Computational miRNomics

EditorialThe term MicroRNA or its contraction miRNA currently appears in 21,215 titles of abstracts, published between 1997 and now, available on Pubmed (2016-21-22:12:59 EET). 4,108 of these were published in 2016 alone which signifies the importance of miRNA-related research. MicroRNAs can be detected experimentally using various techniques like directional cloning of endogenous small RNAs but they are time consuming [1]. Additionally, it is necessary for the miRNA and its mRNA target(s) to be co-expressed to infer a functional relationship which is difficult, if not impossible, to achieve [2]. Since experimental approaches are facing such difficulties, they have been complemented by computational approaches [3] thereby defining the field of computational miRNomics. Due to the rapid development in the discipline, it is important to assess the state-of-the-art. In this special issue, several areas of the field are investigated ranging from pre-miRNA detection via machine learning to application of differential expression analysis in plants. First, Saçar Demirci et al. discuss an approach to virus pre-miRNA detection using machine learning [4]. Such approaches are based on parameterization of miRNAs and Yousef et al. discuss how to select among such features [5]. A different computational perspective is provided by Kotipalli et al. who model the kinetics of miRNA genesis and targeting [6]. To fuel more refined future models for genesis and targeting, it is important to establish miRNA and target expression under varying conditions. Zhang et al. [7] and Kanke et al. [8] discuss two approaches to quantify miRNAs and other non-coding short RNAs. Diler et al., finally, discuss actual biological implications of differentially expressed miRNAs [9]. This special issue on computational miRNomics, thus, provides a trajectory from detection of pre-miRNAs to biological implications of differentially expressed miRNAs. Additional topics will be covered in the upcoming second volume of the special issue on computational miRNomics.

Improvement of TA Cloning Method to Facilitate Direct Directional Cloning of PCR Products

Directional cloning is a prerequisite for the construction of expression vectors in molecular biology laboratories. Although TA cloning is widely used to clone unmodified PCR (polymerase chain reaction) products, a major disadvantage of this technique is that cloning is not directional. Here we reported a novel PCR products cloning vector with one deoxythymidine overhang and one deoxycytidine overhang at two 3'-ends respectively. With the choice of nucleotides of 5'-ends of PCR primers, PCR products can be cloned to this vector both directly and directionally. The feasibility and efficacy of this cloning method were confirmed by using a pET-17b derivative vector and a green fluorescent protein gene (EGFP) and a red fluorescent protein reporter (Ds-Red) gene. This cloning strategy may be useful in the high-throughput construction of expression vectors and could be viewed as an interesting improvement of existing TA cloning method.