psRobot

psRobot predicts stem-loop precursors and target transcripts of small RNAs to identify microRNAs and short hairpin RNAs and to assess smRNA biogenesis, function, and evolutionary conservation.

Key Features:

• Stem-Loop Small RNA Prediction: Aligns user sequences to a selected genome, extracts predicted precursors, and assesses whether these precursors form characteristic stem-loop secondary structures for microRNAs and short hairpin RNAs.
• Small RNA Target Prediction: Uses a modified Smith-Waterman algorithm to predict potential target genes or transcripts from a chosen transcript library and incorporates expression data from plant smRNA biogenesis gene mutants and smRNA-associated protein complexes.
• Evaluation of Prediction Reliability: Integrates mRNA cleavage (degradome) data to enhance specificity and evaluate the reliability of predicted targets.
• Cross-Species Conservation and Target Site Multiplicity: Reports conservation status of smRNAs across species and the multiplicity of their target sites.

Scientific Applications:

• smRNA discovery and annotation: Identification of candidate microRNAs and short hairpin RNAs through stem-loop precursor prediction.
• Target identification and validation: Prediction and assessment of smRNA target genes or transcripts using modified Smith-Waterman, degradome, and expression data.
• Functional and biogenesis studies: Investigation of microRNA and small interfering RNA generation and function by integrating expression in smRNA biogenesis gene mutants and smRNA-associated protein complexes.
• Evolutionary analyses: Assessment of cross-species conservation and target site multiplicity to infer evolutionary conservation of smRNAs.

Methodology:

Aligns sequences to genomes, predicts precursor secondary structures, applies a modified Smith-Waterman algorithm for target prediction, and integrates expression and degradome (mRNA cleavage) data.