Genome-wide identification of MITE-derived microRNAs and their targets in bread wheat.

BACKGROUND: Plant miRNAs are a class of small non-coding RNAs that can repress gene expression at the post-transcriptional level by targeting RNA degradation or promoting translational repression. There is increasing evidence that some miRNAs can derive from a group of non-autonomous class II transposable elements called Miniature Inverted-repeat Transposable Elements (MITEs). RESULTS: We used public small RNA and degradome libraries from Triticum aestivum to screen for microRNAs production and predict their cleavage target sites. In parallel, we also created a comprehensive wheat MITE database by identifying novel elements and compiling known ones. When comparing both data sets, we found high homology between MITEs and 14% of all the miRNAs production sites detected. Furthermore, we show that MITE-derived miRNAs have preference for targeting degradation sites with MITE insertions in the 3' UTR regions of the transcripts. CONCLUSIONS: Our results revealed that MITE-derived miRNAs can underlay the origin of some miRNAs and potentially shape a regulatory gene network. Since MITEs are found in millions of insertions in the wheat genome and are closely linked to genic regions, this kind of regulatory network could have a significant impact on the post-transcriptional control of gene expression.

Phenobook: an open source software for phenotypic data collection.

Background: Research projects often involve observation, registration, and data processing starting from information obtained in field experiments. In many cases, these tasks are carried out by several persons in different places, times, and ways, adding different levels of complexity and error in data collecting. Furthermore, data processing can be time consuming, and input errors may produce unwanted results. Results: We have developed a novel, open source software called Phenobook, an easy, flexible, and intuitive tool to organize, collect, and save experimental data for further analyses. Phenobook was conceived to collect phenotypic observations in a user-friendly, cost-effective way. It consists of a web-based software for experiment design, data input and visualization, and exportation, combined with a mobile application for remote data collecting. We provide in this article a detailed description of the developed tool. Conclusion: Phenobook is a software tool that can be easily implemented in collaborative research and development projects involving data collecting and forward analyses. Adopting Phenobook is expected to improve the involved processes by minimizing input errors, resulting in higher quality and reliability of the research outcomes.