Prioritization of potato genes involved in the formation of agronomically valuable traits using the SOLANUM TUBEROSUM knowledge base

The development of highly efficient technologies in genomics, transcriptomics, proteomics and metabolomics, as well as new technologies in agriculture has led to an “information explosion” in plant biology and crop production, including potato production. Only a small part of the information reaches formalized databases (for example, Uniprot, NCBI Gene, BioGRID, IntAct, etc.). One of the main sources of reliable biological data is the scientific literature. The well-known PubMed database contains more than 18 thousand abstracts of articles on potato. The effective use of knowledge presented in such a number of non-formalized documents in natural language requires the use of modern intellectual methods of analysis. However, in the literature, there is no evidence of a widespread use of intelligent methods for automatically extracting knowledge from scientific publications on cultures such as potatoes. Earlier we developed the SOLANUM TUBEROSUM knowledge base (http://www-bionet.sysbio.cytogen. ru/and/plant/). Integrated into the knowledge base information about the molecular genetic mechanisms underlying the selection of significant traits helps to accelerate the identification of candidate genes for the breeding characteristics of potatoes and the development of diagnostic markers for breeding. The article searches for new potential participants of the molecular genetic mechanisms of resistance to adverse factors in plants. Prioritizing candidate genes has shown that the PHYA, GF14, CNIH1, RCI1A, ABI5, CPK1, RGS1, NHL3, GRF8, and CYP21-4 genes are the most promising for further testing of their relationships with resistance to adverse factors. As a result of the analysis, it was shown that the molecular genetic relationships responsible for the formation of significant agricultural traits are complex and include many direct and indirect interactions. The construction of associative gene networks and their analysis using the SOLANUM TUBEROSUM knowledge base is the basis for searching for target genes for targeted mutagenesis and marker-oriented selection of potato varieties with valuable agricultural characteristics.

potato, Solanum tuberosum, ANDSystem, text mining, knowledge base, automatic extraction of knowledge from texts, prioritization of genes, associative gene networks

1. Aggarwal C.C., Zhai C. Mining Text Data. Springer Science & Business Media, 2012. Belyaev D.V., Nosova A.E., Krivosheeva A.B., Tereshonok D.V., Yur’eva N.O., Rudas V.A., Kuchuk N.V. Expression of the vacuolar antiporter of barley increases the salt tolerance and drought tolerance in transgenic potatoes. Proceedings of the Conference “Modern Aspects of Plant Genetic Engineering”. Kiev, May 30–June 1, 2011. (in Russian)

2. Campbell M.A., Gleichsner A., Hilldorfer L., Horvath D., Suttle J. The sprout inhibitor 1, 4-dimethylnaphthalene induces the expression of the cell cycle inhibitors KRP1 and KRP2 in potatoes. Funct. Integr. Genomics. 2012;12(3):533-541. DOI 10.1007/s10142-011- 0257-9.

3. Cao Y., Liu F., Simpson P., Antieaua L., Bennett A., Cimino J.J., Ely J., Yu H. AskHERMES: An online question answering system for complex clinical questions. J. Biomed. Inform. 2011;44:277-288. DOI 10.1016/j.jbi.2011.01.004.

4. Carles C., Bies‐Etheve N., Aspart L., Léon‐Kloosterziel K.M., Koornneef M., Echeverria M., Delseny M. Regulation of Arabidopsis thaliana Em genes: role of ABI5. Plant J. 2002;30(3):373-383.

5. Catalá R., López-Cobollo R., Castellano M.M., Angosto T., Alonso J.M., Ecker J.R., Salinas J. The Arabidopsis 14-3-3 protein RARE COLD INDUCIBLE 1A links low-temperature response and ethylene biosynthesis to regulate freezing tolerance and cold acclimation. Plant Cell. 2014;26(8):3326-3342. DOI 10.1105/ tpc.114.127605.

6. Chen A., Li C., Hu W., Lau M.Y., Lin H., Rockwell N.C., Martin S.S., Jernstedt J.A., Lagarias J.C., Dubcovsky J. Phytochrome C plays a major role in the acceleration of wheat flowering under long-day photoperiod. Proc. Natl. Acad. Sci. 2014;111(28):10037-10044. DOI 10.1073/pnas.1409795111.

7. Chen J., Bardes E.E., Aronow B.J., Jegga A.G. ToppGene Suite for gene list enrichment analysis and candidate gene prioritization. Nucl. Acids Res. 2009;37(Suppl. 2):W305-W311.

8. Chen Y., Ji F., Xie H., Liang J. Overexpression of the regulator of G-protein signalling protein enhances ABA-mediated inhibition of root elongaion and drought tolerance in Arabidopsis. J. Exp. Bot. 2006;57(9):2101-2110.

9. Chong J., Le Henanff G., Bertsch C., Walter B. Identification, expression analysis and characterization of defense and signaling genes in Vitis vinifera. Plant Physiol. Biochem. 2008;46(4):469-481. DOI 10.1016/j.plaphy.2007.09.010.

10. da Costa E., Tjandrasa H., Djanali S. Text mining for pest and disease identification on rice farming with interactive text messaging. Int. J. Elec. & Comp. Eng. (IJECE). 2018;8(3):1671-1683.

11. Demenkov P.S., Ivanisenko T.V., Kolchanov N.A., Ivanisenko V.A. ANDVisio: a new tool for graphic visualization and analysis of literature mined associative gene networks in the ANDSystem. In Silico Biology. 2012;11(3-4):149-161. DOI 10.3233/ISB-2012-0449.

12. Ellis R.P., Cochrane M.P., Dale M.F.B., Duffus C.M., Lynn A., Morrison I.M., Prentice R.D.M., Swanston J.S., Tiller S.A. Starch production and industrial use. J. Sci. Food Agric. 1998;77(3):289-311. DOI 10.1002/(SICI)1097-0010(199807)77:3 3.0.CO;2-D.

13. Finkelstein R.R. Mutations at two new Arabidopsis ABA response loci are similar to the abi3 mutations. Plant J. 1994;5:765-771.

14. Finkelstein R.R., Lynch T.J. The Arabidopsis abscisic acid response gene ABI5 encodes a basic leucine zipper transcription factor. Plant Cell. 2000;12(4):599-609.

15. Friedman C., Hripcsak G., Shagina L., Liu H. Representing information in patient reports using natural language processing and the extensible markup language. J. Am. Med. Inform. Assoc. 1999;6:76-87. DOI 10.1136/jamia.1999.0060076.

16. Fulgosi H., Soll J., de Faria Maraschin S., Korthout H.A., Wang M., Testerink C. 14-3-3 proteins and plant development. Plant Mol. Biol. 2002;50(6):1019-1029.

17. Gravino M., Savatin D.V., Macone A., De Lorenzo G. Ethylene production in Botrytis cinerea- and oligogalacturonide-induced immunity requires calcium-dependent protein kinases. Plant J. 2015;84(6): 1073-1086. DOI 10.1111/tpj.13057.

18. Huang K., Peng L., Liu Y., Yao R., Liu Z., Li X., Yang Y., Wang J. Arabidopsis calcium-dependent protein kinase AtCPK1 plays a positive role in salt/drought-stress response. Biochem. Biophys. Res. Commun. 2018;498(1):92-98.

19. Ivanisenko V.A., Saik O.V., Ivanisenko N.V., Tiys E.S., Ivanisenko T.V., Demenkov P.S., Kolchanov N.A. ANDSystem: an Associative Network Discovery System for automated literature mining in the field of biology. BMC Syst. Biol. 2015;9(Suppl. 2):S2. DOI 10.1186/1752-0509-9-S2-S2.

20. Ivanisenko T.V., Saik O.V., Demenkov P.S., Khlestkin V.K., Khlestkina E.K., Kolchanov N.A., Ivanisenko V.A. The SOLANUM TUBEROSUM knowledge base: the section on molecular-genetic regulation of metabolic pathways. Vavilovskii Zhurnal Genetiki i Selektsii = Vavilov Journal of Genetics and Breeding. 2018;22(1): 8-17. (in Russian) Jobling S. Improving starch for food and industrial applications. Curr. Opin. Plant Biol. 2004;7(2):210-218. DOI 10.1016/j.pbi.2003.12.001.

21. Jones J.D., Witek K., Verweij W., Jupe F., Cooke D., Dorling S., Tomlinson L., Smoker M., Perkins S., Foster S. Elevating crop disease resistance with cloned genes. Philos. Trans. R. Soc. Lond. B Biol. Sci. 2014;369(1639):20130087. DOI 10.1098/rstb.2013.0087.

22. Khlestkin V.K., Peltek S.E., Kolchanov N.A. Target genes for development of potato (Solanum tuberosum L.) cultivars with desired starch properties. Selskokhozyaystvennaya Biologiya = Agricultural Biology. 2017;52(1):25-36. (in Russian)

23. Khlestkin V.K., Peltek S.E., Kolchanov N.A. Review of direct chemical and biochemical transformations of starch. Carbohydr. Polymers. 2018;181(1):460-476. DOI 10.1016/j.carbpol.2017.10.035. Kikuchi A., Huynh H.D., Endo T., Watanabe K. Review of recent transgenic studies on abiotic stress tolerance and future molecular breeding in potato. Breed. Sci. 2015;65(1):85-102.

24. Kilicoglu H. Biomedical text mining for research rigor and integrity: tasks, challenges, directions. Brief. Bioinform. 2017, Jan 1. DOI 10.1101/108480. Kraak A. Industrial applications of potato starch products. Ind. Crops Prod. 1992;1(2-4):107-112. DOI 10.1016/0926-6690(92)90007-I.

25. Krallinger M., Rodriguez-Penagos C., Tendulkar A., Valencia A. PLAN2L: a web tool for integrated text mining and literaturebased bioentity relation extraction. Nucleic Acids Res. 2009;11; 37(Suppl. 2):W160-W165. DOI 10.1093/nar/gkp484.

26. Li C., Liakata M., Rebholz-Schuhmann D. Biological network extraction from scientific literature: state of the art and challenges. Brief. Bioinform. 2013;15(5):856-877. DOI 10.1093/bib/bbt006.

27. Liu Z., Jia Y., Ding Y., Shi Y., Li Z., Guo Y., Gong Z., Yang S. Plasma membrane CRPK1-mediated phosphorylation of 14-3-3 proteins induces their nuclear import to fine-tune CBF signaling during cold response. Mol. Cell. 2017;66(1):117-128.

28. Lopez-Molina L., Mongrand S., McLachlin D.T., Chait B.T., Chua N.H. ABI5 acts downstream of ABI3 to execute an ABA-dependent growth arrest during germination. Plant J. 2002;32:317-328.

29. Manosalva P.M., Bruce M., Leach J.E. Rice 14-3-3 protein (GF14e) negatively affects cell death and disease resistance. Plant J. 2011; 68(5):777-787.

30. Meystre S.M., Savova G.K., Kipper-Schuler K.C., Hurdle J.F. Extracting information from textual documents in the electronic health record: a review of recent research. Yearb. Med. Inform. 2008;35: 128-144.

31. Mittler R. Oxidative stress, antioxidants and stress tolerance. Trends Plant Sci. 2002;7(9):405-410. DOI 10.1016/S1360-1385(02)02312-9.

32. Monneveux P., Ramírez D.A., Pino M.T. Drought tolerance in potato (S. tuberosum L.): can we learn from drought tolerance research in cereals? Plant Sci. 2013;205:76-86.

33. Park H.J., Lee A., Lee S.S., An D.J., Moon K.B., Ahn J.C., Kim H.S., Cho H.S. Overexpression of Golgi protein CYP21-4s improves crop productivity in potato and rice by increasing the abundance of mannosidic glycoproteins. Front. Plant Sci. 2017;8:1250.

34. Perl A., Perl-Treves R., Galili S., Aviv D., Shalgi E., Malkin S., Galun E. Enhanced oxidative-stress defense in transgenic potato expressing tomato Cu, Zn superoxide dismutases. Theor. Appl. Genet. 1993;85(5):568-576.

35. Ramirez E., Ducreux L.J., Redfern C., Morris W.L., Wiese C., Morris J.A., Paterson C., Hedley P.E., Hancock R.D., Taylor M. A reversible light- and genotype-dependent acquired thermotolerance response protects the potato plant from damage due to excessive temperature. Planta. 2018;247(6):1377-1392.

36. Rebholz-Schuhmann D., Oellrich A., Hoehndorf R. Text-mining solutions for biomedical research: enabling integrative biology. Nat. Rev. Genet. 2012;13:829-839. DOI 10.1038/nrg3337.

37. Rosas-Santiago P., Lagunas-Gomez D., Yáñez-Domínguez C., VeraEstrella R., Zimmermannová O., Sychrová H., Pantoja O. Plant and yeast cornichon possess a conserved acidic motif required for correct targeting of plasma membrane cargos. Biochim. Biophys. Acta Mol. Cell Res. 2017;1864(10):1809-1818. DOI 10.1016/j.bbamcr. 2017.07.004.

38. Saik O.V., Demenkov P.S., Ivanisenko T.V., Kolchanov N.A., Ivanisenko V.A. Development of methods for automatic extraction of knowledge from texts of scientific publications for the creation of a knowledge base SOLANUM TUBEROSUM. Selskokhozyaystvennaya Biologiya = Agricultural Biology. 2017;52(1):63-74. (in Russian)

39. Saik O.V., Ivanisenko T.V., Demenkov P.S., Ivanisenko V.A. Interactome of the hepatitis C virus: Literature mining with ANDSystem. Virus Res. 2016;218:40-48. DOI 10.1016/j.virusres.2015.12.003.

40. Sarker A., Ginn R., Nikfarjam A., O’Connor K., Smith K., Jayaraman S., Upadhaya T., Gonzalez G. Utilizing social media data for pharmacovigilance: A review. J. Biomed. Inform. 2015;54:202-212. DOI 10.1016/j.jbi.2015.02.004. Sawers R.J., Sheehan M.J., Brutnell T.P. Cereal phytochromes: targets of selection, targets for manipulation? Trends Plant Sci. 2005; 10(3):138-143.

41. Schlagnhaufer C.D., Arteca R.N., Pell E.J. Sequential expression of two 1-aminocyclopropane-1-carboxylate synthase genes in response to biotic and abiotic stresses in potato (Solanum tuberosum L.) leaves. Plant Mol. Biol. 1997;35(6):683-688.

42. Shafi A., Pal A.K., Sharma V., Kalia S., Kumar S., Ahuja P.S., Singh A.K. Transgenic potato plants overexpressing SOD and APX exhibit enhanced lignification and starch biosynthesis with improved salt stress tolerance. Plant Mol. Biol. Rep. 2017;35(5):504-518.

43. Shetty K.D., Dalal S.R. Using information mining of the medical literature to improve drug safety. J. Am. Med. Inform. Assoc. 2011;18: 668-674. DOI 10.1136/amiajnl-2011-000096.

44. Świȩdrych A., Prescha A., Matysiak-Kata I., Biernat J., Szopa J. Repression of the 14-3-3 gene affects the amino acid and mineral composition of potato tubers. J. Agric. Food Chem. 2002;50(7):2137- 2141. DOI 10.1021/jf0112825.

45. Tezuka K., Taji T., Hayashi T., Sakata Y. A novel abi5 allele reveals the importance of the conserved Ala in the C3 domain for regulation of downstream genes and salt tolerance during germination in Arabidopsis. Plant Signal. Behav. 2013;8(3):e23455.

46. Trapero-Mozos A., Ducreux L.J., Bita C.E., Morris W., Wiese C., Morris J.A., Taylor M. A reversible light-and genotype-dependent acquired thermotolerance response protects the potato plant from damage due to excessive temperature. Planta. 2018;247(6):1377-1392. DOI 10.1007/s00425-018-2874-1.

47. Varet A., Hause B., Hause G., Scheel D., Lee J. The Arabidopsis NHL3 gene encodes a plasma membrane protein and its overexpression correlates with increased resistance to Pseudomonas syringae pv. tomato DC3000. Plant Physiol. 2003;132(4):2023-2033.

48. Wei C.-H., Kao H.-Y., Lu Z. PubTator: a web-based text mining tool for assisting biocuration. Nucleic Acids Res. 2013;41:W518-W522. DOI 10.1093/nar/gkt441.

49. Wudick M.M., Portes M.T., Michard E., Rosas-Santiago P., Lizzio M.A., Nunes C.O., Campos C., Damineli D.S., Carvalho J.C., Lima P.T., Pantoja O. CORNICHON sorting and regulation of GLR channels underlie pollen tube Ca2+ homeostasis. Science. 2018;360(6388): 533-536.

50. Yankina M.A., Saik O.V., Ivanisenko V.A., Demenkov P.S., Khusnutdinova E.K. Evaluation of prioritization methods of extrinsic apoptotic signaling pathway genes for retrieval of the new candidates associated with major depressive disorder. Genetika = Genetics (Moscow). 2018;54(11):1338-1348. (in Russian)

51. Yanovsky M.J., Izaguirre M., Wagmaister J.A., Gatz C., Jackson S.D., Thomas B., Casal J.J. Phytochrome A resets the circadian clock and delays tuber formation under long days in potato. Plant J. 2000; 23(2):223-232. DOI 10.1046/j.1365-313x.2000.00775.x.

52. Zhang J., Stankey R.J., Vierstra R.D. Structure-guided engineering of plant phytochrome B with altered photochemistry and light signaling. Plant Physiol. 2013;161(3):1445-1457. DOI 10.1104/pp.112. 208892.