Molecular differentiation between Plinia cauliflora (Mart.) Kausel and Plinia trunciflora (O. Berg) Kausel using nuclear SSR markersAbstract
Molecular markers are important tools for genetic studies, including evolution, species differentiation, and population genetics. The genus Plinia (Myrtaceae) consists of various fruit tree species, some of which are referred to as jaboticaba. The subtle interspecific morphological differences among some jaboticaba species make their taxonomy challenging. This study aimed to develop nuclear SSR markers to distinguish and analyze the genetics of two jaboticaba species, Plinia cauliflora and Plinia trunciflora. The developed markers – eight for P. cauliflora and seven for P. trunciflora – were cross-amplified in both species. Jointly, these markers presented high discriminatory power, private alleles at the species level, and distinguished populations of both species.
Key words
Microsatellite markers; genetic diversity; molecular markers; jaboticaba
INTRODUCTION
The taxonomy of tribe Myrteae (Myrtaceae) is considered particularly difficult (Vasconcelos et al. 2017) due to morphological conservatism, relatively homogeneous flowers, and the rarity of unique diagnostic characters for individual clades (Lucas et al. 2019). Not all reproductive characters support the separation of Myrtaceae species, and some genera have a weak delimitation among species (Oliveira et al. 2019). Indeed, the subtle interspecific morphological differences make the taxonomy of the Plinia species difficult in scientific literature (dos Santos et al. 2021). This lack of consensus directly affects species selection, domestication, and reproduction studies. Integrating genetic analyses can provide more accurate information for the taxonomic classification and conservation of these genetic resources.
Shinohara et al. (2021) reported the development of a single nuclear SSR locus to differentiate Plinia jaboticaba ‘cultivars’, showing that such markers, along with plastome-based analysis (e.g., dos Santos et al. 2021, Machado et al. 2022), can effectively differentiate Plinia species. Aiming at generating new genomic tools for Plinia spp., this study reports the development of SSR genetic markers for P. cauliflora and P. trunciflora and their usefulness for species taxonomic differentiation at the molecular level.
MATERIALS AND METHODS
Whole-genome low-coverage sequencing was conducted for a single individual of each species to prospect for nuclear SSR markers. Such loci are widely distributed across the genome and do not require deep sequencing for reliable identification, allowing for optimization of time and resources. For Plinia cauliflora, a total of 1.753.597.007 bp were obtained, corresponding to approximately 5× depth coverage (based on a 351 Mb reference genome; Zhao et al. 2024). For Plinia trunciflora, 130.267.748 bp were generated; although no reference genome is available, it may represent around 0.4× depth coverage if the genome size is similar to P. cauliflora. DNA was isolated from healthy leaves using the CTAB method (Doyle & Doyle 1987). Individual genomic libraries were prepared with the SQK-LSK 109 Ligation Sequencing Kit (ONT) and sequenced on a MinION Mk1B platform (ONT) using R9.4 flowcells. Vouchers of the sampled individuals were deposited in the herbarium of the UTFPR/DV (DVPR002095 for P. cauliflora and DVPR002097 for P. trunciflora). Basecalling was performed using Guppy software (ONT), and trimming and contig assembly were conducted using CLC Genomics Workbench 8.0.1 (Qiagen).
SSR loci were identified using GMata 2.3 (Wang & Wang 2016), with a minimum number of six repeats for dinucleotides (dimers) and five for trinucleotides (trimers). Primers were designed using Primer3 (Untergasser et al. 2012). SPCR 3.0 (Cao et al. 2005) was used for virtual PCR amplification and gel electrophoresis of the prospected SSR loci, using the sequenced genomes as templates. SSR loci that returned amplification products within the expected size without overlapping with nonspecific amplified products were considered potentially informative and used for wet-lab validation. The genomic origin of the loci was characterized as gene-linked nuclear, neutral nuclear, plastid, or mitochondrial through BLAST analysis of the contigs against the GenBank database. After locus characterization, sequencing data were deposited in GenBank.
Adult individuals were sampled from one natural population of each species: Plinia trunciflora, in the municipality of Imbituva (IMB), and Plinia cauliflora in the municipality of Chopinzinho (CHO), both in the state of Paraná, Southern Brazil. Individuals were also selected from plantations: one population of P. trunciflora (SEt) and one of P. cauliflora (SEc), both located in the municipality of Seara, state of Santa Catarina, Southern Brazil. In total, 39 individuals were sampled in IMB, 49 in CHO, 25 in SEt, and 52 in SEc. These samples were used for marker validation through PCR genotyping. Total DNA was isolated from healthy leaves following the CTAB protocol. DNA quantity and quality were determined using a NanoDrop 1000® spectrophotometer.
PCR reactions were performed in a Veriti® or a Biometra TProfessional thermocycler. Each reaction contained 1.0× PCR buffer, 1.5 µl MgCl2 (25 mM), 1 U Taq DNA polymerase, 2.5 mM of each dNTP, 1.0 µM forward primer with a M13-tail at the 5’-end, 2.5 µM reverse primer, 2.5 µM M13-labeled fluorescent primer (6-FAM or HEX dyes), and 100 ng template DNA (Schuelke 2000). The PCR program consisted of a denaturation step at 95 °C/15 min, 10 cycles at 94 °C/1 min, 60 °C/1 min (-1 °C per cycle), and 72 °C/1 min, followed by 25 cycles at 94 °C/1 min, 50 °C/1 min, 72 °C/1 min, and a final step of 72 °C/20 min.
Alleles were resolved by capillary electrophoresis using an ABI 3500xL Genetic Analyzer (Applied Biosystems™) with POP-7™ polymer and GeneScan 600-LIZ standard. Allele sizing and genotyping were performed using GeneMapper® 4.1 (Applied BiosystemsTM).
The total number of alleles (A), effective number of alleles (Ae), number of private alleles, observed heterozygosity (Ho), expected heterozygosity (He), fixation index (F), and probability of identity (PI) were estimated using GenAlEx (Peakall & Smouse 2012). Genetic structure between species was explored using the Analysis of Molecular Variance (AMOVA). A Principal Coordinates Analysis (PCoA) was performed based on the pairwise genetic distances between individuals, using GenAlEx. Finally, a Bayesian clustering approach was conducted using Structure software (Pritchard et al. 2000).
RESULTS
After sequencing, cleaning, and assembling, 3.58×108 base pairs were obtained for P. cauliflora and 3.85×108 for P. trunciflora, with Q-score > 20. A total of 24,100 dinucleotides and trinucleotides SSR loci were prospected for P. cauliflora and 9,926 for P. trunciflora.
Based on in silico validation, thirty nuclear markers (fifteen for P. cauliflora and fifteen for P. trunciflora) that successfully amplified within the expected size, and produced distinct, non-overlapping bands (without cross-amplification or non-specific products), were chosen for wet-lab validation. After bench tests, fifteen markers were selected, eight for P. cauliflora and seven for P. trunciflora. Among the markers selected for P. cauliflora, five were dimers and three were trimers. The seven markers developed for P. trunciflora are dimers. All markers were characterized as nuclear neutral or did not match any sequence in the NCBI database.
The number of alleles (A) and effective number of alleles (Ae) in P. trunciflora presented larger genetic variability, with up to nine alleles per locus and Ae reaching 4.108. Plinia cauliflora showed a significantly more restricted diversity pattern (maximum A = 4 and maximum Ae = 2.1). The observed heterozygosity (Ho) was generally higher in P. trunciflora, although P. cauliflora presented Ho = 1.0 in several loci (Table I). The fixation index (F) in P. trunciflora ranged from F = - 0.594 to F = 0.418 and from F = -0.981 to F = 0.496 in P. cauliflora (Table I). Private alleles with a frequency higher than 10% (Table I) were found in P. trunciflora (45 alleles) and Plinia cauliflora (23 alleles). The probability of identity (PI) of the 15 markers was PI = 2.1×10-⁴ for P. cauliflora and PI = 1.6×10-¹⁰ for P. trunciflora.
Characteristics of SSR markers developed for P. cauliflora (CAU set) and P. trunciflora (TRU set), including primer sequences, expected product sizes according to the sequenced loci, and estimations of total number of alleles (A), effective number of alleles (Ae), observed heterozygosity (Ho), expected heterozygosity (He), fixation index (F), number of private alleles (pA) with frequency lower than 10%, and number of private alleles with frequency higher than 10%.
The AMOVA analysis indicated that 85% of genetic variation is found between species, with 15% attributed to variation within species (Figure 1a). Principal Coordinate Analysis based on the pairwise genetic distance among all samples revealed a clear separation between the species. The first two axes explained 94.34% of the total genetic variation, with two well-defined and non-overlapping clusters (Figure 1b).
Genetic structure between Plinia cauliflora and Plinia trunciflora. a) AMOVA analysis of the four populations of both species. b) Principal coordinates analysis based on pairwise genetic distance between individuals. c) Bayesian structure analysis (STRUCTURE) for K = 3. CHO: Chopinzinho (natural population of P. cauliflora); SEc: plantation of P. cauliflora; IMB: Imbituva (natural population of P. trunciflora); SEt: plantation of P. trunciflora.
The Structure analysis revealed a clear separation between P. cauliflora and P. trunciflora. Samples of P. cauliflora present homogeneous genetic profiles, while P. trunciflora revealed distinct clusters for the natural population and the plantation (Figure 1c).
DISCUSSION
The name ‘jaboticabeira’ is widely used to refer to several species belonging to the genera Plinia or Myrciaria (Espíndola 2018). In Brazil, nine distinct species have been recorded. The taxonomic delimitation of these species has been revised, since their morphological similarity often makes accurate identification difficult (Miranda et al. 2024). Plinia trunciflora is characterized by elliptical, oblong, or lanceolate leaves, tetramerous flowers with ovate, oblong, or obovate petals, and globose fruits with elongated peduncles (Espíndola 2018). Similarly, P. cauliflora is recognized by its smooth trunk, elliptical to ovate leaves, and globose fruits (Espíndola 2018).
The SSR markers developed in this study distinguished P. cauliflora and P. trunciflora as two genetically distinct species. The analysis of molecular variance based on genotypic structure revealed 85% of the variation between species, and the principal coordinate analysis delimited two genetic clusters without any overlap, a pattern also returned by the Bayesian structure analysis. The Bayesian clustering analysis also showed high genetic homogeneity between the natural population and the commercial orchard of P. cauliflora (which seems to be formed mostly by clones and is being further investigated). These findings highlight the evolutionary divergence between P. cauliflora and P. trunciflora, reinforcing their taxonomic distinction and providing insights relevant for conservation and breeding programs. On the other hand, P. trunciflora exhibited significant genetic divergence between the sampled populations. The markers’ discriminatory power is also supported by the presence of private alleles in both species, which may be further exploited as markers for species differentiation. Private SSR alleles reported in Psidium (Myrtaceae) were useful in distinguishing closely related species and identifying unique variants with adaptive potential (Tuler et al. 2015). SSR markers also resulted in a clear genetic structuring between wild and cultivated genotypes for Psidium guajava (Kumar et al. 2020).
Furthermore, the data obtained may enhance our understanding of the genetic diversity and structure of P. trunciflora and P. cauliflora populations. The markers’ classification as nuclear and neutral supports their applicability in studies of genetic diversity, population structure, and conservation (Serrote et al. 2023), while the PI estimations confirm their informative power. Plinia trunciflora showed higher genetic diversity compared to P. cauliflora, concerning Ho, A, and Ae. On the other hand, populations from both species presented negative fixation index estimations, suggesting a complex genetic structure influenced by random crossings and an excess of heterozygotes. These negative estimations may reflect a recent history of population restriction, such as geographic isolation or the effects of domestication, vegetative reproduction, and antropogenic use.
CONCLUSIONS
In addition to clarifying the taxonomic differentiation between these two Plinia species, the newly developed SSR markers represent valuable molecular tools for the conservation, improvement, and sustainable use of P. cauliflora and P. trunciflora. These markers can be applied in breeding programs to select superior genotypes, identify potential hybrids, and protect newly developed cultivars.
Acknowledgements
The authors would like to thank Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq/Brazil) for the financial support (Processes 440301/2022-0 and 441879/2018-7) and grant awarded to V.M.S. (Grant number 303673/2021-4) and M.A.D. (Grant number 305500/2022-8), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES/Brazil) for the scholarship to A.K.S.S. (Finance code 001), and to Fundação de Amparo à Pesquisa e Inovação do Estado de Santa Catarina (FAPESC) for the international interchange grant (Grant number 2024TR001021). Funding to O.G. was provided for the AB3500 capillary sequencer by the “Deutsche Forschungsgemeinschaft (DFG) major instrumentation grant (reference number: 458332906) and the “Niedersächsisches Ministerium für Wissenschaft und Kultur” (MWK).
References
-
CAO Y, WANG L, XU K, KOU C, ZHANG Y, WEI G, HE J, WANG Y & ZHAO L. 2005. Information theory-based algorithm for in silico prediction of PCR products with whole genomic sequences as templates. BMC Bioinformatics 6: 190. DOI https://doi.org/10.1186/1471-2105-6-190.
» https://doi.org/10.1186/1471-2105-6-190 - DOS SANTOS DD, OLIVEIRA LO, BEISE DC, OLIVEIRA LM & STEFENON VM. 2021. Biotechnology in Plinia spp: needs and perspectives for a neglected group of fruit species. Biotecnol Veg 21: 3-14.
- DOYLE JJ & DOYLE JL. 1987. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem Bull 19: 11-15.
- ESPÍNDOLA AS. 2018. Caracterização morfológica de espécies de jabuticabeiras (Plinia spp). Dissertação (Mestrado em Agronomia) – Universidade Federal de Viçosa, Viçosa. (Unpublished).
-
KUMAR C, KUMAR R, SINGH SK, GOSWAMI AK, NAGARAJA A, PALIWAL R & SINGH R. 2020. Development of novel g-SSR markers in guava (Psidium guajava L.) cv. Allahabad Safeda and their application in genetic diversity, population structure and cross species transferability studies. PLoS ONE 15(8): e0237538. DOI https://doi.org/10.1371/journal.pone.0237538.
» https://doi.org/10.1371/journal.pone.0237538 -
LUCAS E, HOLST B, SOBRAL M, MAZINE F, NIC LE, PROENÇA C, COSTA I & VASCONCELOS T. 2019. A new subtribal classification of tribe Myrteae (Myrtaceae). Syst Bot 44: 560-569. DOI https://doi.org/10.1600/036364419X15620113920608.
» https://doi.org/10.1600/036364419X15620113920608 -
MACHADO LO, STEFENON VM, VIEIRA LN & NODARI RO. 2022. Structural and evolutive features of the Plinia phitrantha and Plinia cauliflora plastid genomes and evolutionary relationships within tribe Myrteae (Myrtaceae). Genet Mol Biol 45: e20210193. DOI https://doi.org/10.1590/1678-4685-GMB-2021-0193.
» https://doi.org/10.1590/1678-4685-GMB-2021-0193 - MIRANDA SC, DE-CARVALHO PS, REIS LRS, REIS JPBS, STADNIK A, ALMEIDA TF, SOUZA AB & CARNEIRO MF. 2024. Caracterização morfológica de espécies de Plinia sp. L. Bol Tec 4. Goiânia: EMATER-GO.
-
OLIVEIRA GP, ANGELOTTI-MENDONÇA K, TANAKA FAO, SILVA SR & SCARPARE FILHO JA. 2019. Origin and development of reproductive buds in jaboticaba cv Sabará (Plinia jaboticaba Vell). Sci Hortic 249: 432-438. DOI https://doi.org/10.1016/j.scienta.2019.02.020.
» https://doi.org/10.1016/j.scienta.2019.02.020 -
PEAKALL R & SMOUSE PE. 2012. GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update. Bioinformatics 28: 2537-2539. DOI http://dx.doi.org/10.1093/bioinformatics/bts460.
» https://doi.org/10.1093/bioinformatics/bts460 -
PRITCHARD JK, STEPHENS M & DONNELLY P 2000. Inference of population structure using multilocus genotype data. Genetics 155: 945-959. DOI https://doi.org/10.1093/genetics/155.2.945.
» https://doi.org/10.1093/genetics/155.2.945 -
SCHUELKE M. 2000. An economic method for the fluorescent labeling of PCR fragments. Nat Biotechnol 18: 233-234. DOI https://doi.org/10.1038/72708.
» https://doi.org/10.1038/72708 -
SERROTE CML, REINIGER LRS, STEFANEL CM, SILVA KB & GOLLE DP. 2023. Microsatellites are important for forest genetic resources conservation in Brazilian biomes. Acta Bot Bras 37: e20220176. DOI https://doi.org/10.1590/1677-941X-ABB-2022-0176.
» https://doi.org/10.1590/1677-941X-ABB-2022-0176 -
SHINOHARA T, HONDA S, YOSHIDA S, OHO K, IGARASHI D, WAKUI K, OHTAKE R & TANAKA K. 2021. Development of Simple Sequence Repeat (SSR) and morphological markers to identify jaboticaba cultivars. Trop Agric Dev 65: 68-74. DOI https://doi.org/10.11248/jsta.65.68.
» https://doi.org/10.11248/jsta.65.68 -
TULER AC, CARRIJO TT, NÓIA LR, FERREIRA A, PEIXOTO AL & FERREIRA MFS. 2015. SSR markers: a tool for species identification in Psidium (Myrtaceae). Mol Biol Rep 42: 1501-1513. DOI https://doi.org/10.1007/s11033-015-3927-1.
» https://doi.org/10.1007/s11033-015-3927-1 -
UNTERGASSER A, CUTCUTACHE I, KORESSAAR T, YE J, FAIRCLOTH BC, REMM M & ROZEN SG. 2012. Primer3-new capabilities and interfaces. Nucleic Acids Res 40: e115. DOI https://doi.org/10.1093/nar/gks596.
» https://doi.org/10.1093/nar/gks596 -
VASCONCELOS TNC ET AL. 2017. Myrteae phylogeny, calibration, biogeography and diversification patterns: increased understanding in the most species-rich tribe of Myrtaceae. Mol Phylog Evol 109: 113-137. DOI https://doi.org/10.1016/j.ympev.2017.01.002.
» https://doi.org/10.1016/j.ympev.2017.01.002 -
WANG X & WANG L. 2016. GMATA: an integrated software package for genome-scale SSR mining, marker development and viewing. Front Plant Sci 7: 20: 1350. DOI https://doi.org/10.3389/fpls.2016.01350.
» https://doi.org/10.3389/fpls.2016.01350 -
ZHAO L ET AL. 2024. The telomere-to-telomere genome of jaboticaba reveals the genetic basis of fruit color and citric acid content. Int J Mol Sci 25: 11951. DOI https://doi.org/10.3390/ijms252211951.
» https://doi.org/10.3390/ijms252211951
Edited by
-
Handling editor
Mirco Solé
The sequences of the SSR primers are deposited in the NCBI/GenBank database. Further data may be obtained from the Authors.
