vavilovВавиловский журнал генетики и селекцииVavilov Journal of Genetics and Breeding2500-3259Institute of Cytology and Genetics of Siberian Branch of the RAS10.18699/VJGB-23-119vavilov-4015Research ArticleСИСТЕМНАЯ И КОМПЬЮТЕРНАЯ БИОЛОГИЯSYSTEMS AND COMPUTATIONAL BIOLOGYInterTransViewer: сравнительное описание профилей дифференциальной экспрессии генов из разных экспериментовInterTransViewer: a comparative description of differential gene expression profiles from different experimentshttps://orcid.org/0000-0002-5969-3628ТяпкинА. В.TyapkinА. V.

Новосибирск

Novosibirsk

https://orcid.org/0000-0001-8813-8941ЛаврехаВ. В.LavrekhaV. V.

Новосибирск

Novosibirsk

УбогоеваЕ. В.UbogoevaE. V.

Новосибирск

Novosibirsk

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

Новосибирск

Novosibirsk

ОмельянчукН. А.OmelyanchukN. A.

Новосибирск

Novosibirsk

https://orcid.org/0009-0005-7316-7690ЗемлянскаяЕ. В.ZemlyanskayaE. V.

Новосибирск

Novosibirsk

ezemlyanskaya@bionet.nsc.ruФедеральный 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 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; Новосибирский национальный исследовательский государственный университетРоссия20232912202327810421052Copyright © Тяпкин А.В., Лавреха В.В., Убогоева Е.В., Ощепков Д.Ю., Омельянчук Н.А., Землянская Е.В., 20232023Тяпкин А.В., Лавреха В.В., Убогоева Е.В., Ощепков Д.Ю., Омельянчук Н.А., Землянская Е.В.Tyapkin А.V., Lavrekha V.V., Ubogoeva E.V., Oshchepkov D.Y., Omelyanchuk N.A., Zemlyanskaya E.V.This work is licensed under a Creative Commons Attribution 4.0 License.https://vavilov.elpub.ru/jour/article/view/4015

В настоящее время в связи со стремительным ростом количества полногеномных экспериментов по изучению изменения экспрессии генов в различных условиях все более широкое распространение получают методы метаанализа транскриптомных данных из разных экспериментов, так как интеграция данных может обеспечить большую точность в выявлении генов-кандидатов и позволяет тестировать новые гипотезы, которые невозможно было проверить в отдельных исследованиях. Для повышения информативности такой интеграции необходимо оптимизировать подбор экспериментов. В настоящей работе мы предлагаем набор количественных показателей для всестороннего сравнительного описания транскриптомных данных. Эти показатели легко могут быть визуализированы и интерпретированы. Они включают в себя количество дифференциально экспрессирующихся генов (ДЭГ), долю специфических (уникальных) ДЭГ в каждом наборе данных, попарное сходство экспериментов по составу ДЭГ, оценку однородности профилей дифференциально экспрессирующихся генов. Для автоматического вычисления и визуализации этих показателей мы разработали программу InterTransViewer. Мы применили InterTransViewer для сравнительного описания транскрипционных ответов на обработку фитогормонами у модельного растения Arabidopsis thaliana L., взяв в анализ 23 едино образно обработанных профиля дифференциальной экспрессии генов в ответ на ауксин и 16 профилей дифференциальной экспрессии, индуцированных этиленом или его предшественником – 1-аминоциклопропановой кислотой. Мы продемонстрировали, что комплексное рассмотрение характеристик отдельных профилей ДЭГ в контексте результатов попарных сравнений профилей по составу ДЭГ позволяет позиционировать эксперименты в контексте друг друга, оценивать тенденцию к их интеграции или сегрегации, генерировать гипотезы о влиянии весомых нецелевых факторов на исследуемый транскрипционный ответ. В результате это дает возможность выделять потенциально однородные группы экспериментов. Последующий анализ однородности этих групп профилей с помощью процедуры ресемплинга и установления порога уровня значимости помогает принять решение о целесообразности использования этих данных для метаанализа. В целом InterTransViewer позволяет эффективно формировать выборки экспериментов в зависимости от задачи и методов метаанализа

Meta-analysis of transcriptomic data from different experiments has become increasingly prevalent due to a significantly increasing number of genome-wide experiments investigating gene expression changes under various conditions. Such data integration provides greater accuracy in identifying candidate genes and allows testing new hypotheses, which could not be validated in individual studies. To increase the relevance of experiment integration, it is necessary to optimize the selection of experiments. In this paper, we propose a set of quantitative indicators for a comprehensive comparative description of transcriptomic data. These indicators can be easily visualized and interpreted. They include the number of differentially expressed genes (DEGs), the proportion of experiment-specific (unique) DEGs in each data set, the pairwise similarity of experiments in DEG composition and the homogeneity of DEG profiles. For automatic calculation and visualization of these indicators, we have developed the program InterTransViewer. We have used InterTransViewer to comparatively describe 23 auxin- and 16 ethylene- or 1-aminocyclopropane-1-carboxylic acid (ACC)-induced transcriptomes in Arabidopsis thaliana L. We have demonstrated that analysis of the characteristics of individual DEG profiles and their pairwise comparisons based on DEG composition allow the user to rank experiments in the context of each other, assess the tendency towards their integration or segregation, and generate hypotheses about the influence of non-target factors on the transcriptional response. As a result, InterTransViewer identifies potentially homogeneous groups of experiments. Subsequent estimation of the profile homogeneity within these groups using resampling and setting a significance threshold helps to decide whether these data are appropriate for meta-analysis. Overall, InterTransViewer makes it possible to efficiently select experiments for meta-analysis depending on its task and methods.

транскриптоминтеграция данныхауксинэтиленArabidopsis thaliana L.transcriptomedata integrationauxinethyleneArabidopsis thaliana L.The development of the method was funded by the State Budgetary Project FWNR-2022-0020. Comparative analysis of transcriptomes was supported by the Russian Science Foundation, grant No. 20-14-00140ReferencesBairakdar M.D., Tewari A., Truttmann M.C. A meta-analysis of RNASeq studies to identify novel genes that regulate aging. Exp. Gerontol. 2023;173:112107. DOI 10.1016/j.exger.2023.112107Bairakdar M.D., Tewari A., Truttmann M.C. A meta-analysis of RNASeq studies to identify novel genes that regulate aging. Exp. Gerontol. 2023;173:112107. DOI 10.1016/j.exger.2023.112107Bargmann B.O., Vanneste S., Krouk G., Nawy T., Efroni I., Shani E., Choe G., Friml J., Bergmann D.C., Estelle M., Birnbaum K.D. A map of cell type-specific auxin responses. Mol. Syst. Biol. 2013; 9:688. DOI 10.1038/msb.2013.40Bargmann B.O., Vanneste S., Krouk G., Nawy T., Efroni I., Shani E., Choe G., Friml J., Bergmann D.C., Estelle M., Birnbaum K.D. A map of cell type-specific auxin responses. Mol. Syst. Biol. 2013; 9:688. DOI 10.1038/msb.2013.40Benjamini Y., Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B. Methodol. 1995;57(1):289-300. DOI 10.1111/j.2517-6161.1995.tb02031.xBenjamini Y., Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B. Methodol. 1995;57(1):289-300. DOI 10.1111/j.2517-6161.1995.tb02031.xBrazma A. Minimum information about a microarray experiment ( MIAME) – successes, failures, challenges. Sci. World J. 2009; 29(9):420-423. DOI 10.1100/tsw.2009.57Brazma A. Minimum information about a microarray experiment ( MIAME) – successes, failures, challenges. Sci. World J. 2009; 29(9):420-423. DOI 10.1100/tsw.2009.57Brazma A., Hingamp P., Quackenbush J., Sherlock G., Spellman P., Stoeckert C., Aach J., Ansorge W., Ball C.A., Causton H.C., Gaasterland T., Glenisson P., Holstege F.C., Kim I.F., Markowitz V., Matese J.C., Parkinson H., Robinson A., Sarkans U., Schulze-Kremer S., Stewart J., Taylor R., Vilo J., Vingron M. Minimum information about a microarray experiment (MIAME) – toward standards for microarray data. Nat. Genet. 2001;29(4):365-371. DOI 10.1038/ng1201-365Brazma A., Hingamp P., Quackenbush J., Sherlock G., Spellman P., Stoeckert C., Aach J., Ansorge W., Ball C.A., Causton H.C., Gaasterland T., Glenisson P., Holstege F.C., Kim I.F., Markowitz V., Matese J.C., Parkinson H., Robinson A., Sarkans U., Schulze-Kremer S., Stewart J., Taylor R., Vilo J., Vingron M. Minimum information about a microarray experiment (MIAME) – toward standards for microarray data. Nat. Genet. 2001;29(4):365-371. DOI 10.1038/ng1201-365Cahan P., Rovegno F., Mooney D., Newman J.C., St. Laurent G. 3rd, McCaffrey T.A. Meta-analysis of microarray results: challenges, opportunities, and recommendations for standardization. Gene. 2007; 401(1-2):12-18. DOI 10.1016/j.gene.2007.06.016Cahan P., Rovegno F., Mooney D., Newman J.C., St. Laurent G. 3rd, McCaffrey T.A. Meta-analysis of microarray results: challenges, opportunities, and recommendations for standardization. Gene. 2007; 401(1-2):12-18. DOI 10.1016/j.gene.2007.06.016Chaiwanon J., Wang Z.Y. Spatiotemporal brassinosteroid signaling and antagonism with auxin pattern stem cell dynamics in Arabidopsis roots. Curr. Biol. 2015;25(8):1031-1042. DOI 10.1016/j.cub.2015.02.046Chaiwanon J., Wang Z.Y. Spatiotemporal brassinosteroid signaling and antagonism with auxin pattern stem cell dynamics in Arabidopsis roots. Curr. Biol. 2015;25(8):1031-1042. DOI 10.1016/j.cub.2015.02.046Chang K.N., Zhong S., Weirauch M.T., Hon G., Pelizzola M., Li H., Huang S.S., Schmitz R.J., Urich M.A., Kuo D., Nery J.R., Qiao H., Yang A., Jamali A., Chen H., Ideker T., Ren B., Bar-Joseph Z., Hughes T.R., Ecker J.R. Temporal transcriptional response to ethylene gas drives growth hormone cross-regulation in Arabidopsis. eLife. 2013;2:e00675. DOI 10.7554/eLife.00675Chang K.N., Zhong S., Weirauch M.T., Hon G., Pelizzola M., Li H., Huang S.S., Schmitz R.J., Urich M.A., Kuo D., Nery J.R., Qiao H., Yang A., Jamali A., Chen H., Ideker T., Ren B., Bar-Joseph Z., Hughes T.R., Ecker J.R. Temporal transcriptional response to ethylene gas drives growth hormone cross-regulation in Arabidopsis. eLife. 2013;2:e00675. DOI 10.7554/eLife.00675Chen S., Zhou Y., Chen Y., Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34(17):i884-i890. DOI 10.1093/bioinformatics/bty560Chen S., Zhou Y., Chen Y., Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34(17):i884-i890. DOI 10.1093/bioinformatics/bty560Clough E., Barrett T. The gene expression omnibus database. Me thods Mol. Biol. 2016;1418:93-110. DOI 10.1007/978-1-4939-3578-9_5Clough E., Barrett T. The gene expression omnibus database. Me thods Mol. Biol. 2016;1418:93-110. DOI 10.1007/978-1-4939-3578-9_5De Rybel B., Audenaert D., Xuan W., Overvoorde P., Strader L.C., Kepinski S., Hoye R., Brisbois R., Parizot B., Vanneste S., Liu X., Gilday A., Graham I.A., Nguyen L., Jansen L., Njo M.F., Inzé D., Bartel B., Beeckman T. A role for the root cap in root branching revealed by the non-auxin probe naxillin. Nat. Chem. Biol. 2012;8(9): 798-805. DOI 10.1038/nchembio.1044De Rybel B., Audenaert D., Xuan W., Overvoorde P., Strader L.C., Kepinski S., Hoye R., Brisbois R., Parizot B., Vanneste S., Liu X., Gilday A., Graham I.A., Nguyen L., Jansen L., Njo M.F., Inzé D., Bartel B., Beeckman T. A role for the root cap in root branching revealed by the non-auxin probe naxillin. Nat. Chem. Biol. 2012;8(9): 798-805. DOI 10.1038/nchembio.1044Delker C., Pöschl Y., Raschke A., Ullrich K., Ettingshausen S., Hauptmann V., Grosse I., Quint M. Natural variation of transcriptional auxin response networks in Arabidopsis thaliana. Plant Cell. 2010; 22(7):2184-2200. DOI 10.1105/tpc.110.073957Delker C., Pöschl Y., Raschke A., Ullrich K., Ettingshausen S., Hauptmann V., Grosse I., Quint M. Natural variation of transcriptional auxin response networks in Arabidopsis thaliana. Plant Cell. 2010; 22(7):2184-2200. DOI 10.1105/tpc.110.073957Feng Y., Xu P., Li B., Li P., Wen X., An F., Gong Y., Xin Y., Zhu Z., Wang Y., Guo H. Ethylene promotes root hair growth through coordinated EIN3/EIL1 and RHD6/RSL1 activity in Arabidopsis. Proc. Natl. Acad. Sci. USA. 2017;114:13834-13839. DOI 10.1073/pnas.1711723115Feng Y., Xu P., Li B., Li P., Wen X., An F., Gong Y., Xin Y., Zhu Z., Wang Y., Guo H. Ethylene promotes root hair growth through coordinated EIN3/EIL1 and RHD6/RSL1 activity in Arabidopsis. Proc. Natl. Acad. Sci. USA. 2017;114:13834-13839. DOI 10.1073/pnas.1711723115Freire-Rios A., Tanaka K., Crespo I., van der Wijk E., Sizentsova Ya., Levitsky V., Lindhoud S., Fontana M., Hohlbein J., Boer R., Mironova V., Weijers D. Architecture of DNA elements mediating ARF transcription factor binding and auxin-responsive gene expression in Arabidopsis. Proc. Natl. Acad. Sci. USA. 2020;117(39):24557-24566. DOI 10.1073/pnas.2009554117Freire-Rios A., Tanaka K., Crespo I., van der Wijk E., Sizentsova Ya., Levitsky V., Lindhoud S., Fontana M., Hohlbein J., Boer R., Mironova V., Weijers D. Architecture of DNA elements mediating ARF transcription factor binding and auxin-responsive gene expression in Arabidopsis. Proc. Natl. Acad. Sci. USA. 2020;117(39):24557-24566. DOI 10.1073/pnas.2009554117Fu L., Liu Y., Qin G., Wu P., Zi H., Xu Z., Zhao X., Wang Y., Li Y., Yang S., Peng C., Wong C.C.L., Yoo S.D., Zuo Z., Liu R., Cho Y.H., Xiong Y. The TOR–EIN2 axis mediates nuclear signalling to modulate plant growth. Nature. 2021;591(7849):288-292. DOI 10.1038/s41586-021-03310-yFu L., Liu Y., Qin G., Wu P., Zi H., Xu Z., Zhao X., Wang Y., Li Y., Yang S., Peng C., Wong C.C.L., Yoo S.D., Zuo Z., Liu R., Cho Y.H., Xiong Y. The TOR–EIN2 axis mediates nuclear signalling to modulate plant growth. Nature. 2021;591(7849):288-292. DOI 10.1038/s41586-021-03310-yHarkey A.F., Watkins J.M., Olex A.L., DiNapoli K.T., Lewis D.R., Fetrow J.S., Binder B.M., Muday G.K. Identification of transcriptional and receptor networks that control root responses to ethylene. Plant Physiol. 2018;176(3):2095-2118. DOI 10.1104/pp.17.00907Harkey A.F., Watkins J.M., Olex A.L., DiNapoli K.T., Lewis D.R., Fetrow J.S., Binder B.M., Muday G.K. Identification of transcriptional and receptor networks that control root responses to ethylene. Plant Physiol. 2018;176(3):2095-2118. DOI 10.1104/pp.17.00907Kang D.D., Sibille E., Kaminski N., Tseng G.C. MetaQC: objective quality control and inclusion/exclusion criteria for genomic metaanalysis. Nucleic Acids Res. 2012;40(2):e15. DOI 10.1093/nar/gkr1071Kang D.D., Sibille E., Kaminski N., Tseng G.C. MetaQC: objective quality control and inclusion/exclusion criteria for genomic metaanalysis. Nucleic Acids Res. 2012;40(2):e15. DOI 10.1093/nar/gkr1071Keel B.N., Lindholm-Perry A.K. Recent developments and future directions in meta-analysis of differential gene expression in livestock RNA-Seq. Front. Genet. 2022;19(13):983043. DOI 10.3389/fgene.2022.983043Keel B.N., Lindholm-Perry A.K. Recent developments and future directions in meta-analysis of differential gene expression in livestock RNA-Seq. Front. Genet. 2022;19(13):983043. DOI 10.3389/fgene.2022.983043Kim D., Pertea G., Trapnell C., Pimentel H., Kelley R., Salzberg S.L. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 2013;14:R36. DOI 10.1186/gb-2013-14-4-r36Kim D., Pertea G., Trapnell C., Pimentel H., Kelley R., Salzberg S.L. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 2013;14:R36. DOI 10.1186/gb-2013-14-4-r36Kim D., Paggi J.M., Park C., Bennett C., Salzberg S.L. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol. 2019;37:907-915. DOI 10.1038/s41587-019-0201-4Kim D., Paggi J.M., Park C., Bennett C., Salzberg S.L. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol. 2019;37:907-915. DOI 10.1038/s41587-019-0201-4Lawrence M., Huber W., Pagès H., Aboyoun P., Carlson M., Gentleman R., Morgan M.T., Carey V.J. Software for computing and annotating genomic ranges. PLoS Comput. Biol. 2013;9:e1003118. DOI 10.1371/journal.pcbi.1003118Lawrence M., Huber W., Pagès H., Aboyoun P., Carlson M., Gentleman R., Morgan M.T., Carey V.J. Software for computing and annotating genomic ranges. PLoS Comput. Biol. 2013;9:e1003118. DOI 10.1371/journal.pcbi.1003118Lewis D.R., Olex A.L., Lundy S.R., Turkett W.H., Fetrow J.S., Muday G.K. A kinetic analysis of the auxin transcriptome reveals cell wall remodeling proteins that modulate lateral root development in Arabidopsis. Plant Cell. 2013;25:3329-3346. DOI 10.1105/tpc.113.114868Lewis D.R., Olex A.L., Lundy S.R., Turkett W.H., Fetrow J.S., Muday G.K. A kinetic analysis of the auxin transcriptome reveals cell wall remodeling proteins that modulate lateral root development in Arabidopsis. Plant Cell. 2013;25:3329-3346. DOI 10.1105/tpc.113.114868Love M.I., Huber W., Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014; 15(12):550. DOI 10.1186/s13059-014-0550-8Love M.I., Huber W., Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014; 15(12):550. DOI 10.1186/s13059-014-0550-8Luo Y., Shi H. Direct regulation of phytohormone actions by photoreceptors. Trends Plant Sci. 2019;24:105-108. DOI 10.1016/j.tplants.2018.11.002Luo Y., Shi H. Direct regulation of phytohormone actions by photoreceptors. Trends Plant Sci. 2019;24:105-108. DOI 10.1016/j.tplants.2018.11.002McDermaid A., Monier B., Zhao J., Liu B., Ma Q. Interpretation of differential gene expression results of RNA-seq data: review and integration. Brief. Bioinform. 2019;20(6):2044-2054. DOI 10.1093/bib/bby067McDermaid A., Monier B., Zhao J., Liu B., Ma Q. Interpretation of differential gene expression results of RNA-seq data: review and integration. Brief. Bioinform. 2019;20(6):2044-2054. DOI 10.1093/bib/bby067Mozgová I., Muñoz-Viana R., Hennig L. PRC2 represses hormoneinduced somatic embryogenesis in vegetative tissue of Arabidopsis thaliana. PLoS Genet. 2017;13(1):e1006562. DOI 10.1371/journalpgen.1006562Mozgová I., Muñoz-Viana R., Hennig L. PRC2 represses hormoneinduced somatic embryogenesis in vegetative tissue of Arabidopsis thaliana. PLoS Genet. 2017;13(1):e1006562. DOI 10.1371/journalpgen.1006562Müller D., Waldie T., Miyawaki K., To J.P., Melnyk C.W., Kieber J.J., Kakimoto T., Leyser O. Cytokinin is required for escape but not release from auxin mediated apical dominance. Plant J. 2015;82(5): 874-886. DOI 10.1111/tpj.12862Müller D., Waldie T., Miyawaki K., To J.P., Melnyk C.W., Kieber J.J., Kakimoto T., Leyser O. Cytokinin is required for escape but not release from auxin mediated apical dominance. Plant J. 2015;82(5): 874-886. DOI 10.1111/tpj.12862Okushima Y., Overvoorde P.J., Arima K., Alonso J.M., Chan A., Chang C., Ecker J.R., Hughes B., Lui A., Nguyen D., Onodera C., Quach H., Smith A., Yu G., Theologis A. Functional genomic analysis of the AUXIN RESPONSE FACTOR gene family members in Arabidopsis thaliana: unique and overlapping functions of ARF7 and ARF19. Plant Cell. 2005;17(2):444-463. DOI 10.1105/tpc.104.028316Okushima Y., Overvoorde P.J., Arima K., Alonso J.M., Chan A., Chang C., Ecker J.R., Hughes B., Lui A., Nguyen D., Onodera C., Quach H., Smith A., Yu G., Theologis A. Functional genomic analysis of the AUXIN RESPONSE FACTOR gene family members in Arabidopsis thaliana: unique and overlapping functions of ARF7 and ARF19. Plant Cell. 2005;17(2):444-463. DOI 10.1105/tpc.104.028316Omelyanchuk N.A., Wiebe D.S., Novikova D.D., Levitsky V.G., Klimova N., Gorelova V., Weinholdt C., Vasiliev G.V., Zemlyanskaya E.V., Kolchanov N.A., Kochetov A.V. Auxin regulates functional gene groups in a fold-change-specific manner in Arabidopsis thaliana roots. Sci. Rep. 2017;7(1):2489. DOI 10.1038/s41598-017-02476-8Omelyanchuk N.A., Wiebe D.S., Novikova D.D., Levitsky V.G., Klimova N., Gorelova V., Weinholdt C., Vasiliev G.V., Zemlyanskaya E.V., Kolchanov N.A., Kochetov A.V. Auxin regulates functional gene groups in a fold-change-specific manner in Arabidopsis thaliana roots. Sci. Rep. 2017;7(1):2489. DOI 10.1038/s41598-017-02476-8Ritchie M.E., Phipson B., Wu D., Hu Y., Law C.W., Shi W., Smyth G.K. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43:e47. DOI 10.1093/nar/gkv007Ritchie M.E., Phipson B., Wu D., Hu Y., Law C.W., Shi W., Smyth G.K. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43:e47. DOI 10.1093/nar/gkv007Romero-Puertas M.C., Peláez-Vico M.Á., Pazmiño D.M., Rodríguez-Serrano M., Terrón-Camero L., Bautista R., Gómez-Cadenas A., Claros M.G., León J., Sandalio L.M. Insights into ROS-dependent signalling underlying transcriptomic plant responses to the herbicide 2,4-D. Plant Cell Environ. 2022;45(2):572-590. DOI 10.1111/pce.14229Romero-Puertas M.C., Peláez-Vico M.Á., Pazmiño D.M., Rodríguez-Serrano M., Terrón-Camero L., Bautista R., Gómez-Cadenas A., Claros M.G., León J., Sandalio L.M. Insights into ROS-dependent signalling underlying transcriptomic plant responses to the herbicide 2,4-D. Plant Cell Environ. 2022;45(2):572-590. DOI 10.1111/pce.14229Rousselet G.A., Pernet C.R., Wilcox R.R. The percentile bootstrap: a primer with step-by-step instructions in R. Adv. Meth. Pract. Psychol. Sci. 2021;4(1). DOI 10.1177/2515245920911881Rousselet G.A., Pernet C.R., Wilcox R.R. The percentile bootstrap: a primer with step-by-step instructions in R. Adv. Meth. Pract. Psychol. Sci. 2021;4(1). DOI 10.1177/2515245920911881Rung J., Brazma A. Reuse of public genome-wide gene expression data. Nat. Rev. Genet. 2013;14(2):89-99. DOI 10.1038/nrg3394Rung J., Brazma A. Reuse of public genome-wide gene expression data. Nat. Rev. Genet. 2013;14(2):89-99. DOI 10.1038/nrg3394Sarkans U., Füllgrabe A., Ali A., Athar A., Behrangi E., Diaz N., Fexova S., George N., Iqbal H., Kurri S., Munoz J., Rada J., Papatheodorou I., Brazma A. From arrayexpress to biostudies. Nucleic Acids Res. 2021;49(D1):D1502-D1506. DOI 10.1093/nar/gkaa1062Sarkans U., Füllgrabe A., Ali A., Athar A., Behrangi E., Diaz N., Fexova S., George N., Iqbal H., Kurri S., Munoz J., Rada J., Papatheodorou I., Brazma A. From arrayexpress to biostudies. Nucleic Acids Res. 2021;49(D1):D1502-D1506. DOI 10.1093/nar/gkaa1062Shi H., Liu R., Xue C., Shen X., Wei N., Deng X.W., Zhong S. Seedlings transduce the depth and mechanical pressure of covering soil using COP1 and ethylene to regulate EBF1/EBF2 for soil emergence. Curr. Biol. 2016a;26(2):139-149. DOI 10.1016/j.cub.2015.11.053Shi H., Liu R., Xue C., Shen X., Wei N., Deng X.W., Zhong S. Seedlings transduce the depth and mechanical pressure of covering soil using COP1 and ethylene to regulate EBF1/EBF2 for soil emergence. Curr. Biol. 2016a;26(2):139-149. DOI 10.1016/j.cub.2015.11.053Shi H., Shen X., Liu R., Xue C., Wei N., Deng X.W., Zhong S. The red light receptor phytochrome B directly enhances substrate-E3 ligase interactions to attenuate ethylene responses. Dev. Cell. 2016b;39(5): 597-610. DOI 10.1016/j.devcel.2016.10.020Shi H., Shen X., Liu R., Xue C., Wei N., Deng X.W., Zhong S. The red light receptor phytochrome B directly enhances substrate-E3 ligase interactions to attenuate ethylene responses. Dev. Cell. 2016b;39(5): 597-610. DOI 10.1016/j.devcel.2016.10.020Simonini S., Bencivenga S., Trick M., Østergaard L. Auxin-induced modulation of ETTIN activity orchestrates gene expression in Arabidopsis. Plant Cell. 2017;29(8):1864-1882. DOI 10.1105/tpc.17.00389Simonini S., Bencivenga S., Trick M., Østergaard L. Auxin-induced modulation of ETTIN activity orchestrates gene expression in Arabidopsis. Plant Cell. 2017;29(8):1864-1882. DOI 10.1105/tpc.17.00389Stelpflug S.C., Sekhon R.S., Vaillancourt B., Hirsch C.N., Buell C.R., de Leon N., Kaeppler S.M. An expanded maize gene expression atlas based on RNA sequencing and its use to explore root development. Plant Genome. 2016;9(1):1-16. DOI 10.3835/plantgenome2015.04.0025Stelpflug S.C., Sekhon R.S., Vaillancourt B., Hirsch C.N., Buell C.R., de Leon N., Kaeppler S.M. An expanded maize gene expression atlas based on RNA sequencing and its use to explore root development. Plant Genome. 2016;9(1):1-16. DOI 10.3835/plantgenome2015.04.0025Stepanova A.N., Yun J., Likhacheva A.V., Alonso J.M. Multilevel interactions between ethylene and auxin in Arabidopsis roots. Plant Cell. 2007;19(7):2169-2185. DOI 10.1105/tpc.107.052068Stepanova A.N., Yun J., Likhacheva A.V., Alonso J.M. Multilevel interactions between ethylene and auxin in Arabidopsis roots. Plant Cell. 2007;19(7):2169-2185. DOI 10.1105/tpc.107.052068Sudmant P.H., Alexis M.S., Burge C.B. Meta-analysis of RNA-seq expression data across species, tissues and studies. Genome Biol. 2015; 16:287. DOI 10.1186/s13059-015-0853-4Sudmant P.H., Alexis M.S., Burge C.B. Meta-analysis of RNA-seq expression data across species, tissues and studies. Genome Biol. 2015; 16:287. DOI 10.1186/s13059-015-0853-4Tello-Ruiz M.K., Stein J., Wei S., Preecem J., Olson A., Naithani S., Amarasinghe V., Dharmawardhana P., Jiao Y., Mulvaney J., Kumari S., Chougule K., Elser J., Wang B., Thomason J., Bolser D.M., Kerhornou A., Walts B., Fonseca N.A., Huerta L., Keays M., Tang Y.A., Parkinson H., Fabregat A., McKay S., Weiser J., D’Eustachio P., Stein L., Petryszak R., Kersey P.J., Jaiswal P., Ware D. Gramene 2016: comparative plant genomics and pathway resources. Nucleic Acids Res. 2016;44(D1):D1133-D1140. DOI 10.1093/nar/gkv1179Tello-Ruiz M.K., Stein J., Wei S., Preecem J., Olson A., Naithani S., Amarasinghe V., Dharmawardhana P., Jiao Y., Mulvaney J., Kumari S., Chougule K., Elser J., Wang B., Thomason J., Bolser D.M., Kerhornou A., Walts B., Fonseca N.A., Huerta L., Keays M., Tang Y.A., Parkinson H., Fabregat A., McKay S., Weiser J., D’Eustachio P., Stein L., Petryszak R., Kersey P.J., Jaiswal P., Ware D. Gramene 2016: comparative plant genomics and pathway resources. Nucleic Acids Res. 2016;44(D1):D1133-D1140. DOI 10.1093/nar/gkv1179Vanderstraeten L., Depaepe T., Bertrand S., Van Der Straeten D. The ethylene precursor ACC affects early vegetative development independently of ethylene signaling. Front. Plant Sci. 2019;10:1591. DOI 10.3389/fpls.2019.01591Vanderstraeten L., Depaepe T., Bertrand S., Van Der Straeten D. The ethylene precursor ACC affects early vegetative development independently of ethylene signaling. Front. Plant Sci. 2019;10:1591. DOI 10.3389/fpls.2019.01591Vanneste S., De Rybel B., Beemster G.T., Ljung K., De Smet I., Van Isterdael G., Naudts M., Iida R., Gruissem W., Tasaka M., Inzé D., Fukaki H., Beeckman T. Cell cycle progression in the pericycle is not sufficient for SOLITARY ROOT/IAA14-mediated lateral root initiation in Arabidopsis thaliana. Plant Cell. 2005;17(11):30353050. DOI 10.1105/tpc.105.035493Vanneste S., De Rybel B., Beemster G.T., Ljung K., De Smet I., Van Isterdael G., Naudts M., Iida R., Gruissem W., Tasaka M., Inzé D., Fukaki H., Beeckman T. Cell cycle progression in the pericycle is not sufficient for SOLITARY ROOT/IAA14-mediated lateral root initiation in Arabidopsis thaliana. Plant Cell. 2005;17(11):30353050. DOI 10.1105/tpc.105.035493Winter C., Kosch R., Ludlow M., Osterhaus A.D.M.E., Jung K. Network meta-analysis correlates with analysis of merged independent transcriptome expression data. BMC Bioinformatics. 2019;20(1): 144. DOI 10.1186/s12859-019-2705-9Winter C., Kosch R., Ludlow M., Osterhaus A.D.M.E., Jung K. Network meta-analysis correlates with analysis of merged independent transcriptome expression data. BMC Bioinformatics. 2019;20(1): 144. DOI 10.1186/s12859-019-2705-9Xu K., Liu J., Fan M., Xin W., Hu Y., Xu C. A genome-wide transcriptome profiling reveals the early molecular events during callus initiation in Arabidopsis multiple organs. Genomics. 2012;100(2):116124. DOI 10.1016/j.ygeno.2012.05.013Xu K., Liu J., Fan M., Xin W., Hu Y., Xu C. A genome-wide transcriptome profiling reveals the early molecular events during callus initiation in Arabidopsis multiple organs. Genomics. 2012;100(2):116124. DOI 10.1016/j.ygeno.2012.05.013Xuan W., Audenaert D., Parizot B., Möller B.K., Njo M.F., De Rybel B., De Rop G., Van Isterdael G., Mähönen A.P., Vanneste S., Beeckman T. Root cap-derived auxin pre-patterns the longitudinal axis of the Arabidopsis root. Curr. Biol. 2015;25(10):1381-1388. DOI 10.1016/j.cub.2015.03.046Xuan W., Audenaert D., Parizot B., Möller B.K., Njo M.F., De Rybel B., De Rop G., Van Isterdael G., Mähönen A.P., Vanneste S., Beeckman T. Root cap-derived auxin pre-patterns the longitudinal axis of the Arabidopsis root. Curr. Biol. 2015;25(10):1381-1388. DOI 10.1016/j.cub.2015.03.046Yu X.T., Zeng T. Integrative analysis of omics big data. Methods Mol. Biol. 2018;1754:109-135. DOI 10.1007/978-1-4939-7717-8_7Yu X.T., Zeng T. Integrative analysis of omics big data. Methods Mol. Biol. 2018;1754:109-135. DOI 10.1007/978-1-4939-7717-8_7Zander M., Willige B.C., He Y., Nguyen T.A., Langford A.E., Nehring R., Howell E., McGrath R., Bartlett A., Castanon R., Nery J.R., Chen H., Zhang Z., Jupe F., Stepanova A., Schmitz R.J., Lewsey M.G., Chory J., Ecker J.R. Epigenetic silencing of a multifunctional plant stress regulator. eLife. 2019;8:e47835. DOI 10.7554/eLife.47835Zander M., Willige B.C., He Y., Nguyen T.A., Langford A.E., Nehring R., Howell E., McGrath R., Bartlett A., Castanon R., Nery J.R., Chen H., Zhang Z., Jupe F., Stepanova A., Schmitz R.J., Lewsey M.G., Chory J., Ecker J.R. Epigenetic silencing of a multifunctional plant stress regulator. eLife. 2019;8:e47835. DOI 10.7554/eLife.47835Zhang F., Qi B., Wang L., Zhao B., Rode S., Riggan N.D., Ecker J.R., Qiao H. EIN2-dependent regulation of acetylation of histone H3K14 and non-canonical histone H3K23 in ethylene signalling. Nat. Commun. 2016a;7(1):13018. DOI 10.1038/ncomms13018Zhang F., Qi B., Wang L., Zhao B., Rode S., Riggan N.D., Ecker J.R., Qiao H. EIN2-dependent regulation of acetylation of histone H3K14 and non-canonical histone H3K23 in ethylene signalling. Nat. Commun. 2016a;7(1):13018. DOI 10.1038/ncomms13018Zhang F., Wang L., Lim J.Y., Kim T., Pyo Y., Sung S., Shin C., Qiao H. Phosphorylation of CBP20 links microRNA to root growth in the ethylene response. PLoS Genet. 2016b;12(11):e1006437. DOIZhang F., Wang L., Lim J.Y., Kim T., Pyo Y., Sung S., Shin C., Qiao H. Phosphorylation of CBP20 links microRNA to root growth in the ethylene response. PLoS Genet. 2016b;12(11):e1006437. DOI1371/journal.pgen.10064371371/journal.pgen.1006437Zhou G., Soufan O., Ewald J., Hancock R.E.W., Basu N., Xia J. NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis. Nucleic Acids Res. 2019;47(W1):W234-W241. DOI 10.1093/nar/gkz240Zhou G., Soufan O., Ewald J., Hancock R.E.W., Basu N., Xia J. NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis. Nucleic Acids Res. 2019;47(W1):W234-W241. DOI 10.1093/nar/gkz240

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