MicroRNA and cDNA-Microarray as Potential Targets against Abiotic Stress Response in Plants: Advances and Prospects

Abiotic stresses, such as temperature (heat and cold), salinity, and drought negatively affect plant productivity; hence, the molecular responses of abiotic stresses need to be investigated. Numerous molecular and genetic engineering studies have made substantial contributions and revealed that abiotic stresses are the key factors associated with production losses in plants. In response to abiotic stresses, altered expression patterns of miRNAs have been reported, and, as a result, cDNA-microarray and microRNA (miRNA) have been used to identify genes and their expression patterns against environmental adversities in plants. MicroRNA plays a significant role in environmental stresses, plant growth and development, and regulation of various biological and metabolic activities. MicroRNAs have been studied for over a decade to identify those susceptible to environmental stimuli, characterize expression patterns, and recognize their involvement in stress responses and tolerance. Recent findings have been reported that plants assign miRNAs as critical post-transcriptional regulators of gene expression in a sequence-specific manner to adapt to multiple abiotic stresses during their growth and developmental cycle. In this study, we reviewed the current status and described the application of cDNA-microarray and miRNA to understand the abiotic stress responses and different approaches used in plants to survive against different stresses. Despite the accessibility to suitable miRNAs, there is a lack of simple ways to identify miRNA and the application of cDNA-microarray. The elucidation of miRNA responses to abiotic stresses may lead to developing technologies for the early detection of plant environmental stressors. The miRNAs and cDNA-microarrays are powerful tools to enhance abiotic stress tolerance in plants through multiple advanced sequencing and bioinformatics techniques, including miRNA-regulated network, miRNA target prediction, miRNA identification, expression profile, features (disease or stress, biomarkers) association, tools based on machine learning algorithms, NGS, and tools specific for plants. Such technologies were established to identify miRNA and their target gene network prediction, emphasizing current achievements, impediments, and future perspectives. Furthermore, there is also a need to identify and classify new functional genes that may play a role in stress resistance, since many plant genes constitute an unexplained fraction

TRUEE; a bioinformatic pipeline to define the functional microRNA targetome of plants

In plants, microRNAs (miRNAs) are short non-coding RNAs of approximately 20-24 nt in length which are involved in post-transcriptional regulation of genes controlling many fundamental biological pathways. They guide the miRNA Induced Silencing Complex (miRISC) to bind to target mRNAs of high complementarity where they are negative regulators of gene expression, acting via transcript cleavage and/or translational repression mechanism(s). Identifying functional miRNA-target interactions (MTIs) is central to understanding miRNA function, and this has led to the development of many miRNA target prediction tools. As high miRNA-target complementarity is required for a MTI in plants, it has been a central factor of these miRNA target prediction tools. However, most of these tools result in long lists of targets, for which there is no experimental evidence supporting the MTI, suggesting the majority of predicted targets are false positives. Furthermore, the degree of complementarity is often used to rank the likelihood of a predicted target as a miRNA target, however, many exceptions have been found. These limitations have impeded our understanding of miRNA biology and the functional scope of miRNA-mediated regulation in plants. In this thesis, bioinformatic workflow is developed named TRUEE (Targets Ranked Using Experimental Evidence) that ranks MTIs on the extent to which they are subjected to miRNA-mediated cleavage. It sorts predicted targets into high (HE) and low evidence (LE) groupings based on the frequency and strength of miRNA-guided cleavage degradome signals across multiple degradome experiments. From this, each target is assigned a numerical value, termed a Category Score, ranking the extent to which it is subjected to miRNA-mediated cleavage. As a proof-of-concept, the 428 Arabidopsis miRNAs annotated in miRBase were processed through TRUEE to determine the miRNA "targetome". The vast majority of high-ranking Category Score targets corresponded to highly conserved MTIs, validating the workflow. Very few Arabidopsis-specific, Brassicaceae-specific, or conserved-passenger miRNAs had HE targets with high Category Scores. In total, only several hundred MTIs were found to have Category Scores characteristic of currently known physiologically significant MTIs. Although non-exhaustive, clearly the number of functional MTIs is much narrower than many studies claim. As miRNA-target binding site complementarity is not a definitive indicator of a MTI, this suggests that there are other factors involved in miRNA-mediated regulation. To explore this, TRUEE was applied to conserved miRNAs to determine the identity of HE targets across species and to investigate potential additional factors involved in miRNA-mediated regulation. Firstly, for each conserved miRNA family, HE targets mostly consisted of one conserved primary target family. If an additional HE target family was identified, it was often functionally related to the former. This suggests that a plant miRNA may preferentially regulate genes that are involved in a functionally similar process. To investigate whether sequences beyond complementarity maybe facilitating MTIs, multiple sequences alignments of conserved target gene homologues were performed. In many instances, these alignments found conserved sequences flanking the miRNA-target binding site. Further bioinformatic analysis found that homologues containing these conserved flanking sequences were enriched in HE targets compared to LE targets, suggesting they are facilitating miRNA-mediated regulation. The function of these conserved sequences in the miR160 target, ARF10, were functionally tested. The introduction of synonymous point mutations in the flanking sequences of ARF10 attenuated its silencing by miR160. Together, these findings suggest that these ancient miRNA-target relationships, have developed regulatory complexities beyond complementarity that define them as strongly regulated target genes of miRNAs

Identification of barriers to gene flow between Antirrhinum species

For natural diversity to persist, there must be mechanisms in place to protect it from the homogenising effects of gene flow. Studies at natural hybrid zones have shown that, where divergent populations meet and exchange genes, genetic loci involved in adaptive population characteristics can resist gene flow. This results in a homogeneous landscape of genomic divergence, with gene flow resistant regions showing elevated divergence compared to other loci. Identification of these divergent loci may inform about the genetic basis of population differentiation, and is therefore a major aim of speciation genomics. However, genomic divergence is inherently noisy, varying due to cryptic population histories and intrinsic genomic factors. Here I introduce the grouping tree scan as a method for summarising between-population diversity across groups of populations. By comparing between-population divergence across the whole genome for many populations simultaneously, this method reduces the noise associated with within-population effects, and provides increased power for detecting divergence signals that may not be detectable through conventional two-way genome scans. Furthermore, because relationships between populations are determined independently of a priori assumptions, the approach is resilient to ascertainment bias. I apply this approach to two sympatric subspecies of Antirrhinum majus with contrasting flower colours, demonstrating that colour genes alone may be sufficient to facilitate population divergence through epistatic reproductive barriers. I then expand the approach to look at more distantly related species with distinct growth habits, identifying a subset of genomic regions that may underlie reproductive barriers based on adaptation to different environments. Finally, I outline a bioinformatic approach for detecting sRNA-producing genomic inverted repeats, which may not otherwise be detectable through population comparisons. I propose the grouping tree scan as an extension of the genome scan toolkit, expanding the utility of pooled-sequence data for characterising genetic barriers

From cradle to grave: The influence of mRNA metabolism on plant stress responses

The sessile nature of plants necessitates complex molecular responses to external stimuli, including environmental change. As the intermediary between DNA and protein, mRNA is a crucial cog in plant gene expression, and consequently a key regulatory target. During stress, control of mRNA metabolism (and downstream protein production) takes on particular importance due to the energy constraints imposed on the cell. However, the fate of stress-induced mRNAs, particularly with regard to RNA degradation, remains underexplored. This thesis aimed to address key questions concerning mRNA metabolism within two contexts: activation of transcriptional changes under drought, and the resetting of the transcriptome during recovery from high light stress. Previously, elevated drought tolerance has been observed in Arabidopsis mutants with inhibited activity of the major RNA decay factor XRN. Here, through analysis of RNA sequencing and RNA polymerase II chromatin immunoprecipitation (ChIP), evidence of transcriptional read-through was identified as a consequence of defective XRN-mediated termination. Furthermore, this read-through promoted expression of downstream genes, including stress-responsive loci, providing a potentially novel mechanism by which altered RNA degradation may alter transcriptional dynamics. In comparison to stress-induced changes in gene expression, the recovery phase following cessation of stress has been comparatively under-explored. Previous findings identified rapid downregulation of gene during recovery from high light; however, the mechanism by which this occurs has not been identified. To investigate the role of RNA decay during recovery, transcriptional inhibition experiments were carried out to measure mRNA half-lives. Surprisingly, no change in RNA stability was observed during the shift to recovery. Instead, it appeared that RNA stability was dynamically regulated during stress, including a decrease in stability as gene expression peaked. A shutoff of transcription during recovery then precipitated the rapid decrease in expression observed. Having identified that changes in RNA stability were present during high light stress, the decay pathway responsible was then explored. Previous research had suggested 5' decay was, unexpectedly, not involved in this process; therefore, particular focus was paid here to deadenylation and the 3' decay pathway. However, little evidence could be found substantiating their involvement, nor that of nonsense-mediated decay or post-transcriptional gene silencing. An alternative method was taken to explore the role of translation, which has previously been linked to changes in RNA stability . Characterisation of the high light stress and recovery translatatome was performed, with particular focus paid to genes induced by high light. However, no changes in polysome loading or unloading could be identified that were correlated with changes in RNA stability or gene expression, suggesting that translational changes were not a major contributor to these processes under high light stress. The overall findings of this thesis, particularly with respect to both nuclear and cytosolic RNA decay, emphasise the important role that RNA metabolism has in regulating gene expression in response to environmental stress. The ability to modulate RNA stability to rapidly respond to or recover from such stresses are both a crucial determinant of a plant's survival and productivity, and may also hold implications for further development of crop species that exhibit efficient use of mRNA metabolism in the regulation of gene expression in challenging environments

TarHunter, a tool for predicting conserved microRNA targets and target mimics in plants.

Summary:In plants, the targets of deeply conserved microRNAs (miRNAs) were comprehensively studied. Evidence is emerging that targets of less conserved miRNAs, endogenous target mimics (eTM) and non-canonical targets play functional roles. Existing plant miRNA prediction tools lack a cross-species conservation filter and eTM prediction function. We developed a tool named TarHunter that features a strict cross-species conservation filter and capability of predicting eTMs. TarHunter has higher recall or precision rate as compared with other tools, and the conservation filter effectively increases prediction precision. TarHunter prediction combined with degradome analysis uncovered previously neglected miRNA targets including non-canonical target sites from various plant species, which are available at the TarHunter website (http://tarhunter.genetics.ac.cn/). Availability and implementation:The code of TarHunter is available on Github (https://github.com/XMaBio). Contact:[email protected]. Supplementary information:Supplementary data are available at Bioinformatics online