Skip to main content
NCBI home page
3 Biotech logoLink to 3 Biotech
. 2020 Aug 4;10(8):374. doi: 10.1007/s13205-020-02372-5

Population structure and genetic diversity of watermelon (Citrullus lanatus) based on SNP of chloroplast genome

Haonan Cui 1,2, Zhuo Ding 1,2, Qianglong Zhu 3, Yue Wu 1,2, Peng Gao 1,2,✉
PMCID: PMC7403291  PMID: 32832334

Abstract

Citrullus amarus (citronmelon) is an important crop with resistance to many diseases. The chloroplast genome is important in studying the genetic evolution of plants. The C. amarus chloroplast genome was first reported in this study using a novel assembly method based on whole genome sequencing. We identified 82 SNP sites in chloroplast genome with 313 watermelon materials. The 82 SNPs could effectively divide the natural watermelon population into four groups: C. lanatus subsp. lanatus, C. lanatus subsp. mucosospermus, C. lanatus subsp. vulgaris (ecologically from the Americas) and C. lanatus subsp. vulgaris (ecologically from Asia), with decreasing genetic diversity (π) (6.6 × 10−5, 2.4 × 10−5, 9.8 × 10−6 and 5.41 × 10−6, respectively). The single fruit weight, soluble solids, fruit color and 1000-seed weight of C. lanatus subsp. lanatus were significantly different from those of the other three groups. These results indicate that the complete chloroplast genome can be used in studying population genetics of watermelon, which is helpful for classification among intra species subgroups and identification of core germplasm resources.

Electronic supplementary material

The online version of this article (10.1007/s13205-020-02372-5) contains supplementary material, which is available to authorized users.

Keywords: Chloroplast, Genome, Citrullus amarus, Genetic diversity

Introduction

Watermelon (Citrullus lanatus (Thunb.) Matsum. et Nakai) originated in Africa (Lin 2015). It is a genus of annuals in the family Cucurbitaceae. Watermelon is good fruit for supplying nutrition and water in summer. It is widely planted all over the world. According to the latest statistics of FAO (www.fao.org/faostat/en/), the planting area of watermelon in China accounted for about 54% of the world. Citrullus amarus is a watermelon (Citrullus lanatus) relative that is reported to carry disease resistance alleles to several important pathogens (Maragal et al. 2019).

Chloroplast is an important semi-autonomous organelle with independent genetic material and genetic system in plant cells. Studies have shown that chloroplast genome in watermelon is not only related to important physiological activities such as photosynthesis, respiration, cold tolerance, and sex differentiation (Ali et al. 2014; Levi et al. 2006), but also plays an important role in germplasm resource identification and phylogeny of watermelon and melon (Schaefer et al. 2009; Sebastian et al. 2010).

Chloroplast genome sequence is widely used in the study of plant phylogenetic relationships (Cheng et al. 2018). Chloroplast is the key organelle for photosynthesis and carbon fixation in green plants, and, therefore, their genomes could provide valuable information for taxonomic classification and the reconstruction of phylogeny because of sequence divergence among plant species and individuals (Douglas 1998; Huang et al. 2014). The structure and coding genes of chloroplast genome are relatively conserved, i.e. changed little in the process of plant evolution, which makes it possible to conduct phylogenetic analysis among species with distant plant relationships (Yang et al. 2013). Most of the genes in the chloroplast genome are single-copy, with only a few genes in the IR region being double-copy genes, ensuring that genes are not affected by paralogs in the homology alignment (Li 2015).

The evolutionary rates of different regions of the chloroplast genome are significantly different. For example, the functional gene coding region sequences are restricted by the natural selection pressure, and the evolution rate is slow. In contrast, the unrestricted non-coding region sequences evolve faster, making the chloroplast genome suitable for studying phylogenetic relationships of different classification orders (Palmer et al. 1988). The inheritance mode of chloroplast genome is mainly matrilineal, which can provide a unique insight that differs from the nuclear genome regarding the evolutionary process of plant matrilineal parents. These advantages make chloroplast genome an important molecular evidence for the phylogenetic evolution of higher plants (Choi et al. 2016; Lei et al. 2016; Yang et al. 2013).

In 2009, Schaefer et al. (2009) extracted DNA from dried cucurbitaceous plants, successfully amplified and sequenced five DNA fragments in the chloroplast genome, and constructed the maternal phylogenetic relationship of Cucurbitaceae. The results showed that the Cucurbitaceae plant originated in Asia 60 million years ago, and then spread to Africa, America and Australia. The phylogenetic relationships based on chloroplast genes revealed that monoecious plants in cucurbit family may have evolved from dioecious plants numerous times. The phylogeny constructed by using chloroplast genes in the genus of melon (Chung et al. 2006; Sebastian et al. 2010) clarified the relationships between wild and cultivated species, providing a theoretical basis for genetic improvement of cultivated cucumber and muskmelon with wild resources.

Materials and methods

Plant materials

Fresh and healthy young leaves were collected from adult plants of C. amarus at the Xiangyang farm of Northeast Agricultural University in spring 2017. In April to September 2017, 313 watermelon group materials (accessions) (Table S1) collected from more than 20 countries in Asia, Africa, Europe, and the Americas were planted in the plastic greenhouses of Xiangyang farm in Northeast Agricultural University. For each accession, five plants were planted; three replicates were used. Different accessions and replicates were planted in a completely randomized design. The plants were managed by using standard horticultural procedures typical of the climatic conditions in Harbin. Young fully-expanded leaves were collected at seedling stage for total DNA extraction.

Collection of the phenotype data

The fruits were harvested at maturity for collecting the phenotype data. Single fruit weight, fruit color value and soluble solid content were determined immediately using an electronic scale (SECA 803), Pantone colorimetric cards and a hand-held refractometer on sampling, respectively. 1000-grain weight was determined with an analytical scale after drying the seed. Each trait was measured three times, and the average value was used.

Total DNA extraction, Illumina sequencing and genome assembly

The DNA of C. amarus was extracted from approximately 3 g of young leaves using the CTAB method. Agarose gel electrophoresis (1% w/w) was used to assess the DNA quality and quantity. Approximately 3 μg of whole genome DNA from each accession was indexed and pooled together in 1 lane of an Illumina HiSeq X Ten platform and sequenced by BGI (Shenzhen, China). The resequencing data were deposited in GenBank (https://www.ncbi.nlm.nih.gov/) under BioProject ID PRJNA648815.

The chloroplast genome was assembled using the new method. First, the sequence data were checked by FastQC (Andrews 2013) and filtered by the NGS QC Toolkit (Patel and Jain 2012). Second, the sequence data (0.7 × the coverage of nuclear genome) were randomly extracted using Seqtk (v0.1) and assembled by the plasmidspades.py script in SPAdes (v3.10.1) (Bankevich et al. 2012) to preclude the influence of the consensus reads of nuclear and mitochondrial origin on the chloroplast genome. The contigs representing the chloroplast genome were retrieved, ordered, and joined into a single draft sequence through comparisons with the reference chloroplast genome of C. sativus (NC_007144.1) by using BLAST. Gaps in the chloroplast single draft sequence of each accession were filled by GapCloser (v1.12-r6), and repeated sequences in the gap were deleted manually. The draft sequence was then confirmed and manually corrected by PE-read mapping with BWA and SAMtools (Li et al. 2009).

Statistical analysis of phenotypic data

Microsoft® Excel 2013 was used to enter the numerical values of plant traits for archiving and preliminary sorting. SPSS 22.0 was used to conduct variance and correlation analyses, standard deviation and confidence interval of each trait. The frequency distribution and box diagrams were drawn by GraphPad Prism 5.

Genome resequencing, read mapping and SNP calling

To reduce the interference of nuclear genome sequence, and to analyze all the sample data in the unified data volume, we used Seqtk randomly to identify the nuclear genome data in the total sequencing data, and then used the BWA SAMtools and VarScan combination to extract the data for analysis. We identified all the SNP loci in the samples, and finally used Gapit MEGA and iTOL (Letunic et al. 2019) for analysis of genetic diversity in the natural population of watermelon.

Phylogenetic relationship analysis

Chloroplast genomes of watermelon was aligned using ClustalX (https://www.clustal.org/clustal2/). A phylogenetic tree was constructed via Neighbor Joining (NJ) using Mega7 software.

Genetic diversity analysis based on organelle genome

To analyze genetic diversity among accessions, we conducted a sliding window analysis using DnaSP v5.10 (Librado and Rozas 2009), with the step size and window length set to 200 and 800 bp, respectively.

Results and discussion

Sequencing and assembly of C. amarus chloroplast genome

The total DNA of C. amarus was sequenced and produced 24,435,210 paired-end clean reads (150 bp). Reference-guided assembly validated the four junction regions in the chloroplast genome. The C. amarus chloroplast genome sequence was deposited in GenBank (MF536694). The chloroplast genome was 157,008 bp, and it showed a typical quadripartite structure, consisting of a pair of IRs (26,149 bp) separated by the large single copy (LSC) (86,813 bp) and small single copy regions (SSC) (17,897 bp) (Fig. 1, Table S2).

Fig. 1.

Fig. 1

Open in a new tab

Gene map of the complete chloroplast genome of C. amarus. Genes on the outside ring are transcribed in the clockwise direction, while the genes on the inside ring are transcribed in the counterclockwise direction. Different functional gene groups are color-coded. The dark gray plot in the inner circle corresponds to GC content

Single nucleotide diversity analysis of chloroplast genome in watermelon population

In order to further understand the genetic diversity of watermelon natural population, this study analyzed the single nucleotide diversity (SNP) of watermelon chloroplast genome in 313 watermelon accessions collected. After analysis, 82 SNP loci were obtained. These SNPs were unevenly distributed throughout the chloroplast genome. They were mainly located in the LSC and SSC of the chloroplast genome. The two inverted repeat regions (IRa and IRb) contained almost no SNP sites (Fig. 2, Table S3).

Fig. 2.

Fig. 2

Open in a new tab

The density distribution of SNPs in the chloroplast genome of C. lanatus. IR inverted repeats; LSC large single copy region; SSC small single copy region. Red denotes high SNP density, and blue indicates low SNP density

Population structure analysis of watermelon

In order to further explore the population structure characteristics of watermelon germplasm in this study, we analyzed the population structure of watermelon using 82 SNPs from the whole genome of watermelon chloroplasts. In the phylogenetic tree constructed with Neighbor Joining (NJ), 313 watermelon accessions were divided into four groups (Fig. 3). The number of accessions in group IV (231) was the largest (Table 1). 97.4% of watermelon accessions in the group were C. lanatus subsp. vulgaris, which were mainly distributed in China, Japan, the United States, and Turkey. Only 2.6% of the group were C. lanatus subsp. lanatus. The second was group III that contained 41 watermelon accessions. Most of them were still C. lanatus subsp. vulgaris, but they were mainly distributed in countries other than China, such as the United States, Turkey, Zimbabwe, and Nigeria. Group I contained 29 watermelon accessions, all of which were C. lanatus subsp. lanatus, mainly distributed in Zimbabwe, Zambia, South Africa, Nigeria, and other African countries. Group II had the smallest number, with only 12 watermelon accessions, but this group contained the most watermelon subspecies, with C. lanatus subsp. mucosospermus as the dominant subspecies accounting for 66.7% of the group.

Fig. 3.

Fig. 3

Open in a new tab

The population structure of 313 watermelon accessions based on the SNP loci in the chloroplast genome. Group I is wild type (mainly C. lanatus subsp. lanatus), Group II is semiwild type (mainly C. lanatus subsp. mucosospermus), and Groups III and IV are two cultivars (C. lanatus subsp. vulgaris (ecologically from the Americas) and C. lanatus subsp. vulgaris (ecologically from Asia), respectively.)

Table 1.

The amount and percentage of watermelon subspecies in the four groups

Taxon Group I Group II Group III Group IV Total
C. lanatus subsp. lanatus 29 (100%) 2 (16.7%) 0 6 (2.6%) 37
C. lanatus subsp. mucosospermus 0 8 (66.7%) 3 (7.3%) 0 11
C. lanatus subsp. vulgaris 0 2 (16.7%) 38 (92.7%) 225 (97.4%) 265
Total 29 12 41 231 313
Open in a new tab

Genetic evolution analysis of chloroplast genomes in different populations of watermelon

Group I was mainly C. lanatus subsp. lanatus. The flesh quality of these watermelons was extremely poor, generally with bitter taste, which cannot be directly eaten. However, some of them have extremely strong disease resistance, which has important applicability in watermelon resistance breeding (Wang and Hou 2006).

Group II were mainly C. lanatus subsp. mucosospermus, a type of watermelon with large edible seeds, but with tasteless or bitter flesh.

Group III and IV were mainly C. lanatus subsp. vulgaris. They are the sweet and succulent types of watermelons that are mainly grown and consumed in the world (Guo et al. 2013). According to their main source, we refer to group III as cultivated watermelons ecologically from the Americas. Group IV represented cultivated watermelon ecologically from Asia.

We further studied whether the genetic diversity of the chloroplast genome of watermelon decreased during the selection and domestication of cultivated watermelon. In this study, the genetic diversity of four watermelon subpopulations was analyzed based on the SNP mutation sites in chloroplast genes. The genetic diversity of Group I was 6.6 × 10−5, which was significantly higher than that of Group II (2.4 × 10−5), Group III (9.8 × 10−6) and Group IV (5.41 × 10−6). Moreover, the genetic diversity of C. lanatus subsp. mucosospermus was also significantly higher than that of the two cultivated populations (Fig. 4). In addition, the degree of genetic diversity declined in different regions of the chloroplast genome. The genetic diversity of the LSC segment varied most from C. lanatus subsp. lanatus to C. lanatus subsp. vulgaris, followed by the SSC segment, and two inverted repeats. These conclusions indicate that the decline in genetic diversity of cultivated watermelons during the selection and acclimation of cultivated watermelons did not occur only in the nuclear genome (Guo et al. 2013), but also had a clear effect on diversity in the chloroplast genome.

Fig. 4.

Fig. 4

Open in a new tab

Genetic diversity (π) of four groups on the whole chloroplast genome in watermelon. LSC large single copy region; IR inverted repeats; SSC small single copy region

Fruit-related importance in different groups of watermelon

In order to further understand the fruit-related importance in four different sub-populations of watermelon, such as statistical analysis was conducted on single fruit weight (SFW), soluble solid content of pulp (SSC), fruit color value (FCV), and seed 1000-grain weight (1000SW). The average fruit weight of C. lanatus subsp. lanatus in group I was 6.7 kg (Table S4), and the confidence interval was 3.8–9.6 kg, which was significantly higher than that of the other three groups (Fig. 5a). The flesh of this type of watermelon is firm and generally has a bitter taste. The average soluble solid content was 2.7%, significantly lower than in other watermelon types (Fig. 5b). The flesh was white or light yellow. The average 1000-grain weight was 138.1 g, significantly higher than in the other watermelon types.

Fig. 5.

Fig. 5

Open in a new tab

Statistical analysis of the fruit-related traits in the four watermelon populations. Lower case letters (a, b, c) indicate the significance of differences among different groups (P < 0.05). SFW Single Fruit Weight; SSC Soluble Solid Content; FCV Fruit Color Value; 1000SW 1000 Seed Weight

In group II, containing most of C. lanatus subsp. mucosospermus, the average fruit weight was 3.3 kg, with a confidence interval 1.3–5.2 kg; this was significantly lower than the wild watermelon, but there were no significant differences among cultivated watermelon. The fruit soluble solid content (average 5.1%) was higher than in wild watermelon, but still significantly lower than cultivated watermelon. Flesh color was white or pink, but there were also parts of yellow and orange. The thousand seed weight was significantly lower than in wild watermelon, but there were no significant differences between other types of watermelon (Fig. 5c).

For the C. lanatus subsp. vulgaris in Groups III and IV, although the weight of single fruit was significantly lower than that of wild watermelon, the soluble solid content of pulp was significantly higher than that of wild and semi-wild watermelons. The flesh was red, with some pink and yellow. The seed 1000-grain weight was significantly lower than in wild watermelon (Fig. 5d).

This study applied a new chloroplast genome splicing strategy based on Illumina Hiseq whole genome sequencing data to obtain the complete sequence of plant chloroplast genome efficiently and cost-effectively without the need to isolate and purify chloroplast genomic DNA separately. We designed four pairs of primers across the gap junctions (Table S5). The length of the PCR-amplified product fragments was consistent with expectations (Figure S1), and the product sequencing results were completely correct when compared to the target sequences, indicating the accuracy of the assembly results.

The genetic diversity of watermelons is low (Levi et al. 2001), while the genetic diversity of melons is higher (Nimmakayala et al. 2016). In this study, only 82 SNP loci were identified in the chloroplast genome of the natural population of watermelon. This is the first evidence of low genetic diversity in watermelon population from the perspective of the whole chloroplast genome. So far, the research on the genetic diversity of watermelon mostly utilized molecular markers in the nuclear genome, such as RAPD, AFLP, SSR, SNP, etc. (Garcia-Mas et al. 2000; Nimmakayala et al. 2014; Zhu et al. 2016), whereas only a few studies used chloroplast genome genetic markers in watermelon (Hu et al. 2011). However, this does not indicate that the chloroplast genome genetic markers cannot be applied to intraspecies population genetic research. Indeed, the chloroplast genome is an important molecular genetic tool in plants such as rice (Wambugu et al. 2015) and Nanguo pear (Wuyun et al. 2015), with important results achieved in studying population genetic diversity. In this study, we analyzed the population structure, fruit-related traits and population genetic diversity of natural populations by using the intraspecific SNP markers in the chloroplast genome of watermelon and melon. The results showed that the SNPs in the chloroplast whole genome obtained in this study can effectively characterize watermelons. Four subpopulations, namely wild-type, semi-wild-type, American-cultivated ecotypes, and Asian-cultivated ecotypes, were consistent with Guo et al. (2013) using the SNP data of the whole genome of watermelon to analyze 21 watermelons. The cost of obtaining SNP or SSR markers on the whole nuclear genome was much higher than that in the present study, and the analysis was relatively simple and easy to grasp. Therefore, the conclusions and methods of this study may have important guiding significance for the collection of core germplasm resources in the genetic research on watermelon population, the characterization of genetic diversity in germplasm resources, and the selection of appropriate parental combinations in hybridization experiments.

Conclusion

In watermelon, the SNP in the whole genome of chloroplast was used to analyze the population structure and population genetic diversity of watermelon natural population. 313 watermelon accessions were divided into four groups: C. lanatus subsp. lanatus, C. lanatus subsp. mucosospermus, C. lanatus subsp. vulgaris (American ecotype) and C. lanatus subsp. vulgaris (Asian ecotype). Their genetic diversity (π value) decreased in turn, 6.6 × 10−5, 2.4 × 10−5, 9.8 × 10−6, and 5.41 × 10−6, respectively. The results of this study indicate for the first time that chloroplast whole genome can be used in population genetics study of watermelon, which will be helpful in classification among intra species subgroups and identification of core germplasm resources.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 769 kb) (769.8KB, docx)

Acknowledgements

This study was funded by the National Nature Science Foundation of China (No. 31672177). The authors would like to express their gratitude to EditSprings (https://www.editsprings.com/) for the expert linguistic services provided.

Author contributions

HC, ZD and PG conceived and designed the experiments, QZ and YW collected the phenotypic data, HC and QZ analyzed the re-sequencing data, ZD wrote the original draft and HC reviewed and edited the draft. HC and ZD contributed equally to this research. It is worth noting that HC and ZD are co-first authors.

Funding

This study was funded by the National Nature Science Foundation of China (No. 31672177).

Code availability

Not applicable.

Compliance with ethical standards

Conflict of interest

The authors have no conflict of interest to declare.

Ethics approval

Not applicable.

Availability of data and material

The data that support the findings of this study are available from the corresponding author, Dr. Gao, upon reasonable request.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

References

  1. Ali A, Bang SW, Yang EM, Chung SM, Staub JE. Putative paternal factors controlling chilling tolerance in Korean market-type cucumber (Cucumis sativus L.) Sci Hortic-Amsterdam. 2014;167:145–148. doi: 10.1016/j.scienta.2014.01.004. [DOI] [Google Scholar]
  2. Andrews S (2013) FastQC: A quality control tool for high throughput sequence data [Online]. Available: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/
  3. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI, Pham S, Prjibelski AD, Pyshkin AV, Sirotkin AV, Vyahhi N, Tesler G, Alekseyev MA, Pevzner PA. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19(5):455–477. doi: 10.1089/cmb.2012.0021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Cheng H, Ge C, Zhang H, Qiao Y. Advances on chloroplast genome sequencing and phylogenetic analysis in fruit trees. J Nucl Agric Sci. 2018;32(01):58–69. [Google Scholar]
  5. Choi KS, Chung MG, Park SJ. The complete chloroplast genome sequences of three veroniceae species (plantaginaceae): comparative analysis and highly divergent regions. Front Plant Sci. 2016;7:662. doi: 10.3389/fpls.2016.00355. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Chun SM, Staub JE, Chen JF. Molecular phylogeny of Cucumis species as revealed by consensus chloroplast SSR marker length and sequence variation. Genome. 2006;49(3):219–229. doi: 10.1139/g05-101. [DOI] [PubMed] [Google Scholar]
  7. Douglas SE. Plastid evolution: origins, diversity, trends. Curr Opin Genet Dev. 1998;8(6):655–661. doi: 10.1016/S0959-437X(98)80033-6. [DOI] [PubMed] [Google Scholar]
  8. Garcia-Mas J, Oliver M, Gómez-Paniagua H, de Vicente MC. Comparing AFLP, RAPD and RFLP markers for measuring genetic diversity in melon. Theor Appl Genet. 2000;101(5):860–864. doi: 10.1007/s001220051553. [DOI] [Google Scholar]
  9. Guo S, Zhang J, Sun H. The draft genome of watermelon (Citrullus lanatus) and resequencing of 20 diverse accessions. Nat Genet. 2013;45(1):51–58. doi: 10.1038/ng.2470. [DOI] [PubMed] [Google Scholar]
  10. Hu JB, Li JW, Li Q, Ma SW, Wang JM. The use of chloroplast microsatellite markers for assessing cytoplasmic variation in a watermelon germplasm collection. Mol Biol Rep. 2011;38(8):4985–4990. doi: 10.1007/s11033-010-0643-8. [DOI] [PubMed] [Google Scholar]
  11. Huang H, Shi C, Liu Y, Mao SY, Gao LZ. Thirteen Camellia chloroplast genome sequences determined by high-throughput sequencing: genome structure and phylogenetic relationships. Bmc Evol Biol. 2014;14(1):151. doi: 10.1186/1471-2148-14-151. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Lei W, Ni D, Wang Y, Shao J, Wang X, Yamg D, Yang J, Chen H, Liu C. Intraspecific and heteroplasmic variations, gene losses and inversions in the chloroplast genome of. Sci Rep-UK. 2016;6:21669. doi: 10.1038/srep21669. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Letunic I, Bork P. Interactive tree Of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Res. 2019;47(W1):W256–W259. doi: 10.1093/nar/gkz239. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Levi A, Thomas CE, Wehner TC, Zhang X. Low genetic diversity indicates the need to broaden the genetic base of cultivated watermelon. HortScience. 2001;36(6):1096–1101. doi: 10.21273/HORTSCI.36.6.1096. [DOI] [Google Scholar]
  15. Levi A, Thomas CE, Thies JA, Simmons AM, Ling KS, Harrison HF. Novel watermelon breeding lines containing chloroplast and mitochondrial genomes derived from the desert species Citrullus colocynthis. HortScience. 2006;41(2):463–464. doi: 10.21273/HORTSCI.41.2.463. [DOI] [Google Scholar]
  16. Li X. Phylogenetic genomics study of Paris L Kunming institute of botany. Kunming: CAS; 2015. [Google Scholar]
  17. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R. The sequence alignment/map format and SAMtools. Bioinformatics. 2009;25(16):2078–2079. doi: 10.1093/bioinformatics/btp352. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Librado P, Rozas J. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics. 2009;25(11):1451–1452. doi: 10.1093/bioinformatics/btp187. [DOI] [PubMed] [Google Scholar]
  19. Lin D. A study of systematics for Citrullus Schrad. China Cuc Veg. 2015;28(5):1–4. [Google Scholar]
  20. Maragal S, Rao ES, Reddy DCL. Genetic analysis of fruit quality traits in prebred lines of watermelon derived from a wild accession of Citrullus amarus. Euphytica. 2019;215(12):199. doi: 10.1007/s10681-019-2527-x. [DOI] [Google Scholar]
  21. Nimmakayala P, Levi A, Abburi L, Abburi VL, Tomason YR, Saminathan T, Vajja VG, Malkaram S, Reddy R, Wehner TC, Mitchell SR, Reddy UK. Single nucleotide polymorphisms generated by genotyping by sequencing to characterize genome-wide diversity, linkage disequilibrium, and selective sweeps in cultivated watermelon. BMC Genomics. 2014;15:767. doi: 10.1186/1471-2164-15-767. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Nimmakayala P, Tomason YR, Abburi VL, Alvarado A, Saminathan T, Vajja VG, Salazar G, Panicker GK, Levi A, Wechter WP, McCreight JD, Korol AB, Ronin Y, Garcia-Mas J, Reddy UK. Genome-wide differentiation of various melon horticultural groups for use in GWAS for fruit firmness and construction of a high resolution genetic map. Front Plant Sci. 2016;7:1437. doi: 10.3389/fpls.2016.01437. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Palmer JD, Jansen RK, Michaels HJ, Chase MW, Manhart JR. Chloroplast DNA variation and plant phylogeny. Ann Mo Bot Gard. 1988;75:1180–1206. doi: 10.2307/2399279. [DOI] [Google Scholar]
  24. Patel RK, Jain M. NGS QC Toolkit: a toolkit for quality control of next generation sequencing data. PLoS ONE. 2012;7(2):e30619. doi: 10.1371/journal.pone.0030619. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Schaefer H, Heibl C, Renner SS. Gourds afloat: a dated phylogeny reveals an Asian origin of the gourd family (Cucurbitaceae) and numerous oversea dispersal events. P Roy Soc B-Biol Sci. 2009;276(1658):843–851. doi: 10.1098/rspb.2008.1447. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Sebastian P, Schaefer H, Telford IR, Renner SS. Cucumber (Cucumis sativus) and melon (C. melo) have numerous wild relatives in Asia and Australia, and the sister species of melon is from Australia. P Natl Acad Sci USA. 2010;107(32):14269–14273. doi: 10.1073/pnas.1005338107. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Wambugu PW, Brozynska M, Furtado A, Waters DL, Henry RJ. Relationships of wild and domesticated rices (Oryza AA genome species) based upon whole chloroplast genome sequences. Sci Rep-UK. 2015;5:13957. doi: 10.1038/srep13957. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Wang M, Hou P. Origin, history, classification and breeding achievements of watermelon. Mod Veg. 2006;03:18–19. [Google Scholar]
  29. Wuyun T, Amo H, Xu J, Ma T, Uematsu C, Katayama H. Population structure of and conservation strategies for wild Pyrus ussuriensis Maxim. China Plos One. 2015;10(8):e0133686. doi: 10.1371/journal.pone.0133686. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Yang JB, Yang SX, Li HT, Yang J, Li DZ. Comparative chloroplast genomes of Camellia species. PLoS ONE. 2013;8(8):e73053. doi: 10.1371/journal.pone.0073053. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Zhu H, Song P, Koo DH, Guo L, Li Y, Sun S, Weng Y, Yang L. Genome wide characterization of simple sequence repeats in watermelon genome and their application in comparative mapping and genetic diversity analysis. BMC Genomics. 2016;17:557. doi: 10.1186/s12864-016-2870-4. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary file1 (DOCX 769 kb) (769.8KB, docx)

Data Availability Statement

Not applicable.

Articles from 3 Biotech are provided here courtesy of Springer

RESOURCES