AtmiRNET: a web-based resource for reconstructing regulatory networks of Arabidopsis microRNAs.
Database (Oxford)
; 2015: bav042, 2015.
Article
en En
| MEDLINE
| ID: mdl-25972521
ABSTRACT
Compared with animal microRNAs (miRNAs), our limited knowledge of how miRNAs involve in significant biological processes in plants is still unclear. AtmiRNET is a novel resource geared toward plant scientists for reconstructing regulatory networks of Arabidopsis miRNAs. By means of highlighted miRNA studies in target recognition, functional enrichment of target genes, promoter identification and detection of cis- and trans-elements, AtmiRNET allows users to explore mechanisms of transcriptional regulation and miRNA functions in Arabidopsis thaliana, which are rarely investigated so far. High-throughput next-generation sequencing datasets from transcriptional start sites (TSSs)-relevant experiments as well as five core promoter elements were collected to establish the support vector machine-based prediction model for Arabidopsis miRNA TSSs. Then, high-confidence transcription factors participate in transcriptional regulation of Arabidopsis miRNAs are provided based on statistical approach. Furthermore, both experimentally verified and putative miRNA-target interactions, whose validity was supported by the correlations between the expression levels of miRNAs and their targets, are elucidated for functional enrichment analysis. The inferred regulatory networks give users an intuitive insight into the pivotal roles of Arabidopsis miRNAs through the crosstalk between miRNA transcriptional regulation (upstream) and miRNA-mediate (downstream) gene circuits. The valuable information that is visually oriented in AtmiRNET recruits the scant understanding of plant miRNAs and will be useful (e.g. ABA-miR167c-auxin signaling pathway) for further research. Database URL http//AtmiRNET.itps.ncku.edu.tw/
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Transcripción Genética
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ARN de Planta
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Regulación de la Expresión Génica de las Plantas
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Bases de Datos de Ácidos Nucleicos
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MicroARNs
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Redes Reguladoras de Genes
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Database (Oxford)
Año:
2015
Tipo del documento:
Article
País de afiliación:
Taiwán