Genome-wide SSR markers in bottle gourd: development, characterization, utilization in assessment of genetic diversity of National Genebank of India and synteny with other related cucurbits

Lagenaria siceraria (Molina) Standley is an important cultivated crop with its immense importance in pharmaceutical industry and as vegetable. Its seed, root, stem, leaves, flower, and fruit are used as an ointment for ailment of various diseases throughout Asia. Despite its worldwide importance, informative co-dominant microsatellite markers in the bottle gourd crop are very restricted, impeding genetic improvement, cultivar identification, and phylogenetic studies. Next-generation sequencing has revolutionized the approaches for discovery, assessment, and validation of molecular markers. We conducted a genome-wide analysis, for developing SSR markers by utilizing restriction site-associated DNA sequencing (RAD-Seq) data obtained from NCBI. By performing in silico mining of microsatellite repeat motifs, we developed 45,066 perfect SSR markers. Of which 207 markers were successfully validated and 120 (57.97%) polymorphic primer pairs were utilized for an in-depth genetic diversity and population structure analysis of 96 accessions from the National Genebank of India. Tetranucleotide repeats (∼34.3%) were the most prevalent followed by trinucleotide repeats (∼30.73%), further 21.03%, 9.6%, and 4.3% of di-, penta-, and hexa-nucleotide repeats in the bottle gourd genome, respectively. Synteny of SSR markers on 11 bottle gourd linkage groups was correlated with the 7 chromosomes of cucumber (93.2%), 12 chromosomes of melon (87.4%), and 11 of watermelon (90.8%). The generated SSR markers provide a valuable tool for germplasm characterization, genetic linkage map construction, studying synteny, gene discovery, and for breeding in bottle gourd and other cucurbits species. Development of 45,066 perfect microsatellite markers as a valuable tool for marker assisted selection (MAS) in plant breeding.


Introduction
Bottle gourd (Lagenaria siceraria (Mol.) Standl.) (2n = 2x = 22), is an edible, medicinal container and a grafting stock plant cultivated all over the tropics (Heiser, 1979). The bottle gourd is known as one of the first crops to be cultivated (> 10,000 years ago) (Whitaker, 1971;Erickson et al. 2005) worldwide indicating its importance in agro-industry. High genetic variability exists in bottle gourd, especially in fruit size and shape (Emina et al. 2012). It is reported that bottle gourd is packed with various medical properties like anti-cancerous, cardio-protective (Fard et al. 2008), diuretic, purgative, and cooling effects (Badmanaban and Patel, 2010). It can also treat ulcers, pectoral cough, asthma, and other bronchial disorders (Upaganlawar and Balaraman, 2010). Its seed and fruit extracts (Prashant et al. 2014;Nidhi et al. 2017) exhibit a variety of pharmacological properties and are utilized in the pharmaceutical industry (Sakshi et al. 2015) as well as Ayurveda (Nidhi et al. 2017). Bottle gourd seed oil is also used in cosmetic industry for skin therapy, in cosmetics, and in treatment of Communicated by Izabela Pawłowicz. hyperplasia (Prashant et al. 2014). Bottle gourd fruit is used in craft industries as a raw material for the production of artifacts, musical instruments, and containers for food and beverages (Danieli and Lauren dCD, 2020). The commercial potential of the crop increases by understanding its fruit juice potential in reducing weight, to cure baldness, and aids in preventing tooth decay (Nidhi et al. 2017). Many technologies are being developed to use bottle gourd in many forms, such as making bottle gourd ice cream (Barot et al. 2014) and adding fruit like Jamun to increase the shelf life of bottle gourd beverages (Palamthodi et al. 2019). Though there is an increased demand for cultivation of bottle gourd due to its immense cultivation, craft, and medicinal importance, very scanty information is available about the genetic diversity of its germplasm.
Among various available molecular markers, microsatellite markers are ideal due to their ease of use and co-dominance. Microsatellites or simple sequence repeats (SSRs) are small (1-6 bp) tandem repeats, which are ubiquitously found in the genome of both prokaryotic and eukaryotic organisms (Campomayor et al. 2021;Singh et al. 2021;Sunde et al. 2020;Toth et al. 2000). High mutation rates are the consequences of the change in array length of allele; these repeats signify a rich cause of hyper-variable co-dominant markers (Morgante et al. 2002;Powell et al. 1996). Consequently, SSR markers are considered as an important marker in various research such as population genetics (Innan et al. 1997), linkage mapping (McCouch et al. 2002;Somers et al. 2004), phylogenetics, and structural, functional, or comparative genomics research (Garza et al. 1995;MacHugh et al. 1997). Due to their high reproducibility, multi-allelic variation, co-dominant inheritance, and abundance in the genome (Tautz and Renz, 1984), they are also widely used for marker-assisted breeding and parentage analysis (Bowers and Meredith, 1997). Microsatellites are believed to play significant roles in genome evolution, by producing genetic variability (Kashi et al. 1997), study of gene expression regulation (Santi et al. 2003;Saveliev et al. 2003), acclimatizing the development of the cell cycle , etc. As shown in different SSR data from plants (Morgante et al. 2002), humans (Subramanian et al. 2003), and other eukaryotic species (Toth et al. 2000), SSRs are distributed around the genome in an uneven and non-random manner, with both similarities and differences observed among taxa. The distribution of SSRs in the genome provides important information on their utility as molecular markers. Genomic SSR markers are one among the best markers to be used as transferable markers among related species, making them easier to employ as anchor markers for comparative physical mapping (Bhawna et al. 2015b;Varshney et al. 2005). Technological advancements such as genotypingby-sequencing (GBS) or reduced-representation libraries sequencing (RRLS) appeared to be the promising techniques (Altshuler et al. 2000;Elshire et al. 2011;Helyar et al. 2011). Most significantly, restriction site-associated DNA sequencing (RAD-Seq), one of the techniques known as a genome "complexity reduction" procedure, has been shown to be very valuable in non-model species since it combines the advantages of cheap cost and high output (Rowe et al. 2011). RAD-Seq is known to be used in about 20 species without using any reference genome in many phases of genomic/genetic research, comprising effective marker development approach (Pujolar et al. 2013), comparative mapping studies (Yang et al. 2013), QTL mapping (Hegarty et al. 2013), phylogenetic analyses (Nadeau et al. 2013), and genome-wide studies (Hecht et al. 2013). In species with existing reference genomes, RAD-Seq has been a worthwhile substitute to WGRS (whole-genome resequencing) for population genomic studies (Bruneaux et al. 2013;Varshney et al. 2013). Therefore, available RAD sequencing data provide new opportunities to develop SSR markers in bottle gourd and for several downstream analyses. Despite the significance of SSR markers in many research practices, genome-wide characterization of SSR sequences in the available bottle gourd genome has yet not been endeavored.
Until now more than 4000 molecular markers, viz., 20 ISSR (Bhawna et al. 2014), 3226 SNP (Pei et al. 2013), 920 SSRs (Xu et al. 2011;Bhawna et al. 2015a, b;Jacob et al. 2016;Mehtap et al. 2013;Wang et al. 2018), 54 RAPD (Decker-Walters et al. 2001, two chloroplasts, and five nuclear markers (Andrew et al. 2006) have been available in bottle gourd to assess the crop genetic diversity. However, the aim of our study is to add some more beneficial molecular markers to the existing resources of this beneficial multifarious usage crop. Considering the efficacy of wholegenome sequence-based SSR marker data, we aimed to develop SSR markers from RAD sequence data, and supplement the distribution and density of perfect SSRs in bottle gourd genome sequences. The work will prove to be useful to study phylogenetic, DNA fingerprinting, and in breeding for bottle gourd and other cucurbits crop species, which have very less or no genomic markers.

Detection of SSRs and primer design
The whole-genome sequences of bottle gourd were searched for SSR markers using MISA (MIcroSAtellite identification tool) available at http:// pgrc. ipk-gater sleben. de/ misa/ with default parameters. The genomic flanking sequences of discovered SSR motifs were loaded into the Primer3 module of the MISA program to design primer pairs with default parameters.

Validation of genomic SSRs
For validation of designed SSR markers, the genomic DNA was isolated from the leaves of 96 accessions of bottle gourd (Additional file 1 (Supplement Table S1)) from different region of India from the National Genebank of India, using the CTAB method. The isolated genomic DNA was separated on 0.8% agarose gel (Cambrex, USA) in Tris-borate-EDTA (TBE) buffer (pH 8.0), and quantified by means of NanoDrop, ND-1000 spectrophotometer (Wilmington, Delaware, USA) at 260 nm.
Genomic DNA amplification of the 96 accessions of bottle gourd germplasm was carried out using SSR primers in a total reaction volume of 12.3 µl containing 30 ng/ µl of DNA, 1X Taq polymerase reaction buffer, 2 mM MgCl2, 0.1 mM each of dNTPs, 0.2 mM primer, and 1 U of Taq DNA polymerase (MBI Fermentas, Germany) in a Bioer Thermo Cycler (Hangzhou, P. R. China) with the following reaction conditions: initial denaturation for 5 min at 94 °C followed by 35 cycles of 1 min denaturation at 94 °C, 1 min annealing mostly in the range of 50-55 °C, and 2 min extension at 72 °C, followed by a final extension at 72 °C for 7 min.

Genetic diversity and population structure of the National Genebank accessions of bottle gourd
After electrophoresis, the clear, intense, and consistently amplified bands were scored for each accession in a binary matrix as 1 (presence) or 0 (absence) for diversity analysis study. The genetic relatedness was estimated by the genetic dissimilarity coefficient, and the dendrogram was drawn using the unweighted pair group method (UPGMA) with NTSYS PC 2.1. Binary data was used to calculate allele frequency using GenAlEx software (Peakall and Smouse, 2012). The allele frequencies were used to calculate PIC and heterozygosity in PowerMarker software (Liu and Muse, 2005) as shown in Table 4.
The co-dominant alleles data were also analyzed with POPGENE v. 1.32 (Yeh et al. 1999) to estimate different genetic diversity parameters, viz percentage of polymorphic loci (P), Shannon's information index (i), the observed number of alleles (na), effective number of alleles (ne), and gene flow (Nm). For the examination of population structure, we utilized a model-based clustering method as executed in the software program STRU CTU RE 2.3.4 (Pritchard et al. 2000). To estimate the number of populations (K) and the admixture proportion for each germplasm, the Monte Carlo Markov chain method was used. In this program, we used 100,000 iterations and a burn-in period of 100,000. At least ten independent runs were evaluated for each fixed number of populations (K).

Physical mapping of bottle gourd genomic SSR markers
For determining the physical location (bp) of identified SSR markers on the eleven bottle gourd chromosomes, the flanking genomic sequences of identified SSR repeat motifs were searched against the whole genome sequence of available bottle gourd (Wu et al. 2017), using BLASTn. Optimized BLASTn search parameters with default E-value (0.00001) and low-complexity filter selections were preferred for this analysis. Finally, the physically located SSR markers were visualized using MapChart software.

Comparative genome mapping between bottle gourd and other cucurbits species
The flanking sequences of SSR marker loci that were physically mapped on the eleven chromosomes of bottle gourd (Additional file 1 (Supplement Table S5)) were BLAST searched against genome sequences of other Cucurbitaceae species like cucumber (Cucumis sativus) (Li et al. 2019), melon (Cucumis melo) (Garcia-Mas et al. 2012) and watermelon (Citrullus lanatus) (Wu et al. 2019) to derive marker-based syntenic relationships between bottle gourd and other Cucurbitaceous species. For establishing synteny relationships, sequence with 100%, high-scoring segment pair (HSP) identity and query coverage, and > 80% of alignment length with their presence on the same chromosome, was considered. Syntenic relationships of bottle gourd based on SSR markers analyzed with cucumber, watermelon, and melon were finally visualized by means of software Circos 0.55 (Krzywinski et al. 2009) (http:// circos. ca).

Results and discussion
In the present study, we examined available non-redundant RAD bottle gourd genomic sequence for the distribution of perfect SSR. Repeats were first examined on a wholegenome basis using genomic DNA sequence of bottle gourd and SSR content in DNA sequences. Further, the SSR frequencies were studied and compared with cucumber and Arabidopsis. Mapping of genomic SSRs on linkage groups and their comparative syntenic relationship was also studied with other Cucurbitaceae species.

Distribution of SSR types in genomic sequences
First, a total of 171,019 SSR markers with perfect repeats were detected in the bottle gourd; after removal of the redundant SSR markers, we finally found 45,066 perfect SSRs. The content of perfect SSR primers in genomic sequences of bottle gourd is summarized in Table 1. The studied genome had coverage of 98.3% that estimate an overall density of 133.60 SSRs/Mbp (excluding mononucleotide and compound SSRs). The bottle gourd showed the lowest SSR density among the species compared with that of cucumber (536.60 SSRs/Mbp) and Arabidopsis (364.10 SSRs/Mbp) ( Table 2).
Tetranucleotide repeats were the most common SSR type in bottle gourd genomic sequence representing.
nearly 34% of all SSRs, followed by tri-(30.73%) and dinucleotides (21%) ( Table 2). Penta and hexanucleotides were the least frequent repeat types, together representing less than 15% of the total SSRs. In bottle gourd, tetranucleotides were predominant as in cucumber whereas Arabidopsis has trinucleotides as the abundant SSR types (Additional file 1, Supplement  (Cavagnaro et al. 2010).
The distribution of bottle gourd SSR with respect to the number of repeat units is shown in Supplement Fig. 1. For all SSR types, SSR frequency declined with increase in the number of repeat units. However, the frequency of this variation was more gradual in all nucleotides from di-to tetranucleotides than in longer repeat types, from pentato hexanucleotides showing the most dramatic reduction in frequency with increased repeat units (Table 2). For instance, the mean number of repeat units in dinucleotides is 9.0, which were twice as that of the number of repeat units in tetranucleotides (4.5) ( Table 2); dinucleotides also revealed the presence of more varied motifs despite less number of SSRs than tetranucleotides. Although tetra, penta, and hexa have almost the same mean repeat number like 4.5, 4, and 4, respectively, showing equal contribution to the genome portion that is occupied by SSR nucleotides. Trinucleotide repeat motif occurred more frequently than tetra, penta, and hexanuclotide in the RAD genome data with a mean of 6.5.

Distribution of SSR motifs
We have carried out a detailed analysis of individual repeat motifs for each type of SSRs found in genomic sequences of bottle gourd, along with related calculations used for cucumber and Arabidopsis, which is presented as supplemental data (Additional file 1, Supplement Table S2 (for bottle gourd), Supplement Table S3 (for both cucumber and Arabidopsis)) available with the online version of this paper. The relative frequency (%) of SSR types with different number of repeats present in the bottle gourd genome represent in Supplement Fig. 2 and Table 3. The main results of this analysis were outlined for different motifs separately (Additional file 1 (Supplement Table S2)).

Dinucleotide motifs
In bottle gourd, genomic sequences, analysis of the dinucleotide sequence shows AT motif was predominantly present (Additional file 1 and Table S2), and CG repeats were the least frequent dinucleotides in bottle gourd. In addition, related to other both species, the existence of AT also being the amplest single motif, regardless of repeat type, whereas GC showed the least frequent repeat in both cucumber and Arabidopsis, in all across the genomic data sets examined.  Table S3.

Trinucleotide motifs
In bottle gourd, trinucleotide repeats were the second most abundant in genomic sequences available. Investigating frequencies of diverse trinucleotides revealed that repeats of AAT were more common in bottle gourd genomic data along with cucumber. But this pattern is not like that of Arabidopsis, as in Arabidopsis AAG is predominant one. Conversely, CGT were the rarest trinucleotides in genomic DNA of bottle gourd whereas CCG shows the least abundant in both cucumber and Arabidopsis.

Tetranucleotide motifs
Tetranucleotide repeats were the most frequent in genomic sequences of bottle gourd ( Table 2). The AT-rich motifs AAAT, TTTA, ATTT, TTAT, and AATA were the most abundant tetranucleotides in bottle gourd genomic data, together representing ~ 62% of all tetramer repeats, whereas GC-rich repeats like ACGC, AGGC, CCCG, GCAG, GCCT, and GCGG were the least, with relative frequencies of > 0.1% (Additional file 1 and Table S2). A comparable distribution was perceived in the other dicots also, showing a clear prevalence of these similar AT-rich motifs in study.

Pentanucleotide motifs
Bottle gourd genomic sequences had the least frequency of pentanucleotide repeats. Among them, AT-rich penta repeats were the predominant one accounting a total of ~ 51% penta repeats most common motifs among them are AAAAT, ATTTT, TTTTA, TAAAA, TTTAT, etc. followed by AAAAG (see Additional file 1 and Table S2). In general, these motifs also predominated in both other species, akin to cucumber with the highest density of AAAAG followed by AAAAT repeats in genomic sequences, whereas Arabidopsis had the highest frequency of AAAAT motif followed by AAAAC, AAAAG. Analysis of pentanucleotide frequencies in genomic DNA from all three species revealed that, in both bottle gourd and Arabidopsis, AAAAT was the most abundant repeat, with the next most frequent repeats, AAAAG or AAAAC, but with cucumber, AAAAG is more dominant motif than the AAAAT.

Hexanucleotide motifs
In bottle gourd, genomic sequence least frequent SSRs are the hexanucleotide accounting only 4.3% among all SSRs. AT-rich hexanucleotide motifs such as AAA AAT , ATT TTT , TAT TTT , AAA ATA , and TTA TTT together contribute to 43.38% in bottle gourd genomic data. In all motifs, AAA AAT is the most frequent repeat present followed by AAA AAG , TAA AAA , contributing 43.38% of total hexanucleotide. Similarly, Arabidopsis also has AAA AAT as the predominant one and in cucumber AAA AAG followed by AAA AAT are frequently present.

Development of SSR markers in bottle gourd genome
Initially, we identified 170,775 SSR markers, from the RAD genomic sequence of bottle gourd. After removing redundant and compound SSRs, we finally developed 45,066 perfect SSRs. These SSRs had forward and reverse primers on both sides of the SSR flanking genomic sequences (Additional files 1 (Supplement Table S4)) and had 100% successful primer designing potential. Among developed 45,066 perfect SSRs, 41,871 were effectively anchored to the bottle gourd chromosome (Wu et al. 2017); information of mapped markers is provided in Additional files 1, Supplement Table S5. The genomic distribution of mapped 41,871 SSR markers in the bottle gourd genome revealed their physical localization on the 11 chromosomes of bottle gourd with average marker density of 133 markers/Mb. The average marker density was a maximum of 174.48/Mb in chromosome 1, and minimum in chromosome 6 i.e., 111.65/Mb (Supplement Table S6). These observations suggested that this data is sufficiently high-density SSR marker mapping.
Herein, all genome-wide SSR markers, including both physically mapped and non-mapped markers for bottle gourd genome, were developed. This huge marker data could be advantageous for various applications, like large-scale genotyping, phylogenetic relationship studies, molecular breeding, diversity analysis, and population genetic structure analysis, including mapping of genes and comparative genome mapping involving bottle gourd and other cucurbit crop plants.

Amplification, polymorphic potential, and physical mapping of 207 random SSR markers
The exact positions of SSRs in the bottle gourd RAD sequenced genome, their primers as well as information on expected PCR product length, repeat motifs, and primers AT (annealing temperature), are presented in Additional files 1, Supplementary Table S4. Among mapped 41,871 markers, 207 markers are randomly selected, and their profiling across the bottle gourd germplasm was studied and mapped on the bottle gourd chromosome (Fig. 1). Among 207 primer pairs (Primer name and Seq ID are present at Additional files 1, Supplement Table S7), 57.97% primer pairs were seen polymorphic and the remaining loci were monomorphic.

SSR polymorphism and genetic diversity analysis
The alleles recognized from the 120 novel polymorphic marker pairs varied from 2 to 8 with a mean of 2.43 alleles per locus. The PIC values for these polymorphic SSR markers varied from 0.0103 to 0.375 with a mean of 0.2034 (Table 4). UPGMA dendrogram was used to analyze genetic diversity analysis by using polymorphic markers, based on the distinctive DNA marker profiles (Fig. 2) of all the National Genebank accessions of bottle gourd (Additional file 1, Supplement Table S1), used in the study. Scored polymorphic data were subjected to NTSYS-PC 2.01 software for generating the UPGMA dendrogram based on the Jaccard's similarity coefficient, and the 96 accessions were distributed in two clusters. One cluster was of small size with seven germplasm from the Delhi region and another large cluster contained 5 sub-clusters and a few out-groups (Fig. 2). In sub-cluster 1, maximum germplasm was from the Delhi region except for two IC-317498 from Bihar and IC-341128 from Uttarakhand, whereas sub-cluster 2, 3, 4, and 5 had germplasm from different part of India. In the outgroups IC-92390, IC-430102, IC-0536593, IC-522210, IC-519467, IC-301188, IC-92807, IC-0385816, and IC-0382208 representing germplasm separated from the other clusters, these diverse accessions may be due to the presence of some unique traits and could be utilized in breeding programs. The obtained pairwise genetic similarity matrix of Jaccard's coefficient calculate genetic similarity (GS) ranged from 0.77 to 0.99, with a mean of 0.87. The minimum similarity value, 0.77, between IC-92376 and IC-52220 and the maximum similarity value 0.99 that were scored between IC-33833 and IC-3428, suggested the germplasm is not much diverged.
Various diversity parameters like gene diversity, Shannon's information index, gene flow, and a number of alleles with each of these 120 polymorphic markers are shown in Table 5. The observed number of alleles and an effective number of alleles were 1.99 and 1.45 respectively among the studied accessions of bottle gourd. Nei's gene diversity which is equivalent to the average heterozygosity was 0.25 ± 0.21 and Shannon's Information Index was 0.38 ± 0.27. These results indicated that the accessions harbor less diversity, and high gene flow value was obtained, i.e., 0.25 for the populations used. This gene flow value is possible because of the cross-pollinated nature of the crop and that no boundaries on genetic exchange within India.

Population structure analyses
A model-based clustering analysis was performed for all 96 accessions using 120 polymorphic SSR markers. Ad hoc quantity (ΔK) was used to solve the difficulty in inferring the real K value. A comparatively high value of ΔK was found for K = 4 (Fig. 3). By analyzing the 96 bottle gourd accessions using the STRU CTU RE program (Fig. 4), two germplasm IC-92469 and IC-505650 from Delhi clustered with other germplasm of sub-cluster 1 (blue) and also showed admixing with another sub-cluster of the Delhi region (green). Sub-clusters 2 and 3 showed varying degrees of admixture population. The genetic structuring events between germplasm within populations are a result of the interaction of the various evolutionary forces, mutation, migration, breeding structure, and selection pressure that may influence simultaneously or discreetly. In the UPGMA, clustering sub-clusters 4 and 5 are separated from each other whereas STRU CTU RE merges them into one population.

Comparative genome mapping between bottle gourd and other cucurbits species
For comparative mapping, the physically mapped 41,871 SSR markers of bottle gourd were associated with their physical position on the chromosomes of other correlated cucurbit genomes, namely, cucumber, melon, and watermelon (Fig. 5). Comparative genome mapping has shown a maximum fraction of sequence established orthology. Therefore, SSR markers scattered over 11 bottle gourd linkage groups revealed correlation with 7 chromosomes of cucumber having 12.19% synteny, 12 chromosomes of melon with 12.05% synteny, and 11 chromosomes of watermelon with 9.8% synteny were identified.

Bottle gourd-cucumber synteny
Among 41,871 SSR markers of bottle gourd, 5106 SSRs were mapped over cucumber chromosome. The markers in all 11 bottle gourd chromosome revealed an average frequency of 66.31% to that of marker chromosomal location in cucumber. The physically mapped SSR markers are on the bottle gourd chromosomes 1 and 2 showing maximum synteny of 1080 and 839 markers with chromosome 7, respectively. Bottle gourd chromosome 7 and cucumber chromosome 2 have a synteny of the least number of microsatellites that are 8 SSR markers.

Bottle gourd-watermelon synteny
The comparative mapping between bottle gourd and watermelon genomes has shown a syntenic relationship of 4134 markers. Among them, 546 SSR marker loci dispersed over 1 chromosome of bottle gourd and 11 chromosomes of watermelon. It was identified that a synteny relationship is of the lowest number of genomic SSRs between 10 and 11 chromosomes of bottle gourd and watermelon chromosome numbers 3 with 5 and 2 genomic SSRs, respectively. On an average, 34.2% syntenic relationship of SSR marker loci between bottle gourd and watermelon chromosomes was identified.

Bottle gourd-melon synteny
Similarly, melon has shown a synteny of 5047 markers with bottle gourd genome. The SSR markers physically mapped on the bottle gourd chromosome 11 and showed the least synteny with 2 chromosomes of melon with just 3 markers. The maximum number of 1084 bottle gourd SSR marker on chr 1 loci showed significant matches with genomic regions spanning over 12 chromosomes of melon   We are reporting huge numbers of SSR markers in bottle gourd utilizing RAD sequence data. The current study also provided some interesting information like syntenic relationships of SSR markers between bottle gourd, cucumber, melon, and watermelon. Using synteny study, an idea of genome conservation among cucurbits like cucumber, melon, and watermelon was revealed, and the comparative studies are valuable in understanding the evolutionary progression among cucurbits genome.

Conclusion
RAD sequencing information was proved to be highly valued in large-scale development of SSR markers. In our study, this valuable data had added to a detailed representation of SSRs in the bottle gourd genome. Here, we revealed the genomewide identification of 45,066 SSRs motifs in the bottle gourd, where tetranucleotide repeats were the utmost frequent SSRs present in the genome. All developed markers were used for mapping, among them, 41,871 SSRs were physically mapped on 11 bottle gourd chromosome and were further used to develop synteny with cucumber, melon, and watermelon.
Among 45,066 markers, 207 primer pairs of SSRs were synthesized and successfully validated with quality amplification showing polymorphic potential in bottle gourd accessions. These markers were then utilized for genetic diversity evaluation of the bottle gourd Indian National Genebank germplasm. These reported SSR markers would be of enormous use for germplasm categorization, for gene or QTL detection, cultivar identification, and relative genome mapping involving bottle gourd and other cucurbits species. The SSR marker-based comparative genome mapping amongst  bottle gourd and other cucurbits species such as cucumber, melon, and watermelon would be advantageous in a mapbased isolation of agronomic importance genes from the bottle gourd by means of the marker-based genotyping data.