Scalable Approach to Evaluate Plant microRNA Trimming and Tailing from Small RNA-Seq Data
MicroRNAs are small regulatory RNAs of 20-24 nt, which guide the RNA-induced silencing complex to silence several genes post-transcriptionally. Plant miRNA biogenesis involves many steps, including their 2'-O-methylation at their 3' end, which protects them from degradation. In addition, t...
| Autores: | , , |
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| Formato: | otro |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2025 |
| País: | España |
| Recursos: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/392142 |
| Acesso em linha: | http://hdl.handle.net/10261/392142 https://api.elsevier.com/content/abstract/scopus_id/105005816668 |
| Access Level: | acceso abierto |
| Palavra-chave: | miRNA, Trimming, Tailing, Plants, miRNA turnover, Bioinformatics, sRNA-Seq |
| Resumo: | MicroRNAs are small regulatory RNAs of 20-24 nt, which guide the RNA-induced silencing complex to silence several genes post-transcriptionally. Plant miRNA biogenesis involves many steps, including their 2'-O-methylation at their 3' end, which protects them from degradation. In addition, there are two other types of modifications involved in miRNA turnover: trimming and tailing. This method describes a bioinformatics analysis procedure to evaluate miRNA trimming and tailing from sRNA-Seq data. The pipeline includes the steps required to download the raw data from public repositories and important considerations to analyze a large number of samples. It starts from the raw sequencing reads and involves 3' adaptor removal, quality filtering, alignment to a masked reference genome to discard unwanted reads, and the assessment of the degree of trimming and tailing for each miRNA. Finally, an index for these modifications is calculated, and the results are evaluated graphically and statistically. In conclusion, this scalable pipeline allows researchers to begin with raw data from various sRNA-seq studies and progress to meaningful results and visual representations. |
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