BIO Web Conf.
Volume 25, 2020International Scientific Online-Conference “Bioengineering in the Organization of Processes Concerning Breeding and Reproduction of Perennial Crops” 2020
|Number of page(s)||4|
|Section||DNA Technology in Producing New Varieties of Permanent Crops with Specified Features and Simplified Identification of Genotypes|
|Published online||01 October 2020|
Molecular genetic analysis of strawberry genotypes for the FaOMT fruit aroma gene
Federal State Scientific Institution “I.V. Michurin Federal Science Center”, 30. Michurin st., Michurinsk, Tambov region, Russia, 393774
* Corresponding author: firstname.lastname@example.org
The results of the analysis of allelic polymorphism of strawberry varieties and forms for the FAOMT fruit aroma gene were shown. The non-functional allele FaOMT- in the homozygous state was detected in strawberry variety Quicky. Heterozygous genotype (FaOMT+FaOMT-) was identified in the strawberry varieties Feyerverk, Ostara, Polka and Symphony, and selected forms 26-5 and 928-12. The functional allele FaOMT gene (FaOMT+) in the homozygous state (FaOMT+FaOMT+ genotype) was detected in strawberry varieties Borovitskaya, Kubata, Troitskaya, Tsaritsa, Yarkaya, Korona and Vima Kimberly, and selected forms 932-29 and 298-19-9-43, which allows us to be used as valuable initial forms in breeding for fruit aroma.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Strawberry is one of the most widespread berry crops in the world. Its popularity is due to such traits as early harvest maturity, dessert taste, aroma and rich biochemical composition of the fruit [1, 2]. It should be noted that the strawberry breeding is mainly aimed at improving the commercial qualities of fruits, productivity and plant resistance to unfavorable biotic factors, while the improvement of such consumer qualities as the biochemical composition and aroma of fruits was carried out insufficiently, which led to a decrease in these traits in many widely cultivated strawberry varieties [3, 4].
The pleasant aroma of strawberry fruits is due to the content of a large amount of volatile organic compounds. In strawberry fruits over 360 volatile compounds reported [5-7]. The most important components of the aromatic profile of strawberry fruits are about 20 volatile compounds. These include 2,5-dimethyl-4-hydroxy-3 (2H)-furanone (furaneol) and 4-methoxy-2,5-dimethyl-3-furanone (mesifurane). Furaneol and mesifurane add sweet and caramel notes to the strawberry aroma [8, 9].
The furanones content in strawberry fruits are dependent on the genotype, the degree of fruit maturity and environmental conditions during their growth and development [3, 10, 11]. Moreover, unlike most quantitative traits of strawberry, the formation of which is due to polygenic effects, the concentration of 4-methoxy-2,5-dimethyl-3-furanone in fruits is controlled by the dominant FaOMT gene. The FaOMT gene has two allelic states. Allele FaOMT+ determines a high level of accumulation of mesifurane in strawberry fruits. Allele FaOMT- is inactive (non-functional). The active allele (FaOMT+) differs from the inactive allele (FaOMT-) by the presence in the promoter of several SNPs (Indel) containing potential regulatory elements – the E-box/RRE motif, the MYBL motif, and the ABRE/ACGT motif. . Monogenic control of the mesifurane content in strawberry fruits is also confirmed by the RNA interference, which showed an almost complete absence of mesifurane in strawberry fruits during repression of the FaOMT transcripts . Identification of the main determinants of this trait allows screening of promising forms based on molecular markers [12, 14].
The purpose of study was to study the allelic diversity of the FaOMT fruit aroma gene in strawberry varieties in order to identify promising genotypes for involvement in the strawberry breeding to improve the aroma of fruits.
The studies were carried out in 2019-2020. Biological material was represented by strawberry varieties and selected forms from genetic collection of the FSSI “I.V. Michurin Federal Science Center”.
The alleles of FaOMT gene were identified with the primers FaOMT-SI/NO-F (5’-CGATCATTTCGAAAAGGACTA-3’) and FaOMT-SI/NO-R (5’-AAGCAGGGTTAGTTGTGGAGA-3’). The FaOMT+ allele on the electrophoregram corresponds to a 248 bp fragment, the FaOMT- allele corresponds to a 214 bp fragment .
Reaction mix in final volume 15 μl containing 1.5 μl Taq-buffer, 0.2 mM of each deoxyribonucleotide triphosphate, 2.5 mM magnesium chloride, 0.2 U Taq DNA polymerase, 0.2 μM of each primer and 20 ng of genomic DNA.
The polymerase chain reaction was performed in T100 Thermal Cycler (BioRad). PCR conditions were as follows: 3 min denaturation at 95°C followed by 10 cycles of 30 s at 95°C, 30 s at 60°C (-0.5 °C/cycle), and 45 s at 72 °C, then 25 cycles of 30 s at 95 °C, 30 s at 55°C, and 45 s at 72°C, followed by a final extension step of 5 min at 72°C.
Amplification products were separated by electrophoretic method in agarose gel (agarose concentration – 2%, running buffer – 1x TBE). Amplicon sizes estimated were performed using the Gene Ruler 100 bp DNA Ladder (Thermo Fisher Scientific).
According to the research the functional allele FaOMT+ was detected in 15 forms (93.7%) out of 16 analyzed genotypes. The FaOMT- allele was identified in 43.7% analyzed forms. The FaOMT+FaOMT- genotype was identified in 37.5% forms. The FaOMT+FaOMT+ genotype was detected in 56.2% forms. The homozygous state of nonfunctional allele was identified in foreign strawberry variety Quicky (the example of electrophoresis profile of markers FaOMT-SI/NO is shown in Fig. 1, the results are shown in Tab. 1.).
In most of the analyzed strawberry varieties (58.3 %), the active allele of the FaOMT gene is present in a homozygous form. It should be noted that out of six strawberry varieties of Russian breeding, the homozygous genotype for the FaOMT gene (FaOMT+FaOMT+) was identified in five genotypes (Borovitskaya, Kubata, Troitskaya, Tsaritsa, Yarkaya), while among 6 varieties of foreign breeding – only in two forms (Netherlands’ strawberry varieties Korona and Vima Kimberly). More widespread of the heterozygous genotype of the FaOMT gene in foreign strawberry forms also shown in other studies [17, 18]. The prevalence of the FaOMT+FaOMT- genotype in foreign strawberry varieties can be explained by their genetic proximity due to the active use of several initial forms in hybridization, which presumably could be a donor of the inactive FaOMT- allele.
Among the analyzed selected forms of strawberry, homozygous state of the FaOMT+ allele was identified in hybrids 298-19-9-43 and 932-29. Selected forms 26-5 and 928-12 have the FaOMT+FaOMT- genotype.
Thus, as a result of the research, we studied the allelic polymorphism of the FaOMT gene, which determines the content of 4-methoxy-2,5-dimethyl-3-furanone (mesifurane) in strawberry fruits. Valuable sources of increased concentration of mesifurane in fruits are strawberry varieties Borovitskaya, Kubata, Troitskaya, Tsaritsa, Yarkaya, Korona and Vima Kimberly, and hybrid forms 932-29 and 298-19-9-43 (FaOMT+FaOMT+ genotype).
Electrophoresis profile of markers FaOMT-SI/NO at strawberry genotypes
1 – Borovitskaya, 2 – 298-19-9-43, 3 – 26-5, 4 – Korona, 5 – Vima Kimberly, 6 – Yarkaya, 7 – Troitskaya, 8 – Ostara, 9 – Quicky, 10 – Polka, 11 – 932-29, 12 – Kubata, 13 – Tsaritsa, М – Molecular weight marker
Allelic polymorphism of FaOMT gene in strawberry varieties and forms (1 – allele is presence, 0 – allele is absence)
- F. Giampieri, S. Tulipani, J.M. Alvarez-Suarez, J.L. Quiles, B. Mezzetti, M. Battino, Nutrition, 28(1), 9–19 (2012) https://doi.org/10.1016/j.nut.2011.08.009 [CrossRef] [PubMed] [Google Scholar]
- A. Michalska, C. Carlen, J. Heritier, W. Andlauerc, J. Berry Res., 7(2), 71–84 (2017). https://doi.org/10.3233/JBR-160146 [Google Scholar]
- D. Ulrich, K. Olbricht, J. Appl. Bot. Food Qual., 89, 223–234 (2016). https://doi.org/10.5073/JABFQ.2016.089.029 [Google Scholar]
- G. Bianchi, P. Lucchi, M.L. Maltoni, A.F. Fagherazzi, G. Baruzzi, Acta Hortic., 1156, 673-678 (2017). https://doi.org/10.17660/ActaHortic.2017.1156.98 [Google Scholar]
- G. Cumplido-Laso, L. Medina-Puche, E. Moyano, T. Hoffmann, Q. Sinz, L. Ring, C. StudartWittkowski, J. L. Caballero, W. Schwab, J. Muñoz-Blanco, R. Blanco-Portales, J. Exp. Bot., 63(11), 4275–4290 (2012). https://doi.org/10.1093/jxb/ers120 [CrossRef] [PubMed] [Google Scholar]
- M. L. Schwieterman, T. A. Colquhoun, E. A. Jaworski, L. M. Bartoshuk, J. L. Gilbert, D. M. Tieman, A. Z. Odabasi, H. R. Moskowitz, K. M. Folta, H. J. Klee, C. A. Sims, V. M. Whitaker, D. G. Clark, PloS One, 9(2), e88446 (2014). https://doi.org/10.1371/journal.pone.0088446 [CrossRef] [PubMed] [Google Scholar]
- C. Song, X. Hong, S. Zhao, J. Liu, K. Schulenburg, F.C. Huang, K. Franz-Oberdorf, W. Schwab, Plant Physiol., 171(1), 139–151 (2016). https://doi.org/10.1104/pp.16.00226 [Google Scholar]
- A. H. Chambers, J. Pillet, A. Plotto, J. Bai, V. M. Whitaker, K. M. Folta, BMC genomics, 15(1), 217 (2014). https://doi.org/10.1186/1471-2164-15-217 [CrossRef] [PubMed] [Google Scholar]
- M. Urrutia, J. L. Rambla, K. G. Alexiou, A. Granell, A. Monfort, Plant Physiol. Bioch., 121, 99–117 (2017). https://doi.org/10.1016/j.plaphy.2017.10.015 [CrossRef] [Google Scholar]
- J. W. Yan, Z. J. Ban, H. Y. Lu, D. Li, E. Poverenov, Z. S. Luo, L. Li, J. Sci. Food Agr., 98(12), 4395–4402 (2018). https://doi.org/10.1002/jsfa.9039 [CrossRef] [Google Scholar]
- A. Yamada, K. I. Ishiuchi, T. Makino, H. Mizukami, K. Terasaka, Biosci. Biotech. Biochem., 83(1), 106–113 (2019). https://doi.org/10.1080/09168451.2018.1524706 [CrossRef] [Google Scholar]
- Y. Zorrilla-Fontanesi, J. L. Rambla, A. Cabeza, J. J. Medina, J. F. Sánchez-Sevilla, V. Valpuesta, M. A. Botella, A. Granell, I. Amaya, Plant physiol., 159(2), 851–870 (2012). https://doi.org/10.1104/pp.111.188318 [Google Scholar]
- K. Härtl, G. Kalinowski, T. Hoffmann, A. Preuss, W. Schwab, Plant Biotechnol. J., 15(5), 658–668 (2017). https://doi.org/10.1111/pbi.12664 [CrossRef] [PubMed] [Google Scholar]
- M. C. Gor, C. Candappa, T. de Silva, N. Mantri, E. Pang, Scientific reports 7(1), 1–13 (2017). http://doi.org/10.1038/s41598-017-17448-1 [CrossRef] [PubMed] [Google Scholar]
- I. V. Luk’yanchuk, A. S. Lyzhin, I. I. Kozlova, Vavilov Journal of Genetics and Breeding 22(7), 795–799 (2018). https://doi.org/10.18699/VJ18.423 [CrossRef] [Google Scholar]
- A. S. Lyzhin, I. V. Lukyanchuk, E. V. Zhbanova, Proceedings on Applied Botany, Genetics and Breeding 180(1), 73–77 (2019). https://doi.org/10.30901/2227-8834-2019-1-73-77 [CrossRef] [Google Scholar]
- A. S. Lyzhin, I. V. Luk’yanchuk, E. V. Zhbanova, Vavilov Journal of Genetics and Breeding 24(1), 5–11 (2020). https://doi.org/10.18699/VJ20.588 [CrossRef] [Google Scholar]
- E. Cruz-Rus, R. Sesmero, J. A. Ángel-Pérez, J. F. Sánchez-Sevilla, D. Ulrich, I. Amaya, Mol. Breed., 37(10), 131 (2017). https://doi.org/10.1007/s11032-017-0732-7 [CrossRef] [PubMed] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.