pairs previously developed for related Rhododendron species were initially screened (Table 1 ). PCR amplification was performed in 15 µl reactions containing 1.9 µl PCR buffer with MgCl2, 1.5 µl dNTPs, 0.45 µl of each primer, 0.5 µl Taq DNA polymerase, 8.7 µl molecular-grade water, and 1.5 µl template DNA. Thermal cycling consisted of an initial denaturation at 94°C for 3 min; 35 cycles of 94°C for 1 min, locus-specific annealing temperature for 1 min, and 72°C for 1 min; followed by a final extension at 72°C for 8 min. PCR products were separated on 2% agarose gels, visualized under UV light, and scored as present (1) or absent (0). Polymorphic information content (PIC) was calculated as \(\:PIC=1-\sum\:{P}_{i}^{2}\) , where \(\:{P}_{i}\) is the frequency of the \(\:i\) th allele at a locus (De Riek et al., 2001 ). Table 1 Primer pairs used in the study S.no. Locus Code Motif/SSR Forward Primer (5'-3') Reverse Primer (5'-3') References 1 RHM_MS13 SSR-1 (CTT)5 F: TCGATCTCCACCTACAAACTA R: ACAAAGGCCTTGAACATCT Sharma et al. 2020 2 R394 SSR-2 (TC)16 F: GGAAAGTGTGGGTGTTAGTGC R: TTGAGAGATGGCGAGAGAGAG Choudhary et al. 2014 3 RE101 SSR-3 (AG)16 F: GACGGGAATGAGCAAGGTTG R: CTTCAATTCTGCAAGCCCGA Choudhary et al. 2014 4 RA430 SSR-4 (TC)10(CT)6 F: GCGTAAATCGAGTTCGGAAG R: CTCTCTCTAATCGAATTCCCG Choudhary et al. 2014 5 RF87A SSR-5 (AG)10(AG)10 F: TGGGTCATGTTCTGGAAGGT R: TGAACTAACCCTAGCCACACT Choudhary et al. 2014 6 RA324 SSR-6 (AG)8(GA)8 F: GCGTACAACATGCCCAAATA R: CCCTGTTCTCATTGCTCACA Choudhary et al. 2014 7 RF304 SSR-7 (AG)13(GT)9 F: TCCTAGGGTTTGTTCGCAAT R: TGCTAGCGATTTCCTAGGGT Choudhary et al. 2014 8 RA272A SSR-8 (CT)8(CT)11 F: GCCCCGGTGACTCATAAAAT R: TGGTACAAGTGGGACACGA Choudhary et al. 2014 9 R460 SSR-9 (GA)13(AG)12 F: CCCTACTTCTTTCATCACATACAA R: CAACTCCGGTCATTTTTGGT Choudhary et al. 2014 10 RA267 SSR-10 (GA)11(AG)10 F: ACGGAGAAGCAGTGAGCATT R: TGCACAGGAACACCCAATAA Choudhary et al. 2014 11 RA346 SSR-11 (TC)9 F: CGGAGCAAGCTCTCTTATCG R: CCTCTCCTGTGTAGCAAGTCG Choudhary et al. 2014 12 RM1D1 SSR-12 (CT)17 F: ATCTGGAGGCCATTGGTAGT R: TATTGGGTCCGATGACAGAC Kameyama et al. 2002 13 RM2D2 SSR-13 (CT)16 F: ATGTGTTTCGTTGCTACTGT R: ATGGTTGGTTTGTTTTCCTA Naito et al .1998 14 RM3D4 SSR-14 (CT)7(CT)19 F: CTCCCAACAAACAAATCCAT R: CACCGAACGAAGACACTCAG Naito et al .1998 15 RM9D6 SSR-15 (GA)16 F: CTCGCCTCCCAAAAGCAAT R: CGTGTCCTCACCCCCGTAAC Naito et al .1998 16 RA470 SSR-16 (GA)14(AG)10 F: AGGGACAAGAAGAAGCCACA R: TCGCGCTTATTACAGCTCTTC Choudhary et al. 2014 17 RA254 SSR-17 (CT)16(CT)10 F: AGTAGCAACACCCACACACT R: GGAGGGGCTGTAGTCTGATT Choudhary et al. 2014 18 RA321 SSR-18 (GA)9 F: AGAGATGGGTTTGTGTAAAGTCTG R: TATTTCGCTGCCACCCTAAC Choudhary et al. 2014 19 RA351 SSR-19 (AG)12(AG)11 F: TGTCGCTCTCTCACTGATCG R: TTTGTAGTTTTCCCGTGTCCTT Choudhary et al. 2014 20 R97 SSR-20 (AG)10(AG)13 F: AGCAGCAACAATGGTGTCC R: TCTAGAAGGCCTCCCATTCC Choudhary et al. 2014 2.4 Population genetic analysis Genetic diversity parameters, including number of alleles (Na), effective number of alleles (Ne), Shannon’s information index (I), observed heterozygosity (Ho), expected heterozygosity (He), and fixation index (F), were estimated using GenAlEx v6.5 (Peakall and Smouse, 2012 ).Population structure was analysed using STRUCTURE v2.3.4 with a Bayesian Markov chain Monte Carlo (MCMC) approach (Pritchard et al., 2000 ).Ten independent runs were performed for K values from 1 to 10, each with a burn-in of 100,000 iterations and 200,000 MCMC repetitions.The most likely number of clusters (K) was determined using Structure Harvester based on the ΔK method (Earl and VonHoldt, 2012 ; Evanno et al., 2005 ). AMOVA was conducted to partition genetic variance among populations, among individuals within populations, and within individuals (Excoffier et al., 1992 ).Wright's F-statistics (Fis, Fit, Fst) and gene flow (Nm) were calculated to assess population differentiation and migration. Genetic relationships among populations were visualized using UPGMA/Neighbour-Joining trees constructed in DARwin v6.0 and principal coordinate analysis (PCoA) in GenAlEx (Perrier and Jacquemoud-Collet, 2006 ; Peakall and Smouse, 2012 ). 3 Results 3.1 SSR marker polymorphism Of the 20 SSR primer pairs tested, nine (45%) produced clear and reproducible amplification across all samples and were polymorphic. These nine markers (SSR1, SSR3, SSR9, SSR10, SSR11, SSR13, SSR15, SSR17, SSR18) yielded alleles in the size range 150–310 bp, and representative amplification profiles for SSR11 and SSR15 are shown in Figs. 5 and 6 , respectively. PIC values ranged from 0.231 (SSR13) to 0.540 (SSR11), with an average of 0.390, indicating moderate to high informativeness for population genetic analysis (Table 2 ). 3.2 Genetic diversity assessment Genetic diversity estimates revealed moderate allelic richness but very low heterozygosity. The mean number of different alleles (Na) was 1.94 ± 0.18, ranging from 1.50 (SSR3, SSR10) to 3.00 (SSR9). The effective number of alleles (Ne) varied between 1.10 ± 0.10 (SSR10) and 1.92 ± 0.92 (SSR11), with a mean of 1.38 ± 0.11. Shannon’s information index (I) ranged from 0.12 ± 0.06 (SSR18) to 0.59 ± 0.06 (SSR15), with an overall mean of 0.35 ± 0.07. Observed heterozygosity (Ho) was extremely low, ranging from 0.00 for five loci (SSR10, SSR11, SSR13, SSR15, SSR17) to 0.12 ± 0.06 (SSR18), with a grand mean of 0.032 ± 0.01. In contrast, expected heterozygosity (He) ranged from 0.00 (SSR17) to 0.40 ± 0.06 (SSR15), with a mean of 0.218 ± 0.04. Fixation indices (F) were high and positive for most loci, ranging from 0.13 ± 0.15 (SSR18) to 1.00 ± 0.00, with a mean of 0.731 ± 0.09, indicating strong heterozygote deficiency and a predominance of homozygotes (Table 3 ). Table 2 List of successfully amplified primers with allele size and PIC Locus Code Motif/SSR Forward Primer (5'-3') Reverse Primer (5'-3') Allele size (bp) Tm°C PIC RHM_MS13 SSR-1 (CTT)5 F: TCGATCTCCACCTACAAACTA R: ACAAAGGCCTTGAACATCT 235–270 55.7 0.371 RE101 SSR-3 (AG)16 F: GACGGGAATGAGCAAGGTTG R: CTTCAATTCTGCAAGCCCGA 165–181 50.5 0.373 R460 SSR-9 (GA)13(AG)12 F: CCCTACTTCTTTCATCACATACAA R: CAACTCCGGTCATTTTTGGT 245–275 59.4 0.431 RA267 SSR-10 (GA)11(AG)10 F: ACGGAGAAGCAGTGAGCATT R: TGCACAGGAACACCCAATAA 205–225 58.2 0.366 RA346 SSR-11 (TC)9 F: CGGAGCAAGCTCTCTTATCG R: CCTCTCCTGTGTAGCAAGTCG 290–310 60.1 0.540 RM2D2 SSR-13 (CT)16 F: ATGTGTTTCGTTGCTACTGT R: ATGGTTGGTTTGTTTTCCTA 165–181 58.7 0.231 RM9D6 SSR-15 (GA)16 F: CTCGCCTCCCAAAAGCAAT R: CGTGTCCTCACCCCCGTAAC 250–310 55.7 0.471 RA254 SSR-17 (CT)16(CT)10 F: AGTAGCAACACCCACACACT R: GGAGGGGCTGTAGTCTGATT 150–190 57.3 0.356 RA321 SSR-18 (GA)9 F:AGAGATGGGTTTGTGTAAAGTCTG R: TATTTCGCTGCCACCCTAAC 175–190 59.9 0.372 Table 3 Assessment of genetic diversity characters for 9 SSR molecular markers on 50 genotypes of R. mechukae Primer code N N a N e I H o H e u H e F SSR- 1 24.50 ± 7.50 2.00 ± 0.00 1.60 ± 0.03 0.56 ± 0.01 0.07 ± 0.04 0.37 ± 0.01 0.38 ± 0.01 0.79 ± 0.12 SSR- 3 24.50 ± 6.50 1.50 ± 0.50 1.16 ± 0.16 0.20 ± 0.20 0.01 ± 0.01 0.12 ± 0.12 0.12 ± 0.12 0.87 ± 0.12 SSR- 9 24.00 ± 8.00 3.00 ± 1.00 1.51 ± 0.45 0.48 ± 0.34 0.07 ± 0.01 0.27 ± 0.21 0.28 ± 0.21 0.38 ± 0.42 SSR- 10 24.50 ± 7.50 1.50 ± 0.50 1.10 ± 0.10 0.15 ± 0.15 0.00 ± 0.00 0.08 ± 0.08 0.08 ± 0.08 1.00 ± 0.08 SSR- 11 25.00 ± 7.00 2.00 ± 0.00 1.92 ± 0.92 0.53 ± 0.53 0.00 ± 0.00 0.32 ± 0.32 0.32 ± 0.32 1.00 ± 0.32 SSR- 13 25.00 ± 7.00 2.00 ± 0.00 1.28 ± 0.17 0.39 ± 0.17 0.00 ± 0.00 0.21 ± 0.10 0.21 ± 0.10 1.00 ± 0.00 SSR- 15 25.00 ± 7.00 2.00 ± 0.00 1.70 ± 0.17 0.59 ± 0.06 0.00 ± 0.00 0.40 ± 0.06 0.41 ± 0.06 1.00 ± 0.00 SSR- 17 24.50 ± 6.50 2.00 ± 0.00 1.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 NA SSR- 18 25.00 ± 7.00 2.00 ± 0.00 1.20 ± 0.15 0.12 ± 0.06 0.12 ± 0.06 0.15 ± 0.10 0.16 ± 0.10 0.13 ± 0.15 Grand mean 24.66 ± 1.73 1.94 ± 0.18 1.38 ± 0.11 0.35 ± 0.07 0.032 ± 0.01 0.218 ± 0.04 0.222 ± 0.04 0.731 ± 0.09 N = No. of alleles, N a = No. of different alleles, N e = No. of effective alleles, I = Information Index, H o= Observed heterozygosity, H e= Expected heterozygosity, u H e= Unbiased heterozygosity, PIC= Polymorphic Information Content, F=Fixation Index 3.3 Population structure STRUCTURE analysis supported K = 2 as the most probable number of genetic clusters among the 50 genotypes. Population 1 comprised 31 genotypes, Population 2 comprised 18 genotypes, and one genotype (CHFRM28) showed admixed ancestry between the two clusters (Table 3 ) and the STRUCTURE bar plot illustrating membership coefficients is presented in Fig. 8 . The Neighbour-Joining dendrogram based on Nei’s genetic distance clearly separated the two main groups (Fig. 9 ), and PCoA also placed genotypes into two clusters in multivariate space (Fig. 10). AMOVA showed that 63% of the genetic variation occurred among populations, 32% among individuals within populations, and only 4% within individuals. This distribution indicates that most genetic variation is structured at the population level, consistent with strong subdivision and limited gene exchange. Estimates of population differentiation and gene flow further supported this pattern. The overall Fst value was 0.517, indicating very high genetic differentiation among populations, while gene flow (Nm = 0.815) was lower than the threshold generally required to counteract genetic drift. Population 1 harboured six private alleles, whereas Population 2 had three, suggesting that Population 1 may be an important reservoir of unique genetic variants. Figure 10 Principal coordinate analysis (PCoA) of 50 R. mechukae genotypes based on SSR markers 4 Discussion 4.1 Genetic diversity and population structure This study provides the first molecular evidence of population genetic structure in R. mechukae , revealing a combination of moderate species-level diversity and strong population subdivision. The presence of two well-defined genetic clusters with limited gene flow reflects the narrow distribution and patchy habitat of R. mechukae in the Mechuka landscape. The overall diversity parameters observed here are lower than those reported for several other Rhododendron species, including R. longipedicellatum , R. simsii , R. pudingense , and R. rex subsp. rex , where higher heterozygosity or greater within-population variation has been documented (Cao et al., 2022 ; Wang et al., 2019 ; He et al., 2024 ; Zhang et al., 2020 ). 4.2 Inbreeding and heterozygote deficiency The combination of very low observed heterozygosity and moderate expected heterozygosity indicates pronounced deviations from Hardy-Weinberg equilibrium. The high fixation index (mean F = 0.731) suggests strong inbreeding, likely driven by small effective population sizes, geographic isolation, and limited pollen and seed dispersal (Frankham, 2005 ).The absence of heterozygotes at several loci may reflect founder effects or strong drift in small, isolated populations (Frankham, 2005 ). Such homozygosity excess can reduce fitness and adaptive potential, increasing the risk of local extinction (Reed and Frankham, 2003 ; Frankham, 2005 ).Compared with congeners for which moderate differentiation and higher within-population variation have been reported, R. mechukae shows much stronger spatial structuring, emphasizing its vulnerability in a restricted and fragmented habitat (He et al., 2024 ; Cao et al., 2022 ; Frankham, 2005 ) 4.3 Conservation implications The strong genetic differentiation and low gene flow among populations of R. mechukae imply that each population should be treated as a distinct management unit. Population 1, which harbours higher diversity and more private alleles, should be prioritized as a key reservoir of adaptive genetic variation.Restoring or maintaining habitat connectivity could promote gene flow and help counteract drift, but the current levels of inbreeding suggest that some populations may already be experiencing reduced viability (Frankham, 2005 ). Compared with other Rhododendron species that show higher within-population variation and lower Fst, R. mechukae appears to be particularly affected by habitat fragmentation and narrow ecological amplitude, underscoring the urgency of targeted conservation measures (Torres-Díaz et al., 2021 ; Johnson and Molano-Flores, 2023 ; Cao et al., 2022 ; He et al., 2024 ). 5 Conclusions This study demonstrates that R. mechukae faces serious genetic challenges despite retaining moderate overall diversity. Extreme population fragmentation, high inbreeding, and restricted gene flow have produced strong genetic structuring and severe heterozygote deficiency. The existence of two distinct genetic lineages may reflect adaptation to local environmental conditions, but continued erosion of genetic variation threatens the long-term viability of the species. Effective conservation of R. mechukae will require integrated strategies that include strict protection of existing habitats, improvement of landscape connectivity, and active genetic management where necessary. The baseline information generated here provides a foundation for designing such interventions and highlights the importance of incorporating genetic data into conservation planning for endemic Himalayan species. Future work should focus on high-resolution genomic approaches such as single nucleotide polymorphism (SNP) genotyping to identify adaptive variation and detect fine-scale population structure. Studies on reproductive biology, including pollination ecology and seed dispersal, are needed to clarify the mechanisms limiting gene flow. Ecological niche modelling under current and projected climate scenarios could help predict future habitat suitability and guide potential assisted migration. Comparative studies with other co-occurring Rhododendron species would also help place the genetic status of R. mechukae in a broader phylogeographic and conservation context. Declarations Data statement The data that support the findings of this study are available from the corresponding author upon reasonable request Acknowledgements The authors gratefully acknowledge Central Agricultural University, Imphal, Manipur, for institutional support. References Bharali S, Paul A, Khan ML (2013) Population status of Rhododendron mechukae – a newly recorded endemic species from Eastern Himalaya, India. J Biodivers Manag For 2(3):5–10 Cao Y, Ma Y, Li Z, Liu X, Liu D, Qu S, Ma H (2022) Genetic diversity and population structure of Rhododendron longipedicellatum , an endangered species. Trop Conserv Sci 15:19400829221078112 Choudhary S, Thakur S, Saini RG, Bhardwaj P (2014) Development and characterization of genomic microsatellite markers in Rhododendron arboreum . Conserv Genet Resour 6(4):1–4 De Riek J, Calsyn E, Everaert I, Van Bockstaele E, De Loose M (2001) AFLP based alternatives for the assessment of distinctness, uniformity and stability of sugar beet varieties. Theor Appl Genet 103(8):1254–1265 Doyle JJ, Doyle JL (1993) Isolation of plant DNA from fresh tissue. Focus 12:13–15 Earl DA, VonHoldt BM (2012) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4(2):359–361 Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14(8):2611–2620 Excoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131(2):479–491 Frankham R (2005) Genetics and extinction. Biol Conserv 126(2):131–140 He S, Yuan C, Zhang P, Wang H, Luo D, Dai X (2024) Characteristics of genetic diversity in different populations of Guizhou endemic plant Rhododendron pudingense based on microsatellite markers. BMC Plant Biol 24(1):77 Jiajia L, Muhammad A, Dongdong D, Xin H, Qianwen G, Fan Y (2023) Diversity of plant communities in different habitats and distinct methanotrophic communities. Rhizosphere 26:100690 Johnson SA, Molano-Flores B (2023) Is the endangered species act living to its full potential? Reassessment of the conservation status and recovery of Macbridea alba Chapm. Front Conserv Sci 4:1116848 Kameyama Y, Isagi Y, Nakagoshi N (2002) Relatedness structure in Rhododendron metternichii var. hondoense revealed by microsatellite analysis. Mol Ecol 11(3):519–527 Mao AA, Bhaumik M, Paul A, Bharali S, Khan ML (2013) Rhododendron mechukae (Ericaceae), a new species from India. Edinb J Bot 70(1):57–60 Naito K, Isagi Y, Nakagoshi N (1998) Isolation and characterization of microsatellites of Rhododendron metternichii Sieb. et Zucc. var. hondoense Nakai. Mol Ecol 7:927–929 Nautiyal S, Kaechele H (2007) Conserving the Himalayan forests: approaches and implications of different conservation regimes. Biodivers Conserv 16(13):3737–3754 Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research. Bioinformatics 28(19):2537–2539 Perrier X, Jacquemoud-Collet JP (2006) DARwin software. http://darwin.cirad.fr/darwin (accessed on 28.05.2024) Pradhan BK, Dahal S, Nilson J, Lachungpa D (2015) A note on Rhododendron mekongense : a new species record from Sikkim Himalaya, India. J Am Rhododendron Soc 1:76–80 Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155(2):945–959 Reed DH, Frankham R (2003) Correlation between fitness and genetic diversity. Conserv Biol 17(1):230–237 Sharma H, Kumar P, Singh A, Aggarwal K, Roy J, Sharma V, Rawat S (2020) Development of polymorphic EST-SSR markers and their applicability in genetic diversity evaluation in Rhododendron arboreum . Mol Biol Rep 47(4):2447–2457 Torres-Díaz C, Ruiz E, González F, Fuentes G, Cavieres LA (2021) Genetic diversity and population structure in fragmented populations of the Chilean endemic species Lupinus oreophilus . Front Plant Sci 12:612854 Wang J, Luo J, Ma Y, Tang S, Li J, Huang Y, Sun W (2019) Genetic diversity and population structure of Rhododendron simsii Planch. populations using molecular markers. Genet Resour Crop Evol 66(5):1145–1157 Zhang CQ, Ruan X, Zhang TT, Tong ZK, Pan B, Xu YM, Li H (2020) Genetic diversity and population structure of Rhododendron rex subsp. rex inferred from microsatellite markers and chloroplast DNA sequences. Front Plant Sci 11:954 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9681924","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":638414919,"identity":"2e6821ab-5244-4f6e-86b5-4a03fe975499","order_by":0,"name":"Sabbir Mondal","email":"","orcid":"","institution":"College of Horticulture \u0026 Forestry","correspondingAuthor":false,"prefix":"","firstName":"Sabbir","middleName":"","lastName":"Mondal","suffix":""},{"id":638414920,"identity":"1fb70dfe-30a6-40ea-a379-1390ea0730af","order_by":1,"name":"Shivani Dobhal","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYDACCcYGCMkOog0sSNHCcwCkRYIYLRCKsUEiAYmLD8jPbm6T+LnDQrZf8vnVDT8KJBj427sT8GoxuHOwTbL3jITxzNk5ZTd7gA6TOHN2A34tEonNBrxtEokbbuek3eABajGQyMWvRX5GYrPhX5CWm2fSbv4hRgvDjcTGx2BbbrAfu02ULQYgLbJtQL/05LDdljGQ4CHoF/kZ6Q8Ovm2rk+1nP/7s5ps/NnL87b0EHIYAPAZgkljlIMD+gBTVo2AUjIJRMIIAACnISdP93SG7AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-7710-2951","institution":"COLLEGE OF HORTICULTURE \u0026 FORESTRY CENTRAL AGRICULTURAL UNIVERSITY","correspondingAuthor":true,"prefix":"","firstName":"Shivani","middleName":"","lastName":"Dobhal","suffix":""},{"id":638414921,"identity":"f0b92d49-bf71-42ec-bc99-5fb434cf8af5","order_by":2,"name":"Siddhartha Singh","email":"","orcid":"","institution":"COLLEGE OF HORTICULTURE \u0026 FORESTRY CENTRAL AGRICULTURAL UNIVERSITY","correspondingAuthor":false,"prefix":"","firstName":"Siddhartha","middleName":"","lastName":"Singh","suffix":""},{"id":638414922,"identity":"788c90a4-e414-4986-a299-4ced341659fd","order_by":3,"name":"Tisu Tayeng","email":"","orcid":"","institution":"COLLEGE OF HORTICULTURE \u0026 FORESTRY CENTRAL AGRICULTURAL UNIVERSITY","correspondingAuthor":false,"prefix":"","firstName":"Tisu","middleName":"","lastName":"Tayeng","suffix":""},{"id":638414923,"identity":"0154bda7-c1b7-4f83-a175-467e79f8182c","order_by":4,"name":"T S Mehra","email":"","orcid":"","institution":"COLLEGE OF HORTICULTURE \u0026 FORESTRY CENTRAL AGRICULTURAL UNIVERSITY","correspondingAuthor":false,"prefix":"","firstName":"T","middleName":"S","lastName":"Mehra","suffix":""}],"badges":[],"createdAt":"2026-05-11 15:51:04","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9681924/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9681924/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109205361,"identity":"f4f5b503-dd4c-4cb5-973a-baf9ad1d10f3","added_by":"auto","created_at":"2026-05-13 15:04:26","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":40647,"visible":true,"origin":"","legend":"\u003cp\u003ePopulations of \u003cem\u003eRhododendron mechukae\u003c/em\u003e in natural stands at Mechuka.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9681924/v1/2a8ab90e476f577b81472fb6.jpg"},{"id":109167620,"identity":"c9a69965-7823-4aa0-b118-36b43a68da2c","added_by":"auto","created_at":"2026-05-13 08:28:49","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":390401,"visible":true,"origin":"","legend":"\u003cp\u003eTaxonomic characters of \u003cem\u003eR. mechukae\u003c/em\u003e: (A) leaf; (B) rufous abaxial leaf surface; (C) bark; (D) cone; (E) pollen under high magnification; (F) pollen grains in microscopic field; (G) transverse section of gynoecium under high magnification; (H) transverse section of gynoecium in microscopic field.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9681924/v1/e0dbe562d86e947d6e53d0dd.jpg"},{"id":109167617,"identity":"dd11561c-530f-45b8-8c0e-676043850cbe","added_by":"auto","created_at":"2026-05-13 08:28:48","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":41446,"visible":true,"origin":"","legend":"\u003cp\u003eFlowers of \u003cem\u003eR. mechukae\u003c/em\u003e: (A) carpel and numerous stamens; (B) sepals dissected from main cluster; (C) flower with cone.\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9681924/v1/9c0fc056a9107195e32c3377.jpg"},{"id":109167619,"identity":"56ee7024-91b3-447c-8848-3e103d5af648","added_by":"auto","created_at":"2026-05-13 08:28:49","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":33035,"visible":true,"origin":"","legend":"\u003cp\u003eSampling locations \u003cem\u003eof R. mechukae\u003c/em\u003e populations in Mechuka region, Arunachal Pradesh, India\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9681924/v1/68911506a760e326babaa3f9.jpg"},{"id":109167639,"identity":"cbb07c9c-23f9-41a4-95ee-a8e2ec015042","added_by":"auto","created_at":"2026-05-13 08:28:53","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":31844,"visible":true,"origin":"","legend":"\u003cp\u003eSSR11 amplification profile in \u003cem\u003eR. mechukae\u003c/em\u003e genotypes on 2% agarose gel.\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9681924/v1/ea9539ba425380fef01de41e.jpg"},{"id":109167610,"identity":"2a1ef2cb-17a9-4cea-a9ea-591a509289e1","added_by":"auto","created_at":"2026-05-13 08:28:47","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":29880,"visible":true,"origin":"","legend":"\u003cp\u003eSSR15 amplification profile in \u003cem\u003eR. mechukae\u003c/em\u003e genotypes on 2% agarose gel.\u003c/p\u003e","description":"","filename":"Picture6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9681924/v1/4fb3a3cb2efa09ce03e63104.jpg"},{"id":109167821,"identity":"718f2d7f-bdd4-4c60-8b33-bbc06f027698","added_by":"auto","created_at":"2026-05-13 08:30:00","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":13083,"visible":true,"origin":"","legend":"\u003cp\u003eΔK values used to infer the most likely number of genetic clusters (K) in 50 \u003cem\u003eR. mechukae\u003c/em\u003e genotypes.\u003c/p\u003e","description":"","filename":"Picture7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9681924/v1/58873c6a87065aeee9c0cf8f.jpg"},{"id":109167635,"identity":"18a246f5-7448-4ddd-bd9b-8ae2ed07fd41","added_by":"auto","created_at":"2026-05-13 08:28:52","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":30068,"visible":true,"origin":"","legend":"\u003cp\u003eSTRUCTURE bar plot showing individual membership coefficients for K = 2 clusters: (A) progenies in original order; (B) progenies sorted by inferred ancestry (Q).\u003c/p\u003e","description":"","filename":"Picture8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9681924/v1/987918736ec3b8df6cc2ba7a.jpg"},{"id":109167612,"identity":"fe3b8ffc-56a5-4d3f-99ec-dafde6e68d60","added_by":"auto","created_at":"2026-05-13 08:28:47","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":26859,"visible":true,"origin":"","legend":"\u003cp\u003eNeighbour‑Joining dendrogram of 50 \u003cem\u003eR. mechukae\u003c/em\u003e genotypes based on SSR data.\u003c/p\u003e","description":"","filename":"Picture9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9681924/v1/d9b0df52343698840bf0f118.jpg"},{"id":109167640,"identity":"c690dd42-dd51-40cb-870a-96b3916f9ecc","added_by":"auto","created_at":"2026-05-13 08:28:53","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":30078,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal coordinate analysis (PCoA) of 50 \u003cem\u003eR. mechukae\u003c/em\u003e genotypes based on SSR markers\u003c/p\u003e","description":"","filename":"Picture10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9681924/v1/6cf6c5ebaf05406fd7e1143c.jpg"},{"id":109207399,"identity":"b237cd96-fc05-4aa7-8ec4-6e06adb7adb6","added_by":"auto","created_at":"2026-05-13 15:19:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1010593,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9681924/v1/a9f2d46b-8eb4-4168-ba19-017817882605.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eStudy on population genetics of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eRhododendron mechukae\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e, an endemic species of the Eastern Himalayas\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eThe Eastern Himalayas are a globally important biodiversity hotspot that supports exceptional floristic diversity but is increasingly threatened by anthropogenic pressures and climate change (Nautiyal and Kaechele, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).The genus \u003cem\u003eRhododendron\u003c/em\u003e (Ericaceae), with more than 1,200 species worldwide, reaches its highest diversity in this region, and Asian mountains harbour approximately 90% of wild \u003cem\u003eRhododendron\u003c/em\u003e populations (Pradhan et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).These species often function as keystone taxa in fragile high-altitude ecosystems, stabilizing slopes, providing habitat, and supporting complex ecological interactions (Bharali et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eRhododendron mechukae\u003c/em\u003e, recently described from Arunachal Pradesh, India, is a narrowly distributed endemic species restricted to temperate forests in the Mechuka region (Mao et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).It is characterized by rough brownish peeling bark, leaves with rufous-brown indumentum on the abaxial surface, short pedicels up to 1.8 cm long, and early flowering from February to March (Mao et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).Its distribution is highly localized, and populations are under strong pressure from habitat degradation and timber extraction (Mao et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Bharali et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConserving endangered plant species is essential for maintaining biological diversity and ecosystem stability (Torres-D\u0026iacute;az et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Genetic diversity within and among populations strongly influences long-term survival, adaptability, and resilience to environmental change (Jiajia et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePopulations with reduced genetic variation are more vulnerable to extinction because of inbreeding depression, genetic drift, and limited adaptive potential (Reed and Frankham, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Frankham, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Johnson and Molano-Flores, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Characterizing genetic variation within and between populations is therefore crucial for designing effective conservation strategies for small and fragmented populations (Frankham, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Johnson and Molano-Flores, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite its conservation importance, no molecular or genomic data were previously available for \u003cem\u003eR. mechukae\u003c/em\u003e, leaving a major gap in evidence-based conservation planning.\u003c/p\u003e \u003cp\u003eThe present study addresses this gap by providing the first population-level genetic assessment of \u003cem\u003eR. mechukae\u003c/em\u003e using microsatellite markers, with the aims of quantifying genetic diversity, resolving population structure, and generating baseline information for conservation management.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"2 Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study area and sample collection\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eField surveys were conducted in the natural distribution range of \u003cem\u003eR. mechukae\u003c/em\u003e in Mechuka, Shi Yomi district, Arunachal Pradesh, India (28\u0026deg;39\u0026prime;53.70\u0026Prime; N, 93\u0026deg;59\u0026prime;08.70\u0026Prime; E) at elevations of 2,000\u0026ndash;3,500 m. A total of 50 individual genotypes were randomly sampled from five populations (Segong, Hanuman Camp, Yorlung, Pogor, and Lamang) using linear transects, and the sampling locations are presented in Fig.\u0026nbsp;4. GPS coordinates were recorded for each sampled plant, and three healthy leaves per genotype were collected during September-March 2024 following the original taxonomic description. Leaf samples were rapidly desiccated in silica gel and stored at \u0026minus;\u0026thinsp;80\u0026deg;C until DNA extraction.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eFigure\u0026nbsp;4 Sampling locations \u003cem\u003eof R. mechukae\u003c/em\u003e populations in Mechuka region, Arunachal Pradesh, India\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 DNA extraction and quantification\u003c/h2\u003e \u003cp\u003eGenomic DNA was extracted using a modified cetyltrimethylammonium bromide (CTAB) method following Doyle and Doyle (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). Approximately 2 g of leaf tissue was ground to a fine powder in liquid nitrogen using a pre-cooled mortar and pestle. The powder was mixed with CTAB extraction buffer (100 mM Tris\u0026ndash;HCl, pH 8.0; 20 mM EDTA; 1.42 M NaCl; 5 mM ascorbic acid; 3% CTAB; 3% polyvinylpyrrolidone) and incubated at 55\u0026deg;C for 45 min. After extraction with chloroform:isoamyl alcohol (24:1) and precipitation with isopropanol, DNA pellets were dissolved in sterile water and treated with RNase. DNA concentration and purity were measured spectrophotometrically using A260/A280 ratios, with values around 1.8 indicating acceptable purity. DNA quality was further checked on 0.8% agarose gels, which showed intact high-molecular-weight bands with minimal degradation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 SSR marker analysis\u003c/h2\u003e \u003cp\u003eTwenty SSR primer pairs previously developed for related \u003cem\u003eRhododendron\u003c/em\u003e species were initially screened (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). PCR amplification was performed in 15 \u0026micro;l reactions containing 1.9 \u0026micro;l PCR buffer with MgCl2, 1.5 \u0026micro;l dNTPs, 0.45 \u0026micro;l of each primer, 0.5 \u0026micro;l Taq DNA polymerase, 8.7 \u0026micro;l molecular-grade water, and 1.5 \u0026micro;l template DNA. Thermal cycling consisted of an initial denaturation at 94\u0026deg;C for 3 min; 35 cycles of 94\u0026deg;C for 1 min, locus-specific annealing temperature for 1 min, and 72\u0026deg;C for 1 min; followed by a final extension at 72\u0026deg;C for 8 min. PCR products were separated on 2% agarose gels, visualized under UV light, and scored as present (1) or absent (0). Polymorphic information content (PIC) was calculated as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:PIC=1-\\sum\\:{P}_{i}^{2}\\)\u003c/span\u003e\u003c/span\u003e, where \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{P}_{i}\\)\u003c/span\u003e\u003c/span\u003e is the frequency of the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:i\\)\u003c/span\u003e\u003c/span\u003eth allele at a locus (De Riek et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrimer pairs used in the study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS.no.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLocus\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCode\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMotif/SSR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eForward Primer (5'-3')\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReverse Primer (5'-3')\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eReferences\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRHM_MS13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(CTT)5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: TCGATCTCCACCTACAAACTA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: ACAAAGGCCTTGAACATCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSharma et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(TC)16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: GGAAAGTGTGGGTGTTAGTGC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: TTGAGAGATGGCGAGAGAGAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChoudhary et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRE101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(AG)16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: GACGGGAATGAGCAAGGTTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: CTTCAATTCTGCAAGCCCGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChoudhary et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRA430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(TC)10(CT)6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: GCGTAAATCGAGTTCGGAAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: CTCTCTCTAATCGAATTCCCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChoudhary et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRF87A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(AG)10(AG)10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: TGGGTCATGTTCTGGAAGGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: TGAACTAACCCTAGCCACACT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChoudhary et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRA324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(AG)8(GA)8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: GCGTACAACATGCCCAAATA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: CCCTGTTCTCATTGCTCACA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChoudhary et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRF304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(AG)13(GT)9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: TCCTAGGGTTTGTTCGCAAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: TGCTAGCGATTTCCTAGGGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChoudhary et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRA272A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(CT)8(CT)11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: GCCCCGGTGACTCATAAAAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: TGGTACAAGTGGGACACGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChoudhary et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(GA)13(AG)12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: CCCTACTTCTTTCATCACATACAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: CAACTCCGGTCATTTTTGGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChoudhary et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRA267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(GA)11(AG)10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: ACGGAGAAGCAGTGAGCATT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: TGCACAGGAACACCCAATAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChoudhary et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRA346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(TC)9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: CGGAGCAAGCTCTCTTATCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: CCTCTCCTGTGTAGCAAGTCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChoudhary et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRM1D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(CT)17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: ATCTGGAGGCCATTGGTAGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: TATTGGGTCCGATGACAGAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eKameyama et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2002\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRM2D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(CT)16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: ATGTGTTTCGTTGCTACTGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: ATGGTTGGTTTGTTTTCCTA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNaito \u003cem\u003eet al\u003c/em\u003e.1998\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRM3D4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(CT)7(CT)19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: CTCCCAACAAACAAATCCAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: CACCGAACGAAGACACTCAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNaito \u003cem\u003eet al\u003c/em\u003e.1998\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRM9D6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(GA)16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: CTCGCCTCCCAAAAGCAAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: CGTGTCCTCACCCCCGTAAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNaito \u003cem\u003eet al\u003c/em\u003e.1998\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRA470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(GA)14(AG)10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: AGGGACAAGAAGAAGCCACA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: TCGCGCTTATTACAGCTCTTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChoudhary et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRA254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(CT)16(CT)10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: AGTAGCAACACCCACACACT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: GGAGGGGCTGTAGTCTGATT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChoudhary et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRA321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(GA)9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: AGAGATGGGTTTGTGTAAAGTCTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: TATTTCGCTGCCACCCTAAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChoudhary et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRA351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(AG)12(AG)11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: TGTCGCTCTCTCACTGATCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: TTTGTAGTTTTCCCGTGTCCTT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChoudhary et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR-20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(AG)10(AG)13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF: AGCAGCAACAATGGTGTCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eR: TCTAGAAGGCCTCCCATTCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChoudhary et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Population genetic analysis\u003c/h2\u003e \u003cp\u003eGenetic diversity parameters, including number of alleles (Na), effective number of alleles (Ne), Shannon\u0026rsquo;s information index (I), observed heterozygosity (Ho), expected heterozygosity (He), and fixation index (F), were estimated using GenAlEx v6.5 (Peakall and Smouse, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).Population structure was analysed using STRUCTURE v2.3.4 with a Bayesian Markov chain Monte Carlo (MCMC) approach (Pritchard et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2000\u003c/span\u003e).Ten independent runs were performed for K values from 1 to 10, each with a burn-in of 100,000 iterations and 200,000 MCMC repetitions.The most likely number of clusters (K) was determined using Structure Harvester based on the ΔK method (Earl and VonHoldt, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Evanno et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAMOVA was conducted to partition genetic variance among populations, among individuals within populations, and within individuals (Excoffier et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1992\u003c/span\u003e).Wright's F-statistics (Fis, Fit, Fst) and gene flow (Nm) were calculated to assess population differentiation and migration. Genetic relationships among populations were visualized using UPGMA/Neighbour-Joining trees constructed in DARwin v6.0 and principal coordinate analysis (PCoA) in GenAlEx (Perrier and Jacquemoud-Collet, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Peakall and Smouse, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 SSR marker polymorphism\u003c/h2\u003e \u003cp\u003eOf the 20 SSR primer pairs tested, nine (45%) produced clear and reproducible amplification across all samples and were polymorphic. These nine markers (SSR1, SSR3, SSR9, SSR10, SSR11, SSR13, SSR15, SSR17, SSR18) yielded alleles in the size range 150\u0026ndash;310 bp, and representative amplification profiles for SSR11 and SSR15 are shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003e, respectively. PIC values ranged from 0.231 (SSR13) to 0.540 (SSR11), with an average of 0.390, indicating moderate to high informativeness for population genetic analysis (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Genetic diversity assessment\u003c/h2\u003e \u003cp\u003eGenetic diversity estimates revealed moderate allelic richness but very low heterozygosity. The mean number of different alleles (Na) was 1.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18, ranging from 1.50 (SSR3, SSR10) to 3.00 (SSR9). The effective number of alleles (Ne) varied between 1.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10 (SSR10) and 1.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92 (SSR11), with a mean of 1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11. Shannon\u0026rsquo;s information index (I) ranged from 0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 (SSR18) to 0.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 (SSR15), with an overall mean of 0.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07. Observed heterozygosity (Ho) was extremely low, ranging from 0.00 for five loci (SSR10, SSR11, SSR13, SSR15, SSR17) to 0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 (SSR18), with a grand mean of 0.032\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01. In contrast, expected heterozygosity (He) ranged from 0.00 (SSR17) to 0.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 (SSR15), with a mean of 0.218\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04. Fixation indices (F) were high and positive for most loci, ranging from 0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15 (SSR18) to 1.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00, with a mean of 0.731\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09, indicating strong heterozygote deficiency and a predominance of homozygotes (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of successfully amplified primers with allele size and PIC\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocus\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCode\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMotif/SSR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eForward Primer (5'-3')\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReverse Primer (5'-3')\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAllele size (bp)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTm\u0026deg;C\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePIC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRHM_MS13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSSR-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(CTT)5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF: TCGATCTCCACCTACAAACTA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR: ACAAAGGCCTTGAACATCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e235\u0026ndash;270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e55.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.371\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRE101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSSR-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(AG)16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF: GACGGGAATGAGCAAGGTTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR: CTTCAATTCTGCAAGCCCGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e165\u0026ndash;181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e50.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.373\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSSR-9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(GA)13(AG)12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF: CCCTACTTCTTTCATCACATACAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR: CAACTCCGGTCATTTTTGGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e245\u0026ndash;275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e59.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.431\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRA267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSSR-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(GA)11(AG)10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF: ACGGAGAAGCAGTGAGCATT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR: TGCACAGGAACACCCAATAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e205\u0026ndash;225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e58.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.366\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRA346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSSR-11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(TC)9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF: CGGAGCAAGCTCTCTTATCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR: CCTCTCCTGTGTAGCAAGTCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e290\u0026ndash;310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e60.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.540\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRM2D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSSR-13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(CT)16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF: ATGTGTTTCGTTGCTACTGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR: ATGGTTGGTTTGTTTTCCTA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e165\u0026ndash;181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e58.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRM9D6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSSR-15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(GA)16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF: CTCGCCTCCCAAAAGCAAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR: CGTGTCCTCACCCCCGTAAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e250\u0026ndash;310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e55.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.471\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRA254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSSR-17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(CT)16(CT)10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF: AGTAGCAACACCCACACACT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR: GGAGGGGCTGTAGTCTGATT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e150\u0026ndash;190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e57.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.356\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRA321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSSR-18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(GA)9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF:AGAGATGGGTTTGTGTAAAGTCTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR: TATTTCGCTGCCACCCTAAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e175\u0026ndash;190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e59.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.372\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssessment of genetic diversity characters for 9 SSR molecular markers on 50 genotypes of \u003cem\u003eR. mechukae\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimer code\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003ea\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003ee\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eH\u003c/em\u003eo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eH\u003c/em\u003ee\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eu\u003cem\u003eH\u003c/em\u003ee\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSSR- 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e24.50\u0026thinsp;\u0026plusmn;\u0026thinsp;7.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSSR- 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e24.50\u0026thinsp;\u0026plusmn;\u0026thinsp;6.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSSR- 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e24.00\u0026thinsp;\u0026plusmn;\u0026thinsp;8.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.00\u0026thinsp;\u0026plusmn;\u0026thinsp;1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSSR- 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e24.50\u0026thinsp;\u0026plusmn;\u0026thinsp;7.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSSR- 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e25.00\u0026thinsp;\u0026plusmn;\u0026thinsp;7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSSR- 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e25.00\u0026thinsp;\u0026plusmn;\u0026thinsp;7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSSR- 15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e25.00\u0026thinsp;\u0026plusmn;\u0026thinsp;7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e0.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSSR- 17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e24.50\u0026thinsp;\u0026plusmn;\u0026thinsp;6.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e0.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSSR- 18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e25.00\u0026thinsp;\u0026plusmn;\u0026thinsp;7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrand mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e24.66\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.032\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.218\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e0.222\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.731\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eN\u0026thinsp;=\u0026thinsp;No. of alleles, \u003cem\u003eN\u003c/em\u003ea\u0026thinsp;=\u0026thinsp;No. of different alleles, \u003cem\u003eN\u003c/em\u003ee\u0026thinsp;=\u0026thinsp;No. of effective alleles, \u003cem\u003eI\u003c/em\u003e\u0026thinsp;=\u0026thinsp;Information Index, \u003cem\u003eH\u003c/em\u003eo= Observed heterozygosity, \u003cem\u003eH\u003c/em\u003ee= Expected heterozygosity, u\u003cem\u003eH\u003c/em\u003ee= Unbiased heterozygosity, PIC= Polymorphic Information Content, F=Fixation Index\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Population structure\u003c/h2\u003e \u003cp\u003eSTRUCTURE analysis supported K\u0026thinsp;=\u0026thinsp;2 as the most probable number of genetic clusters among the 50 genotypes. Population 1 comprised 31 genotypes, Population 2 comprised 18 genotypes, and one genotype (CHFRM28) showed admixed ancestry between the two clusters (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) and the STRUCTURE bar plot illustrating membership coefficients is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe Neighbour-Joining dendrogram based on Nei\u0026rsquo;s genetic distance clearly separated the two main groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e9\u003c/span\u003e), and PCoA also placed genotypes into two clusters in multivariate space (Fig.\u0026nbsp;10). AMOVA showed that 63% of the genetic variation occurred among populations, 32% among individuals within populations, and only 4% within individuals. This distribution indicates that most genetic variation is structured at the population level, consistent with strong subdivision and limited gene exchange. Estimates of population differentiation and gene flow further supported this pattern. The overall Fst value was 0.517, indicating very high genetic differentiation among populations, while gene flow (Nm\u0026thinsp;=\u0026thinsp;0.815) was lower than the threshold generally required to counteract genetic drift. Population 1 harboured six private alleles, whereas Population 2 had three, suggesting that Population 1 may be an important reservoir of unique genetic variants.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFigure\u0026nbsp;10 Principal coordinate analysis (PCoA) of 50 \u003cem\u003eR. mechukae\u003c/em\u003e genotypes based on SSR markers\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Genetic diversity and population structure\u003c/h2\u003e \u003cp\u003eThis study provides the first molecular evidence of population genetic structure in \u003cem\u003eR. mechukae\u003c/em\u003e, revealing a combination of moderate species-level diversity and strong population subdivision.\u003c/p\u003e \u003cp\u003eThe presence of two well-defined genetic clusters with limited gene flow reflects the narrow distribution and patchy habitat of \u003cem\u003eR. mechukae\u003c/em\u003e in the Mechuka landscape.\u003c/p\u003e \u003cp\u003eThe overall diversity parameters observed here are lower than those reported for several other \u003cem\u003eRhododendron\u003c/em\u003e species, including \u003cem\u003eR. longipedicellatum\u003c/em\u003e, \u003cem\u003eR. simsii\u003c/em\u003e, \u003cem\u003eR. pudingense\u003c/em\u003e, and \u003cem\u003eR. rex\u003c/em\u003e subsp. \u003cem\u003erex\u003c/em\u003e, where higher heterozygosity or greater within-population variation has been documented (Cao et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; He et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Inbreeding and heterozygote deficiency\u003c/h2\u003e \u003cp\u003eThe combination of very low observed heterozygosity and moderate expected heterozygosity indicates pronounced deviations from Hardy-Weinberg equilibrium.\u003c/p\u003e \u003cp\u003eThe high fixation index (mean F\u0026thinsp;=\u0026thinsp;0.731) suggests strong inbreeding, likely driven by small effective population sizes, geographic isolation, and limited pollen and seed dispersal (Frankham, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).The absence of heterozygotes at several loci may reflect founder effects or strong drift in small, isolated populations (Frankham, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Such homozygosity excess can reduce fitness and adaptive potential, increasing the risk of local extinction (Reed and Frankham, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Frankham, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).Compared with congeners for which moderate differentiation and higher within-population variation have been reported, \u003cem\u003eR. mechukae\u003c/em\u003e shows much stronger spatial structuring, emphasizing its vulnerability in a restricted and fragmented habitat (He et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Cao et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Frankham, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Conservation implications\u003c/h2\u003e \u003cp\u003eThe strong genetic differentiation and low gene flow among populations of \u003cem\u003eR. mechukae\u003c/em\u003e imply that each population should be treated as a distinct management unit.\u003c/p\u003e \u003cp\u003ePopulation 1, which harbours higher diversity and more private alleles, should be prioritized as a key reservoir of adaptive genetic variation.Restoring or maintaining habitat connectivity could promote gene flow and help counteract drift, but the current levels of inbreeding suggest that some populations may already be experiencing reduced viability (Frankham, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Compared with other \u003cem\u003eRhododendron\u003c/em\u003e species that show higher within-population variation and lower Fst, \u003cem\u003eR. mechukae\u003c/em\u003e appears to be particularly affected by habitat fragmentation and narrow ecological amplitude, underscoring the urgency of targeted conservation measures (Torres-D\u0026iacute;az et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Johnson and Molano-Flores, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Cao et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; He et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"5 Conclusions","content":"\u003cp\u003eThis study demonstrates that \u003cem\u003eR. mechukae\u003c/em\u003e faces serious genetic challenges despite retaining moderate overall diversity. Extreme population fragmentation, high inbreeding, and restricted gene flow have produced strong genetic structuring and severe heterozygote deficiency. The existence of two distinct genetic lineages may reflect adaptation to local environmental conditions, but continued erosion of genetic variation threatens the long-term viability of the species. Effective conservation of \u003cem\u003eR. mechukae\u003c/em\u003e will require integrated strategies that include strict protection of existing habitats, improvement of landscape connectivity, and active genetic management where necessary. The baseline information generated here provides a foundation for designing such interventions and highlights the importance of incorporating genetic data into conservation planning for endemic Himalayan species.\u003c/p\u003e \u003cp\u003eFuture work should focus on high-resolution genomic approaches such as single nucleotide polymorphism (SNP) genotyping to identify adaptive variation and detect fine-scale population structure. Studies on reproductive biology, including pollination ecology and seed dispersal, are needed to clarify the mechanisms limiting gene flow. Ecological niche modelling under current and projected climate scenarios could help predict future habitat suitability and guide potential assisted migration. Comparative studies with other co-occurring \u003cem\u003eRhododendron\u003c/em\u003e species would also help place the genetic status of \u003cem\u003eR. mechukae\u003c/em\u003e in a broader phylogeographic and conservation context.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eData statement\u003c/h2\u003e \u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe authors gratefully acknowledge Central Agricultural University, Imphal, Manipur, for institutional support.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBharali S, Paul A, Khan ML (2013) Population status of \u003cem\u003eRhododendron mechukae\u003c/em\u003e \u0026ndash; a newly recorded endemic species from Eastern Himalaya, India. J Biodivers Manag For 2(3):5\u0026ndash;10\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCao Y, Ma Y, Li Z, Liu X, Liu D, Qu S, Ma H (2022) Genetic diversity and population structure of \u003cem\u003eRhododendron longipedicellatum\u003c/em\u003e, an endangered species. Trop Conserv Sci 15:19400829221078112\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChoudhary S, Thakur S, Saini RG, Bhardwaj P (2014) Development and characterization of genomic microsatellite markers in \u003cem\u003eRhododendron arboreum\u003c/em\u003e. Conserv Genet Resour 6(4):1\u0026ndash;4\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Riek J, Calsyn E, Everaert I, Van Bockstaele E, De Loose M (2001) AFLP based alternatives for the assessment of distinctness, uniformity and stability of sugar beet varieties. Theor Appl Genet 103(8):1254\u0026ndash;1265\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDoyle JJ, Doyle JL (1993) Isolation of plant DNA from fresh tissue. Focus 12:13\u0026ndash;15\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEarl DA, VonHoldt BM (2012) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4(2):359\u0026ndash;361\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEvanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14(8):2611\u0026ndash;2620\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eExcoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131(2):479\u0026ndash;491\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrankham R (2005) Genetics and extinction. Biol Conserv 126(2):131\u0026ndash;140\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHe S, Yuan C, Zhang P, Wang H, Luo D, Dai X (2024) Characteristics of genetic diversity in different populations of Guizhou endemic plant \u003cem\u003eRhododendron pudingense\u003c/em\u003e based on microsatellite markers. BMC Plant Biol 24(1):77\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJiajia L, Muhammad A, Dongdong D, Xin H, Qianwen G, Fan Y (2023) Diversity of plant communities in different habitats and distinct methanotrophic communities. Rhizosphere 26:100690\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohnson SA, Molano-Flores B (2023) Is the endangered species act living to its full potential? Reassessment of the conservation status and recovery of \u003cem\u003eMacbridea alba\u003c/em\u003e Chapm. Front Conserv Sci 4:1116848\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKameyama Y, Isagi Y, Nakagoshi N (2002) Relatedness structure in \u003cem\u003eRhododendron metternichii\u003c/em\u003e var. \u003cem\u003ehondoense\u003c/em\u003e revealed by microsatellite analysis. Mol Ecol 11(3):519\u0026ndash;527\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMao AA, Bhaumik M, Paul A, Bharali S, Khan ML (2013) \u003cem\u003eRhododendron mechukae\u003c/em\u003e (Ericaceae), a new species from India. Edinb J Bot 70(1):57\u0026ndash;60\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNaito K, Isagi Y, Nakagoshi N (1998) Isolation and characterization of microsatellites of \u003cem\u003eRhododendron metternichii\u003c/em\u003e Sieb. et Zucc. var. \u003cem\u003ehondoense\u003c/em\u003e Nakai. Mol Ecol 7:927\u0026ndash;929\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNautiyal S, Kaechele H (2007) Conserving the Himalayan forests: approaches and implications of different conservation regimes. Biodivers Conserv 16(13):3737\u0026ndash;3754\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research. Bioinformatics 28(19):2537\u0026ndash;2539\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePerrier X, Jacquemoud-Collet JP (2006) DARwin software. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://darwin.cirad.fr/darwin\u003c/span\u003e\u003cspan address=\"http://darwin.cirad.fr/darwin\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (accessed on 28.05.2024)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePradhan BK, Dahal S, Nilson J, Lachungpa D (2015) A note on \u003cem\u003eRhododendron mekongense\u003c/em\u003e: a new species record from Sikkim Himalaya, India. J Am Rhododendron Soc 1:76\u0026ndash;80\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155(2):945\u0026ndash;959\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReed DH, Frankham R (2003) Correlation between fitness and genetic diversity. Conserv Biol 17(1):230\u0026ndash;237\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSharma H, Kumar P, Singh A, Aggarwal K, Roy J, Sharma V, Rawat S (2020) Development of polymorphic EST-SSR markers and their applicability in genetic diversity evaluation in \u003cem\u003eRhododendron arboreum\u003c/em\u003e. Mol Biol Rep 47(4):2447\u0026ndash;2457\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTorres-D\u0026iacute;az C, Ruiz E, Gonz\u0026aacute;lez F, Fuentes G, Cavieres LA (2021) Genetic diversity and population structure in fragmented populations of the Chilean endemic species \u003cem\u003eLupinus oreophilus\u003c/em\u003e. Front Plant Sci 12:612854\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang J, Luo J, Ma Y, Tang S, Li J, Huang Y, Sun W (2019) Genetic diversity and population structure of \u003cem\u003eRhododendron simsii\u003c/em\u003e Planch. populations using molecular markers. Genet Resour Crop Evol 66(5):1145\u0026ndash;1157\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang CQ, Ruan X, Zhang TT, Tong ZK, Pan B, Xu YM, Li H (2020) Genetic diversity and population structure of \u003cem\u003eRhododendron rex\u003c/em\u003e subsp. \u003cem\u003erex\u003c/em\u003e inferred from microsatellite markers and chloroplast DNA sequences. Front Plant Sci 11:954\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Central Agricultural University Imphal Manipur ","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"population genetics, SSR markers, genetic diversity, conservation genetics, Eastern Himalayas, endangered species","lastPublishedDoi":"10.21203/rs.3.rs-9681924/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9681924/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study presents the first molecular analysis of \u003cem\u003eRhododendron mechukae\u003c/em\u003e, a critically endangered and narrowly distributed species endemic to Arunachal Pradesh in the Eastern Himalayas. Population genetic diversity was assessed using simple sequence repeat (SSR) markers across 50 genotypes sampled from natural populations in Mechuka, Shi Yomi district. Out of 20 SSR primer pairs screened, nine exhibited successful amplification with polymorphic information content (PIC) values ranging from 0.231 to 0.540. The effective number of alleles (Ne) averaged 1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11, Shannon\u0026rsquo;s information index (I) was 0.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07, and observed heterozygosity (Ho) was extremely low at 0.032\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01. STRUCTURE analysis revealed two distinct genetic clusters (K\u0026thinsp;=\u0026thinsp;2), with Population 1 showing higher genetic diversity (Na\u0026thinsp;=\u0026thinsp;2.333, He\u0026thinsp;=\u0026thinsp;0.333) than Population 2 (Na\u0026thinsp;=\u0026thinsp;1.556, He\u0026thinsp;=\u0026thinsp;0.103). Analysis of molecular variance (AMOVA) indicated that 63% of the total genetic variance occurred among populations, confirming strong genetic structuring. The mean fixation index (F\u0026thinsp;=\u0026thinsp;0.731\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09) indicated severe heterozygote deficiency and a high prevalence of homozygosity. These findings show that although \u003cem\u003eR. mechukae\u003c/em\u003e retains moderate genetic diversity at the species level, it faces pronounced vulnerability due to limited gene flow and population isolation, highlighting the need for urgent conservation interventions.\u003c/p\u003e","manuscriptTitle":"Study on population genetics of Rhododendron mechukae, an endemic species of the Eastern Himalayas","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-13 08:24:39","doi":"10.21203/rs.3.rs-9681924/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a8fe5b0a-47c1-493d-8e50-cbeead0d01a1","owner":[],"postedDate":"May 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":67947807,"name":"Forestry"}],"tags":[],"updatedAt":"2026-05-13T08:24:39+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-13 08:24:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9681924","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9681924","identity":"rs-9681924","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}