Development of species specific putative miRNA and its target prediction tool in wheat (Triticum aestivum L.)

RNAinsecta: A tool for prediction of precursor microRNA in insects and search for their target in the model organism Drosophila melanogaster

INTRODUCTION AND BACKGROUND

Pre-MicroRNAs are the hairpin loops from which microRNAs are produced that have been found to negatively regulate gene expression in several organisms. In insects, microRNAs participate in several biological processes including metamorphosis, reproduction, immune response, etc. Numerous tools have been designed in recent years to predict novel pre-microRNA using binary machine learning classifiers where prediction models are trained with true and pseudo pre-microRNA hairpin loops. Currently, there are no existing tool that is exclusively designed for insect pre-microRNA detection.

AIM

Application of machine learning algorithms to develop an open source tool for prediction of novel precursor microRNA in insects and search for their miRNA targets in the model insect organism, Drosophila melanogaster.

METHODS

Machine learning algorithms such as Random Forest, Support Vector Machine, Logistic Regression and K-Nearest Neighbours were used to train insect true and false pre-microRNA features with 10-fold Cross Validation on SMOTE and Near-Miss datasets. miRNA targets IDs were collected from miRTarbase and their corresponding transcripts were collected from FlyBase. We used miRanda algorithm for the target searching.

RESULTS

In our experiment, SMOTE performed significantly better than Near-Miss for which it was used for modelling. We kept the best performing parameters after obtaining initial mean accuracy scores >90% of Cross Validation. The trained models on Support Vector Machine achieved accuracy of 92.19% while the Random Forest attained an accuracy of 80.28% on our validation dataset. These models are hosted online as web application called RNAinsecta. Further, searching target for the predicted pre-microRNA in Drosophila melanogaster has been provided in RNAinsecta.

Stress-induced miRNAs isolated from wheat have a unique therapeutic potential in ultraviolet-stressed human keratinocyte cells

Increasing evidence supports the existence of cross-kingdom gene regulation. However, the therapeutic potential of stress-specific plant miRNAs and their role in UV-related pathologies in human tissue remain largely unexplored. The aim of this study was to investigate the therapeutic potential and mechanisms of action of stress-induced miRNA cocktails (SI-WmiRs) from Einkorn wheat (Triticum monococcum L.) on human keratinocyte (HaCaT) cells exposed to a high dose of UV-B radiation. We used a biofactory approach and irradiated wheatgrass with UV-C for 240 min to obtain the specific SI-WmiRs that wheat produces to recover from UV stress. We followed the plant with molecular and biochemical analyses and extracted our SI-WmiRs at the most appropriate time (0 h and 6 h after UV-C application). Then, we applied the SI-WmiR cocktail to HaCaT cells exposed to high-dose of UV-B radiation. Our results show that UV-B radiation induced lipid peroxidation and DNA damage, as demonstrated by increased malondialdehyde (MDA) levels and changes in the RAPD band profile, respectively. UV stress also impaired IL6/JAK2/STAT3 signalling and activated the inflammatory mediators IL6 and TNF-α in HaCaT cells, leading to significant induction of apoptotic cell death. We found that SI-WmiR transfection prevents lipid peroxidation and oxidative stress-related DNA damage by increasing antioxidant (CuZn-SOD, Mn-SOD) and DNA repair (EXO1, SMUG1 and XRCC3) gene expression. In addition, SI-WmiRs regulated IL6/JAK2/STAT3 signalling by reducing JAK2 and STAT3 gene expression and phosphorylated protein levels compared to the control treatments. Moreover, SI-WmiRs inhibited pro-apoptotic BAX, Caspase 3 and Caspase 8 gene expression and protein levels to prevent apoptosis of UV-stressed HaCaT cells. Our results demonstrate that stress-induced wheat miRNAs produced using a biofactory approach have strong potential as a novel and effective alternative therapy for UV stress-related skin damage.

Differential expression profiling of microRNAs and their target genes during wheat-Bipolaris sorokiniana pathosystem

Wheat spot blotch, caused by Bipolaris sorokiniana, is a serious constraint to wheat production, reducing grain yield and consequently having severe economic impact. Several plant miRNAs have recently been discovered as regulators of gene expression involved in cellular and metabolic functions. So far reports on the roles of miRNAs in B. sorokiniana infection response of wheat are scanty. To further understand the defence mechanism of miRNAs- regulated cellular functions, we examined the expression patterns of 17 miRNAs and their targets involved in the interaction between wheat and B. sorokiniana in two contrasting wheat genotypes, Chiriya-1 and WH-147. All of the miRNAs and target genes were shown to be expressed differentially in both genotypes after B. sorokiniana infection. Seven and nine miRNAs were observed as up-regulated in the resistant genotype Chiriya-1 and the susceptible genotype WH147, respectively. Among the up-regulated miRNAs, ptc-miR901 (~ 10.21 times) accumulated the most in Chiriya-1 followed by ptc-miR1450 (~ 7.6 times) in WH-147. Furthermore, only two miRNAs, tae-miR156 and ptc-miR482c showed a complete inverse relation with their target genes, SPL and NBS-LRR, respectively. This research sheds light on the temporal differential regulation of miRNAs and their targets, which may play a role in wheat adaptation to B. sorokiniana infection.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-01092-1.

In Silico Identification of miRNA and Targets from Chrysopogon zizanioides (L.) Roberty with Functional Validation from Leaf and Root Tissues

microRNAs are small non-coding RNA molecule that plays an important role in metabolism. Chrysopogon zizanioides (L.) Roberty is an important aromatic plant used in perfumery industries, soil, water conservation, and agricultural practices. In this study, the transcriptomic sequence of vetiver leaf and root was subjected to miRNA identification by the computational methods. miRNA identification was carried out using a homology-based method by C-mii software with several other online tools. A total of 80 miRNA were identified from both leaf and root sequences. Target identification was done by identified miRNA sets. A total of 25 and 31 miRNA families were identified in both leaf and root, respectively, with ten common families involve in different ontological function. miR169 and miR5021 regulate most of the target in leaf and root. In vetiver, many primary and secondary metabolism elements are regulated by miRNA as photo-system, transcription factor, terpenoid metabolism, etc. Here is the first in silico study revealing the specific miRNAs and their target genes for corresponding root and leaf tissues respectively in C. zizanioides.