vavilovВавиловский журнал генетики и селекцииVavilov Journal of Genetics and Breeding2500-3259Institute of Cytology and Genetics of Siberian Branch of the RAS10.18699/VJ19.501vavilov-2023Research ArticleСелекция растений на иммунитет и продуктивностьPlant breeding for immunity and performanceПриоритизация генов картофеля, вовлеченных в формирование селекционно-значимых признаков, с использованием базы знаний SOLANUM TUBEROSUMPrioritization of potato genes involved in the formation of agronomically valuable traits using the SOLANUM TUBEROSUM knowledge baseДеменковП. С.DemenkovP. S.demps@bionet.nsc.ruСайкО. В.SaikO. V.ИванисенкоТ. В.IvanisenkoT. V.КолчановН. А.KolchanovN. A.https://orcid.org/0000-0003-3151-5181КочетовА. В.KochetovA. V.ИванисенкоВ. А.IvanisenkoV. A.Федеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук; Новосибирский национальный исследовательский государственный университетРоссияInstitute of Cytology and Genetics, SB RAS; Novosibirsk State UniversityRussian FederationФедеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наукРоссияInstitute of Cytology and Genetics, SB RASRussian Federation201914052019233312319Copyright © Деменков П.С., Сайк О.В., Иванисенко Т.В., Колчанов Н.А., Кочетов А.В., Иванисенко В.А., 20192019Деменков П.С., Сайк О.В., Иванисенко Т.В., Колчанов Н.А., Кочетов А.В., Иванисенко В.А.Demenkov P.S., Saik O.V., Ivanisenko T.V., Kolchanov N.A., Kochetov A.V., Ivanisenko V.A.This work is licensed under a Creative Commons Attribution 4.0 License.https://vavilov.elpub.ru/jour/article/view/2023

Развитие высокоэффективных технологий в геномике, транскриптомике, протеомике и метаболомике, а также новых технологий в сельском хозяйстве привело к «информационному взрыву» в биологии растений и растениеводстве, включая производство картофеля. Лишь небольшая часть информации попадает в формализованные базы данных (например, Uniprot, NCBI Gene, BioGRID, IntAct и др.). Один из основных источников достоверных биологических данных – научная литература. Объем литературы велик, так, известная база данных PubMed содержит более 18 тыс. тезисов статей, посвященных картофелю. Эффективное получение знаний, представленных в таком количестве неформализованных текстовых документов, требует применения современных интеллектуальных методов анализа. Однако в литературе нет свидетельств широкого применения интеллектуальных методов автоматического извлечения знаний из научных публика ций по таким культурам, как картофель. В рамках настоящей работы использовалась разработанная нами ранее база знаний SOLANUM TUBEROSUM (http://www-bionet.sysbio.cytogen.ru/and/plant/). Интегрированная в базе знаний информация о молекулярно-генетических механизмах, лежащих в основе селекционнозначимых признаков, способствует ускорению идентификации генов-кандидатов для селекционно-значимых характеристик картофеля и разработки диагностических маркеров для селекции. В статье выполнен поиск новых потенциальных участников молекулярно-генетических механизмов устойчивости к неблагоприятным факторам у растений. Приоритизация генов-кандидатов показала, что гены PHYA, GF14, CNIH1, RCI1A, ABI5, CPK1, RGS1, NHL3, GRF8 и CYP21-4 наиболее перспективны для дальнейшей проверки их связей с устойчивостью к неблагоприятным факторам. В результате проведенного анализа выявлено, что молекулярно-генетические взаимоотношения, ответственные за формирование значимых сельскохозяйственных признаков, являются комплексными и включают множество как прямых, так и опосредованных взаимодействий. Построение ассоциативных генных сетей и их анализ с использованием базы знаний SOLANUM TUBEROSUM – это основа поиска генов-мишеней для направленного мутагенеза и маркер-ориентированной селекции сортов картофеля, обладающих ценными сельскохозяйственными признаками.

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.

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