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. 2016 Apr 18;4(4):apps.1500110. doi: 10.3732/apps.1500110

Development and characterization of 14 microsatellite markers for Indigofera pseudotinctoria (Fabaceae)1

Tomoko Otao 2, Tatsuaki Kobayashi 2, Koichi Uehara 2,3
PMCID: PMC4850052  PMID: 27144104

Abstract

Premise of the study:

Microsatellite markers can be used to evaluate population structure and genetic diversity in native populations of Indigofera pseudotinctoria (Fabaceae) and assess genetic disturbance caused by nonnative plants of the same species.

Methods and Results:

We developed 14 markers for I. pseudotinctoria using next-generation sequencing and applied them to test two native populations, totaling 77 individuals, and a transplanted population, imported from a foreign country, of 17 individuals. The mean number of alleles was 3.310, observed heterozygosity was 0.242, and expected heterozygosity was 0.346. The fixation index in the transplanted population was 0.469, which was higher than in the native populations (0.154 and 0.158). In addition, the transplanted population contains one allele that is not shared by the native population.

Conclusions:

Microsatellite markers can be useful for evaluating genetic diversity within and between populations and for studying population genetics in I. pseudotinctoria and related species.

Keywords: 454 next-generation sequencing, Fabaceae, Indigofera pseudotinctoria, invasive species, microsatellites


Genetic disturbances caused by invasive species reduce biodiversity in native populations (Byrne et al., 2011). Invasive, nonnative species are strictly regulated by species name to prevent their introduction into the native range. However, regulation is difficult when nonnative plants belong to the same species as native plants. In Japan, seeds used to vegetate roadsides after maintenance projects are usually imported from China, South Korea, and Taiwan (Uemachi et al., 2013) due to the lower cost of seed collection and transportation. In many cases, plants of the same species differ genetically between regions. Therefore, imported plants can cause genetic disturbance of native populations (McKay et al., 2005; Shimono et al., 2013), which may result in outbreeding depression between native and transplanted populations via secondary contact between these populations (Rhymer and Simberloff, 1996; Ewel et al., 1999; Allendorf et al., 2001).

Indigofera L. (Fabaceae) is a large pantropical genus containing 750 species. Among these, I. pseudotinctoria Matsum. is an economically important species distributed in China, Korea, and Japan (Satake et al., 1982) and used as a cover crop. The artificial migration of this species from China to Japan may affect native biodiversity. Therefore, it is important to develop a set of markers to study genetic disturbance in native populations caused by transplanted populations.

In this study, we designed microsatellite markers for I. pseudotinctoria and developed 14 microsatellite primers using 454 next-generation sequencing to identify appropriate transplanting zones based on genetic differentiation between nonnative and native I. pseudotinctoria populations.

METHODS AND RESULTS

Three populations were evaluated in this study: two native and one transplanted. The native populations were collected from Tokyo (n = 38) and Saitama Prefecture (n = 39), while the imported population was transplanted into an area in Mie Prefecture (n = 17). Individuals of the Mie population were imported from unspecified locations in China. Furthermore, we collected an additional seven species and two forms of the genus Indigofera: I. bungeana Walp., I. tinctoria L., I. gerardiana Graham ex Baker, I. decora Lindl., I. decora f. alba (Sarg.) Honda (for each taxon, n = 1), I. kirilowii Maxim. ex Palibin, I. pseudotinctoria f. albiflora Okuyama, I. trifoliata L., and I. suffruticosa Mill. (for each taxon, n = 2) (Appendix 1).

Total genomic DNA was extracted from leaf tissue using a DNeasy Plant Mini Kit (QIAGEN, Venlo, The Netherlands) and the cetyltrimethylammonium bromide method (CTAB) (Porebski et al., 1997). DNA was subjected to shotgun sequencing using a Roche 454 Genome Sequencer Junior with the GS FLX Titanium Rapid Library Preparation Kit (454 Life Sciences, a Roche Company, Basel, Switzerland) according to the manufacturer’s instructions. One sample of I. pseudotinctoria used in shotgun sequencing was obtained from the sample native to Nagano Prefecture.

DNA library sequencing resulted in 15,243 reads of 32–662 bp. We found 572 contigs of 60–660 bp using CLC Genomics Workbench version 5.5 (QIAGEN). Microsatellite motifs were found in 533 reads using MSATCOMMANDER (Faircloth, 2008). Many microsatellite motifs had repeats that were either too long or too short or comprised single base pair repeats. Primer3 (Koressaar and Remm, 2007; Untergasser et al., 2012) was used to design primers for 63 loci, of which 25 were polymorphic. Eleven loci were excluded because of weak PCR amplification or difficulty in identifying the peaks. Therefore, a total of 14 microsatellite loci were selected, and the fragments were amplified by touchdown PCR using a QIAGEN Multiplex PCR Kit with fluorescent primer pairs for each microsatellite (Table 1). The 14 loci include AAJSO, ACUJQ, AN24U, AUHSL, AZQ4M, A7G7T, A913S, BSN57, BTPFL, BP01Y, B0L6E, AQ11D, A2T7M, and AHK5H. The number of microsatellite motifs was detected by resequencing the I. pseudotinctoria sample from Nagano Prefecture. Fluorescent primer pairs were labeled using Dye Set G5 (Applied Biosystems by Thermo Fisher Scientific, Waltham, Massachusetts, USA). Primer combinations used in a multiplex PCR are given in Table 1. PCR was conducted in 10-μL reactions containing 20 ng/μL genomic DNA, 5 μM each primer, and 5 μL QIAGEN Multiplex PCR Master Mix. The following touchdown PCR profile was used for all multiplex PCR reactions: initial denaturation for 15 min at 94°C; followed by three cycles of 3 s at 94°C, 90 s at 65°C (54°C), and 1 min at 72°C; three cycles of 3 s at 94°C, 90 s at 62°C (51°C), and 1 min at 72°C; 30 cycles of 3 s at 94°C, 90 s at 59°C (48°C), and 1 min at 72°C; and final elongation for 30 min at 60°C. PCR products were analyzed using an ABI Prism 3130 sequencer and visualized with GeneMapper (Applied Biosystems, Grand Island, New York, USA). The size standard was GeneScan 600 LIZ Size Standard (Applied Biosystems). The significance of linkage disequilibrium (LD) was calculated with CERVUS 3.03 (Kalinowski et al., 2007); the number of alleles (A), allelic richness (AR), and fixation index (FIS) were determined with FSTAT 2.9.3 (Goudet, 2001); and observed heterozygosity (Ho), expected heterozygosity (He), and Hardy–Weinberg equilibrium (HWE) were analyzed with GenAlEx 6.5 (Peakall and Smouse, 2012). The allele-sharing distance (ASD) matrix was calculated using Excel Microsatellite Toolkit 3.3.1 (Park, 2001).

Table 1.

Characteristics of 14 microsatellite markers developed for Indigofera pseudotinctoria.

Locus Primer sequences (5′–3′) Repeat motif Multiplexa Fluorescent dye Allele size range (bp) Ta (°C) A DDBJ accession no.
A7G7T F: TGCAATCTCCCGTCGCATATTC (AAT)12 1 PET 258–267 60 5 AB827329
R: TGAGGAGTTGAGGTCTTGTG
A913S F: CGTGTCGTGAGAGAATGAGTTTGG (AAT)8(AAG)2 1 VIC 179–188 60 4 AB827330
R: CCGTTAGGGTTTTCTGGTTGGTAG
AAJSO F: CAAGGGCCAAGCAAGAACAAC (TTA)10T(TTA)3 3 6-FAM 303–326 60 9 AB827331
R: GTTAGTGTCAGCCCCTCCTTCC
ACUJQ F: GCTGATTGTTTCCTACCTA (AAT)17 3 VIC 195–221 60 10 AB827332
R: AGCATCAAACTTCATCACAG
AN24U F: CATTGGAGCAGGTGTTTCGACG (AAC)4…(GAA)7 1 VIC 246–249 60 4 AB827333
R: CGTCCAAAAGCTCCATTATCGTCA
AUHSL F: TGGGTTGCTTCATGTTGCC (CCT)8 2 VIC 312–328 60 6 AB827334
R: GGTTCCTCACTGCATATC
AZQ4M F: GGAAAATAGAGAAGGGTAGGAC (GA)9 2 6-FAM 261–269 60 7 AB827335
R: GGTCCATCAAATCCATCTCTCTC
BSN57 F: AGCTCCGACACCTGTTTTGA (AT)3AATT(TA)5(AT)3A(ATATA)2(ATA)3 3 PET 150–170 60 7 AB827337
R: GAGGAAAAAGCATTCGGGTA
BTPFL F: GTCGTCGTGTCGTGAGAGAA (AAT)8 2 PET 188–197 60 5 AB827338
R: ACGCCTAGGGTTTTCTGGTT
BP01Y F: CGTTTTGTTTTCTTCTGTACTGGAC (TTTGCA)6 5 VIC 231–249 48 5 AB917736
R: CACTAGTCAATCAACCGAAAAAGAG
B0L6E F: CATTGTGGCATCGTTGATTC (TTG)9 5 6-FAM 175–194 48 7 AB917737
R: GTCATGATGATATTACTGAGGAACG
AQ11D F: ATTTTCCAGTCCACCAACTGAT (TTA)6 4 VIC 210–275 48 5 AB917738
R: TCTAATCCCGTGTAATGTGTGC
A2T7M F: AAGAGTTCACTAGCCTTCTTTGGA (TTC)8 5 NED 177–199 48 6 AB917739
R: AAACTAGAACCTGGTGGTTCCTC
AHK5H F: GATCTCCTTGGTGGTCTCTGATA (TTC)10 4 6-FAM 198–213 48 8 AB917740
R: GCGTCTTCGTGAACTTGTTACAT

Note: A = expressed total number of alleles; DDBJ = DNA Data Bank of Japan; Ta = annealing temperature.

a

Multiplex PCR primer combination.

No LD was observed in any of the studied populations. The mean number of alleles across populations was 3.310, Ho was 0.000–0.718 (mean 0.242), and He was 0.000–0.820 (mean 0.346). The Mie population showed higher He (e.g., 0.78 for the B0L6E locus) than Ho (e.g., 0.06 for the B0L6E locus) (Table 2).

Table 2.

Polymorphism analysis of 14 microsatellite markers in three populations of Indigofera pseudotinctoria.

Tokyo (N = 38) Saitama (N = 39) Mie (N = 17)
Locus A AR Ho He FISa A AR Ho He FISa A AR Ho He FISa
AAJSO 1.000 1.000 0.000 0.000 NA 6.000 1.000 0.385 0.526 0.280*** 7.000 7.000 0.471 0.820 0.451**
ACUJQ 3.000 2.942 0.211 0.278 0.255*** 6.000 5.807 0.564 0.776 0.285*** 7.000 7.000 0.588 0.787 0.281***
AN24U 1.000 1.000 0.000 0.000 NA 1.000 1.000 0.000 0.000 NA 4.000 4.000 0.412 0.469 0.152**
AUHSL 1.000 1.000 0.00 0.000 NA 4.000 3.120 0.308 0.3106 0.008 5.000 5.000 0.353 0.666 0.493
AZQ4M 2.000 1.913 0.105 0.100 −0.042 6.000 5.364 0.718 0.646 −0.098 2.000 2.000 0.059 0.161 0.652**
A7G7T 2.000 1.913 0.105 0.100 −0.042 1.000 1.000 0.000 0.000 NA 5.000 5.000 0.588 0.701 0.190
A913S 3.000 2.993 0.395 0.405 0.040* 2.000 1.949 0.077 0.120 0.370* 3.000 3.000 0.294 0.503 0.441
BSN57 3.000 2.953 0.316 0.351 0.115 2.000 1.826 0.077 0.074 −0.027 4.000 4.000 0.235 0.559 0.599**
BTPFL 3.000 2.992 0.395 0.389 0.001 2.000 1.949 0.077 0.120 0.370* 4.000 4.000 0.176 0.618 0.729***
BP01Y 3.000 2.992 0.474 0.658 0.293 4.000 3.436 0.538 0.641 0.172 2.000 2.000 0.059 0.057 0.000
B0L6E 3.000 2.401 0.158 0.147 −0.060 2.000 1.436 0.026 0.025 0.000 6.000 6.000 0.059 0.777 0.929**
AQ11D 1.000 1.000 0.00 0.000 NA 2.000 1.436 0.026 0.025 0.000 5.000 5.000 0.118 0.396 0.718***
A2T7M 1.000 1.000 0.026 0.000 NA 2.000 1.905 0.051 0.197 0.483** 5.00 5.000 0.588 0.709 0.200
AHK5H 3.000 2.913 0.342 0.481 0.30* 3.000 2.973 0.487 0.541 0.113** 7.00 7.00 0.294 0.521 0.459

Note: A = number of alleles; AR = allelic richness; FIS = fixation index; He = expected heterozygosity; Ho = observed heterozygosity; N = number of individuals sampled; NA = not analyzed.

a

Significant deviation from Hardy–Weinberg equilibrium in each population is indicated as *P < 0.05, **P < 0.01, and ***P < 0.001.

The Mie population also deviated from HWE because the seeds from this population did not result from natural breeding but originated from different locations in China and were translocated to the Mie Prefecture. The mean number of alleles per population was 2.142 for the Tokyo population, 3.071 for the Saitama population, and 4.714 for the Mie population. The mean FIS was 0.154 for the Tokyo population, 0.158 for the Saitama population, and 0.469 for the Mie population, as analyzed by FSTAT (Goudet, 2001).

A and FIS were low in the Tokyo and Saitama populations (Table 2). Higher levels of polymorphism were found in the Mie population (2–7, mean 4.714) than in the Saitama (1–3, mean 2.07) or Tokyo populations (1–5.80, mean 2.74) (Table 2). The ASD matrix was calculated from the number of shared alleles among individual pairwise allele-sharing distances; the resulting values were 0.429–0.893, 0.071–0.464, and 0.071–0.429 for the Tokyo–Saitama, Mie–Saitama, and Mie–Tokyo populations, respectively. Indigofera pseudotinctoria and I. pseudotinctoria f. albiflora were amplified using 14 markers, whereas I. trifoliata, I. decora f. alba, and I. kirilowii were amplified using 10 markers and I. tinctoria, I. gerardiana, and I. decora were amplified using nine markers (Table 3).

Table 3.

Cross-amplification and polymorphism analysis of 14 microsatellite markers developed for Indigofera pseudotinctoria in nine species of Indigofera.a

Locus I. bungeana (N = 1) I. decora (N = 1) I. decora f. alba (N = 1) I. gerardiana (N = 1) I. kirilowii (N = 1) I. pseudotinctoria f. albiflora (N = 2) I. suffruticosa (N = 2) I. tinctoria (N = 1) I. trifoliata (N = 2)
AAJSO ++ + ++ +
ACUJQ ++ ++ + ba
AN24U ++ + + + ba ba
AUHSL ++ ++ +
AZQ4M ba + ba ba +
A7G7T + + + + + + +
A913S ++ + + + + + + + +
BSN57 + + ++ + + + + +
BTPFL + + + ++ +
BP01Y + + + + ++ + +
B0L6E + + + + + + + + +
A2T7M + + + + + + + + +
AHK5H + + + + + + ++ +
AQ11D + + + + + + + + +

Note: — = no amplification product; + = single band; ++ = two bands; ba = stuttered amplification; N = number of individuals sampled.

a

The expected single band in three populations of nine Indigofera spp.

CONCLUSIONS

Population assessment with 14 microsatellite markers revealed that the nonnative population was highly polymorphic, included alleles different from those in native populations, and the difference was not due to neutral variation. Our results indicate that the transplanted and native populations did not share the few same alleles and that the Mie population had few unique alleles. To compare the origin of Chinese and Japanese populations, natural populations of China should be analyzed. Overall, microsatellite markers developed in this study could be used to discriminate native from nonnative I. pseudotinctoria individuals in Japan and determine genetic disturbance in native populations caused by imported plants.

Appendix 1.

Voucher information for 10 taxa in the genus Indigofera used in this study.

Species Locality Geographic coordinates/Location Origin of sample Institutea Herbarium Herbarium voucher no.
I. bungeana Walp. Tokyo 1833-81 Todori, Hachioji City, Tokyo Herbarium Tama Forest Science Garden Tama Forest Science Garden TFA51609
I. decora Lindl. Unknown 648 Matsudo, Matsudo City, Chiba Prefecture Purchased Graduate School of Horticulture, Chiba Univ. Graduate School of Horticulture, Chiba Univ. MTDO4130
I. decora Lindl. f. alba (Sarg.) Honda Tochigi 1842 Hanaishi, Nikko City, Tochigi Prefecture Cultivated Koishikawa Botanical Garden Graduate School of Horticulture, Chiba Univ. MTDO4124
I. gerardiana Graham ex Baker Tokyo 1833-81 Todori, Hachioji City, Tokyo Herbarium Tama Forest Science Garden Tama Forest Science Garden TFA014490
I. kirilowii Maxim. ex Palib. Ibaragi 4-1-1 Amakubo, Tukuba City, Ibaragi Prefecture Cultivated Tsukuba Botanical Garden Graduate School of Horticulture, Chiba Univ. MTDO4128
I. pseudotinctoria Matsum. Nagano 648 Matsudo, Matsudo City, Chiba Prefecture Purchased Graduate School of Horticulture, Chiba Univ. Graduate School of Horticulture, Chiba Univ. MTDO4134
I. pseudotinctoria Matsum. Tokyo 35°35′29.0″N, 139°25′45.1″E Local Graduate School of Horticulture, Chiba Univ. MTDO4137
I. pseudotinctoria Matsum. Saitama 36°08′17.5″N, 139°19′55.9″E Local Graduate School of Horticulture, Chiba Univ. MTDO4140
I. pseudotinctoria Matsum. Mie 34°20′02.8″N, 136°48′31.1″E Local Graduate School of Horticulture, Chiba Univ. MTDO4143
I. pseudotinctoria Matsum. f. albiflora Okuyama Kanagawa 35°19′22.60″N, 139°34′16.15″E Cultivated Zyomiyouzi Temple in Kamakura City Graduate School of Horticulture, Chiba Univ. MTDO4120
I. suffruticosa Mill. Toyama Kamikutuwada 42, Toyama City, Toyama Prefecture Cultivated Botanic Gardens of Toyamab Graduate School of Horticulture, Chiba Univ. MTDO4151
I. tinctoria L. Toyama Kamikutuwada 42, Toyama City, Toyama Prefecture Cultivated Botanic Gardens of Toyamab Graduate School of Horticulture, Chiba Univ. MTDO4146
I. trifoliata L. Okinawa 35°35′29.0″N, 139°25′45.1″E Local Graduate School of Horticulture, Chiba Univ. MTDO4129
a

Institute whose personnel collected the samples. Koishikawa Botanical Garden = Koishikawa Botanical Garden, University of Tokyo; Tama Forest Science Garden = Tama Forest Science Garden, Forestry and Forest Products Research Institute; Tsukuba Botanical Garden = Tsukuba Botanical Garden, National Science Museum.

b

Accession numbers of the Botanic Gardens of Toyama: 48223 (I. suffruticosa) and BGT45639 (I. tinctoria).

LITERATURE CITED

  1. Allendorf F. W., Leary R. F., Spruell P., Wenburg J. K. 2001. The problems with hybrids: Setting conservation guidelines. Trends in Ecology & Evolution 16: 613–622. [Google Scholar]
  2. Byrne M., Stone L., Millar M. A. 2011. Assessing genetic risk in vegetation. Journal of Applied Ecology 48: 1365–1373. [Google Scholar]
  3. Ewel J. J., O’Dowd D. J., Bergelson J., Daehler C. C., D’Antonio C. M., Gomez L. D., Gordon D. R., et al. 1999. Deliberate introductions of species: Research needs. Bioscience 49: 619–630. [Google Scholar]
  4. Faircloth B. C. 2008. MSATCOMMANDER: Detection of microsatellite repeat arrays and automated, locus-specific primer design. Molecular Ecology Resources 8: 92–94. [DOI] [PubMed] [Google Scholar]
  5. Goudet J. 2001. FSTAT: A program to estimate and test gene diversities and fixation indices, version 2.9.3, March 2004. Website http://www2.unil.ch/popgen/softwares/fstat.htm [accessed 31 January 2013].
  6. Kalinowski S. T., Taper M. L., Marshall T. C. 2007. Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Molecular Ecology 16: 1099–1106. [DOI] [PubMed] [Google Scholar]
  7. Koressaar T., Remm M. 2007. Enhancements and modifications of primer design program Primer3. Bioinformatics (Oxford, England) 23: 1289–1291. [DOI] [PubMed] [Google Scholar]
  8. McKay J. K., Christian C. E., Harrison S., Rice K. J. 2005. “How local is local?” A review of practical and conceptual issues in the genetics of restoration. Restoration Ecology 13: 432–440. [Google Scholar]
  9. Park S. D. E. 2001. Trypanotolerance in West African cattle and the population genetics effects of selection. Ph.D. thesis, University of Dublin, Dublin, Ireland.
  10. Peakall R., Smouse P. E. 2012. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research—An update. Bioinformatics (Oxford, England) 28: 2537–2539. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Porebski S., Bailey L. G., Baum B. R. 1997. Modification of a CTAB DNA extraction protocol for plants containing high polysaccharide and polyphenol components. Plant Molecular Biology Reporter 15: 8–15. [Google Scholar]
  12. Rhymer J. M., Simberloff D. 1996. Extinction by hybridization and introgression. Annual Review of Ecology and Systematics 27: 83–109. [Google Scholar]
  13. Satake Y., Ohwi J., Kitamura S., Shunji W., Tadao T. 1982. Leguminosae (Fabaceae). In H. Ohashi , Wild flowers of Japan 2: Herbaceous plants (including dwarf subshrubs), 186–190. Heibonsha, Tokyo, Japan. [Google Scholar]
  14. Shimono Y., Hayakawa H., Kurokawa S., Nishida T., Ikeda H., Futagami N. 2013. Phylogeography of mugwort (Artemisia indica), a native pioneer herb in Japan. Journal of Heredity 104: 830–841. [DOI] [PubMed] [Google Scholar]
  15. Uemachi A., Fukui W., Shimomura T. 2013. Identification of Trachelospermum plants and detection of hybrids using RAPD analysis. Journal of the Japanese Society of Revegetation Technology 39: 9–14. [Google Scholar]
  16. Untergasser A., Cutcutache I., Koressaar T., Ye J., Faircloth B. C., Remm M., Rozen S. G. 2012. Primer3—New capabilities and interfaces. Nucleic Acids Research 40: e115. [DOI] [PMC free article] [PubMed] [Google Scholar]

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