In Vitro Pathogenesis Caused by Phytophthora cactorum and DNA Analysis of the Strawberry-Resistant Microplants with ISSR Markers
Abstract
:1. Introduction
2. Materials and Methods
3. Results and Discussion
- 0—plants without infection symptoms;
- 1—infection involving one leaf (25%);
- 2—infection involving two leaves (50%);
- 3—infection involving three leaves (75%);
- 4—infection involving four or more leaves or entirely infected plants (100%).
- 0—no leaf chlorosis;
- 1—chlorosis involving one leaf (25%);
- 2—chlorosis involving two leaves (50%);
- 3—chlorosis involving three leaves (75%);
- 4—chlorosis involving four or more leaves (100%);
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Michalik, B.; Spiss, L. Plant breeding directions. In Plant Breeding with Elements of Genetics and Biotechnology; PWRiL: Poznań, Poland, 2009; pp. 153–168. [Google Scholar]
- Woźny, A.; Przybył, K. Plant Cells under Stress. Vol. II. In Vitro Cells; UAM: Poznań, Poland, 2007. [Google Scholar]
- Michalik, B. Application of in vitro cultures. In Plant Breeding with Elements of Genetics and Biotechnology; PWRiL: Poznań, Poland, 2009; pp. 298–311. [Google Scholar]
- Paczos-Grzęda, E.; Olek, A. Use of in vitro culture in plant breeding. In Agrobiotechnology; Kowalczyk, K., Ed.; Publishing House of the University of Life Sciences: Lublin, Poland, 2013; pp. 58–69. [Google Scholar]
- Sowik, I.; Michalczuk, L.; Wójcik, D. A method for in vitro testing strawberry susceptibility to Verticillium wilt. J. Fruit Ornam. Plant. Res. 2008, 16, 111–121. [Google Scholar]
- Żebrowska, J.I. In vitro selection in resistance breeding of strawberry (Fragaria × ananassa duch.). Commun. Agric. Appl. Biol. Sci. 2010, 75, 699–704. [Google Scholar] [PubMed]
- Żebrowska, J.I. Efficacy of resistance selection to verticillium wilt in strawberry (Fragaria × ananassa Duch.) tissue culture. Acta Agrobot. 2011, 64, 3–12. [Google Scholar] [CrossRef]
- Hantula, J.; Lilja, A.; Nuorteva, H.; Parikka, P.; Werres, S. Pathogenicity, morphology and genetic variation of Phytophthora cactorum from strawberry, apple, rhododendron, and silver birch. Mycol. Res. 2000, 104, 1062–1068. [Google Scholar] [CrossRef]
- Garrido, C.; González-Rodríguez, V.E.; Carbú, M.; Husaini, A.M.; Cantoral, J.M. Fungal diseases of strawberry and their diagnosis. In Strawberry: Growth, Development and Diseases; Husaini, A.M., Neri, D., Eds.; CAB International: Wallingford, UK, 2016; pp. 157–195. [Google Scholar] [CrossRef]
- Ribeiro, O.K. A Source Book of the Genus Phytophthora; Strauss & Cramer GmbH: Bramsche, Germany, 1978. [Google Scholar]
- Bielenin, A. Fungi of the Genus Phytophthora in Fruit Crops: Occurrence, Harmfulness and Control, 1st ed.; Uniwersytet Przyrodniczy w Poznaniu: Skierniewice, Poland, 2002; pp. 1–78. [Google Scholar]
- Horst, R.K. Westcott’s Plant. Disease Handbook, 7th ed.; Springer-Verlag Berlin Heidelberg: New York, NY, USA, 2008. [Google Scholar] [CrossRef]
- Orlikowski, L.B.; Ptaszek, M.; Trzewik, A.; Orlikowska, T.; Szkuta, G.; Meszka, B.; Skrzypczak, C. Risk of horticultural plants by Phytophthora species. Prog. Plant. Prot. 2012, 52, 2–100. [Google Scholar]
- Orlikowski, L.B.; Meszka, B.; Ptaszek, M.; Łazecka, U.; Krawiec, P. Causes of soil dieback of raspberries: The most dangerous pathogens, similarities and differences in disease symptoms and the possibility of preventing their occurrence. In Proceedings of the Fruit Conference in Kraśnik “Jagodowe Trendy 2017”, Kraśnik, Poland, 1 March 2017; pp. 80–83. [Google Scholar]
- Hetman, B. Caution Phytophthora! Jagodnik 2015, 3, 20–23. [Google Scholar]
- Szkuta, G. Disease symptoms. In Phytophthora Cactorum (Leb. & Cohn) Schröeter—The Perpetrator Crown Rot of Strawberry; Państwowa Inspekcja Ochrony Roślin i Nasiennictwa Główny Inspektorat, PIORiN: Warsaw, Poland, 2005. [Google Scholar]
- Bielenin, A.; Cieślińska, M.; Łabanowska, B.H. Atlas of Diseases and Pests of Strawberry, 1st ed.; APS Press: St. Paul, MN, USA, 1998; pp. 1–60. [Google Scholar]
- Paulus, A.O. Fungal diseases of strawberry. Hort. Sci. 1990, 25, 885–889. [Google Scholar] [CrossRef] [Green Version]
- Sadowska, K.; Rataj-Guranowska, M. Phytophthora cactorum (Lebert & Cohn) J. Schröt. In A compendium of Symptoms of Plant Diseases and the Morphology of their Perpetrators. Phytophthora, Issue 8; Institute of Plant Protection–National Research Institute Bank of Plant Pathogens and Research on Their Biodiversity: Poznań, Poland, 2010; pp. 38–50. [Google Scholar]
- Ellis, M.A.; Wilcox, W.F.; Madden, L.V. Efficacy of metalaxyl, fosetyl-aluminum, and straw mulch for control of strawberry leather rot caused by Phytophthora cactorum. Plant. Dis. 1998, 82, 329–332. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Bielenin, A. Strawberry crown rot-a new disease in Polish conditions. Prog. Plant. Prot. 1999, 39, 332–335. [Google Scholar]
- Murashige, T.; Skoog, F. A revised medium for rapid growth and bioassays with tobacco tissue cultures. Physiol. Plant. 1962, 15, 473–497. [Google Scholar] [CrossRef]
- McKinney, H.H. Influence of soil temperature and moisture on infection of wheat seedlings by Helminthosporium sativum. J. Agr. Res. 1923, 26, 195–217. [Google Scholar]
- Simmonds, N.W. Fundamentals of Plant Breeding; PWRiL: Warsaw, Poland, 1987. [Google Scholar]
- Gawel, N.J.; Jarret, R.L. A modified CTAB DNA extraction procedure for Musa and Ipomoea. Plant. Mol. Biol. Rep. 1991, 9, 262–266. [Google Scholar] [CrossRef]
- Shokaeva, D.B.; Solovykh, N.V.; Skovorodnikov, D.N. In vitro selection and strawberry plant regeneration for developing resistance to Botrytis cinerea Pers., Phytophthora cactorum Leb. et Cohn (Schroet) and salinity stress. In Genomics, Transgenics, Molecular Breeding and Biotechnology of Strawberry; Husaini, A.M., Mercado, J.A., Eds.; Global Science Books Ltd., UK: Ikenobe, Kagawa ken, Japan, 2011; pp. 115–125. [Google Scholar]
- Eikemo, H.; Stensvand, A.; Davik, J.; Tronsmo, A.M. Resistance to crown rot (Phytophthora cactorum) in strawberry cultivars and in offspring from crosses between cultivars differing in susceptibility to the disease. Ann. Appl. Biol. 2003, 142, 83–89. [Google Scholar] [CrossRef]
- Schafleitner, S.; Bonneta, A.; Pedeprata, N.; Roccaa, D.; Chartierc, P.; Denoyes, B. Genetic variation of resistance of the cultivated strawberry to crown rot caused by Phytophthora cactorum. J. Berry Res. 2013, 3, 79–91. [Google Scholar] [CrossRef] [Green Version]
- Kaleybar, B.S.; Nematzadeh, G.A.; Ghasemi, Y.; Hamidreza, S.; Petroudi, H. Assessment of genetic diversity and fingerprinting of strawberry genotypes using inter simple sequence repeat marker. Horticult. Int. J. 2018, 2, 264–269. [Google Scholar] [CrossRef] [Green Version]
- Morales, R.; Resende, J.; Faria, M.; Andrade, M.; Resende, L.; Delatorre, C.; Silva, P. Genetic similarity among strawberry cultivars assessed by RAPD and ISSR markers. Sci. Agric. 2011, 68, 665–670. [Google Scholar] [CrossRef] [Green Version]
Starter | Sequence (5′–3′) (a) | Number of Loci | |||
---|---|---|---|---|---|
Total | Polymorphic | %P (b) | Size Range (bp) | ||
1 | VBVACACACACACACAC | 7 | 7 | 100.0 | 400–2000 |
2 | BDBCACACACACACACA | No products | - | - | - |
3 | HBHCTCTCTCTCTCTCT | No products | - | - | - |
4 | GCVTCTCTCTCTCTCTC | No products | - | - | - |
5 | VCGTCTCTCTCTCTCTC | No products | - | - | - |
6 | BDVAGAGAGAGAGAGAG | No products | - | - | - |
7 | HVHTGTTGTTGTTGTTGT | 6 | 5 | 83.3 | 600–3000 |
8 | BDBCACCACCACCACCAC | 8 | 8 | 100.0 | 300–1500 |
9 | BDVCAGCAGCAGCAGCAG | No products | - | - | - |
10 | GAAGAAGAAGAAGAAGAA | 5 | 5 | 100.0 | 1000–1500 |
11 | ATGATGATGATGATGATG | 6 | 3 | 50.0 | 300–3000 |
12 | TGGTGGTGGTGGTGGTGG | No products | - | - | - |
13 | GATAGATAGATAGATAGATA | 7 | 7 | 100.0 | 700–3500 |
14 | GACAGACAGACAGACAGACA | 6 | 5 | 83.3 | 300–2500 |
15 | CTAGCTAGCTAGCTAG | No products | - | - | - |
16 | AGTGAGTGAGTGAGTG | 7 | 7 | 100.0 | 300–2500 |
Mean | 6.5 | 5.9 | - | - | |
Totality | 52 | 47 | 89.58 | 300–3500 |
Microclone | Evaluation Scale (0–4) | Observation Time Points | ||||
---|---|---|---|---|---|---|
I | II | III | IV | V | ||
‘Elsanta’ | 0 | 54.00 | 30.67 | 22.67 | 16.00 | 9.33 |
1 | 32.67 | 38.33 | 37.67 | 29.67 | 21.00 | |
2 | 7.67 | 19.00 | 22.67 | 30.00 | 32.33 | |
3 | 4.00 | 7.67 | 10.00 | 10.33 | 14.67 | |
4 | 1.67 | 4.33 | 7.00 | 14.00 | 22.67 | |
‘Feltar’ | 0 | 80.00 | 62.00 | 43.33 | 32.33 | 24.67 |
1 | 18.00 | 28.33 | 35.67 | 36.00 | 36.00 | |
2 | 1.67 | 7.33 | 12.00 | 15.33 | 18.33 | |
3 | 0.33 | 2.33 | 6.67 | 8.67 | 6.67 | |
4 | 0.00 | 0.00 | 2.33 | 7.67 | 14.33 | |
‘Plena SVdT’ | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
1 | 3.33 | 0.00 | 0.00 | 0.00 | 0.00 | |
2 | 36.67 | 1.67 | 1.67 | 1.67 | 1.33 | |
3 | 46.33 | 49.00 | 31.00 | 5.67 | 3.33 | |
4 | 13.67 | 49.33 | 67.33 | 92.67 | 95.33 | |
‘Teresa’ | 0 | 59.67 | 29.67 | 16.33 | 8.00 | 6.33 |
1 | 24.67 | 31.33 | 27.00 | 18.00 | 13.67 | |
2 | 9.33 | 14.00 | 22.00 | 26.33 | 16.33 | |
3 | 3.33 | 11.00 | 11.67 | 13.00 | 14.00 | |
4 | 3.00 | 14.00 | 23.00 | 34.67 | 49.67 |
Microclone | Evaluation Scale (0–4) | Observation Time Points | ||||
---|---|---|---|---|---|---|
I | II | III | IV | V | ||
‘Elsanta’ | 0 | 96.00 | 95.00 | 95.00 | 95.00 | 93.00 |
1 | 4.00 | 4.00 | 3.00 | 2.00 | 2.00 | |
2 | 0.00 | 1.00 | 2.00 | 2.00 | 2.00 | |
3 | 0.00 | 0.00 | 0.00 | 1.00 | 1.00 | |
4 | 0.00 | 0.00 | 0.00 | 0.00 | 2.00 | |
‘Feltar’ | 0 | 96.00 | 96.00 | 96.00 | 93.00 | 92.00 |
1 | 3.00 | 2.00 | 1.00 | 2.00 | 2.00 | |
2 | 1.00 | 2.00 | 3.00 | 3.00 | 2.00 | |
3 | 0.00 | 0.00 | 0.00 | 2.00 | 2.00 | |
4 | 0.00 | 0.00 | 0.00 | 0.00 | 2.00 | |
‘Plena SVdT’ | 0 | 93.00 | 92.00 | 92.00 | 92.00 | 92.00 |
1 | 4.00 | 5.00 | 4.00 | 4.00 | 3.00 | |
2 | 2.00 | 2.00 | 3.00 | 1.00 | 1.00 | |
3 | 1.00 | 1.00 | 1.00 | 2.00 | 2.00 | |
4 | 0.00 | 0.00 | 0.00 | 1.00 | 2.00 | |
‘Teresa’ | 0 | 96.00 | 95.00 | 91.00 | 91.00 | 90.00 |
1 | 3.00 | 2.00 | 6.00 | 5.00 | 4.00 | |
2 | 1.00 | 3.00 | 3.00 | 3.00 | 2.00 | |
3 | 0.00 | 0.00 | 0.00 | 1.00 | 3.00 | |
4 | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 |
Microclone | ‘Elsanta’ | ‘Elsanta’ Control | ‘Feltar’ | ‘Feltar’ Control | ‘Plena SVdT’ | ‘Plena SVdT’ Control | ‘Teresa’ | ‘Teresa’ Control |
---|---|---|---|---|---|---|---|---|
Mean extent (%) | 31.57a | 5.65b | 19.50a | 6.50b | 84.74a | 9.40b | 43.53a | 7.60b |
Mean rate | 0.1399a | 0.0200b | 0.1128a | 0.0941a | 0.0710a | 0.0295b | 0.1414a | 0.0279b |
Microclone | ‘Plena SVdT’ | ‘Teresa’ | ‘Elsanta’ | ‘Feltar’ |
---|---|---|---|---|
Mean McKinney disease index (%) | 84.74a | 43.53b | 31.57c | 19.50d |
Microclone | Evaluation Scale (0–4) | Observation Time Points | ||||
---|---|---|---|---|---|---|
I | II | III | IV | V | ||
‘Elsanta’ | 0 | 0.2355 | 0.2043 | 0.1670 | 0.1291 | 0.0803 |
1 | 0.2198 | 0.2360 | 0.2341 | 0.2062 | 0.1646 | |
2 | 0.0680 | 0.1537 | 0.1745 | 0.2091 | 0.2148 | |
3 | 0.0359 | 0.0672 | 0.0875 | 0.0897 | 0.1231 | |
4 | 0.0158 | 0.0398 | 0.0633 | 0.1153 | 0.1633 | |
‘Elsanta’ control | 0 | 0.0384 | 0.0475 | 0.0475 | 0.0475 | 0.0651 |
1 | 0.0384 | 0.0384 | 0.0291 | 0.0196 | 0.0196 | |
2 | 0.0000 | 0.0099 | 0.0196 | 0.0196 | 0.0196 | |
3 | 0.0000 | 0.0000 | 0.0000 | 0.0099 | 0.0099 | |
4 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0196 | |
‘Feltar’ | 0 | 0.1567 | 0.2175 | 0.2089 | 0.1949 | 0.1585 |
1 | 0.1450 | 0.1838 | 0.2150 | 0.2243 | 0.2291 | |
2 | 0.0161 | 0.0678 | 0.0983 | 0.1241 | 0.1432 | |
3 | 0.0033 | 0.0227 | 0.0614 | 0.0767 | 0.0616 | |
4 | 0.0000 | 0.0000 | 0.0226 | 0.0691 | 0.1190 | |
‘Feltar’ control | 0 | 0.1322 | 0.1702 | 0.1652 | 0.1569 | 0.1334 |
1 | 0.1240 | 0.1500 | 0.1688 | 0.1740 | 0.1766 | |
2 | 0.0158 | 0.0632 | 0.0887 | 0.1087 | 0.1227 | |
3 | 0.0033 | 0.0222 | 0.0576 | 0.0708 | 0.0578 | |
4 | 0.0000 | 0.0000 | 0.0221 | 0.0643 | 0.1049 | |
‘Plena SVdT’ | 0 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 |
1 | 0.0319 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | |
2 | 0.2206 | 0.0164 | 0.0164 | 0.0164 | 0.0131 | |
3 | 0.2362 | 0.2432 | 0.2086 | 0.0530 | 0.0321 | |
4 | 0.1174 | 0.2439 | 0.2153 | 0.0673 | 0.0442 | |
‘Plena SVdT’ control | 0 | 0.0651 | 0.0736 | 0.0736 | 0.0736 | 0.0736 |
1 | 0.0384 | 0.0475 | 0.0384 | 0.0384 | 0.0291 | |
2 | 0.0196 | 0.0196 | 0.0291 | 0.0099 | 0.0099 | |
3 | 0.0099 | 0.0099 | 0.0099 | 0.0196 | 0.0196 | |
4 | 0.0000 | 0.0000 | 0.0000 | 0.0099 | 0.0196 | |
‘Teresa’ | 0 | 0.2406 | 0.2086 | 0.1356 | 0.0718 | 0.0582 |
1 | 0.1842 | 0.2146 | 0.1953 | 0.1426 | 0.1158 | |
2 | 0.0845 | 0.1202 | 0.1714 | 0.1939 | 0.1352 | |
3 | 0.0319 | 0.0961 | 0.1030 | 0.1123 | 0.1202 | |
4 | 0.0278 | 0.1186 | 0.1763 | 0.2264 | 0.2486 | |
‘Teresa’ control | 0 | 0.0384 | 0.0475 | 0.0819 | 0.0819 | 0.0900 |
1 | 0.0291 | 0.0196 | 0.0564 | 0.0475 | 0.0384 | |
2 | 0.0099 | 0.0291 | 0.0291 | 0.0291 | 0.0196 | |
3 | 0.0000 | 0.0000 | 0.0000 | 0.0099 | 0.0291 | |
4 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0099 |
Microclone | ‘Teresa’ | ‘Elsanta’ | ‘Feltar’ | ‘Plena SVdT’ |
---|---|---|---|---|
Mean Simmonds disease index | 0.1414a | 0.1399a | 0.1128ab | 0.0710b |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Marecki, W.; Żebrowska, J. In Vitro Pathogenesis Caused by Phytophthora cactorum and DNA Analysis of the Strawberry-Resistant Microplants with ISSR Markers. Agronomy 2021, 11, 1279. https://doi.org/10.3390/agronomy11071279
Marecki W, Żebrowska J. In Vitro Pathogenesis Caused by Phytophthora cactorum and DNA Analysis of the Strawberry-Resistant Microplants with ISSR Markers. Agronomy. 2021; 11(7):1279. https://doi.org/10.3390/agronomy11071279
Chicago/Turabian StyleMarecki, Wojciech, and Jadwiga Żebrowska. 2021. "In Vitro Pathogenesis Caused by Phytophthora cactorum and DNA Analysis of the Strawberry-Resistant Microplants with ISSR Markers" Agronomy 11, no. 7: 1279. https://doi.org/10.3390/agronomy11071279