Research progress of prediction of bacterial sRNA genes and their targets－A review

Abstract:

Abstract: Bacterial sRNAs are a class of non-coding RNAs with 40-500 nucleotides in length. Most of them function as posttranscriptional regulation of gene expression through binding to the translation initiation region of their target mRNAs. In view that prediction of sRNAs and their targets provides support for experimental identification, some prediction methods have been developed for both of them in recent years. In this review, we firstly gave an overview of methods for prediction of sRNA genes, which are classified into three categories, namely, comparative genomics-based, transcription units-based and machine learning-based prediction methods. Secondly, the methods for sRNA target prediction are classified into two types, which are sequence alignment-based method and prediction of RNA secondary structure-based method, respectively. Finally, the principles, advantages and limitations of each kind of method are discussed, and perspectives for prediction methods of sRNA and their targets is pointed out.