SUMMARY: In recent years, phased small interfering RNA has been found to play crucial roles in many biological processes in plants. However, efficiently predicting phasiRNA regulatory cascades with computational methods is still challenging. Here, we introduce PhasiHunter, a phasiRNA regulatory network prediction tool that has several distinctive features compared to existing tools: (i) PhasiHunter employs two major phasiRNA prediction algorithms, namely phase score and hypergeometric distribution-based methods, to ensure the integrity and accuracy of prediction; (ii) PhasiHunter can identify phasiRNAs and their regulatory networks based on multiple reference sequences and the predicted results can be automatically integrated; (iii) PhasiHunter can efficiently identify the phasiRNAs generated through alternative splicing events; and (iv) the excellent data structure and parallel computing architecture allow PhasiHunter to predict phasiRNAs and their regulatory pathways with high efficiency. AVAILABILITY AND IMPLEMENTATION: PhasiHunter is an open-source tool that is available at https://github.com/HuangLab-CBI/PhasiHunter.

A critical aspect for exploring the biological function of a microRNA (miRNA) lies on exact detection and validation of its target mRNAs. However, no convenient and efficient web-based server is available for plant biologists to identify the experimentally verified target mRNAs of miRNAs. In this work, we built a comprehensive web-based platform for miRNA-target analysis, named as Whole-degradome-based Plant MiRNA-target Interaction Analysis Server (WPMIAS), for validation of predicted interactions of miRNAs and their target mRNAs (MTIs) by user-submitted data or all available pre-loaded degradome data. Besides, the server can construct degradome-based miRNA regulatory networks (MRNs) based on the validated MTIs to help study the functions and relations among miRNAs and target mRNAs. WPMIAS is also suitable for other small RNAs (sRNAs), such as 21-nt phased siRNAs (phasiRNAs) and natural antisense siRNAs (nat-siRNAs), which direct cleavage of target mRNAs. Currently, WPMIAS supports 64 plant species with ∼200 cDNA libraries and 274 pre-loaded plant degradome datasets. The user can identify all validated MTIs by analyzing all degradome data at a time and understand when and where MTIs take place and their cleavage levels. With the data obtained from WPMIAS, the user can build a plant miRNA-target map, where it is convenient to find interesting research ideas on miRNAs. In summary, WPMIAS is able to support a comprehensive web-based plant miRNA-target analysis and expected to greatly promote future research on plant miRNAs. AVAILABILITY: It can be freely accessed at https://cbi.njau.edu.cn/WPMIAS/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Motivation: MicroRNAs (miRNAs) play essential roles in plant growth, development and stress responses through post-transcriptionally regulating the expression levels of their target mRNAs. Although some tools and databases were developed for predicting the relationships between miRNAs and their targets (miR-Tar), most of them were dependent on computational methods without experimental validations. With the development of degradome sequencing techniques, researchers can identify potential interactions based on degradome sequencing data. The validations with specific degradome data are useful to identify the miR-Tar interactions (MTIs) occurring in/under some specific tissues or treatments. Degradome-based plant miRNA-target interaction and network database (DPMIND) collected almost all available plant degradome data and built a retrieval and analysis platform of miRNA-target interactions and miRNA regulatory networks (MRNs). Results: DPMIND contains the recently updated 3794 miRNAs and 28 666 verified MTIs with 69 degradomes from 10 plant species. Not only the verified MTIs but also the degradome-based MRNs can be retrieved from DPMIND. Users can search for the verified MTIs and build degradome-based MRNs for the specific miRNAs or targets. DPMIND can build the MRNs based on all degradomes or specific degradomes, which helps to identify all possible connections among specific miR-Tar and compare the miRNA-mediated networks among various tissues or treatments. It can also build the networks mediated by all known miRNAs based on specific degradomes. Furthermore, DPMIND can be used to study the conservation and specificity of MTIs and sub-networks across different plant tissues or species. Availability and implementation: http://202.195.246.60/DPMIND/. Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.