TY - JOUR
T1 - AtmiRNET
T2 - A web-based resource for reconstructing regulatory networks of Arabidopsis microRNAs
AU - Chien, Chia Hung
AU - Chiang-Hsieh, Yi Fan
AU - Chen, Yi An
AU - Chow, Chi Nga
AU - Wu, Nai Yun
AU - Hou, Ping Fu
AU - Chang, Wen Chi
N1 - Publisher Copyright:
© The Author(s) 2015. Published by Oxford University Press.
PY - 2015
Y1 - 2015
N2 - 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 transelements, AtmiRNET allows users to explore mechanisms of transcriptional regulation and miRNA functions in Arabidopsis thaliana, which are rarely investigated so far. Highthroughput 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.
AB - 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 transelements, AtmiRNET allows users to explore mechanisms of transcriptional regulation and miRNA functions in Arabidopsis thaliana, which are rarely investigated so far. Highthroughput 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.
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U2 - 10.1093/database/bav042
DO - 10.1093/database/bav042
M3 - Article
C2 - 25972521
AN - SCOPUS:84943159758
SN - 1758-0463
VL - 2015
JO - Database
JF - Database
M1 - bav042
ER -