A Comprehensive Plant microRNA Simple Sequence Repeat Marker Database to Accelerate Genetic Improvements in Crops

Microsatellites, or simple sequences repeat (SSRs), are distributed in genes, intergenic regions and transposable elements in the genome. SSRs were identified for developing markers from draft genome assemblies, transcriptome sequences and genome survey sequences in plant and animals. The identification, distribution, and density of microsatellites in pre-microRNAs (miRNAs) are not well documented in plants. In this study, SSRs were identified in 16,892 pre-miRNA sequences from 292 plant species in six taxonomic groups (algae to dicots). Fifty-one percent of pre-miRNA sequences contained SSRs. Mononucleotide repeats were the most abundant, followed by di- and trinucleotide repeats. Tetra-, penta-, and hexarepeats were rare. A total of 9,498 (57.46%) microsatellite loci had potential as pre-miRNA SSR markers. Of the markers, 3,573 (37.62%) were non-redundant, and 2,341 (65.51%) primer pairs could be transferred to at least one of the plant taxonomic groups. All data and primer pairs were deposited in a user-friendly, freely accessible plant miRNA SSR marker database. The data presented in this study, accelerate the understanding of pre-miRNA evolution and serve as valuable genomic treasure for genetic improvements in a wide range of crops, including legumes, cereals, and cruciferous crops.

PmiREN2.0: from data annotation to functional exploration of plant microRNAs

Nearly 200 plant genomes have been sequenced over the last two years, and new functions of plant microRNAs (miRNAs) have been revealed. Therefore, timely update of the plant miRNA databases by incorporating miRNAs from the newly sequenced species and functional information is required to provide useful resources for advancing plant miRNA research. Here we report the update of PmiREN2.0 (https://pmiren.com/) with an addition of 19 363 miRNA entries from 91 plants, doubling the amount of data in the original version. Meanwhile, abundant regulatory information centred on miRNAs was added, including predicted upstream transcription factors through binding motifs scanning and elaborate annotation of miRNA targets. As an example, a genome-wide regulatory network centred on miRNAs was constructed for Arabidopsis. Furthermore, phylogenetic trees of conserved miRNA families were built to expand the understanding of miRNA evolution across the plant lineages. These data are helpful to deduce the regulatory relationships concerning miRNA functions in diverse plants. Beside the new data, a suite of design tools was incorporated to facilitate experimental practice. Finally, a forum named ‘PmiREN Community’ was added for discussion and resource and new discovery sharing. With these upgrades, PmiREN2.0 should serve the community better and accelerate miRNA research in plants.

R-Loops between nascent pri-miRNAs and the encoding loci promote co-transcriptional processing of miRNAs in plants

SummaryIn most organisms, the maturation of nascent RNAs is coupled to transcription, undergoing many processing steps co-transcriptionally. Unlike in animals, the RNA polymerase II (RNAPII) transcribes microRNAs (miRNAs) as long and structurally variable pri-miRNAs in plants. Current evidence suggests that the miRNA biogenesis complex assembly initiates early during the transcription of pri-miRNAs in plants. However, it is unknown whether miRNA processing occurs co-transcriptionally. Here, we show that plant miRNA biogenesis is coupled to transcription in a process that relies on the formation of DNA:RNA hybrids (R-loops) between the nascent transcript and the encoding loci. We used native elongating transcript sequencing data and imaging techniques to demonstrate that plant miRNA biogenesis occurs co-transcriptionally. We found that the entire biogenesis occurs coupled to transcription for pri-miRNAs processed from the loop but requires a second nucleoplasmic step for those processed from the base of the hairpin. Furthermore, we found that co- and post-transcriptional miRNA processing mechanisms co-exist for most miRNAs in a dynamic balance. Notably, we discovered that R-loops between the 5’-end single-stranded arm of the pri-miRNAs and the encoding loci anchor the transcript, promoting co-transcriptional processing. Our data demonstrate the coupling of transcription and miRNA processing in plants and discovered an unexpected function for R-loops promoting RNA processing. Furthermore, our results suggest the neo-functionalization of co-transcriptionally processed miRNAs, boosting countless regulatory scenarios.

Identification and Functional Characterization of Plant MiRNA Under Salt Stress Shed Light on Salinity Resistance Improvement Through MiRNA Manipulation in Crops

Salinity, as a major environmental stressor, limits plant growth, development, and crop yield remarkably. However, plants evolve their own defense systems in response to salt stress. Recently, microRNA (miRNA) has been broadly studied and considered to be an important regulator of the plant salt-stress response at the post-transcription level. In this review, we have summarized the recent research progress on the identification, functional characterization, and regulatory mechanism of miRNA involved in salt stress, have discussed the emerging manipulation of miRNA to improve crop salt resistance, and have provided future direction for plant miRNA study under salt stress, suggesting that the salinity resistance of crops could be improved by the manipulation of microRNA.

TarDB: an online database for plant miRNA targets and miRNA-triggered phased siRNAs

Background In plants, microRNAs (miRNAs) are pivotal regulators of plant development and stress responses. Different computational tools and web servers have been developed for plant miRNA target prediction; however, in silico prediction normally contains false positive results. In addition, many plant miRNA target prediction servers lack information for miRNA-triggered phased small interfering RNAs (phasiRNAs). Creating a comprehensive and relatively high-confidence plant miRNA target database is much needed. Results Here, we report TarDB, an online database that collects three categories of relatively high-confidence plant miRNA targets: (i) cross-species conserved miRNA targets; (ii) degradome/PARE (Parallel Analysis of RNA Ends) sequencing supported miRNA targets; (iii) miRNA-triggered phasiRNA loci. TarDB provides a user-friendly interface that enables users to easily search, browse and retrieve miRNA targets and miRNA initiated phasiRNAs in a broad variety of plants. TarDB has a comprehensive collection of reliable plant miRNA targets containing previously unreported miRNA targets and miRNA-triggered phasiRNAs even in the well-studied model species. Most of these novel miRNA targets are relevant to lineage-specific or species-specific miRNAs. TarDB data is freely available at http://www.biosequencing.cn/TarDB. Conclusions In summary, TarDB serves as a useful web resource for exploring relatively high-confidence miRNA targets and miRNA-triggered phasiRNAs in plants.

MicroRNA annotation in plants: current status and challenges

Last two decades, the studies on microRNAs (miRNAs) and the numbers of annotated miRNAs in plants and animals have surged. Herein, we reviewed the current progress and challenges of miRNA annotation in plants. Via the comparison of plant and animal miRNAs, we pinpointed out the difficulties on plant miRNA annotation and proposed potential solutions. In terms of recalling the history of methods and criteria in plant miRNA annotation, we detailed how the major progresses made and evolved. By collecting and categorizing bioinformatics tools for plant miRNA annotation, we surveyed their advantages and disadvantages, especially for ones with the principle of mimicking the miRNA biogenesis pathway by parsing deeply sequenced small RNA (sRNA) libraries. In addition, we summarized all available databases hosting plant miRNAs, and posted the potential optimization solutions such as how to increase the signal-to-noise ratio (SNR) in these databases. Finally, we discussed the challenges and perspectives of plant miRNA annotations, and indicated the possibilities offered by an all-in-one tool and platform according to the integration of artificial intelligence.