vavilovВавиловский журнал генетики и селекцииVavilov Journal of Genetics and Breeding2500-3259Institute of Cytology and Genetics of Siberian Branch of the RAS10.18699/vjgb-26-34vavilov-5044Research ArticleВЫСОКОПРОИЗВОДИТЕЛЬНОЕ СЕКВЕНИРОВАНИЕHIGH-THROUGHPUT SEQUENCINGРазработка и валидация программы PipeSeq для анализа данных секвенирования РНК на модели Chlamydomonas reinhardtiiDevelopment and validation of the PipeSeq program for RNA-seq data analysis in the Chlamydomonas reinhardtii as a modelНерезенкоА. М.NerezenkoA. M.

Санкт-Петербург

St. Petersburg

alexnerezenko@gmail.comВиролайненП. А.VirolainenP. A.

Санкт-Петербург

St. Petersburg

ТупицынаС. А.TupitsynaS. A.

Санкт-Петербург

St. Petersburg

ЧекуноваЕ. М.ChekunovaE. M.

Санкт-Петербург

St. Petersburg

Санкт-Петербургский государственный университетРоссияSaint-Petersburg UniversityRussian Federation202606042026302299310Copyright © Нерезенко А.М., Виролайнен П.А., Тупицына С.А., Чекунова Е.М., 20262026Нерезенко А.М., Виролайнен П.А., Тупицына С.А., Чекунова Е.М.Nerezenko A.M., Virolainen P.A., Tupitsyna S.A., Chekunova E.M.This work is licensed under a Creative Commons Attribution 4.0 License.https://vavilov.elpub.ru/jour/article/view/5044

Секвенирование РНК (РНК-сек) – высокочувствительный метод анализа транскриптома, позволяющий одновременно оценивать экспрессию тысяч генов и выявлять паттерны экспрессии в различных условиях. Существующее разнообразие форматов данных РНК-сек, методов нормализации и подходов к статистической обработке результатов затрудняет сопоставление данных разных исследований и снижает воспроизводимость анализа. В настоящей работе представлен автоматизированный пайплайн PipeSeq, объединяющий стандартные этапы обработки данных РНК-сек – от загрузки (SRA Toolkit), выравнивания прочтений на референсный геном (HISAT2) и сборки транскриптов (StringTie) до подсчета транскриптов (FeatureCounts) и статистического анализа дифференциальной экспрессии генов в различных экспериментальных условиях (DESeq2). Программа PipeSeq имеет простой визуальный интерфейс, поддерживает многопоточность и формирует готовые для анализа тепловые карты экспрессии генов и отчеты в форме таблиц и графиков. Функциональность пайплайна продемонстрирована на трех наборах пакетов сырых данных секвенирования РНК клеток зеленой водоросли Chlamydomonas reinhardtii, доступных в открытой базе данных NCBI SRA. Результаты этих экспериментов были использованы для анализа дифференциальной экспрессии генов C. reinhardtii, кодирующих факторы транскрипции семейства GATA, в различных световых условиях культивирования. Полученные методами in silico данные верифицированы методом полимеразной цепной реакции в реальном времени с обратной транскрипцией (ОТ-ПЦР-РВ) по 12 генам GATA, что позволило выдвинуть предположения об их функциях, а также оценить степень согласованности между массовым (РНК-сек) и таргетным (ОТ-ПЦР-РВ) подходами. Результаты нашего исследования показали, что методы секвенирования РНК и ОТ-ПЦР-РВ выявляют схожие направления изменения экспрессии генов, но демонстрируют различия по оценке степени размера эффекта и чувствительности, что подчеркивает необходимость совместного применения двух подходов. Таким образом, программа PipeSeq представляет собой инструмент для проведения полного цикла биоинформатического анализа данных РНК-сек, дает возможность обрабатывать данные ОТ-ПЦР-РВ и выполнять сравнительный статистический анализ полученных результатов.

RNA sequencing (RNA-seq) is a highly sensitive method for transcriptome analysis that allows simultaneous assessment of expression of thousands of genes and identification of expression patterns under various conditions. The existing variety of RNA-seq data formats, normalization methods, and approaches to statistical processing of results complicates comparison of data from different studies and reduces reproducibility of the analysis. This study presents an automated pipeline PipeSeq that combines standard steps of RNA-seq data processing: loading (SRA Toolkit), read alignment to the reference genome (HISAT2), transcript assembly (StringTie), transcript counting (FeatureCounts) and statistical analysis of differential gene expression under various experimental conditions (DESeq2). PipeSeq has a simple visual interface, supports multithreading, and generates ready-to-analyze gene expression heat maps, tables and graphs. The functionality of the pipeline is demonstrated on three sets of raw RNA-seq data from the green alga Chlamydomonas reinhardtii cells available in the NCBI SRA database. The data from these experiments were used to analyze the differential expression of C. reinhardtii genes encoding the GATA family transcription factors under different light cultivation conditions. The data obtained by in silico methods were verified by real-time reverse transcription polymerase chain reaction (RT-qPCR) for 12 GATA genes, which allowed us to hypothesize their functions and evaluate the correlation between the bulk (RNA-seq) and targeted (RT-qPCR) approaches. Our results showed that RNA-seq and RT-qPCR methods reveal similar directions of gene expression changes, but demonstrate differences in the effect size and sensitivity, which emphasizes the need for a combined use of the two approaches. Thus, the PipeSeq program is a tool for conducting a full cycle of bioinformatic analysis of RNA-seq data, additionally providing the opportunity to process RT-qPCR data and perform a comparative statistical analysis of the results obtained.

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