Detecting Genetic Mobility Using a Transposon-Based Marker System in Gamma-Ray Irradiated Soybean Mutants
<p>Dendrograms revealed by unweighted pair group method with arithmetic mean cluster analyses and the population structure of soybean MDP lines based on target region amplification polymorphism (TE-TRAP) markers (<b>a</b>) PONG; (<b>b</b>) miniature inverted-repeat transposable element (MITE)-Stowaway, and (<b>c</b>) MITE-Tourist. * Indicates original cultivars. Mutant line abbreviations are based on the names of the original cultivars. HK and BS populations are indicated with green and yellow circles, respectively, 94Seori and DB populations are indicated with green and blue squares, respectively, KAS360 and DP populations are indicated with blue and brown triangles, respectively, and P and 527 populations are indicated with pink and red quadrangles, respectively.</p> "> Figure 2
<p>Two-dimensional principal component analysis ordination of MDP mutant lines based on Pong TE-TRAP marker diversity.</p> ">
Abstract
:1. Introduction
2. Results
2.1. Numbers of Amplicons and Polymorphisms among the TE-TRAP Markers
2.2. Genetic Differentiation
2.3. Analysis of Molecular Variance (AMOVA)
3. Discussion
4. Materials and Methods
4.1. Plant Materials and Genomic DNA Extraction
4.2. TE-TRAP Analysis
4.3. Data Analyses
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Qiu, L.-J.; Xing, L.-L.; Guo, Y.; Wang, J.; Jackson, S.A.; Chang, R.-Z. A platform for soybean molecular breeding: The utilization of core collections for food security. Plant Mol. Biol. 2013, 83, 41–50. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sathyapalan, T.A.M.; Rigby, A.; Thatcher, N.J.; Dargham, S.R.; Kilpatrick, E.S. Soy isoflavones improve cardiovascular disease risk markers in women during the early menopause. Nutr. Metab. Cardiovasc. Dis. 2018, 28, 691–697. [Google Scholar] [CrossRef]
- Hartman, G.L.; West, E.D.; Herman, T.K. Crops that feed the World Soybean—worldwide production, use, and constraints caused by pathogens and pests. Food Secur. 2011, 3, 5–17. [Google Scholar] [CrossRef]
- Young, V.R. Soy protein in relation to human protein and amino acid nutrition. J. Am. Diet. Assoc. 1991, 91, 828–835. [Google Scholar]
- Andrews, M.; Lea, P.; Raven, J.; Azevedo, R. Nitrogen use efficiency. Nitrogen fixation: Genes and costs. Ann. Appl. Biol. 2009, 155, 1–13. [Google Scholar] [CrossRef]
- Jiang, S.-Y.; Ramachandran, S. Natural and artificial mutants as valuable resources for functional genomics and molecular breeding. Int. J. Biol. Sci. 2010, 6, 228–251. [Google Scholar] [CrossRef]
- Ali, H.; Ghori, Z.; Sheikh, S.; Gul, A. Effects of Gamma Radiation on Crop Production. In Crop Production and Global Environmental Issues; Springer: Cham, Switzerland, 2015; pp. 27–78. [Google Scholar]
- Oladosu, Y.; Rafii, M.Y.; Abdullah, N.; Hussin, G.; Ramli, A.; Rahim, H.A.; Miah, G.; Usman, M. Principle and application of plant mutagenesis in crop improvement: A review. Biotechnol. Biotechnol. Equip. 2016, 30, 1–16. [Google Scholar] [CrossRef] [Green Version]
- Beyaz, R. The Use of Gamma Irradiation in Plant Mutation Breeding. Plant Eng. 2017. [Google Scholar] [CrossRef] [Green Version]
- Wallace, S.S. Biological consequences of free radical-damaged DNA. Free. Radic. Biol. Med. 2002, 33, 1–14. [Google Scholar] [CrossRef]
- Killion, D.; Constantin, M.; Siemer, E. Acute gamma irradiation of the soybean plant: Effects of exposure, exposure rate and developmental stage on growth and yield. Radiat. Bot. 1971, 11, 225–232. [Google Scholar] [CrossRef]
- Lee, K.J.; HWang, J.E.; Velusamy, V.; Ha, B.-K.; Kim, J.-B.; Kim, S.H.; Ahn, J.-W.; Kang, S.-Y.; Kim, D.S. Selection and molecular characterization of a lipoxygenase-free soybean mutant line induced by gamma irradiation. Theor. Appl. Genet. 2014, 127, 2405–2413. [Google Scholar] [CrossRef]
- Yuan, F.-J.; Zhu, D.-H.; Tan, Y.-Y.; Dong, D.-K.; Fu, X.-J.; Zhu, S.-L.; Li, B.-Q.; Shu, Q. Identification and characterization of the soybean IPK1 ortholog of a low phytic acid mutant reveals an exon-excluding splice-site mutation. Theor. Appl. Genet. 2012, 125, 1413–1423. [Google Scholar] [CrossRef]
- Jones, P.; Binns, D.; Chang, H.-Y.; Fraser, M.; Li, W.; McAnulla, C.; McWilliam, H.; Maslen, J.; Mitchell, A.; Nuka, G.; et al. InterProScan 5: Genome-scale protein function classification. Bioinformatics 2014, 30, 1236–1240. [Google Scholar] [CrossRef] [Green Version]
- Komatsu, S.; Nanjo, Y.; Nishimura, M. Proteomic analysis of the flooding tolerance mechanism in mutant soybean. J. Proteom. 2013, 79, 231–250. [Google Scholar] [CrossRef]
- McClintock, B. The origin and behavior of mutable loci in maize. Proc. Natl. Acad. Sci. USA 1950, 36, 344–355. [Google Scholar] [CrossRef] [Green Version]
- Kashkush, K.; Feldman, M.; Levy, A.A. Transcriptional activation of retrotransposons alters the expression of adjacent genes in wheat. Nat. Genet. 2003, 33, 102–106. [Google Scholar] [CrossRef] [PubMed]
- Zhang, W.; Lee, H.-R.; Koo, D.-H.; Jiang, J. Epigenetic Modification of Centromeric Chromatin: Hypomethylation of DNA Sequences in the CENH3-Associated Chromatin in Arabidopsis thaliana and Maize. Plant Cell 2008, 20, 25–34. [Google Scholar] [CrossRef] [Green Version]
- Ma, J.; Bennetzen, J.L. Recombination, rearrangement, reshuffling, and divergence in a centromeric region of rice. Proc. Natl. Acad. Sci. USA 2005, 103, 383–388. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Flavell, A.J.; Pearce, S.R.; Kumar, A. Plant transposable elements and the genome. Curr. Opin. Genet. Dev. 1994, 4, 838–844. [Google Scholar] [CrossRef]
- Akakpo, R.; Carpentier, M.; Hsing, Y.I.; Panaud, O. The impact of transposable elements on the structure, evolution and function of the rice genome. New Phytol. 2019, 226, 44–49. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Feschotte, C.E.D.; Jiang, N.; Wessler, S.R. Plant transposable elements: Where genetics meets genomics. Nat. Rev. Genet. 2002, 3, 329–341. [Google Scholar] [CrossRef]
- Du, J.; Grant, D.; Tian, Z.; Nelson, R.T.; Zhu, L.; Shoemaker, R.C.; Ma, J. SoyTEdb: A comprehensive database of transposable elements in the soybean genome. BMC Genom. 2010, 11, 113. [Google Scholar] [CrossRef] [Green Version]
- Schmutz, J.; Cannon, S.B.; Schlueter, J.A.; Ma, J.; Mitros, T.; Nelson, W.; Hyten, D.L.; Song, Q.; Thelen, J.J.; Cheng, J.; et al. Genome sequence of the palaeopolyploid soybean. Nature 2010, 463, 178–183. [Google Scholar] [CrossRef] [Green Version]
- Bilyeu, K.; Ratnaparkhe, M.; Kole, C. Genetics, Genomics, and Breeding of Soybean; CRC Press: Boca Raton, FL, USA, 2016; pp. 1–362. [Google Scholar]
- Park, K.C.; Kim, N.H.; Cho, Y.S.; Kang, K.H.; Lee, J.K.; Kim, N.-S. Genetic variations of AA genome Oryza species measured by MITE-AFLP. Theor. Appl. Genet. 2003, 107, 203–209. [Google Scholar] [CrossRef] [PubMed]
- Lee, J.K.; Park, J.-Y.; Kim, J.-H.; Kwon, S.-J.; Shin, J.-H.; Hong, S.-K.; Min, H.-K.; Kim, N.-S. Genetic mapping of the Isaac-CACTA transposon in maize. Theor. Appl. Genet. 2006, 113, 16–22. [Google Scholar] [CrossRef]
- Kwon, S.-J.; Hong, S.-W.; Son, J.-H.; Lee, J.K.; Cha, Y.-S.; Eun, M.Y.; Kim, N.-S. CACTA and MITE transposon distributions on a genetic map of rice using F15 RILs derived from Milyang 23 and Gihobyeo hybrids. Mol. Cells 2006, 21, 360–366. [Google Scholar]
- Roy, N.S.; Park, K.-C.; Lee, S.-I.; Im, M.-J.; Ramekar, R.V.; Kim, N.-S. Development of CACTA transposon derived SCAR markers and their use in population structure analysis in Zea mays. Genetica 2017, 146, 1–12. [Google Scholar] [CrossRef]
- Zhang, X.; Wessler, S.R. Genome-wide comparative analysis of the transposable elements in the related species Arabidopsis thaliana and Brassica oleracea. Proc. Natl. Acad. Sci. USA 2004, 101, 5589–5594. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Im, S.; Kwon, S.-J.; Ryu, J.; Jeong, S.; Kim, J.; Ahn, J.-W.; Kim, S.; Jo, Y.; Choi, H.-I.; Kang, S.-Y. Development of a transposon-based marker system for mutation breeding in sorghum (Sorghum bicolor L.). Genet. Mol. Res. 2016, 15. [Google Scholar] [CrossRef] [PubMed]
- Hu, J.; Vick, B.A. Target region amplification polymorphism: A novel marker technique for plant genotyping. Plant. Mol. Biol. Report. 2003, 21, 289–294. [Google Scholar] [CrossRef]
- Lee, M.-K.; Lyu, J.I.; Hong, M.J.; Kim, D.-G.; Kim, J.M.; Kim, J.-B.; Eom, S.H.; Ha, B.-K.; Kwon, S.-J. Utility of TRAP markers to determine indel mutation frequencies induced by gamma-ray irradiation of faba bean (Vicia faba L.) seeds. Int. J. Radiat. Biol. 2019, 95, 1160–1171. [Google Scholar] [CrossRef]
- Kikuchi, K.; Terauchi, K.; Wada, M.; Hirano, H. The plant MITE mPing is mobilized in anther culture. Nat. Cell Biol. 2003, 421, 167–170. [Google Scholar] [CrossRef] [PubMed]
- Li, G.; Quiros, C.F. Sequence-related amplified polymorphism (SRAP), a new marker system based on a simple PCR reaction: Its application to mapping and gene tagging in Brassica. Theor. Appl. Genet. 2001, 103, 455–461. [Google Scholar] [CrossRef]
- Hu, J.; Ochoa, O.E.; Truco, M.J.; Vick, B.A. Application of the TRAP technique to lettuce (Lactuca sativa L.) genotyping. Euphytica 2005, 144, 225–235. [Google Scholar] [CrossRef]
- Jiang, N.; Bao, Z.; Zhang, X.; Hirochika, H.; Eddy, S.R.; McCouch, S.R.; Wessler, S.R. An active DNA transposon family in rice. Nat. Cell Biol. 2003, 421, 163–167. [Google Scholar] [CrossRef] [PubMed]
- Roy, N.S.; Choi, J.-Y.; Lee, S.-I.; Kim, N.-S. Marker utility of transposable elements for plant genetics, breeding, and ecology: A review. Genes Genom. 2014, 37, 141–151. [Google Scholar] [CrossRef]
- Kim, D.-G.; Lyu, J.I.; Lee, M.-K.; Kim, J.-M.; Hung, N.N.; Hong, M.J.; Kim, J.-B.; Bae, C.-H.; Kwon, S.-J. Construction of Soybean Mutant Diversity Pool (MDP) Lines and an Analysis of Their Genetic Relationships and Associations Using TRAP Markers. Agronomy 2020, 10, 253. [Google Scholar] [CrossRef] [Green Version]
- Lee, J.K.; Park, J.Y.; Choi, S.H.; Kim, J.H.; Choi, J.K.; Min, H.K.; Kim, N.S. Genetic mapping of maize with the intermated Mo17 x KW7 population using MITE-AFLP and SSR markers. Korean J. Genet. 2004, 26, 63. [Google Scholar]
- Lee, J.K. Genetic Diversity and Interrelationships among Maize Inbred Lines using MITEAFLE. Korean J. Breed 2002, 34, 356–362. [Google Scholar]
- Andrew, K.; Lee, J.K.; Park, J.Y.; Kwon, S.J. Genetic Diversity among Waxy Corn Inbred Lines Revealed by CACTA-TD Markers. Korean J. Breed 2004, 36, 200–206. [Google Scholar]
- Kurowska, M.; Labocha-Pawłowska, A.; Gnizda, D.; Maluszynski, M.; Szarejko, I. Molecular analysis of point mutations in a barley genome exposed to MNU and gamma rays. Mutat. Res. Mol. Mech. Mutagen. 2012, 52–70. [Google Scholar] [CrossRef] [PubMed]
- Kang, E.-J.; Lee, Y.-M.; Sung, S.Y.; Ha, B.-K.; Kim, S.H.; Kim, N.S.; Kim, J.-B.; Kang, S.-Y. Analysis of the genetic relationship of gamma-irradiated in vitro mutants derived from standard-type chrysanthemum cv. Migok. Hortic. Environ. Biotechnol. 2013, 54, 76–81. [Google Scholar] [CrossRef]
- Singh, S.; Nandha, P.S.; Singh, J. Transposon-based genetic diversity assessment in wild and cultivated barley. Crop. J. 2017, 5, 296–304. [Google Scholar] [CrossRef]
- Lai, J.; Li, Y.; Messing, J.; Dooner, H.K. Gene movement by Helitron transposons contributes to the haplotype variability of maize. Proc. Natl. Acad. Sci. USA 2005, 102, 9068–9073. [Google Scholar] [CrossRef] [Green Version]
- Morgante, M.; Brunner, S.; Pea, G.; Fengler, K.; Zuccolo, A.; Rafalski, A.J. Gene duplication and exon shuffling by helitron-like transposons generate intraspecies diversity in maize. Nat. Genet. 2005, 37, 997–1002. [Google Scholar] [CrossRef] [PubMed]
- Nandini, B. Miniature inverted-repeat transposable elements (MITEs), derived insertional polymorphism as a tool of marker systems for molecular plant breeding. Mol. Biol. Rep. 2020, 47, 3155–3167. [Google Scholar] [CrossRef]
- Macko, A.; Grzebelus, D. DcMaster transposon display markers as a tool for diversity evaluation of carrot breeding materials and for hybrid seed purity testing. J. Appl. Genet. 2008, 49, 33–39. [Google Scholar] [CrossRef] [PubMed]
- Weiss, J.; Mallona, I.; Gómez, P.; Fernández-Valera, J.M.; Egea-Cortines, M. Genotyping Antirrhinum commercial varieties using miniature inverted-repeat transposable elements (MITEs). Sci. Hortic. 2012, 144, 161–167. [Google Scholar] [CrossRef]
- Rozewicki, J.; Li, S.; Amada, K.M.; Standley, D.M.; Katoh, K. MAFFT-DASH: Integrated protein sequence and structural alignment. Nucleic Acids Res. 2019, 47, W5–W10. [Google Scholar] [CrossRef]
- Liu, K.; Muse, S.V. PowerMarker: An integrated analysis environment for genetic marker analysis. Bioinformatics 2005, 21, 2128–2129. [Google Scholar] [CrossRef] [Green Version]
- Nei, M. Genetic Distance between Populations. Am. Nat. 1972, 106, 283–292. [Google Scholar] [CrossRef]
- Peakall, R.; Smouse, P.E. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research—An update. Bioinformatics 2012, 28, 2537–2539. [Google Scholar] [CrossRef] [PubMed] [Green Version]
MITE 1-Tourist | MITE-Stowaway | PONG | |
---|---|---|---|
Numbers of fragments | 139 | 162 | 106 |
Numbers of polymorphic fragments | 73 | 98 | 66 |
Percentages of polymorphic fragments (%) | 53.4 | 59.9 | 60.7 |
Numbers of monomorphic fragments | 66 | 64 | 40 |
Percentages of monomorphic fragments (%) | 47.6 | 40.1 | 39.3 |
PIC values | 0.12 | 0.14 | 0.15 |
Primer Combination | Total Number of Fragments | Polymorphic Fragments | Polymorphism (%) | PIC |
---|---|---|---|---|
MITE 1-Stowaway + Sa4 | 39 | 15 | 38.46 | 0.09 |
MITE-Stowaway + Sa12 | 33 | 22 | 66.67 | 0.15 |
MITE-Stowaway + Ga3 | 32 | 21 | 65.63 | 0.17 |
MITE-Stowaway + Ga5 | 35 | 15 | 42.86 | 0.09 |
Total/Average | 139 | 73 | 53.40 | 0.12 |
MITE-Tourist + Sa4 | 47 | 28 | 59.57 | 0.14 |
MITE-Tourist + Sa12 | 46 | 31 | 67.39 | 0.14 |
MITE-Tourist + Ga3 | 32 | 17 | 53.13 | 0.14 |
MITE-Tourist + Ga5 | 37 | 22 | 59.46 | 0.15 |
Total/Average | 162 | 98 | 59.89 | 0.14 |
PONG + Sa4 | 31 | 24 | 74.42 | 0.20 |
PONG + Sa12 | 24 | 13 | 54.17 | 0.13 |
PONG + Ga3 | 29 | 16 | 55.17 | 0.15 |
PONG + Ga5 | 22 | 13 | 59.09 | 0.11 |
Total/Average | 106 | 66 | 61.46 | 0.15 |
Total | 407 | 237 | ||
Average | 33.92 | 19.75 | 58 | 0.14 |
Est. Var. | Percentage of Variation | |
---|---|---|
PONG | ||
Among pop. | 3.151 | 29% |
Within pop. | 7.646 | 71% |
Total | 10.797 | 100% |
MITE 1-Stowaway | ||
Among pop. | 2.209 | 20% |
Within pop. | 8.957 | 80% |
Total | 11.166 | 100% |
MITE-Tourist | ||
Among pop. | 2.766 | 18% |
Within pop. | 12.385 | 82% |
Total | 15.151 | 100% |
Primer Name | Sequence (5′–3′) |
---|---|
Fixed primers | |
MITE 1-Stowaway | CTT WTA DTT AGG GAY ARA GGG AG |
MITE-Tourist | AAT TYT CTA TCC AAA CRC ACT C |
PONG | AGA ARC CTG CAY TGG AGA TGC TC |
Arbitrary primers | |
Sa4 | TTA CCT TGG TCA TAC AAC ATT |
Sa12 | TTC TAG GTA ATC CAA CAA CA |
Ga3 | TCA TCT CAA ACC ATC TAC AC |
Ga5 | GGA ACC AAA CAC ATG AAG A |
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Hung, N.N.; Kim, D.-G.; Lyu, J.I.; Park, K.-C.; Kim, J.M.; Kim, J.-B.; Ha, B.-K.; Kwon, S.-J. Detecting Genetic Mobility Using a Transposon-Based Marker System in Gamma-Ray Irradiated Soybean Mutants. Plants 2021, 10, 373. https://doi.org/10.3390/plants10020373
Hung NN, Kim D-G, Lyu JI, Park K-C, Kim JM, Kim J-B, Ha B-K, Kwon S-J. Detecting Genetic Mobility Using a Transposon-Based Marker System in Gamma-Ray Irradiated Soybean Mutants. Plants. 2021; 10(2):373. https://doi.org/10.3390/plants10020373
Chicago/Turabian StyleHung, Nguyen Ngoc, Dong-Gun Kim, Jae Il Lyu, Kyong-Cheul Park, Jung Min Kim, Jin-Baek Kim, Bo-Keun Ha, and Soon-Jae Kwon. 2021. "Detecting Genetic Mobility Using a Transposon-Based Marker System in Gamma-Ray Irradiated Soybean Mutants" Plants 10, no. 2: 373. https://doi.org/10.3390/plants10020373