vavilovВавиловский журнал генетики и селекцииVavilov Journal of Genetics and Breeding2500-3259Institute of Cytology and Genetics of Siberian Branch of the RAS10.18699/VJ17.229vavilov-910Research ArticleПерспективные направленияPromising trendsПерспективы метаболомных исследований растений картофеляThe perspectives of metabolomics studies of potato plantsПузанскийР. К.PuzanskiyR. K.

Санкт-Петербург

St. Petersburg

ЕмельяновВ. В.YemelyanovV. V.

Санкт-Петербург

St. Petersburg

ГавриленкоТ. А.GavrilenkoT. A.

Санкт-Петербург

St. Petersburg

ШишоваМ. Ф.ShishovaM. F.

Санкт-Петербург

St. Petersburg

mshishova@mail.ruФедеральное государственное бюджетное научное учреждение «Федеральный исследовательский центр Всероссийский институт генетических ресурсов растений им. Н.И. Вавилова» (ВИР); Федеральное государственное бюджетное образовательное учреждение высшего образования «Санкт-Петербургский государственный университет»РоссияFederal Research Center the N.I. Vavilov All-Russian Institute of Plant Genetic Resources (VIR); St. Petersburg State UniversityRussian FederationФедеральное государственное бюджетное образовательное учреждение высшего образования «Санкт-Петербургский государственный университет»РоссияSt. Petersburg State UniversityRussian Federation201724032017211112123Copyright © Пузанский Р.К., Емельянов В.В., Гавриленко Т.А., Шишова М.Ф., 20172017Пузанский Р.К., Емельянов В.В., Гавриленко Т.А., Шишова М.Ф.Puzanskiy R.K., Yemelyanov V.V., Gavrilenko T.A., Shishova M.F.This work is licensed under a Creative Commons Attribution 4.0 License.https://vavilov.elpub.ru/jour/article/view/910

По данным FAO, картофель представляет собой четвертую по объемам производства продовольственную культуру после риса, пшеницы, кукурузы и первую среди клубнеплодных и корнеплодных культур. Он служит ценным источником углеводов, антиоксидантов и витаминов. Огромное число работ сфокусировано на изучении метаболических процессов, происходящих в растениях картофеля, с тем чтобы расшифровать механизмы, отвечающие за продуктивность и накопление соединений, определяющих вкусовые и питательные качества, продолжительность периода покоя клубней, устойчивость растений и др. Результатом функционирования метаболических сетей является совокупность метаболитов, которую принято называть метаболомом. Комплексные исследования метаболического разнообразия с применением самых современных методов хроматографического анализа и детекции индивидуальных соединений выявили специфичность метаболомных спектров от субклеточного до организменного уровня, удивительную пластичность этих спектров при действии самых разнообразных факторов среды и внутренних стимулов. Уже сейчас метаболомные методы используют для фенотипирования линий, сортов и образцов диких и культурных видов картофеля, для изучения устойчивости растений к факторам окружающей среды и оценки изменений, происходящих в клубнях в процессе хранения. Метаболомный анализ активно применяется для изучения отличий генетически модифицированных форм картофеля от исходных растений. Даже небольшое число системных исследований, проведенных к настоящему времени и сочетающих оценку метаболома с изучением генома, транскриптома и протеома, указывает на значимую роль генетических факторов в определении интенсивности метаболизма растений картофеля. Очевидно, что поиск биохимических маркеров зависит от стандартизации методов выращивания, пробоподготовки и последующего анализа, от тех унифицирующих подходов, которые позволили достичь огромного прогресса в геномных и транскриптомных исследованиях. В перспективе анализ метаболома картофеля может дополнить традиционные и молекулярно-генетические методы селекции, направленные на создание новых гибридов, доноров ценных признаков, инбредных линий и сортов.

According to FAO (Food and Agricultural Organization of the United Nation), potato is the fourth crop in terms of food production after rice, wheat and maize, and the first among the tubers and roots. The importance of potato is difficult to overestimate; it is a valuable source of carbohydrates, antioxidants and vitamins. A huge number of investigations are focused on the study of metabolic processes occurring in the potato plant in order to elucidate the mechanisms responsible for productivity and accumulation of compounds that determine taste and nutritional quality, keeping quality of tubers, plant resistance, etc. The sum of metabolites, which is produced as a result of metabolic network activity, is defined as metabolome. Complex studies of metabolic diversity with the use of modern state-of-the-art chromatography approaches and highly precise detection of individual compounds revealed specificity of metabolic spectra from subcellular to organism levels and its amazing plasticity under the influence of a variety of internal and external stimuli. Metabolomic approaches are already in use for phenotyping available species, lines and varieties as well as for evaluation of potato plant resistance to environmental challenges and for detection of changes in tubers during storage. Metabolome profiling is widely employed to study differences between genetically modified forms of potatoes from untransformed relatives. A limited number of systemic studies on potatoes combines metabolome investigation with genome, transcriptome and proteome analysis and suggests an important role of the genome in the determination of metabolic rates. It is obvious that the search for biochemical markers depends on standartization of cultivation techniques, sample preparation and subsequent analysis similar to what has been developed for progress in genomic and transcriptomic studies. In the future, potato metabolome studies might complete classical and molecular approaches to develop new lines and varieties.

картофельметаболомикасистемная биологияселекцияpotatometabolomicssystem biologybreedingРоссийский научный фондReferencesAcharjee A., Kloosterman B., de Vos R.C., Werij J.S., Bachem C.W., Visser R.G.F., Maliepaard C. Data integration and network reconstruction with ~omics data using Random Forest regression in potato. Anal. Chim. Acta. 2011;705(1-2):56-63. DOI http://dx.doi.org/10.1016/j.aca.2011.03.050.Acharjee A., Kloosterman B., de Vos R.C., Werij J.S., Bachem C.W., Visser R.G.F., Maliepaard C. Data integration and network reconstruction with ~omics data using Random Forest regression in potato. Anal. Chim. Acta. 2011;705(1-2):56-63. DOI http://dx.doi.org/10.1016/j.aca.2011.03.050.Acharjee A., Kloosterman B., Visser R.G., Maliepaard C. Integration of multi-omics data for prediction of phenotypic traits using random forest. BMC Bioinformatics. 2016;17(5):180. DOI 10.1186/s12859016-1043-4.Acharjee A., Kloosterman B., Visser R.G., Maliepaard C. Integration of multi-omics data for prediction of phenotypic traits using random forest. BMC Bioinformatics. 2016;17(5):180. DOI 10.1186/s12859016-1043-4.Beckmann M., Enot D.P., Overy D.P., Draper J. Representation, comparison and interpretation of metabolome fingerprint data for total composition analysis and quality trait investigation in potato cultivars. J. Agric. Food Chem. 2007;55(9):3444-3451. DOI 10.1021/jf0701842.Beckmann M., Enot D.P., Overy D.P., Draper J. Representation, comparison and interpretation of metabolome fingerprint data for total composition analysis and quality trait investigation in potato cultivars. J. Agric. Food Chem. 2007;55(9):3444-3451. DOI 10.1021/jf0701842.Benkeblia N., Shinano T., Osaki M. Metabolite profiling and assessment of metabolome compartmentation of soybean leaves using non-aqueous fractionation and GC-MS analysis. Metabolomics. 2007;3(3):297-305. DOI 10.1007/s11306-007-0078-y.Benkeblia N., Shinano T., Osaki M. Metabolite profiling and assessment of metabolome compartmentation of soybean leaves using non-aqueous fractionation and GC-MS analysis. Metabolomics. 2007;3(3):297-305. DOI 10.1007/s11306-007-0078-y.Boughton B.A., Thinagaran D., Sarabia D., Bacic A., Roessner U. Mass spectrometry imaging for plant biology: a review. Phytochem. Rev. 2016;15(3):445-488. DOI 10.1007/s11101-015-9440-2.Boughton B.A., Thinagaran D., Sarabia D., Bacic A., Roessner U. Mass spectrometry imaging for plant biology: a review. Phytochem. Rev. 2016;15(3):445-488. DOI 10.1007/s11101-015-9440-2.Breiman L. Random Forests. Mach. Learn. 2001;45(1):5-32. DOI 10.1023/A:1010933404324.Breiman L. Random Forests. Mach. Learn. 2001;45(1):5-32. DOI 10.1023/A:1010933404324.Bylesjö M., Rantalainen M., Cloarec O., Nicholson J.K., Holmes E., Trygg J. OPLS discriminant analysis: combining the strengths of PLS-DA and SIMCA classification. J.Chemometrics. 2006;20(8-10): 341-351. DOI 10.1002/cem.1006.Bylesjö M., Rantalainen M., Cloarec O., Nicholson J.K., Holmes E., Trygg J. OPLS discriminant analysis: combining the strengths of PLS-DA and SIMCA classification. J.Chemometrics. 2006;20(8-10): 341-351. DOI 10.1002/cem.1006.Carreno-Quintero N., Acharjee A., Maliepaard C., Bachem C.W., Mumm R., Bouwmeester H., Visser R.G., Keurentjes J.J. Untargeted metabolic quantitative trait loci analyses reveal a relationship between primary metabolism and potato tuber quality. Plant Physiol. 2012;158(3):1306-1318. DOI 10.1104/pp.111.188441.Carreno-Quintero N., Acharjee A., Maliepaard C., Bachem C.W., Mumm R., Bouwmeester H., Visser R.G., Keurentjes J.J. Untargeted metabolic quantitative trait loci analyses reveal a relationship between primary metabolism and potato tuber quality. Plant Physiol. 2012;158(3):1306-1318. DOI 10.1104/pp.111.188441.Carreno-Quintero N., Bouwmeester H.J., Keurentjes J.J. Genetic analysis of metabolome-phenotype interactions: from model to crop species. Trends Genet. 2013;29(1):41-50. DOI http://dx.doi.org/10.1016/j.tig.2012.09.006.Carreno-Quintero N., Bouwmeester H.J., Keurentjes J.J. Genetic analysis of metabolome-phenotype interactions: from model to crop species. Trends Genet. 2013;29(1):41-50. DOI http://dx.doi.org/10.1016/j.tig.2012.09.006.Catchpole G., Beckmann M., Enot D., Mondhe M., Zywicki B., Taylor J., Hardy N., Smith A., King R., Kell D., Fiehn O., Draper J. Hierarchical metabolomics demonstrates substantial compositional similarity between genetically modified and conventional potato crops. Proc. Natl. Acad. Sci. USA. 2005;102(40):14458-14462. DOI 10.1073/pnas.0503955102.Catchpole G., Beckmann M., Enot D., Mondhe M., Zywicki B., Taylor J., Hardy N., Smith A., King R., Kell D., Fiehn O., Draper J. Hierarchical metabolomics demonstrates substantial compositional similarity between genetically modified and conventional potato crops. Proc. Natl. Acad. Sci. USA. 2005;102(40):14458-14462. DOI 10.1073/pnas.0503955102.Chin E., Slupsky C. Applications of metabolomics in food science: food composition and quality, sensory and nutritional attributes. Metabolomics in Food and Nutrition. Elsevier, 2013;217-230. DOI http://dx.doi.org/10.1533/9780857098818.2.217.Chin E., Slupsky C. Applications of metabolomics in food science: food composition and quality, sensory and nutritional attributes. Metabolomics in Food and Nutrition. Elsevier, 2013;217-230. DOI http://dx.doi.org/10.1533/9780857098818.2.217.Cho K., Cho K.S., Sohn H.B., Ha I.J., Hong S.Y., Lee H., Kim Y.M., Nam H.M. Network analysis of the metabolome and transcriptome reveals novel regulation of potato pigmentation. J. Exp. Bot. 2016;67(5):1519-1533. DOI 10.1093/jxb/erv549.Cho K., Cho K.S., Sohn H.B., Ha I.J., Hong S.Y., Lee H., Kim Y.M., Nam H.M. Network analysis of the metabolome and transcriptome reveals novel regulation of potato pigmentation. J. Exp. Bot. 2016;67(5):1519-1533. DOI 10.1093/jxb/erv549.Chon g E.S.L., McGhie T.K., Heyes J.A., Stowell K.M. Metabolite profiling and quantification of phytochemicals in potato extracts using ultra-high-performance liquid chromatography-mass spectrometry. J. Sci. Food Agr. 2013;93(15):3801-3808. DOI 10.1002/jsfa.6285.Chon g E.S.L., McGhie T.K., Heyes J.A., Stowell K.M. Metabolite profiling and quantification of phytochemicals in potato extracts using ultra-high-performance liquid chromatography-mass spectrometry. J. Sci. Food Agr. 2013;93(15):3801-3808. DOI 10.1002/jsfa.6285.Corsini D.L., Pavek J.J., Dean B. Differences in free and proteinbound tyrosine among potato genotypes and the relationship to internal blackspot resistance. Am. Potato J. 1992;69(7):423-435. DOI 10.1007/BF02852293.Corsini D.L., Pavek J.J., Dean B. Differences in free and proteinbound tyrosine among potato genotypes and the relationship to internal blackspot resistance. Am. Potato J. 1992;69(7):423-435. DOI 10.1007/BF02852293.Dalgliesh C.E., Horning E.C., Horning M.G., Knox K.L., Yarger K. A gas-liquid-chromatographic procedure for separating a wide range of metabolites occurring in urine or tissue extracts. Biochem. J. 1966;101(3):792-810. DOI 10.1042/bj1010792.Dalgliesh C.E., Horning E.C., Horning M.G., Knox K.L., Yarger K. A gas-liquid-chromatographic procedure for separating a wide range of metabolites occurring in urine or tissue extracts. Biochem. J. 1966;101(3):792-810. DOI 10.1042/bj1010792.Dao L., Friedman M. Chlorogenic acid content of fresh and processed potatoes determined by ultraviolet spectrophotometry. J. Agric. Food Chem. 1992;40(11):2152-2156. DOI 10.1021/jf00023a022.Dao L., Friedman M. Chlorogenic acid content of fresh and processed potatoes determined by ultraviolet spectrophotometry. J. Agric. Food Chem. 1992;40(11):2152-2156. DOI 10.1021/jf00023a022.Davies H.V., Shepherd L.V., Burrell M.M., Carrari F., UrbanczykWochniak E., LeisseA., Hancock R.D., Taylor M., Viola R., Ross H., McRae D., Willmitzer L., Fernie A.R. Modulation of fructokinase activity of potato (Solanum tuberosum) results in substantial shifts in tuber metabolism. Plant Cell Physiol. 2005;46(7):1103-1115. DOI 10.1093/pcp/pci123.Davies H.V., Shepherd L.V., Burrell M.M., Carrari F., UrbanczykWochniak E., LeisseA., Hancock R.D., Taylor M., Viola R., Ross H., McRae D., Willmitzer L., Fernie A.R. Modulation of fructokinase activity of potato (Solanum tuberosum) results in substantial shifts in tuber metabolism. Plant Cell Physiol. 2005;46(7):1103-1115. DOI 10.1093/pcp/pci123.Debon S.J.J., Tester R.F., Millam S., Davies H.V. Effect of temperature on the synthesis, composition and physical properties of potato microtuber starch. J. Sci. Food Agric. 1998;76(4):599-607. DOI 10.1002/(SICI)1097-0010(199804)76:4<599::AID-JSFA995>3.0.CO;2-F.Debon S.J.J., Tester R.F., Millam S., Davies H.V. Effect of temperature on the synthesis, composition and physical properties of potato microtuber starch. J. Sci. Food Agric. 1998;76(4):599-607. DOI 10.1002/(SICI)1097-0010(199804)76:4<599::AID-JSFA995>3.0.CO;2-F.Defernez M., Gunning Y.M., Parr A.J., Shepherd L.V., Davies H.V., Colquhoun I.J. NMR and HPLC-UV profiling of potatoes with genetic modifications to metabolic pathways. J. Agric. Food Chem. 2004;52(20):6075-6085. DOI 10.1021/jf049522e.Defernez M., Gunning Y.M., Parr A.J., Shepherd L.V., Davies H.V., Colquhoun I.J. NMR and HPLC-UV profiling of potatoes with genetic modifications to metabolic pathways. J. Agric. Food Chem. 2004;52(20):6075-6085. DOI 10.1021/jf049522e.Desire S., Couillerot J.P., Hilbert J.L., Vasseur J. Protein changes in Solanum tuberosum during in vitro tuberization of nodal cuttings. Plant Physiol. Biochem. 1995;33(4):303-310.Desire S., Couillerot J.P., Hilbert J.L., Vasseur J. Protein changes in Solanum tuberosum during in vitro tuberization of nodal cuttings. Plant Physiol. Biochem. 1995;33(4):303-310.Dixon R.A., Gang D.R., Charlton A.J., Fiehn O., Kuiper H.A., Reynolds T.L., Tjeerdema R.S., Jeffery E.H., German J.B., Ridley W.P., Seiber J.N. Applications of metabolomics in agriculture. J. Agric. Food Chem. 2006;54(24):8984-8994. DOI 10.1021/jf061218t.Dixon R.A., Gang D.R., Charlton A.J., Fiehn O., Kuiper H.A., Reynolds T.L., Tjeerdema R.S., Jeffery E.H., German J.B., Ridley W.P., Seiber J.N. Applications of metabolomics in agriculture. J. Agric. Food Chem. 2006;54(24):8984-8994. DOI 10.1021/jf061218t.Dobson G., Shepherd T., Verrall S.R., Conner S., McNicol J.W., Ramsay G., Shepherd L.V., Davies H.V., Stewart D. Phytochemical diversity in tubers of potato cultivars and landraces using a GC-MS metabolomics approach. J. Agric. Food Chem. 2008;56(21):1028010291. DOI 10.1021/jf801370b.Dobson G., Shepherd T., Verrall S.R., Conner S., McNicol J.W., Ramsay G., Shepherd L.V., Davies H.V., Stewart D. Phytochemical diversity in tubers of potato cultivars and landraces using a GC-MS metabolomics approach. J. Agric. Food Chem. 2008;56(21):1028010291. DOI 10.1021/jf801370b.Dobson G., Shepherd T., Verrall S.R., Griffiths W.D., Ramsay G., McNicol J.W., Davies H.V., Stewart D. A metabolomics study of cultivated potato (Solanum tuberosum) groups Andigena, Phureja, Stenotomum, and tuberosum using gas chromatography-mass spectrometry. J. Agric. Food Chem. 2010;58(2):1214-1223. DOI 10.1021/jf903104b.Dobson G., Shepherd T., Verrall S.R., Griffiths W.D., Ramsay G., McNicol J.W., Davies H.V., Stewart D. A metabolomics study of cultivated potato (Solanum tuberosum) groups Andigena, Phureja, Stenotomum, and tuberosum using gas chromatography-mass spectrometry. J. Agric. Food Chem. 2010;58(2):1214-1223. DOI 10.1021/jf903104b.Dodds K.S. Classification of cultivated potatoes. The Potato and its Wild Relatives. Ed. D.S. Correll. Contrib. Texas Res. Foundation, Bot. Stud. 1962;4:517-539.Dodds K.S. Classification of cultivated potatoes. The Potato and its Wild Relatives. Ed. D.S. Correll. Contrib. Texas Res. Foundation, Bot. Stud. 1962;4:517-539.Doerge R.W. Mapping and analysis of quantitative trait loci in experimental populations. Nature Rev. Genet. 2002;3(1):43-52. DOI 10.1038/nrg703.Doerge R.W. Mapping and analysis of quantitative trait loci in experimental populations. Nature Rev. Genet. 2002;3(1):43-52. DOI 10.1038/nrg703.Duckham S.C., Dodson A.T., Bakker J., Ames J.M. Volatile flavour components of baked potato flesh. A comparison of eleven potato cultivars. Nahrung. 2001;45(5):317-323. DOI 10.1002/1521-3803 (20011001)45:5<317::AID-FOOD317>3.0.CO;2-4.Duckham S.C., Dodson A.T., Bakker J., Ames J.M. Volatile flavour components of baked potato flesh. A comparison of eleven potato cultivars. Nahrung. 2001;45(5):317-323. DOI 10.1002/1521-3803 (20011001)45:5<317::AID-FOOD317>3.0.CO;2-4.Enot D.P., Beckmann M., Draper J. Detecting a difference – assessing generalisability when modelling metabolome fingerprint data in longer term studies of genetically modified plants. Metabolomics. 2007; 3(3):335-347. DOI 10.1007/s11306-007-0064-4.Enot D.P., Beckmann M., Draper J. Detecting a difference – assessing generalisability when modelling metabolome fingerprint data in longer term studies of genetically modified plants. Metabolomics. 2007; 3(3):335-347. DOI 10.1007/s11306-007-0064-4.Farre E.M., Fernie A.R., Willmitzer L. Analysis of subcellular metabolite levels of potato tubers (Solanum tuberosum) displaying alterations in cellular or extracellular sucrose metabolism. Metabolomics. 2008;4(2):161-170. DOI 10.1007/s11306-008-0107-5.Farre E.M., Fernie A.R., Willmitzer L. Analysis of subcellular metabolite levels of potato tubers (Solanum tuberosum) displaying alterations in cellular or extracellular sucrose metabolism. Metabolomics. 2008;4(2):161-170. DOI 10.1007/s11306-008-0107-5.Fernie A.R., Schauer N. Metabolomics-assisted breeding: a viable option for crop improvement? Trends Genet. 2009;25(1):39-48. DOI http://dx.doi.org/10.1016/j.tig.2008.10.010.Fernie A.R., Schauer N. Metabolomics-assisted breeding: a viable option for crop improvement? Trends Genet. 2009;25(1):39-48. DOI http://dx.doi.org/10.1016/j.tig.2008.10.010.Fernie A.R., Tauberger E., Lytovchenko A., Roessner U., Willmitzer L., Trethewey R.N. Antisense repression of cytosolic phosphoglucomutase in potato (Solanum tuberosum) results in severe growth retardation, reduction in tuber number and altered carbon metabolism. Planta. 2002;214(4):510-520. DOI 10.1007/s004250100644.Fernie A.R., Tauberger E., Lytovchenko A., Roessner U., Willmitzer L., Trethewey R.N. Antisense repression of cytosolic phosphoglucomutase in potato (Solanum tuberosum) results in severe growth retardation, reduction in tuber number and altered carbon metabolism. Planta. 2002;214(4):510-520. DOI 10.1007/s004250100644.Fernie A.R., Willmitzer L. Molecular and biochemical triggers of potato tuber development. Plant Physiol. 2001;127(4):1459-1465. DOI 10.1104/pp.010764.Fernie A.R., Willmitzer L. Molecular and biochemical triggers of potato tuber development. Plant Physiol. 2001;127(4):1459-1465. DOI 10.1104/pp.010764.Fiehn O., Kopka J., Dormann P., Altmann T., Trethewey R.N., Willmitzer L. Metabolite profiling for plant functional genomics. Nature Biotechnol. 2000;18(11):1157-1161. DOI 10.1038/81137.Fiehn O., Kopka J., Dormann P., Altmann T., Trethewey R.N., Willmitzer L. Metabolite profiling for plant functional genomics. Nature Biotechnol. 2000;18(11):1157-1161. DOI 10.1038/81137.Fly R., Lloyd J., Krueger S., Fernie A., Van der Merwe M.J. Improvements to define mitochondrial metabolomics using nonaqueous fractionation. Methods Mol. Biol. 2015;1305:197-210. DOI 10.1007/978-1-4939-2639-8_14.Fly R., Lloyd J., Krueger S., Fernie A., Van der Merwe M.J. Improvements to define mitochondrial metabolomics using nonaqueous fractionation. Methods Mol. Biol. 2015;1305:197-210. DOI 10.1007/978-1-4939-2639-8_14.Frank T., Engel K. Metabolomic analysis of plants and crops. Metabolomics in Food and Nutrition. Elsevier, 2013;148-191. DOI 10.1533/9780857098818.2.148.Frank T., Engel K. Metabolomic analysis of plants and crops. Metabolomics in Food and Nutrition. Elsevier, 2013;148-191. DOI 10.1533/9780857098818.2.148.Friedman M. Potato glycoalkaloids and metabolites: roles in the plant and in the diet. J. Agric. Food Chem. 2006;54(23):8655-8681. DOI 10.1021/jf061471t.Friedman M. Potato glycoalkaloids and metabolites: roles in the plant and in the diet. J. Agric. Food Chem. 2006;54(23):8655-8681. DOI 10.1021/jf061471t.Fukushima A., Engel M. Recent progress in the development of metabolome databases for plant systems biology. Front. Plant Sci. 2013; 4:73. DOI 10.3389/fpls.2013.00073.Fukushima A., Engel M. Recent progress in the development of metabolome databases for plant systems biology. Front. Plant Sci. 2013; 4:73. DOI 10.3389/fpls.2013.00073.Geigenberger P., Tiessen A., Meurer J. Use of non-aqueous fractionation and metabolomics to study chloroplast function in Arabidopsis. Methods Mol. Biol. 2011;775:135-160. DOI 10.1007/978-161779-237-3_8.Geigenberger P., Tiessen A., Meurer J. Use of non-aqueous fractionation and metabolomics to study chloroplast function in Arabidopsis. Methods Mol. Biol. 2011;775:135-160. DOI 10.1007/978-161779-237-3_8.Grierson C.S., Barnes S.R., Chase M.W., Clarke M., Grierson D., Edwards K.J., Jellis G.J., Jones J.D., Knapp S., Oldroyd G., Poppy G., Temple P., Williams R., Bastow R. One hundred important questions facing plant science research. New Phytol. 2011;192(1):6-12. DOI 10.1111/j.1469-8137.2011.03859.x.Grierson C.S., Barnes S.R., Chase M.W., Clarke M., Grierson D., Edwards K.J., Jellis G.J., Jones J.D., Knapp S., Oldroyd G., Poppy G., Temple P., Williams R., Bastow R. One hundred important questions facing plant science research. New Phytol. 2011;192(1):6-12. DOI 10.1111/j.1469-8137.2011.03859.x.Guedon E., Desvaux M., Pettitdemange H. Kinetic analysis of Clostridium cellulyticum carbohydrate metabolism: importance of glucose 1-phosphate and glucose 6-phosphate branch points for distribution of carbon fluxes inside and outside cells as revealed by steadystate continuous culture. J. Bacteriol. 2000;182(7):2010-2017. DOI 10.1128/JB.182.7.2010-2017.2000.Guedon E., Desvaux M., Pettitdemange H. Kinetic analysis of Clostridium cellulyticum carbohydrate metabolism: importance of glucose 1-phosphate and glucose 6-phosphate branch points for distribution of carbon fluxes inside and outside cells as revealed by steadystate continuous culture. J. Bacteriol. 2000;182(7):2010-2017. DOI 10.1128/JB.182.7.2010-2017.2000.Hall R.D., Brouwer I.D., Fitzgerald M.A. Plant metabolomics and its potential application for human nutrition. Physiol. Plant. 2008; 132(2):162-175. DOI 10.1111/j.1399-3054.2007.00989.x.Hall R.D., Brouwer I.D., Fitzgerald M.A. Plant metabolomics and its potential application for human nutrition. Physiol. Plant. 2008; 132(2):162-175. DOI 10.1111/j.1399-3054.2007.00989.x.Hellwege E., Czapla S., Jahnke A., Willmitzer L., Heyer A. Transgenic potato (Solanum tuberosum) tubers synthesize the full spectrum of inulin molecules naturally occurring in globe artichoke (Cynara scolymus) roots. Proc. Natl. Acad. Sci. USA. 2000;97(15):86998704. DOI 10.1073/pnas.150043797.Hellwege E., Czapla S., Jahnke A., Willmitzer L., Heyer A. Transgenic potato (Solanum tuberosum) tubers synthesize the full spectrum of inulin molecules naturally occurring in globe artichoke (Cynara scolymus) roots. Proc. Natl. Acad. Sci. USA. 2000;97(15):86998704. DOI 10.1073/pnas.150043797.Hill C.B., Taylor J.D., Edwards J., Mather D., Langridge P., Bacic A., Roessner U. Detection of QTL for metabolic and agronomic traits in wheat with adjustments for variation at genetic loci that affect plant phenology. Plant Sci. 2015;233:143-154. DOI http://dx.doi.org/10.1016/j.plantsci.2015.01.008.Hill C.B., Taylor J.D., Edwards J., Mather D., Langridge P., Bacic A., Roessner U. Detection of QTL for metabolic and agronomic traits in wheat with adjustments for variation at genetic loci that affect plant phenology. Plant Sci. 2015;233:143-154. DOI http://dx.doi.org/10.1016/j.plantsci.2015.01.008.Hoekenga O.A. Using metabolomics to estimate unintended effects in transgenic crop plants: problems, promises, and opportunities. J. Biomol. Tech. 2008;19(3):159-166.Hoekenga O.A. Using metabolomics to estimate unintended effects in transgenic crop plants: problems, promises, and opportunities. J. Biomol. Tech. 2008;19(3):159-166.Horning E.C., Horning M.G. Human metabolic profiles obtained by GC and GC/MS. J. Chromatogr. Sci. 1971;9(3):129-140. DOI 10.1093/chromsci/9.3.129.Horning E.C., Horning M.G. Human metabolic profiles obtained by GC and GC/MS. J. Chromatogr. Sci. 1971;9(3):129-140. DOI 10.1093/chromsci/9.3.129.Jaakola L. New insights into the regulation of anthocyanin biosynthesis in fruits. Trends Plant Sci. 2013;18(9):477-483. DOI http://dx.doi.org/10.1016/j.tplants.2013.06.003.Jaakola L. New insights into the regulation of anthocyanin biosynthesis in fruits. Trends Plant Sci. 2013;18(9):477-483. DOI http://dx.doi.org/10.1016/j.tplants.2013.06.003.Joseph B., Atwell S., Corwin J.A., Li B., Kliebenstein D.J. Metaanalysis of metabolome QTLs in Arabidopsis: trying to estimate the network size controlling genetic variation of the metabolome. Front. Plant Sci. 2014;5:461. DOI http://dx.doi.org/10.3389/fpls.2014.00461.Joseph B., Atwell S., Corwin J.A., Li B., Kliebenstein D.J. Metaanalysis of metabolome QTLs in Arabidopsis: trying to estimate the network size controlling genetic variation of the metabolome. Front. Plant Sci. 2014;5:461. DOI http://dx.doi.org/10.3389/fpls.2014.00461.Joseph B., Corwin J.A., Kliebenstein D.J. Genetic variation in the nuclear and organellar genomes modulates stochastic variation in the metabolome, growth, and defense. PLoS Genet. 2015;11(1):e1004779. DOI 10.1371/journal.pgen.1004779.Joseph B., Corwin J.A., Kliebenstein D.J. Genetic variation in the nuclear and organellar genomes modulates stochastic variation in the metabolome, growth, and defense. PLoS Genet. 2015;11(1):e1004779. DOI 10.1371/journal.pgen.1004779.Joseph B., Corwin J.A., Li B., Atwell S., Kliebenstein D.J. Cytoplasmic genetic variation and extensive cytonuclear interactions influence natural variation in the metabolome. eLife. 2013;2:e00776. DOI 10.7554/eLife.0077.Joseph B., Corwin J.A., Li B., Atwell S., Kliebenstein D.J. Cytoplasmic genetic variation and extensive cytonuclear interactions influence natural variation in the metabolome. eLife. 2013;2:e00776. DOI 10.7554/eLife.0077.Juzepczuk S.W., Bukasov S.M. K voprosu o proiskhozhdenii kartofelya [A contribution to the question of the origin of potato]. Trudy Vsesoyuznogo s’ezda po genetike, selektsii, semenovodstvu i plemennomu zhivotnovodstvu [Proceedings of the All-Union Congress on genetics, seed farming, and livestock breeding]. 1929;3:593-611. (in Russin)Juzepczuk S.W., Bukasov S.M. K voprosu o proiskhozhdenii kartofelya [A contribution to the question of the origin of potato]. Trudy Vsesoyuznogo s’ezda po genetike, selektsii, semenovodstvu i plemennomu zhivotnovodstvu [Proceedings of the All-Union Congress on genetics, seed farming, and livestock breeding]. 1929;3:593-611. (in Russin)Kloosterman B., Oortwijn M., uitdeWilligen J., America T., de Vos R., Visser R.G.F., Bachem C.W. From QTL to candidate gene: genetical genomics of simple and complex traits in potato using a pooling strategy. BMC Genomics. 2010;11:158. DOI 10.1186/1471-216411-158.Kloosterman B., Oortwijn M., uitdeWilligen J., America T., de Vos R., Visser R.G.F., Bachem C.W. From QTL to candidate gene: genetical genomics of simple and complex traits in potato using a pooling strategy. BMC Genomics. 2010;11:158. DOI 10.1186/1471-216411-158.Kolbe H., Stephan-Beckmann S. Development, growth and chemical composition of the potato crop (Solanum tuberosum L.). II. Tuber and whole plant. Potato Res. 1997;40(2):135-153. DOI 10.1007/BF02358240.Kolbe H., Stephan-Beckmann S. Development, growth and chemical composition of the potato crop (Solanum tuberosum L.). II. Tuber and whole plant. Potato Res. 1997;40(2):135-153. DOI 10.1007/BF02358240.Lachman J., Hamouz K. Red and purple coloured potatoes as a significant antioxidant source in human nutrition – a review. Plant Soil Environ. 2005;51(11):477-482.Lachman J., Hamouz K. Red and purple coloured potatoes as a significant antioxidant source in human nutrition – a review. Plant Soil Environ. 2005;51(11):477-482.Lachman J., Hamouz K., Orsák M., Pivec V. Potato tubers as a significant source of antioxidants in human nutrition. Rostlinná Vyroba. 2000;46(5):231-236.Lachman J., Hamouz K., Orsák M., Pivec V. Potato tubers as a significant source of antioxidants in human nutrition. Rostlinná Vyroba. 2000;46(5):231-236.Leidreiter K., Kruse A., Heineke D., Robinson D.G., Heldt H.W. Subcellular volumes and metabolite concentrations in potato (Solanum tuberosum cv. Desiree) leaves. Bot. Acta. 1995;108(5):439-444. DOI 10.1111/j.1438-8677.1995.tb00518.x.Leidreiter K., Kruse A., Heineke D., Robinson D.G., Heldt H.W. Subcellular volumes and metabolite concentrations in potato (Solanum tuberosum cv. Desiree) leaves. Bot. Acta. 1995;108(5):439-444. DOI 10.1111/j.1438-8677.1995.tb00518.x.Liebeke M., Bruford M.W., Donnelly R.K., Ebbels T.M.D., Hao J., Kille P., Lahive E., Madison R.M., Morgan A.J., Pinto-Juma G.A., Spurgeon D.J., Svendsen C., Bundy J.G. Identifying biochemical phenotypic differences between cryptic species. Biol. Lett. 2014; 10(9):20140615. DOI 10.1098/rsbl.2014.0615.Liebeke M., Bruford M.W., Donnelly R.K., Ebbels T.M.D., Hao J., Kille P., Lahive E., Madison R.M., Morgan A.J., Pinto-Juma G.A., Spurgeon D.J., Svendsen C., Bundy J.G. Identifying biochemical phenotypic differences between cryptic species. Biol. Lett. 2014; 10(9):20140615. DOI 10.1098/rsbl.2014.0615.López-Caamal A., Tovar-Sánchez E. Genetic, morphological, and chemical patterns of plant hybridization. Rev. Chil. Hist. Nat. 2014; 87:16. DOI 10.1186/s40693-014-0016-0.López-Caamal A., Tovar-Sánchez E. Genetic, morphological, and chemical patterns of plant hybridization. Rev. Chil. Hist. Nat. 2014; 87:16. DOI 10.1186/s40693-014-0016-0.Lytovchenko A., Bieberich K., Willmitzer L., Fernie A.R. Carbon assimilation and metabolism in potato leaves deficient in plastidial phosphoglucomutase. Planta. 2002a;215(5):802-811. DOI 10.1007/s00425-002-0810-9.Lytovchenko A., Bieberich K., Willmitzer L., Fernie A.R. Carbon assimilation and metabolism in potato leaves deficient in plastidial phosphoglucomutase. Planta. 2002a;215(5):802-811. DOI 10.1007/s00425-002-0810-9.Lytovchenko A., Sweetlove L., Pauly M., Fernie A.R. The influence of cytosolic phosphoglucomutase on photosynthetic carbohydrate metabolism. Planta. 2002b;215(6):1013-1021. DOI 10.1007/s00425002-0826-1.Lytovchenko A., Sweetlove L., Pauly M., Fernie A.R. The influence of cytosolic phosphoglucomutase on photosynthetic carbohydrate metabolism. Planta. 2002b;215(6):1013-1021. DOI 10.1007/s00425002-0826-1.Martin F., Ames J.M. Formation of Strecker aldehydes and pyrazines in a fried potato model system. J. Agric. Food Chem. 2001;49(8):38853892. DOI 10.1021/jf010310g.Martin F., Ames J.M. Formation of Strecker aldehydes and pyrazines in a fried potato model system. J. Agric. Food Chem. 2001;49(8):38853892. DOI 10.1021/jf010310g.Nema P.K., Ramayya N., Duncan E., Niranjan K. Potato glycoalkaloids: formation and strategies for 392 mitigation. J. Sci. Food Agr. 2008;88(11):1869-1881. DOI 10.1002/jsfa.3302.Nema P.K., Ramayya N., Duncan E., Niranjan K. Potato glycoalkaloids: formation and strategies for 392 mitigation. J. Sci. Food Agr. 2008;88(11):1869-1881. DOI 10.1002/jsfa.3302.Oliver S.G., Winson M.K., Kell D.B., Baganz F. Systematic functional analysis of the yeast genome. Trends Biotechnol. 1998;16(9):373378. DOI http://dx.doi.org/10.1016/S0167-7799(98)01214-1.Oliver S.G., Winson M.K., Kell D.B., Baganz F. Systematic functional analysis of the yeast genome. Trends Biotechnol. 1998;16(9):373378. DOI http://dx.doi.org/10.1016/S0167-7799(98)01214-1.Park Y., Cho J., Cho H., Yi J., Seo H., Choung M. A new potato cultivar “Hongyoung”, with red skin and flesh color, and high concentrations of anthocyanins. Korean J. Breed. Sci. 2009a;41(4):502-506.Park Y., Cho J., Cho H., Yi J., Seo H., Choung M. A new potato cultivar “Hongyoung”, with red skin and flesh color, and high concentrations of anthocyanins. Korean J. Breed. Sci. 2009a;41(4):502-506.Park Y., Cho J., Cho H., Yi J., Seo H., Chung M. A new potato cultivar “Jayoung”, with high concentration of anthocyanin. Korean J. Breed. Sci. 2009b;41(1):51-55.Park Y., Cho J., Cho H., Yi J., Seo H., Chung M. A new potato cultivar “Jayoung”, with high concentration of anthocyanin. Korean J. Breed. Sci. 2009b;41(1):51-55.Pauling L., Robinson A.B., Teranishi R., Cary P. Quantitative analysis of urine vapor and breath by gas-liquid partition chromatography. Proc. Natl. Acad. Sci. USA. 1971;68(10):2374-2376.Pauling L., Robinson A.B., Teranishi R., Cary P. Quantitative analysis of urine vapor and breath by gas-liquid partition chromatography. Proc. Natl. Acad. Sci. USA. 1971;68(10):2374-2376.Puzanskiy R.K., Shavarda A.L., Shishova M.F. Dinamika metaboloma kletok avtotrofnoy kul’tury Chlamydomonas reinhardtii v period eksponentsial’noy i statsionaronoy fazy rosta. [Dynamics of autotrophic Chlamydomonas reinhardtii metabolome during exponentional and stationary phase]. Vestnik Leningradskogo gosudarstvennogo universiteta im. A.S. Pushkina [Vestnik of Pushkin Leningrad State University Ser. 3]. 2015;1:104-121. (in Russin)Puzanskiy R.K., Shavarda A.L., Shishova M.F. Dinamika metaboloma kletok avtotrofnoy kul’tury Chlamydomonas reinhardtii v period eksponentsial’noy i statsionaronoy fazy rosta. [Dynamics of autotrophic Chlamydomonas reinhardtii metabolome during exponentional and stationary phase]. Vestnik Leningradskogo gosudarstvennogo universiteta im. A.S. Pushkina [Vestnik of Pushkin Leningrad State University Ser. 3]. 2015;1:104-121. (in Russin)Raamsdonk L.M., Teusink B., Broadhurst D., Zhang N., Hayes A., Walsh M.C., Berden J.A., Brindle K.M., Kell D.B., Rowland J.J., Westerhoff H.V., van Dam K., Oliver S.G. A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations. Nature Biotechnol. 2001;19(1):45-50. DOI 10.1038/83496.Raamsdonk L.M., Teusink B., Broadhurst D., Zhang N., Hayes A., Walsh M.C., Berden J.A., Brindle K.M., Kell D.B., Rowland J.J., Westerhoff H.V., van Dam K., Oliver S.G. A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations. Nature Biotechnol. 2001;19(1):45-50. DOI 10.1038/83496.Ray W.J., Peck E.J. Phosphoglucomutases. The Enzymes. New York: Acad. Press, 1973;407-488.Ray W.J., Peck E.J. Phosphoglucomutases. The Enzymes. New York: Acad. Press, 1973;407-488.Richardson D.L., Davies H.V., Ross H.A. Potato tuber sugar content during development and storage (10 °C): possible predictors of storage potential and the role of sucrose in storage hexose accumulation. Potato Res. 1990;33(2):241-245. DOI 10.1007/BF02358452.Richardson D.L., Davies H.V., Ross H.A. Potato tuber sugar content during development and storage (10 °C): possible predictors of storage potential and the role of sucrose in storage hexose accumulation. Potato Res. 1990;33(2):241-245. DOI 10.1007/BF02358452.Roessner U., Luedemann A., Brust D., Fiehn O., Linke T., Willmitzer L., Fernie A.R. Metabolic profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. Plant Cell. 2001;13(1):11-29. DOI 10.1105/tpc.13.1.11.Roessner U., Luedemann A., Brust D., Fiehn O., Linke T., Willmitzer L., Fernie A.R. Metabolic profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. Plant Cell. 2001;13(1):11-29. DOI 10.1105/tpc.13.1.11.Roessner U., Wagner C., Kopka J., Trethewey R.N., Willmitzer L. Simultaneous analysis of metabolites in potato tuber by gas chromatography-mass spectrometry. Plant J. 2000;23(1):131-142. DOI 10.1046/j.1365-313x.2000.00774.x.Roessner U., Wagner C., Kopka J., Trethewey R.N., Willmitzer L. Simultaneous analysis of metabolites in potato tuber by gas chromatography-mass spectrometry. Plant J. 2000;23(1):131-142. DOI 10.1046/j.1365-313x.2000.00774.x.Ruan C.J., Teixeira da Silva J.A. Metabolomics: creating new potentials for unraveling the mechanisms in response to salt and drought stress and for the biotechnological improvement of xero-halophytes. Crit. Rev. Biotechnol. 2011;31(2):153-69. DOI http://dx.doi.org/10.3109/07388551.2010.505908.Ruan C.J., Teixeira da Silva J.A. Metabolomics: creating new potentials for unraveling the mechanisms in response to salt and drought stress and for the biotechnological improvement of xero-halophytes. Crit. Rev. Biotechnol. 2011;31(2):153-69. DOI http://dx.doi.org/10.3109/07388551.2010.505908.Sauter H., Lauer M., Fritsch H. Metabolic profiling of plants a new diagnostic technique. ACS Symp. Ser. 1991;443:288-299. DOI 10.1021/bk-1991-0443.ch024.Sauter H., Lauer M., Fritsch H. Metabolic profiling of plants a new diagnostic technique. ACS Symp. Ser. 1991;443:288-299. DOI 10.1021/bk-1991-0443.ch024.Schauer N., Semel Y., Roessner U., Gur A., Balbo I., Carrari F., Pleban T., Perez-Melis A., Bruedigam C., Kopka J., Willmitzer L., Zamir D., Ferni A.R. Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement. Nature Biotechnol. 2006;24(4):447-454. DOI 10.1038/nbt1192.Schauer N., Semel Y., Roessner U., Gur A., Balbo I., Carrari F., Pleban T., Perez-Melis A., Bruedigam C., Kopka J., Willmitzer L., Zamir D., Ferni A.R. Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement. Nature Biotechnol. 2006;24(4):447-454. DOI 10.1038/nbt1192.Shepherd L.V., Fraser P., Stewart D. Metabolomics: a second-generation platform for crop and food analysis. Bioanalysis. 2011;3(10):11431159. DOI 10.4155/bio.11.61.Shepherd L.V., Fraser P., Stewart D. Metabolomics: a second-generation platform for crop and food analysis. Bioanalysis. 2011;3(10):11431159. DOI 10.4155/bio.11.61.Shepherd L.V., Hackett C.A., Alexander C.J., McNicol J.W., Sungurtas J.A., McRae D., McCue K.F., Belknap W.R., Davies H.V. Impact of light-exposure on the metabolite balance of transgenic potato tubers with modified glycoalkaloid biosynthesis. Food Chem. 2016; 200:263-273. DOI http://dx.doi.org/10.1016/j.foodchem. 2015. 12.095.Shepherd L.V., Hackett C.A., Alexander C.J., McNicol J.W., Sungurtas J.A., McRae D., McCue K.F., Belknap W.R., Davies H.V. Impact of light-exposure on the metabolite balance of transgenic potato tubers with modified glycoalkaloid biosynthesis. Food Chem. 2016; 200:263-273. DOI http://dx.doi.org/10.1016/j.foodchem. 2015. 12.095.Shepherd L.V., Hackett C.A., Alexander C.J., McNicol J.W., Sungurtas J.A., Stewart D., McCue K.F., Belknap W.R., Davies H.V. Modifying glycoalkaloid content in transgenic potato – Metabolome impacts. Food Chem. 2015;187:437-443. DOI http://dx.doi.org/10.1016/j.foodchem.2015.04.111.Shepherd L.V., Hackett C.A., Alexander C.J., McNicol J.W., Sungurtas J.A., Stewart D., McCue K.F., Belknap W.R., Davies H.V. Modifying glycoalkaloid content in transgenic potato – Metabolome impacts. Food Chem. 2015;187:437-443. DOI http://dx.doi.org/10.1016/j.foodchem.2015.04.111.Shepherd T., Dobson G., Verrall S., Conner S., Griffiths D., McNicol J., Davies H., Stewart D. Potato metabolomics by GC-MS: what are the limiting factors? Metabolomics. 2007;3(4):475-488. DOI 10.1007/s11306-007-0058-2.Shepherd T., Dobson G., Verrall S., Conner S., Griffiths D., McNicol J., Davies H., Stewart D. Potato metabolomics by GC-MS: what are the limiting factors? Metabolomics. 2007;3(4):475-488. DOI 10.1007/s11306-007-0058-2.Spooner D.M., Ghislain M., Simon R., Jansky S.H., Gavrilenko T. Systematics, diversity, genetics, and evolution of wild and cultivated potatoes. Bot. Rev. 2014;80(4):283-383. DOI 10.1007/s12229014-9146-y.Spooner D.M., Ghislain M., Simon R., Jansky S.H., Gavrilenko T. Systematics, diversity, genetics, and evolution of wild and cultivated potatoes. Bot. Rev. 2014;80(4):283-383. DOI 10.1007/s12229014-9146-y.Stacklies W., Redestig H., Scholz M., Walther D., Selbig J. pcaMethods-a bioconductor package providing PCA methods for incomplete data. Bioinformatics. 2007;23(9):1164-1167. DOI 10.1093/bioinformatics/btm069.Stacklies W., Redestig H., Scholz M., Walther D., Selbig J. pcaMethods-a bioconductor package providing PCA methods for incomplete data. Bioinformatics. 2007;23(9):1164-1167. DOI 10.1093/bioinformatics/btm069.Stewart D., Shepherd L.V.T. Metabolomics for the safety assessment of genetically modified (GM) crops. Metabolomics in Food and Nutrition. Elsevier, 2013;192-216. DOI http://dx.doi.org/10.1533/9780857098818.2.192.Stewart D., Shepherd L.V.T. Metabolomics for the safety assessment of genetically modified (GM) crops. Metabolomics in Food and Nutrition. Elsevier, 2013;192-216. DOI http://dx.doi.org/10.1533/9780857098818.2.192.Stewart D., Shepherd L.V.T., Hall R., Fraser P. Crops and tasty, nutritious food – How can metabolomics help? Annual Plant Rev. 2011;43:181-217.Stewart D., Shepherd L.V.T., Hall R., Fraser P. Crops and tasty, nutritious food – How can metabolomics help? Annual Plant Rev. 2011;43:181-217.Stushnoff C., Ducreux L.J., Hancock R.D., Hedley P.E., Holm D.G., McDougall G.J., McNicol J.W., Morris J., Morris W.L., Sungurtas J.A. Flavonoid profiling and transcriptome analysis reveals new gene – metabolite correlations in tubers of Solanum tuberosum L. J. Exp. Bot. 2010;61(4):1225-1238. DOI 10.1093/jxb/erp394.Stushnoff C., Ducreux L.J., Hancock R.D., Hedley P.E., Holm D.G., McDougall G.J., McNicol J.W., Morris J., Morris W.L., Sungurtas J.A. Flavonoid profiling and transcriptome analysis reveals new gene – metabolite correlations in tubers of Solanum tuberosum L. J. Exp. Bot. 2010;61(4):1225-1238. DOI 10.1093/jxb/erp394.Tauberger E., Fernie A.R., Emmermann M., Renz A., Kossmann J., Willmitzer L., Trethewey R.N. Antisense inhibition of plastidial phosphoglucomutase provides compelling evidence that potato tuber amyloplasts import carbon from the cytosol in the form of glucose-6-phosphate. Plant J. 2000;23(1):43-53. DOI 10.1046/j.1365313x.2000.00783.x.Tauberger E., Fernie A.R., Emmermann M., Renz A., Kossmann J., Willmitzer L., Trethewey R.N. Antisense inhibition of plastidial phosphoglucomutase provides compelling evidence that potato tuber amyloplasts import carbon from the cytosol in the form of glucose-6-phosphate. Plant J. 2000;23(1):43-53. DOI 10.1046/j.1365313x.2000.00783.x.Tiessen A., Nerlich A., Faix B., Hümmer C., Fox S., Trafford K., Weber H., Weschke W., Geigenberger P. Subcellular analysis of starch metabolism in developing barley seeds using a non-aqueous fractionation method. J. Exp. Bot. 2012;63(5):2071-2087. DOI 10.1093/jxb/err408.Tiessen A., Nerlich A., Faix B., Hümmer C., Fox S., Trafford K., Weber H., Weschke W., Geigenberger P. Subcellular analysis of starch metabolism in developing barley seeds using a non-aqueous fractionation method. J. Exp. Bot. 2012;63(5):2071-2087. DOI 10.1093/jxb/err408.Trethewey R.N., Krotzky A.J., Willmitzer L. Metabolic profiling: a Rosetta Stone for genomics? Curr. Opin. Plant Biol. 1999;2(2):8385. DOI 10.1016/S1369-5266(99)80017-X.Trethewey R.N., Krotzky A.J., Willmitzer L. Metabolic profiling: a Rosetta Stone for genomics? Curr. Opin. Plant Biol. 1999;2(2):8385. DOI 10.1016/S1369-5266(99)80017-X.Truong V.-D., Deighton N., Thompson R.T., McFeeters R.F., Dean L.O., Pecota K.V., Yencho G.C. Characterization of anthocyanins and anthocyanidins in purple-fleshed sweetpotatoes by HPLC-DAD/ESI-MS/MS. J. Agric. Food Chem. 2010;58(1):404410. DOI 10.1021/jf902799a.Truong V.-D., Deighton N., Thompson R.T., McFeeters R.F., Dean L.O., Pecota K.V., Yencho G.C. Characterization of anthocyanins and anthocyanidins in purple-fleshed sweetpotatoes by HPLC-DAD/ESI-MS/MS. J. Agric. Food Chem. 2010;58(1):404410. DOI 10.1021/jf902799a.Tweeddale H., Notley-McRobb L., Ferenci T. Effect of slow growth on metabolism of Escherichia coli, as revealed by global metabolite pool (“Metabolome”) analysis. J. Bacteriol. 1998;180(19):51095116.Tweeddale H., Notley-McRobb L., Ferenci T. Effect of slow growth on metabolism of Escherichia coli, as revealed by global metabolite pool (“Metabolome”) analysis. J. Bacteriol. 1998;180(19):51095116.Urbanczyk-Wochniak E., Baxter C., Kolbe A., Kopka J., Sweetlove L.J., Fernie A.R. Profiling of diurnal patterns of metabolite and transcript abundance in potato (Solanum tuberosum) leaves. Planta. 2005;221(6):891-903. DOI 10.1007/s00425-005-1483-y.Urbanczyk-Wochniak E., Baxter C., Kolbe A., Kopka J., Sweetlove L.J., Fernie A.R. Profiling of diurnal patterns of metabolite and transcript abundance in potato (Solanum tuberosum) leaves. Planta. 2005;221(6):891-903. DOI 10.1007/s00425-005-1483-y.Uri C., Juhász Z., Polgár Z., Bánfalvi Z. A GC-MS-based metabolomics study on the tubers of commercial potato cultivars upon storage. Food Chem. 2014;159:287-292. DOI http://dx.doi.org/10.1016/j.foodchem.2014.03.010.Uri C., Juhász Z., Polgár Z., Bánfalvi Z. A GC-MS-based metabolomics study on the tubers of commercial potato cultivars upon storage. Food Chem. 2014;159:287-292. DOI http://dx.doi.org/10.1016/j.foodchem.2014.03.010.van Eck H.J., Jacobs J.M., Stam P., Ton J., Stiekema W.J., Jacobsen E. Multiple alleles for tuber shape in diploid potato detected by qualitative and quantitative genetic analysis using RFLPs. Genetics. 1994; 137(1):303-309.van Eck H.J., Jacobs J.M., Stam P., Ton J., Stiekema W.J., Jacobsen E. Multiple alleles for tuber shape in diploid potato detected by qualitative and quantitative genetic analysis using RFLPs. Genetics. 1994; 137(1):303-309.van Gelder W.M.J. Chemistry, toxicology, and occurrence of steroidal glycoalkaloids: potential contaminants of the potato (Solanum tuberosum L.). Poisonous Plant Contamination of Edible Plants. Boca Raton, Florida: CRC Press, 1990;117-156.van Gelder W.M.J. Chemistry, toxicology, and occurrence of steroidal glycoalkaloids: potential contaminants of the potato (Solanum tuberosum L.). Poisonous Plant Contamination of Edible Plants. Boca Raton, Florida: CRC Press, 1990;117-156.Veramendi J., Willmitzer L., Trethewey R. In vitro grown potato microtubers are a suitable system for the study of transgenic lines altered in primary carbohydrate metabolism. Plant Physiol. Biochem. 1999;37(9):693-697. DOI http://dx.doi.org/10.1016/S09819428(00)80100-X.Veramendi J., Willmitzer L., Trethewey R. In vitro grown potato microtubers are a suitable system for the study of transgenic lines altered in primary carbohydrate metabolism. Plant Physiol. Biochem. 1999;37(9):693-697. DOI http://dx.doi.org/10.1016/S09819428(00)80100-X.Visser R.G.F., Vreugdenhil D., Hendriks D., Jacobsen T. Gene expression and carbohydrate metabolism during stolon to tuber transition in potatoes (Solanum tuberosum L.). Physiol. Plant. 1994;90(2):285292. DOI 10.1111/j.1399-3054.1994.tb00389.x.Visser R.G.F., Vreugdenhil D., Hendriks D., Jacobsen T. Gene expression and carbohydrate metabolism during stolon to tuber transition in potatoes (Solanum tuberosum L.). Physiol. Plant. 1994;90(2):285292. DOI 10.1111/j.1399-3054.1994.tb00389.x.Weckwerth W., Loureiro M.E., Wenzel K., Fiehn O. Differential metabolic networks unravel the effects of silent plant phenotypes. Proc. Natl. Acad. Sci. USA. 2004;101(20):7809-7814. DOI 10.1073/pnas. 0303415101.Weckwerth W., Loureiro M.E., Wenzel K., Fiehn O. Differential metabolic networks unravel the effects of silent plant phenotypes. Proc. Natl. Acad. Sci. USA. 2004;101(20):7809-7814. DOI 10.1073/pnas. 0303415101.Wiklund S., Johansson E., Sjöström L., Mellerowicz E.J., Edlund U., Shockcor J.P., Gottfries J., Moritz T., Trygg J. Visualization of GC/TOF-MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models. Anal. Chem. 2008;80(1):115-122. DOI 10.1021/ac0713510.Wiklund S., Johansson E., Sjöström L., Mellerowicz E.J., Edlund U., Shockcor J.P., Gottfries J., Moritz T., Trygg J. Visualization of GC/TOF-MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models. Anal. Chem. 2008;80(1):115-122. DOI 10.1021/ac0713510.Wink M. Evolution of secondary metabolites from an ecological and molecular phylogenetic perspective. Phytochemistry. 2003;64(1):319. DOI http://dx.doi.org/10.1016/S0031-9422(03)00300-5.Wink M. Evolution of secondary metabolites from an ecological and molecular phylogenetic perspective. Phytochemistry. 2003;64(1):319. DOI http://dx.doi.org/10.1016/S0031-9422(03)00300-5.Wold S., Sjöström M., Eriksson L. PLS-regression: A basic tool of chemometrics. Chemometr. Intell. Lab. 2001;58(2):109-130. DOI http://dx.doi.org/10.1016/S0169-7439(01)00155-1.Wold S., Sjöström M., Eriksson L. PLS-regression: A basic tool of chemometrics. Chemometr. Intell. Lab. 2001;58(2):109-130. DOI http://dx.doi.org/10.1016/S0169-7439(01)00155-1.Wolfender J.L., Rudaz S., Choi Y.H., Kim H.K. Plant metabolomics: from holistic data to relevant biomarkers. Curr. Med. Chem. 2013;20(8):1056-1090. DOI 10.2174/0929867311320080009.Wolfender J.L., Rudaz S., Choi Y.H., Kim H.K. Plant metabolomics: from holistic data to relevant biomarkers. Curr. Med. Chem. 2013;20(8):1056-1090. DOI 10.2174/0929867311320080009.

The authors declare that there are no conflicts of interest present.