vavilovВавиловский журнал генетики и селекцииVavilov Journal of Genetics and Breeding2500-3259Institute of Cytology and Genetics of Siberian Branch of the RAS10.18699/VJ16.194vavilov-850Research ArticleАнализ регуляторных последовательностейAnalysis of regulatory sequencesКомпьютерный анализ совместной локализации сайтов связывания транскрипционных факторов в геноме по данным ChIP-seqComputer analysis of co-localization of transcription factor binding sites in genome by ChIP-seq dataДергилевА. И.DergilevA. I.

Новосибирск, Россия

Novosibirsk, Russia

arturd1993@yandex.ruСпицинаА. М.SpitsinaA. M.

Новосибирск, Россия

Novosibirsk, Russia

ЧадаеваИ. В.ChadaevaI. V.

Новосибирск, Россия

Novosibirsk, Russia

СвичкаревА. В.SvichkarevA. V.

Новосибирск, Россия

Санкт-Петербург, Россия

Novosibirsk, Russia

Saint-Petersburg, Russia

НауменкоФ. М.NaumenkoF. M.

Новосибирск, Россия

Novosibirsk, Russia

КулаковаЕ. В.KulakovaE. V.

Новосибирск, Россия

Novosibirsk, Russia

ГалиеваЭ. Р.GalievaE. R.

Новосибирск, Россия

Novosibirsk, Russia

ВитяевЕ. Е.VityaevE. E.

Новосибирск, Россия

Novosibirsk, Russia

ЧенМ.ChenM.

Ханчжоу, Китай

Hangzhou, China

ОрловЮ. Л.OrlovY. L.

Новосибирск, Россия

Novosibirsk, Russia

orlov@bionet.nsc.ruФедеральное государственное автономное образовательное учреждение высшего образования «Новосибирский национальный исследовательский государственный университет» Федеральное государственное бюджетное научное учреждение «Федеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук»РоссияNovosibirsk State University Institute of Cytology and Genetics SB RASRussian FederationФедеральное государственное автономное образовательное учреждение высшего образования «Новосибирский национальный исследовательский государственный университет»РоссияNovosibirsk State UniversityRussian FederationФедеральное государственное автономное образовательное учреждение высшего образования «Новосибирский национальный исследовательский государственный университет» Федеральное государственное бюджетное научное учреждение «Федеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук»РоссияNovosibirsk State University Institute of Cytology and Genetics SB RASRussian FederationФедеральное государственное автономное образовательное учреждение высшего образования «Новосибирский национальный исследовательский государственный университет» Федеральное государственное автономное образовательное учреждение высшего образования «Санкт-Петербургский политехнический университет Петра Великого»РоссияNovosibirsk State University Peter the Great St. Petersburg Polytechnic UniversityRussian FederationФедеральное государственное бюджетное научное учреждение «Федеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук» Федеральное государственное бюджетное учреждение науки Институт математики им. С.Л. Соболева Сибирского отделения Российской академии наукРоссияInstitute of Cytology and Genetics SB RAS Institute of Mathematics SB RASRussian FederationУниверситет ЧжэцзянРоссияZhejiang UniversityRussian Federation201601022017206770778Copyright © Дергилев А.И., Спицина А.М., Чадаева И.В., Свичкарев А.В., Науменко Ф.М., Кулакова Е.В., Галиева Э.Р., Витяев Е.Е., Чен М., Орлов Ю.Л., 20172017Дергилев А.И., Спицина А.М., Чадаева И.В., Свичкарев А.В., Науменко Ф.М., Кулакова Е.В., Галиева Э.Р., Витяев Е.Е., Чен М., Орлов Ю.Л.Dergilev A.I., Spitsina A.M., Chadaeva I.V., Svichkarev A.V., Naumenko F.M., Kulakova E.V., Galieva E.R., Vityaev E.E., Chen M., Orlov Y.L.This work is licensed under a Creative Commons Attribution 4.0 License.https://vavilov.elpub.ru/jour/article/view/850

Разработана компьютерная программа расчета кластеров сайтов связывания различных транскрипционных факторов (ТФ) по данным геномных координат пиков профиля ChIP-seq (Chromatin ImmunoPrecipitation-sequencing). Рассмотрены статистические особенности распределения сайтов связывания транскрипционных факторов в геноме мыши, полученных с помощью ChIP-seq экспериментов в эмбриональных стволовых клетках. Определены кластеры сайтов, содержащие четыре (и более) сайта связывания различных транскрипционных факторов в геноме мыши, описано их расположение относительно регуляторных районов генов. Подтверждено наличие двух типов совместной локализации сайтов: кластеры, содержащие сайты связывания факторов Oct4, Nanog, Sox2, расположенные в дистальных районах, и кластеры с сайтами связывания n-Myc, c-Myc, находящиеся в основном в промоторных районах генов мыши. Анализ новых данных ChIP- seq по связыванию транскрипционных факторов Nr5a2, Tbx3, Cep, SRF, USF1 в том же типе клеток подтвердил разделение кластеров сайтов связывания транскрипционных факторов на два типа: содержащие сайты связывания регуляторов плюрипотентности (Oct4, Nanog и Sox2) и не включающие их. Разработана компьютерная программа статистической обработки данных о расположении сайтов в генах, использующая экспериментальные данные локализации сайтов, которые получены методами ChIP- seq в геномах мыши и человека. С помощью этой программы выявлены закономерности локализации сайтов связывания транскрипционных факторов различных типов. Рассчитаны расстояния между ближайшими сайтами связывания ТФ группы Oct4, Nanog, Sox2 и сайтами связывания других факторов в кластерах сайтов, которые служат основой для анализа совместного связывания белковых комплексов с ДНК. Рассчитана доля присутствия известных нуклеотидных мотивов сайтов связывания транскрипционных факторов в геномных участках ChIP-seq. Пересчитаны весовые матрицы для таких нуклеотидных мотивов. Показана корреляция присутствия мотивов с интенсивностью связывания ChIP-seq. Программы, реализующие разработанные компьютерные методы оценки кластеризации сайтов связывания различных транскрипционных факторов для новых данных ChIP-seq, доступны по запросу к авторам.

Statistical features of the distribution of transcription factor binding sites in the mouse genome that are obtained by ChIP-seq experiments in embryonic stem cells have been considered. Clusters of sites that contain four or more different transcription factor binding sites in the mouse genome have been defined, also their location relatively to the regulatory regions of genes has been described. The presence of two types of site co-localization has been shown: clusters containing binding sites for factors Oct4, Nanog, Sox2, located in the distal regions, and clusters containing binding sites n-Myc, c-Myc, mainly located in the promoter regions of mouse genes. Analysis of new ChIPseq data about binding of transcription factors Nr5a2, Tbx3 in the same cell type has confirmed the division of clusters of transcription factors binding sites into two types: those containing the binding sites of regulators of pluripotency (Oct4, Nanog, and others) and those not. The computer program of the statistical data processing of gene location and chromatin domains that analyzes experimental data of site localization obtained by ChIP-seq in the mouse genome and the human genome has been developed. The presence of preferences at position of transcription factor binding sites of various types has been revealed, the distances between the nearest groups of TF binding sites Oct4, Nanog, Sox2 and TF binding sites n-Myc and c-Myc have been calculated using this program. The presence of nucleotide motifs of transcription factor binding sites in the selected areas of ChIP-seq has been estimated, nucleotide motifs have been refined. A correlation between the presence of motifs and the intensity of ChIPseq binding has been shown. Computer methods for estimating the clustering of different transcription factors binding sites for new data ChIP-seq have been developed. Programs are available upon the request to the authors.

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