Genetic differentiation of two phenotypes of Plantago media L. In South Timan

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Abstract

Background. The investigation of the genetic nature of plant phenotypic variability is of great importance for understanding biological diversity, distribution and adaptation of plants to environmental conditions.

The aim of our work was to study the genetic differentiation of two phenotypes of Plantago media in South Timan.

Materials and methods. The genetic differentiation of light and shadow phenotypes of Plantago media plants was evaluated using intersimple sequence repeats (ISSR) markers.

Results. The population-genetic analysis of 210 loci revealed two clusters, which boundaries coincided with the boundaries between plants of light and shadow phenotypes. The results of the discriminatory analysis of the main components and AMOVA (FST = 0.07, p = 0.001) confirmed that there are statistically significant genetic differences between these phenotypes even though they possess a high genetic similarity.

Conclusion. Light and shadow Plantago media phenotypes adapted to different ecological conditions are genetically differentiated. The population genetic analysis using ISSR markers is a sensitive tool for identifying the genetic diversity of phenotypic plant variations formed under the influence of environmental factors.

About the authors

Ilya G. Zakhozhiy

Institute of Biology of Komi Science Centre of the Ural Branch of the Russian Academy of Sciences

Author for correspondence.
Email: zakhozhiy@ib.komisc.ru
ORCID iD: 0000-0003-0918-745X
SPIN-code: 3615-9301
Scopus Author ID: 36613922200
ResearcherId: P-9869-2015

PhD, Researcher, Laboratory of Ecological Physiology of Plants

Russian Federation, Syktyvkar

Dmitry M. Shadrin

Institute of Biology of Komi Science Centre of the Ural Branch of the Russian Academy of Sciences

Email: shdimas@yandex.ru
ORCID iD: 0000-0003-4365-0145
SPIN-code: 1453-3893
Scopus Author ID: 56644695300
ResearcherId: P-9808-2015

PhD, Researcher, Center for Collective Use “Molecular Biology”

Russian Federation, Syktyvkar

Yana I. Pylina

Institute of Biology of Komi Science Centre of the Ural Branch of the Russian Academy of Sciences

Email: yanapylina@yandex.ru
ORCID iD: 0000-0003-4981-8930
SPIN-code: 5636-5693
Scopus Author ID: 56644812300
ResearcherId: P-9565-2015

Junior Research Scientist, Center for Collective Use “Molecular Biology”

Russian Federation, Syktyvkar

Ivan F. Chadin

Institute of Biology of Komi Science Centre of the Ural Branch of the Russian Academy of Sciences

Email: chadin@ib.komisc.ru
ORCID iD: 0000-0001-6299-2285
SPIN-code: 9787-2449
Scopus Author ID: 7801456952
ResearcherId: P-4940-2015

PhD, Head of Moleculal Biology Core Facility

Russian Federation, Syktyvkar

Tamara K. Golovko

Institute of Biology of Komi Science Centre of the Ural Branch of the Russian Academy of Sciences

Email: golovko@ib.komisc.ru
ORCID iD: 0000-0002-7993-9541
SPIN-code: 4344-7144
Scopus Author ID: 7004365574
ResearcherId: P-4922-2015

Doctor of Science, Main Researcher, Laboratory of Ecological Physiology of Plants

Russian Federation, Syktyvkar

References

  1. Инге-Вечтомов С.Г. Что мы знаем об изменчивости? // Экологическая генетика. – 2010. – Т. 8. – № 4. – С. 4–9. [Inge-Vechtomov SG. What do we know about variability? Ecological genetics. 2010;8(4):4-9. (In Russ.)]
  2. Sultan SE. Phenotypic plasticity for plant development, function and life history. Trends Plant Sci. 2000;5(12):537-542. https://doi.org/10.1016/S1360-1385(00)01797-0.
  3. Флора Северо-Востока Европейской части СССР. Cемейства Umbelliferae-Compositae / Под ред. А.И. Толмачева. Т. 4. – Л.: Наука. Ленингр. отд-ние, 1977. – 312 с. [Flora Severo-Vostoka Evropeiskoi chasti SSSR. Semeistva Umbelliferae-Compositae. Vol. 4. Ed. by A.I. Tolmachev. Leningrad: Nauka. Leningr. otd-nie; 1977. 312 р. (In Russ.)]
  4. Kuiper PJ, Bos M. Plantago: a multidisciplinary study. Ecological Studies. 1992. https://doi.org/10.1007/978-3-642-76392-2.
  5. Golovko TK, Dalke IV, Zakhozhiy IG, et al. Functional plasticity of photosynthetic apparatus and its resistance to photoinhibition in Plantago media. Russ J Plant Physiol. 2011;58:549-59. https://doi.org/10.1134/S1021443711040054.
  6. Golovko T, Dymova O, Zakhozhiy I, et al. Photoprotection by carotenoids of Plantago media photosynthetic apparatus in natural conditions. Acta Biochimica Polonica. 2012;59:145-7. https://doi.org/10.18388/abp.2012_2192.
  7. Rozentsvet OA, Golovko TK, Bogdanova ES, et al. Polar lipid pool modification in leaves of hoary plantain (Plantago media L.) plants during their light adaptation under natural conditions. Biology Bulletin. 2013;40:138-145. https://doi.org/10.1134/S1062359013020118.
  8. Воробьева Л.А. Теория и практика химического анализа почв. – М.: Изд-во МГУ, 2006. – 400 с. [Vorob’eva LA. Teoriya i praktika khimicheskogo analiza pochv. Moscow: Publishing house Moscow State University; 2006. 400 р. (In Russ.)]
  9. R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2015.
  10. ISSR321 – The R-script for merging ISSR data replications [Online] GitHub / Accessed 16.08.2016. Доступно по: https://github.com/chadinkomi/ISSR321. Ссылка активна на 06.08.2019.
  11. Kamvar ZN, Tabima JF, Grünwald NJ. Poppr: an R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. Peer J. 2014;2:e281. https://doi.org/10.7717/peerj.281.
  12. Jombart T, Devillard S, Balloux F. Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genet. 2010;11:94. https://doi.org/10.1186/1471-2156-11-94.
  13. Pritchard JK, Stephens M, Donnelly P. Inference of population structure using multilocus genotype data. Genetics. 2000;155(2):945-959.
  14. Falush D, Stephens M, Pritchard JK. Inference of population structure using multilocus genotype data: dominant markers and null alleles. Mol Ecol Notes. 2007;7(4):574-578. https://doi.org/10.1111/j.1471-8286.2007.01758.x.
  15. Evanno G, Regnaut S, Goudet J. Detecting the number of clusters of individuals using the software structure: a simulation study. Mol Ecol. 2005;14(8):2611-2620. https://doi.org/10.1111/j.1365-294X.2005.02553.x.
  16. Jombart T. Adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics. 2008;24(11):1403-1405. https://doi.org/10.1093/bioinformatics/btn129.
  17. Bazzaz FA. Plants in changing environments: linking physiological, population, and community ecology. Cambridge; New York: Cambridge University Press; 1996.
  18. Любименко В.Н. Избранные труды. Работы по фотосинтезу и приспособлению растений к свету. Т. 1 / под ред. А.С. Оканенко. – Киев: Изд-во АН Украинской ССР, 1963. – 614 с. [Lyubimenko VN. Izbrannye trudy. Raboty po fotosintezu i prisposobleniyu rastenii k svetu. Vol. 1. Kiev: Izdatel’stvo AN Ukrainskoi SSR; 1963. 614 р. (In Russ.)]
  19. Горышина Т.К., Заботина Л.Н., Пружина Л.Г. Пластидный аппарат травянистых растений в разных условиях освещения // Экология. – 1975. – № 5. – С. 15–22. [Goryshina TK, Zabotina LN, Pruzhina LG. Plastidnyi apparat travyanistykh rastenii v raznykh usloviyakh osveshcheniya. Ekologiia. 1975;(5):15-22. (In Russ.)]
  20. Boardman NK. Comparative photosynthesis of sun and shade plants. Annu Rev Plant Physiol. 1977;28(1):355-377. https://doi.org/10.1146/annurev.pp.28.060177.002035.
  21. Masarovicová E, Štefančík L. Some ecophysiological features in sun and shade leaves of tall beech trees. Biol Plant. 1990;32(5):374-387. https://doi.org/10.1007/BF02898503.
  22. Larcher W. Physiological plant ecology: ecophysiology and stress physiology of functional groups. 4th ed. Berlin; New York: Springer; 2003.
  23. Kuiper D, Smid A. Genetic differentiation and phenotypic plasticity in Plantago major ssp. I. The effect of differences in level of irradiance on growth, photosynthesis, respiration and chlorophyll content. Physiol Plant. 1985;65(4):520-528. https://doi.org/10.1111/j.1399-3054.1985.tb08684.x.
  24. Lambers H, Posthumus F, Stulen I, et al. Energy metabolism of Plantago major ssp. major as dependent on the supply of mineral nutrients. Physiol Plant. 1981;51(1):85-92. https://doi.org/10.1111/j.1399-3054.1981.tb00883.x.
  25. Mudrik V, Kosobrukhov A, Knyazeva I, Pigulevskaya T. Changes in the photosynthetic characteristics of Plantago major plants caused by soil drought stress. Plant Growth Regulation. 2003;40(1):1-6. https://doi.org/10.1023/ A:1023009025426.
  26. Odat N, Hellwig FH, Jetschke G, Fischer M. On the relationship between plant species diversity and genetic diversity of Plantago lanceolata (Plantaginaceae) within and between grassland communities. J Plant Ecology. 2010;3(1):41-48. https://doi.org/10.1093/jpe/rtp017.

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2. Fig. 1. Diurnal course of photosynthetic photon flux density (PPFD) (a), intensity of the ultraviolet radiation (b), and the air temperature (c) in Plantago media habitats. 1 – open slope, 2 – forest. Measurements were made in the first decade of July 2014 on a cloudless sunny day

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3. Fig. 2. Results of cluster analysis of the composition of 210 ISSR loci of Plantago media and Plantago major identified using STRUCTURE [13]. In the horizontal direction: each individual column corresponds to one sample; 1 and 2 – two groups of P. media plants on open slope and forest; 3 – P. major plants. In the vertical direction: the probability of assigning each sample (individual) to one of the clusters. Variants of the number of clusters are indicated above the graphs: K = 2 – the most probable number of clusters determined by the Evanno method [15]; K = 3 – the number of clusters corresponding to the number of studied plant groups

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4. Fig. 3. Scatter plot obtained on the basis of the results of the discriminant analysis of the principal components (DAPC) of the matrix of 210 ISSR loci of Plantago media and Plantago major plants. 1 and 2 – P. media plants from the forest and on the open slope, 3 – P. major plants. Axis 1 – values of discriminant function 1, axis 2 – values of discriminant function 2. In the lower right corner of the graph are the values of the DAPC eigenvalues

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Copyright (c) 2020 Zakhozhiy I.G., Shadrin D.M., Pylina Y.I., Chadin I.F., Golovko T.K.

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This work is licensed under a Creative Commons Attribution 4.0 International License.
 


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