Computational prediction of miRNAs in Arabidopsis thaliana.
MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression in animals and plants. Comparative genomic computational methods have been developed to predict new miRNAs in worms, flies, and humans. Here, we present a novel single genome approach for the detection of miRNAs in Arabidopsis thaliana. This was initiated by producing a candidate miRNA-target data set using an algorithm called findMiRNA, which predicts potential miRNAs within candidate precursor sequences that have corresponding target sites within transcripts. From this data set, we used a characteristic divergence pattern of miRNA precursor families to select 13 potential new miRNAs for experimental verification, and found that corresponding small RNAs could be detected for at least eight of the candidate miRNAs. Expression of some of these miRNAs appears to be under developmental control. Our results are consistent with the idea that targets of miRNAs encompass a wide range of transcripts, including those for F-box factors, ubiquitin conjugases, Leucine-rich repeat proteins, and metabolic enzymes, and that regulation by miRNAs might be widespread in the genome. The entire set of annotated transcripts in the Arabidopsis genome has been run through find MiRNA to yield a data set that will enable identification of potential miRNAs directed against any target gene.
Adai
Alex
A
Biological and Medical Informatics, University of California San Francisco, San Francisco, California 94143, USA.
Johnson
Cameron
C
Mlotshwa
Sizolwenkosi
S
Archer-Evans
Sarah
S
Manocha
Varun
V
Vance
Vicki
V
Sundaresan
Venkatesan
V
D000465:Algorithms; D017360:Arabidopsis / Q000235:genetics*; D019295:Computational Biology / Q000379:methods*; D014644:Genetic Variation / Q000235:genetics; D018745:Genome, Plant; D020407:Internet; D035683:MicroRNAs / Q000235:genetics*; D005810:Multigene Family / Q000235:genetics; D011237:Predictive Value of Tests; D012322:RNA Precursors / Q000235:genetics; D018749:RNA, Plant / Q000235:genetics; D012984:Software
D035683:MicroRNAs; D012322:RNA Precursors; D018749:RNA, Plant