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1. Short day transcriptomic programming during induction of dormancy in grapevine

   https://doi.org/doi.org/10.3389/fpls.2015.00834  

   Fennell, AY; Schlauch, KA; Gouthu, S; Deluc, LG; Khadka, V; Sreekantan, L; Grimplet, J; Cramer, GR; Mathiason, KL (November 2015, Frontiers in plant science)

   Bud dormancy in grapevine is an adaptive strategy for the survival of drought, high and low temperatures and freeze dehydration stress that limit the range of cultivar adaptation. Therefore, development of a comprehensive understanding of the biological mechanisms involved in bud dormancy is needed to promote advances in selection and breeding, and to develop improved cultural practices for existing grape cultivars. The seasonally indeterminate grapevine, which continuously develops compound axillary buds during the growing season, provides an excellent system for dissecting dormancy, because the grapevine does not transition through terminal bud development prior to dormancy. This study used gene expression patterns and targeted metabolite analysis of two grapevine genotypes that are short photoperiod responsive (Vitis riparia) and non-responsive (V. hybrid, Seyval) for dormancy development to determine differences between bud maturation and dormancy commitment. Grapevine gene expression and metabolites were monitored at seven time points under long (LD, 15 h) and short (SD, 13 h) day treatments. The use of age-matched buds and a small (2 h) photoperiod difference minimized developmental differences and allowed us to separate general photoperiod from dormancy specific gene responses. Gene expression profiles indicated three distinct phases (perception, induction and dormancy) in SD-induced dormancy development in V. riparia. Different genes fromthe NAC DOMAIN CONTAINING PROTEIN 19 and WRKY families of transcription factors were differentially expressed in each phase of dormancy. Metabolite and transcriptome analyses indicated ABA, trehalose, raffinose and resveratrol compounds have a potential role in dormancy commitment. Finally, a comparison between V. riparia compound axillary bud dormancy and dormancy responses in other species emphasized the relationship between dormancy and the expression of RESVERATROL SYNTHASE and genes associated with C3HC4-TYPE RING FINGER and NAC DOMAIN CONTAINING PROTEIN 19 transcription factors. 

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2. Cell Cycle-dependent Regulation and Function of ARGONAUTE1 in Plants

   https://doi.org/10.1105/tpc.19.00069  

   Trolet, Adrien; Baldrich, Patricia; Criqui, Marie-Claire; Dubois, Marieke; Clavel, Marion; Meyers, Blake C.; Genschik, Pascal (August 2019, The Plant Cell)

   Regulated gene expression is key to the orchestrated progression of the cell cycle. Many genes are expressed at specific points in the cell cycle, including important cell cycle regulators, plus factors involved in signal transduction, hormonal regulation and metabolic control. We demonstrate that post-embryonic depletion of Arabidopsis thaliana ARGONAUTE1 (AGO1), the main effector of plant microRNAs, impairs cell division in the root meristem. We utilized the highly synchronizable tobacco (Nicotiana tabacum) BY2 cell suspension to analyze mRNA, small RNAs, and mRNA cleavage products of synchronized BY2 cells at S, G2, M and G1 phases of the cell cycle. This revealed that in plants, only a few miRNAs show differential accumulation during the cell cycle, and miRNA-target pairs were only identified for a small proportion of the more than 13,000 differentially expressed genes during the cell cycle. However, this unique set of microRNA-target pairs could be key to attenuate the expression of several transcription factors and disease resistance genes. We also demonstrate that AGO1 binds to a set of 19 nt, tRNA-derived fragments during the cell cycle progression. 

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3. A computational modeling of pri-miRNA expression

   https://doi.org/10.1371/journal.pone.0290768  

   Zheng, Hansi; Wang, Saidi; Li, Xiaoman; Hu, Haiyan (January 2024, PLOS ONE)

   Helmer-Citterich, Manuela (Ed.)

   MicroRNAs (miRNAs) play crucial roles in gene regulation. Most studies focus on mature miRNAs, which leaves many unknowns about primary miRNAs (pri-miRNAs). To fill the gap, we attempted to model the expression of pri-miRNAs in 1829 primary cell types, cell lines, and tissues in this study. We demonstrated that the expression of pri-miRNAs can be modeled well by the expression of specific sets of mRNAs, which we termed their associated mRNAs. These associated mRNAs differ from their corresponding target mRNAs and are enriched with specific functions. Most associated mRNAs of a miRNA are shared across conditions, while on average, about one-fifth of the associated mRNAs are condition-specific. Our study shed new light on understanding miRNA biogenesis and general gene transcriptional regulation. 

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4. Identification and developmental profiling of microRNAs in the acoel worm Hofstenia miamia

   https://doi.org/10.1101/2024.12.01.626237  

   Duan, Ye; Segev, Tomer; Veksler-Lublinsky, Isana; Ambros, Victor; Srivastava, Mansi (December 2024, bioRxiv)

   ABSTRACT The acoel wormHofstenia miamia (H. miamia)has recently emerged as a model organism for studying whole-body regeneration and embryonic development. Previous studies suggest that post-transcriptional mechanisms likely play important roles in whole-body regeneration. Here, we establish a resource for studyingH. miamiamicroRNA-mediated gene regulation, a major aspect of post-transcriptional control in animals. Using small RNA-sequencing samples spanning key developmental stages, we annotatedH. miamiamicroRNAs. Our analysis uncovered a total of 1,050 microRNA loci, including 479 high-confidence loci based on structural and read abundance criteria. Comparison of microRNA seed sequences with those in other bilaterian species revealed thatH. miamiaencodes the majority of known conserved bilaterian microRNA families and that several microRNA families previously reported only in protostomes or deuterostomes likely have ancient bilaterian origins. We profiled the expression dynamics of theH. miamiamiRNAs across embryonic and post-embryonic development. We observed that thelet-7andmir-125microRNAs are unconventionally enriched at early embryonic stages. To generate hypotheses for miRNA function, we annotated the 3’ UTRs ofH. miamiaprotein-coding genes and performed miRNA target site predictions. Focusing on genes that are known to function in the wound response, posterior patterning, and neural differentiation inH. miamia, we found that these processes may be under substantial miRNA regulation. Notably, we found that miRNAs in MIR-7 and MIR-9 families which have target sites in the posterior genesfz-1,wnt-3, andsp5are indeed expressed in the anterior of the animal, consistent with a repressive effect on their corresponding target genes. Our annotation offers candidate miRNAs for further functional investigation, providing a resource for future studies of post-transcriptional control during development and regeneration. 

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5. A two-stream convolutional neural network for microRNA transcription start site feature integration and identification

   https://doi.org/10.1038/s41598-021-85173-x  

   Cha, Mingyu; Zheng, Hansi; Talukder, Amlan; Barham, Clayton; Li, Xiaoman; Hu, Haiyan (December 2021, Scientific Reports)

   null (Ed.)

   Abstract MicroRNAs (miRNAs) play important roles in post-transcriptional gene regulation and phenotype development. Understanding the regulation of miRNA genes is critical to understand gene regulation. One of the challenges to study miRNA gene regulation is the lack of condition-specific annotation of miRNA transcription start sites (TSSs). Unlike protein-coding genes, miRNA TSSs can be tens of thousands of nucleotides away from the precursor miRNAs and they are hard to be detected by conventional RNA-Seq experiments. A number of studies have been attempted to computationally predict miRNA TSSs. However, high-resolution condition-specific miRNA TSS prediction remains a challenging problem. Recently, deep learning models have been successfully applied to various bioinformatics problems but have not been effectively created for condition-specific miRNA TSS prediction. Here we created a two-stream deep learning model called D-miRT for computational prediction of condition-specific miRNA TSSs ( http://hulab.ucf.edu/research/projects/DmiRT/ ). D-miRT is a natural fit for the integration of low-resolution epigenetic features (DNase-Seq and histone modification data) and high-resolution sequence features. Compared with alternative computational models on different sets of training data, D-miRT outperformed all baseline models and demonstrated high accuracy for condition-specific miRNA TSS prediction tasks. Comparing with the most recent approaches on cell-specific miRNA TSS identification using cell lines that were unseen to the model training processes, D-miRT also showed superior performance. 

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