SmartCrop: база знаний молекулярно-генетических механизмов адаптации риса и пшеницы к стрессовым факторам

Изучение молекулярно-генетических механизмов реакций растений на специфические условия роста и стрессовые факторы – одно из приоритетных направлений исследований, нацеленных на создание новых сортов сельскохозяйственных культур, в частности риса и пшеницы. К числу таких факторов относятся абиотические стрессы (высокие или низкие температуры, засуха, засоление, загрязнение почвы металлами), биотические стрессы (патогены, вредители), а также реакции растений на регуляторные факторы (удобрения, гормоны, элиситоры и другие соединения). Современные исследования в области генетики растений основаны на понимании того, что формирование любых фенотипических характеристик (молекулярно-генетических, биохимических, физиологических, морфологических и др.) контролируется генными сетями – группами согласованно функционирующих генов, взаимодействующих через свои продукты (РНК, белки и метаболиты). Ранее с целью реконструкции генных сетей, значимых для биологии и биомедицины, нами была разработана интеллектуальная компьютерная система ANDSystem, предназначенная для автоматизированного извлечения знаний из текстов научных публикаций и баз данных. В настоящей работе, используя адаптированную версию ANDSystem для растений, мы создали базу знаний SmartCrop для решения задач, связанных с изучением молекулярно-генетических механизмов взаимодействий «генотип–фенотип–среда» для сельскохозяйственно ценных культур риса и пшеницы. SmartCrop предназначена для помощи исследователям в решении таких задач, как интерпретация результатов омиксных экспериментов на растениях: установление связей между наборами генов и биологическими процессами, фенотипическими признаками и др.; реконструкция генных сетей, описывающих отношения между молекулярно-генетическими объектами и понятиями в селекции, феномике, семеноводстве, фитопатологии; выявление регуляторных и сигнальных путей, ответных реакций растений на специфические условия роста и биотические и абиотические стрессы; прогнозирование генов-кандидатов для генотипирования; поиск маркеров для маркер-опосредованной селекции; выявление потенциальных мишеней (генов и белков) для субстанций, влияющих на растения (контролирующих процессы прорастания семян, вегетативного роста, эффективного поглощения питательных веществ и улучшения устойчивости к стрессовым факторам).

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