Translator Disclaimer
12 May 2017 Chloroplast and Mitochondrial Microsatellites for Millettia pinnata (Fabaceae) and Cross-Amplification in Related Species
Author Affiliations +

Millettia pinnata (L.) Panigrahi (syn. Pongamia pinnata (L.) Pierre; Fabaceae) is an arboreal legume of the subfamily Papilionoideae and, more specifically, of the tribe Millettieae. According to Scott et al. (2008), this species is widely distributed in the Indian subcontinent and Southeast Asia, extending to Polynesia and northern Australia. Historically, this plant has been used as a source of traditional medicine, animal fodder, green manure, timber, fish poison, and fuel in India and neighboring regions (Satyavati et al., 1987). Seeds of M. pinnata contain oils that are inedible but useful for biodiesel, and thus it has received increasing attention as a sustainable biofuel crop in the past decade.

Population genetic studies on M. pinnata have used molecular biological methods including amplified fragment length polymorphisms (AFLPs), three endonuclease (TE)-AFLP (Sharma et al., 2011), inter-simple sequence repeats (ISSRs) (Sahoo et al., 2010; Sharma et al., 2014), and the chloroplast trnK/matK and the internal transcribed spacer (ITS) region of nuclear ribosomal DNA (Hu et al., 2000, 2002; Arpiwi et al., 2013). Huang et al. (2016) developed nuclear simple sequence repeat (SSR) markers for M. pinnata; however, there is still a lack of plastid (chloroplast and mitochondrial) SSR markers capable of detecting high levels of polymorphism in this species. The uniparentally inherited characteristics of chloroplast and mitochondria can supply information on phylogenetic relationships between individuals because their lineages are not disturbed by recombination (Soranzo et al., 1999). In general, for the maternally inherited chloroplast, the higher sequence variations of SSR loci are distributed throughout the noncoding regions and the flanking regions are conserved (Powell et al., 1995), which makes it possible to monitor the population structure affected by pollen flow and seed-mediated gene flow (Provan et al., 2001). The search for mitochondrial SSR (mtSSR) loci might also be informative, although preliminary studies on plant mitochondrial microsatellites have shown little intraspecific variability (Soranzo et al., 1999). Therefore, plastid SSR markers can be effective for analyzing genetic diversity, population structure, paternity inheritance, and germplasm resource identification (Provan et al., 2001).

In this study, we developed a set of novel SSRs based on publicly available chloroplast and mitochondrial genome sequence data of M. pinnata to assess the genetic variation and population genetic structure of this species. Furthermore, we tested the transferability of these markers in the related species M. pulchra (Benth.) Kurz.

METHODS AND RESULTS

In this study, the complete chloroplast and mitochondrial genome sequence data of M. pinnata were downloaded from the National Center for Biotechnology Information (NCBI) GenBank database (GenBank accession no. JN673818.2 and JN872550.1, respectively). The SSR loci distributed throughout the M. pinnata chloroplast and mitochondrial genomes were screened using MISA software (Thiel et al., 2003). The SSR motifs contained one to five nucleotides with the minimum number of repeats as follows: 10 for mononucleotides, five for dinucleotides, four for trinucleotides, and three for tetranucleotides and pentanucleotides. A total of 97 repeat motifs were identified in the chloroplast and mitochondrial genomes, among which the most frequent types were mononucleotides (69 [71.1%]) and dinucleotides (17 [17.5%]), while tri- (5 [5.1%]) and tetranucleotide (6 [6.2%]) motifs were rare. Forty-two loci were selected at random to design primers using Primer3 (Rozen and Skaletsky, 1999), with the optimum conditions set at length of 22 bp (20–26 bp), temperature of 55–60°C, and product size range of 100–500 bp.

Table 1.

Characteristics of 17 novel microsatellite markers developed in Millettia pinnata.

t01_01.gif

Eighty-nine individuals of M. pinnata from four natural populations (Appendix 1) were used to evaluate polymorphism of the target microsatellite loci. Genomic DNA from silica-dried leaves was isolated using the advanced cetyltrimethylammonium bromide (CTAB) method (Doyle, 1991). PCR amplifications were performed in a final volume of 15 µL, containing 30 ng of genomic DNA, 1× PCR buffer (10 mM Tris-HCl [pH 8.4] and 1.5 mM MgCl2; TransGen Biotech Co., Beijing, China), 0.2 mM dNTPs (Bocai Biotech Co., Shanghai, China), 0.5 µM of each primer (BGI Sequencing Co., Beijing, China), and 0.5 units EasyTaq DNA polymerase (TransGen Biotech Co.). PCR reactions were conducted in a Bio-Rad PTC-200 thermal cycler (Bio-Rad Laboratories, Hercules, California, USA) under the following conditions: initial denaturation at 94°C for 4 min; followed by 35 cycles of 94°C for 1 min, 45 s at the specific annealing temperature for each primer pair (Table 1), and 72°C for 60 s; and a final extension of 10 min at 72°C. PCR products were detected using 1.0% agarose gel electrophoresis to test the utility of the primers. Finally, among the 42 selected primer pairs, 40 were successfully amplified but products from only 17 primer pairs exhibited clear SSR polymorphisms. Six individuals from the related species M. pulchra were used to evaluate the transferability of these polymorphic markers applying the 17 screened primers. With the Quant-iT PicoGreen dsDNA Reagent and Kit (including the 35–400-bp Range DNA Ladder; Invitrogen, Carlsbad, California, USA), the Fragment Analyzer Automated CE System (Advanced Analytical Technologies [AATI], Ames, Iowa, USA) was applied to perform SSR genotyping. Raw data were exported, and the number of alleles and allele sizes per locus were called using PROSize software (version 2.0, AATI). All sequences of cpSSR and mtSSR loci were deposited in GenBank, and their accession numbers are presented in Table 1. Because it would be difficult to score the mononucleotide microsatellites consistently, we conducted direct sequencing of the PCR products using the BigDye Terminator v3.1 Cycle Sequencing Kit and ABI PRISM 3730 sequencer (Applied Biosystems, Waltham, Massachusetts, USA) with both forward and reverse primers, to verify the allelic variants tested in this study. Sequences were visualized and analyzed with the DNASTAR software package (DNASTAR, Madison, Wisconsin, USA).

Table 2.

Characterization of 17 novel microsatellite markers in populations of Millettia pinnata and M. pulchra.a

t02_01.gif

The 17 selected primers exhibited high polymorphisms across 89 individuals of four M. pinnata populations. For each of these loci, the number of alleles per population, the number of effective alleles per population, Shannon's information index, and the unbiased haploid diversity (hunb) of each microsatellite locus were calculated using GenAlEx version 6.5 (Peakall and Smouse, 2012). Among chloroplast loci, the number of alleles per locus per population varied from two to six, while hunb ranged from 0.391 to 0.857. For mitochondrial loci, two to four alleles per locus per population were detected and hunb ranged from 0.264 to 0.740 (Table 2). Subsequently, 16 of the 17 developed markers were successfully amplified in the related species M. pulchra, demonstrating their transferability (Table 2).

CONCLUSIONS

The 17 polymorphic SSR markers developed here proved useful in the evaluation of the genetic diversity of M. pinnata, and 16 showed high transferability within the related species M. pulchra. This set of novel polymorphic SSR markers will serve as a very useful tool for the genetic diversity analysis, clonal identification, and germplasm conservation of M. pinnata and its related species.

ACKNOWLEDGMENTS

The authors thank S. He and Y. Liu for their assistance in collecting plant materials. This study was supported by grants from the National Natural Science Foundation of China (31200466 and 41276107), the Natural Science Foundation of Guangdong Province (2015A030313136), the Guangdong Provincial Outstanding Young Teacher Training Foundation (YQ2014030), and the Jin Sui Plan Training Program of the College of Agriculture, South China Agricultural University (20160209 and 20160213).

LITERATURE CITED

1.

Arpiwi, N. L., G. Yan, E. L. Barbour, and J. A. Plummer. 2013. Genetic diversity, seed traits and salinity tolerance of Millettia pinnata (L.) Panigrahi, a biodiesel tree. Genetic Resources and Crop Evolution 60: 677–692. Google Scholar

2.

Doyle, J. J. 1991. DNA protocols for plants. In G. M. Hewitt, A. W. B. Johnston, and J. P. W. Young [eds.], Molecular techniques in taxonomy, 283–293. Springer-Verlag, Berlin, Germany. Google Scholar

3.

Hu, J. M., M. Lavin, M. F. Wojciechowski, and M. J. Sanderson. 2000. Phylogenetic systematics of the tribe Millettieae (Leguminosae) based on chloroplast trnK/matK sequences and its implications for evolutionary patterns in Papilionoideae. American Journal of Botany 87: 418–430. Google Scholar

4.

Hu, J. M., M. Lavin, M. F. Wojciechowski, and M. J. Sanderson. 2002. Phylogenetic analysis of nuclear ribosomal ITS/5.8S sequences in the tribe Millettieae (Fabaceae): Poecilanthe-Cyclolobium, the core Millettieae, and the Callerya group. Systematic Botany 27: 722–733. Google Scholar

5.

Huang, J. Z., X. H. Guo, X. H. Hao, W. K. Zhang, S. Y. Chen, R. F. Huang, P. M. Gresshoff, and Y. Z. Zheng. 2016. De novo sequencing and characterization of seed transcriptome of the tree legume Millettia pinnata for gene discovery and SSR marker development. Molecular Breeding 36: 75. Google Scholar

6.

Peakall, R., and P. E. Smouse. 2012. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research-An update. Bioinfoimatics (Oxford, England) 28: 2537–2539. Google Scholar

7.

Powell, W., M. Morgante, C. Andre, J. W. McNicol, G. C. Machray, J. J. Doyle, S. V. Tingey, and J. A. Rafalski. 1995. Hypervariable microsatellites provide a general source of polymorphic DNA markers for the chloroplast genome. Current Biology 5: 1023–1029. Google Scholar

8.

Provan, J., W. Powell, and P. M. Hollingsworth. 2001. Chloroplast microsatellites: New tools for studies in plant ecology and evolution. Trends in Ecology & Evolution 16: 142–147. Google Scholar

9.

Rozen, S., and H. Skaletsky. 1999. Primer3 on the WWW for general users and for biologist programmers. In S. Misener and S. A. Krawetz [eds.]. Methods in molecular biology, vol. 132: Bioinformatics: Methods and protocols. 365–386. Humana Press. Totowa, New Jersey, USA. Google Scholar

10.

Sahoo, D. P., S. Aparajita, and G. R. Rout. 2010. Inter and intra-population variability of Pongamia pinnata: A bioenergy legume tree. Plant Systematics and Evolution 285: 121–125. Google Scholar

11.

Satyavati, G. V., A. K. Gupta, and N. Tandon. 1987. Medicinal plants of India, vol. 2, p. 490. India Council of Medicinal Research, New Delhi, India. Google Scholar

12.

Scott, P. T., L. Pregelj, N. Chen, J. S. Hadler, M. A. Djordjevic, and P. M. Gresshoff. 2008. Pongamia pinnata: An untapped resource for the biofuels industry of the future. BioEnergy Research 1: 2–11. Google Scholar

13.

Sharma, S. S., M. S. Negi, P. Sinha, K. Kumar, and S. B. Tripathi. 2011. Assessment of genetic diversity of biodiesel species Pongamia pinnata accessions using AFLP and Three Endonuclease-AFLP. Plant Molecular Biology Reporter 29: 12–18. Google Scholar

14.

Sharma, S. S., M. A. Islam, M. S. Negi, and S. B. Tripathi. 2014. Isolation and characterization of a first set of nine polymorphic microsatellite loci in Pongamia pinnata (Fabaceae). Journal of Genetics 93: e70–e74. Google Scholar

15.

Soranzo, N., J. Provan, and W. Powell. 1999. An example of microsatellite length variation in the mitochondrial genome of conifers. Genome 42: 158–161. Google Scholar

16.

Thiel, T., W. Michalek, R. K. Varshney, and A. Graner. 2003. Exploiting EST databases for the development and characterization of gene derived SSR-markers in barley (Hordeum vulgare L.). Theoretical and Applied Genetics 106: 411–422. Google Scholar

Appendices

Appendix 1.

Sampling information for the populations of Millettia pinnata and M. pulchra used in this study.

tA01_01.gif
Yanling Wang, Hongxian Xie, Yi Yang, Yelin Huang, Jianwu Wang, and Fengxiao Tan "Chloroplast and Mitochondrial Microsatellites for Millettia pinnata (Fabaceae) and Cross-Amplification in Related Species," Applications in Plant Sciences 5(5), (12 May 2017). https://doi.org/10.3732/apps.1700034
Received: 10 April 2017; Accepted: 1 April 2017; Published: 12 May 2017
JOURNAL ARTICLE
PAGES


SHARE
ARTICLE IMPACT
Back to Top