vavilovВавиловский журнал генетики и селекцииVavilov Journal of Genetics and Breeding2500-3259Institute of Cytology and Genetics of Siberian Branch of the RAS10.18699/vjgb-25-18vavilov-4487Research ArticleБИОМЕДИЦИНАBIOMEDICINEБаза знаний MiceDEGdb по дифференциально экспрессирующимся генам мыши как модельного объекта биомедицинских исследованийMiceDEGdb: a knowledge base on differentially expressed mouse genes as a model object in biomedical researchhttps://orcid.org/0000-0003-3247-0114ПодколоднаяО. А.PodkolodnayaO. A.

Новосибирск

Novosibirsk

https://orcid.org/0000-0002-2724-5441ЧадаеваИ. В.ChadaevaI. V.

Новосибирск

Novosibirsk

ФилоновС. В.FilonovS. V.

Новосибирск

Novosibirsk

https://orcid.org/0000-0001-9132-7997ПодколодныйН. Л.PodkolodnyyN. L.

Новосибирск

Novosibirsk

https://orcid.org/0000-0003-4795-0954РассказовД. А.RasskazovD. A.

Новосибирск

Novosibirsk

ТвердохлебН. Н.TverdokhlebN. N.

Новосибирск

Novosibirsk

https://orcid.org/0009-0006-3933-208XЗолотареваК. А.ZolotarevaK. A.

Новосибирск

Novosibirsk

https://orcid.org/0000-0003-4359-6089БогомоловА. Г.BogomolovA. G.

Новосибирск

Novosibirsk

https://orcid.org/0000-0001-8672-7216КондратюкЕ. Ю.KondratyukE. Yu.

Новосибирск; Новосибирская область; р. п. Краснообск 

Novosibirsk; Novosibirsk region; Krasnoobsk

https://orcid.org/0000-0002-6097-5155ОщепковД. Ю.OshchepkovD. Yu.

Новосибирск

Novosibirsk

https://orcid.org/0000-0003-1663-318XПономаренкоМ. П.PonomarenkoM. P.

Новосибирск

Novosibirsk

pon@bionet.nsc.ruФедеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наукРоссияInstitute of Cytology and Genetics of the Siberian Branch of the Russian Academy of SciencesRussian FederationФедеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук; Курчатовский геномный центр ИЦиГ СО РАНРоссияInstitute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences; Kurchatov Genomic Center of ICG SB RASRussian FederationФедеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук; Институт вычислительной математики и математической геофизики Сибирского отделения Российской академии наукРоссияInstitute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences; Institute of Computational Mathematics and Mathematical Geophysics of the Siberian Branch of the Russian Academy of SciencesRussian FederationФедеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук; Новосибирский национальный исследовательский государственный университетРоссияInstitute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences; Novosibirsk State UniversityRussian FederationФедеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук; Сибирский федеральный научный центр агробиотехнологий Российской академии наукРоссияInstitute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences; Siberian Federal Scientific Centre of Agro-BioTechnologies of the Russian Academy of SciencesRussian FederationФедеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук; Курчатовский геномный центр ИЦиГ СО РАН; Новосибирский национальный исследовательский государственный университетРоссияInstitute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences; Kurchatov Genomic Center of ICG SB RAS; Novosibirsk State UniversityRussian Federation202504032025291153161Copyright © Подколодная О.А., Чадаева И.В., Филонов С.В., Подколодный Н.Л., Рассказов Д.А., Твердохлеб Н.Н., Золотарева К.А., Богомолов А.Г., Кондратюк Е.Ю., Ощепков Д.Ю., Пономаренко М.П., 20252025Подколодная О.А., Чадаева И.В., Филонов С.В., Подколодный Н.Л., Рассказов Д.А., Твердохлеб Н.Н., Золотарева К.А., Богомолов А.Г., Кондратюк Е.Ю., Ощепков Д.Ю., Пономаренко М.П.Podkolodnaya O.A., Chadaeva I.V., Filonov S.V., Podkolodnyy N.L., Rasskazov D.A., Tverdokhleb N.N., Zolotareva K.A., Bogomolov A.G., Kondratyuk E.Y., Oshchepkov D.Y., Ponomarenko M.P.This work is licensed under a Creative Commons Attribution 4.0 License.https://vavilov.elpub.ru/jour/article/view/4487

   Фундаментальное понимание многих биологических процессов, происходящих в организме человека, стало возможным благодаря экспериментальным исследованиям на животных моделях. Основным стержнем современных биомедицинских исследований является использование мышиных моделей для изучения важных патофизиологических механизмов, оценки новых терапевтических подходов и принятия решений о переходе или отказе от новых кандидатов на препараты в доклинических испытаниях. Преимущество задействования мышей заключается в их небольших размерах, простых условиях содержания и относительно легкой генетической модификации. В настоящее время более 90 % грызунов, используемых для фармацевтических исследований, – мыши. В представленной работе создана пилотная версия базы знаний MiceDEGdb по дифференциально экспрессирующимся генам (ДЭГ) мыши как модельного объекта в биомедицинских исследованиях. Она представляет собой коллекцию опубликованных данных по экспрессии генов у мышей разных линий, предназначенных для изучения возрастных заболеваний: гипертонии, пародонтита, хрупкости кости, фиброза почки, ремоделирования гладких мышц, сердечной недостаточности, нарушения циркадного ритма. Пилотный выпуск базы знаний MiceDEGdb содержит 21 754 ДЭГ, представляющих 9769 уникальных генов Mus musculus, у которых изменяется уровень транскрипции в 25 экспериментах по технологии RNA-seq с использованием восьми тканей (десна, кость, почка, правый желудочек сердца, дуга аорты, гиппокамп, скелетная мышца и матка) в шести генетических линиях мышей, C57BL/6J, Ren1cCre|ZsGreen, B6.129S7(Cg)-Polgtm1Prol/J, BPN/3J, BPH/2J и Kunming, в качестве моделей восьми заболеваний человека согласно 10 оригинальным статьям. Новшеством MiceDEGdb в сравнении с другими базами данных о ДЭГ мышей является курируемая аннотация отклонений ДЭГ мыши от соответствующей нормы с помощью независимых биомедицинских публикаций о сонаправленных изменениях экспрессии гомологичных генов человека у пациентов с теми или иными заболеваниями относительно условно здоровых добровольцев. В пилотном выпуске MiceDEGdb документировано 85 092 таких аннотаций для 318 генов человека при 895 заболеваниях согласно 912 научным статьям, цитируемым с помощью их идентификаторов PubMed ID. Информационное содержание MiceDEGdb может быть интересным для генетиков, молекулярных биологов, биоинформатиков, клиницистов, фармацевтов и генетических консультантов по персонализированной медицине. База знаний MiceDEGdb находится в свободном доступе по гиперссылке: https://www.sysbio.ru/MiceDEGdb.

   The fundamental understanding of many biological processes that unfold in a human body has become possible due to experimental studies on animal models. The backbone of modern biomedical research is the use of mouse models for studying important pathophysiological mechanisms, assessing new therapeutic approaches and making decisions on acceptance or rejection of new candidate medicines in preclinical trials. The use of mice is advantageous because they have small size, are easy to keep and to genetically modify. Mice make up more than 90 % of the rodents used for pharmaceutical research. We present the pilot version of MiceDEGdb, a knowledge base on the genes that are differentially expressed in the mouse used as a model object in biomedical researc h. MiceDEGdb is a collection of published data on gene expression in mouse strains used for studying age-related diseases, such as hypertension, pe rio dontal disease, bone fragility, renal fibrosis, smooth muscle remodeling, heart failure and circadian rhythm disorder. The pilot release of MiceDEGdb contains 21,754 DEGs representing 9,769 unique Mus musculus genes the transcription levels whereof were found as being changed in 25 RNA-seq experiments involving eight tissues – gum, bone, kidney, right ventricle, aortic arch, hippocampus, skeletal muscle and uterus – in six genetic mouse strains (C57BL/6J, Ren1cCre|ZsGreen, B6.129S7(Cg)-Polgtm1Prol/J, BPN/3J, BPH/2J and Kunming) used as models of eight human diseases – all these data were based on information in 10 original articles. MiceDEGdb is novel in that it features a curated annotation of changes in the expression levels of mouse DEGs using independent biomedical publications about same-direction changes in the expression levels of human homologs in patients with one disease or the other. In its pilot release, MiceDEGdb documented 85,092 such annotations for 318 human genes in 895 diseases, as suggest to 912 scientific articles referenced by their PubMed ID. The information contained in MiceDEGdb may be of interest to geneticists, molecular biologists, bioinformatics scientists, clinicians, pharmacologists and genetic advisors in personalized medicine. MiceDEGdb is freely available at https://www.sysbio.ru/MiceDEGdb.

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