Abstract
In the last decade, miRNAs have attracted noticeable interest as potential biomarkers of neuropsychiatric conditions. However, a standard methodology for miRNA-Seq analysis does not yet exist, raising concerns about the reproducibility of the in-silico results and limiting their usefulness. This situation motivated us to design a miRNA-Seq pipeline specialized in the analysis of neuropsychiatric data, aiming to integrate the results of several bioinformatics tools in a highly reproducible workflow. In this study, we performed an initial test of the usefulness of our new pipeline, named myBrain-Seq, by reanalyzing four recent miRNA-Seq studies of neuropsychiatric conditions. We then compared the myBrain-Seq results with the original results and with an additional reanalysis done with another pipeline in order to make an estimation of the overall replicability. We found one of the three myBrain-Seq methodologies to be the one with best replicability, although the heterogeneity of the results and the absence of an experimental validation limits our conclusions. Further work is required to assess myBrain-Seq’ performance using a bigger dataset of studies with experimental validation data available.
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References
Esteller M (2011) Non-coding RNAs in human disease. Nat Rev Genet 12:861–874. https://doi.org/10.1038/nrg3074
Winkle M, El-Daly SM, Fabbri M, Calin GA (2021) Noncoding RNA therapeutics - challenges and potential solutions. Nat Rev Drug Discov 20:629–651. https://doi.org/10.1038/s41573-021-00219-z
Gebert LFR, MacRae IJ (2019) Regulation of microRNA function in animals. Nat Rev Mol Cell Biol 20:21–37. https://doi.org/10.1038/s41580-018-0045-7
Zovoilis A, Agbemenyah HY, Agis-Balboa RC, Stilling RM, Edbauer D, Rao P, Farinelli L, Delalle I, Schmitt A, Falkai P, Bahari-Javan S, Burkhardt S, Sananbenesi F, Fischer A (2011) microRNA-34c is a novel target to treat dementias. EMBO J 30:4299–4308. https://doi.org/10.1038/emboj.2011.327
Pérez-Rodríguez D, López-Fernández H, Agís-Balboa RC (2021) Application of miRNA-seq in neuropsychiatry: a methodological perspective. Comput Biol Med 135:104603 (2021). https://doi.org/10.1016/j.compbiomed.2021.104603
Andrés-León E, Núñez-Torres R, Rojas AM (2016) miARma-Seq: a comprehensive tool for miRNA, mRNA and circRNA analysis. Sci Rep 6:25749. https://doi.org/10.1038/srep25749
Pérez-Rodríguez D, López-Fernández H, Agís-Balboa RC (2022) On the reproducibility of MiRNA-Seq differential expression analyses in neuropsychiatric diseases. In: Rocha M, Fdez-Riverola F, Mohamad MS, Casado-Vara R (eds) Practical applications of computational biology & bioinformatics, 15th international conference (PACBB 2021). Springer, Cham, pp 41–51. https://doi.org/10.1007/978-3-030-86258-9_5.
Mavrikaki M, Pantano L, Potter D, Rogers-Grazado MA, Anastasiadou E, Slack FJ, Amr SS, Ressler KJ, Daskalakis NP, Chartoff E (2019) Sex-dependent changes in miRNA expression in the bed nucleus of the stria terminalis following stress. Front Mol Neurosci 12. https://doi.org/10.3389/fnmol.2019.00236
López-Fernández H, Graña-Castro O, Nogueira-Rodríguez A, Reboiro-Jato M, Glez-Peña D (2021) Compi: a framework for portable and reproducible pipelines. PeerJ Comput Sci 7:e593. https://doi.org/10.7717/peerj-cs.593
Wang LJ, Li SC, Lee MJ, Chou MC, Chou WJ, Lee SY, Hsu CW, Huang LH, Kuo HC (2018) Blood-Bourne microRNA biomarker evaluation in attention-deficit/hyperactivity disorder of Han Chinese individuals: an exploratory study. Front Psychiat 9. https://doi.org/10.3389/fpsyt.2018.00227
Martin CG, Kim H, Yun S, Livingston W, Fetta J, Mysliwiec V, Baxter T, Gill JM (2017) Circulating miRNA associated with posttraumatic stress disorder in a cohort of military combat veterans. Psychiatry Res 251:261–265. https://doi.org/10.1016/j.psychres.2017.01.081
Nie C, Sun Y, Zhen H, Guo M, Ye J, Liu Z, Yang Y, Zhang X (2020) Differential expression of plasma Exo-miRNA in neurodegenerative diseases by next-generation sequencing. Front Neurosci 14. https://doi.org/10.3389/fnins.2020.00438
Hicks SD, Ignacio C, Gentile K, Middleton FA (2016) Salivary miRNA profiles identify children with autism spectrum disorder, correlate with adaptive behavior, and implicate ASD candidate genes involved in neurodevelopment. BMC Pediatrics 16. https://doi.org/10.1186/s12887-016-0586-x
Hoss AG, Labadorf A, Beach TG, Latourelle JC, Myers RH (2016) microRNA profiles in Parkinson’s disease prefrontal cortex. Front Aging Neurosci 8. https://doi.org/10.3389/fnagi.2016.00036
NCBI Datasets. https://www.ncbi.nlm.nih.gov/datasets/. Accessed 11 May 2021
Kozomara A, Birgaoanu M, Griffiths-Jones S (2019) miRBase: from microRNA sequences to function. Nucleic Acids Res 47:D155–D162. https://doi.org/10.1093/nar/gky1141
Nogueira-Rodríguez A, López-Fernández H, Graña-Castro O, Reboiro-Jato M, Glez-Peña D (2021) Compi Hub: a public repository for sharing and discovering Compi pipelines. In: Panuccio G, Rocha M, Fdez-Riverola F, Mohamad MS, Casado-Vara R (eds) Practical applications of computational biology & bioinformatics, 14th international conference (PACBB 2020), pp 51–59. Springer, Cham. https://doi.org/10.1007/978-3-030-54568-0_6
Andrews S (2010) FASTQC. A quality control tool for high throughput sequence data
Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17:10–12. https://doi.org/10.14806/ej.17.1.200
Langmead B, Trapnell C, Pop M, Salzberg SL (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10:R25. https://doi.org/10.1186/gb-2009-10-3-r25
Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R (2009) 1000 genome project data processing subgroup: the sequence alignment/map format and SAMtools. Bioinformatics 25:2078–2079. https://doi.org/10.1093/bioinformatics/btp352
Liao Y, Smyth GK, Shi W (2014) featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30:923–930. https://doi.org/10.1093/bioinformatics/btt656
Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15:550. https://doi.org/10.1186/s13059-014-0550-8
Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26:139–140. https://doi.org/10.1093/bioinformatics/btp616
Chen H, Boutros PC (2011) VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R. BMC Bioinform 12:35. https://doi.org/10.1186/1471-2105-12-35
Blighe K (2022) EnhancedVolcano: publication-ready volcano plots with enhanced colouring and labeling
López-Fernández H, Ferreira P, Reboiro-Jato M, Vieira CP, Vieira J (2021) The pegi3s bioinformatics docker images project. In: Rocha M, Fdez-Riverola F, Mohamad MS, Casado-Vara R (eds) Practical applications of computational biology & bioinformatics, 15th international conference (PACBB 2021). Springer, pp 31–40
Ewels P, Magnusson M, Lundin S, Käller M (2016) MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics 32:3047–3048. https://doi.org/10.1093/bioinformatics/btw354
Acknowledgements
This study was partially supported by: (i) Instituto de Salud Carlos III through the project PI18/01311 (co-funded by European Regional Development Fund, “A way to make Europe”) to R.C. Agís-Balboa, and (ii) Consellería de Educación, Universidades e Formación Professional (Xunta de Galicia) under the scope of the strategic funding ED431C2018/55-GRC Competitive Reference Group. H. López-Fernández is supported by a “María Zambrano” post-doctoral contract from Ministerio de Universidades (Gobierno de España). D. Pérez-Rodríguez is supported by an “Investigo program” predoctoral contract from Xunta de Galicia.
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Pérez-Rodríguez, D., Pérez-Rodríguez, M., Agís-Balboa, R.C., López-Fernández, H. (2023). Towards a Flexible and Portable Workflow for Analyzing miRNA-Seq Neuropsychiatric Data: An Initial Replicability Assessment. In: Fdez-Riverola, F., Rocha, M., Mohamad, M.S., Caraiman, S., Gil-González, A.B. (eds) Practical Applications of Computational Biology and Bioinformatics, 16th International Conference (PACBB 2022). PACBB 2022. Lecture Notes in Networks and Systems, vol 553. Springer, Cham. https://doi.org/10.1007/978-3-031-17024-9_4
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