Functional miRNA Targets Research Articles

Posterior cingulate cortex microRNA alterations in cognitive resilience, mild cognitive impairment, and Alzheimer’s disease

AbstractBackgroundMicroRNA (miRNA) dysregulation is linked to Alzheimer’s disease (AD) pathophysiology. We recently reported a role for miR‐298 and miR‐20b in AD risk and amyloid and tau metabolism. To examine the extent to which miRNAs are dysregulated during the earliest stages of AD, we quantified miRNA transcript levels in postmortem samples of posterior cingulate cortex (PCC), a default mode network (DMN) hub that underlies autobiographical memory, in normal subjects and those who died within the AD continuum.MethodPCC samples were obtained from Rush ROS/MAP participants who came to autopsy with a diagnosis of a) no cognitive impairment and low pathology (NCI‐LP, Braak stage I/II, n = 12), b) NCI with high pathology (NCI‐HP, Braak stage IV, representing cognitive resilience, n = 8), c) mild cognitive impairment (MCI, n = 10), or d) dementia due to AD (n = 9). Illumina‐based sequencing of total RNA was performed and trimmed reads with a size of 15‐31 bases were analyzed.ResultDifferential expression analysis (FDR ≤ 0.04) revealed 42 miRNAs significantly dysregulated among the NCI (independent of Braak stage), MCI, and AD groups. Two miRNAs, miR‐99a (FDR‐adjusted p = 0.01) and miR‐664b (p = 0.005), were downregulated in AD vs NCI and MCI, while miR‐30a (p = 0.006), miR‐374a (p = 0.004), and miR‐501 (p = 0.005) were significantly upregulated in MCI vs. NCI and AD. Three miRNAs were significantly downregulated in NCI‐HP vs. NCI‐LP: miR‐103a (p = 0.04), miR‐211 (p = 0.03), and miR‐4443 (p = 0.03). These miRNAs may operate in resilience‐related pathways. Correlation analysis revealed that decreasing PCC levels of miR‐664b levels were associated with poorer performance on antemortem tests of episodic memory (r = 0.41, p = 0.009), semantic memory (r = 0.44, p = 0.004), and visuospatial ability (r = 0.45, p = 0.004).ConclusionTaken together, these data may identify potential pathogenic or protective miRNA‐related mechanisms contributing to PCC and DMN function during the progression of AD, which may inform biomarker and intervention strategies. Ongoing analysis will identify functional pathway enrichment and miRNA targets.

Detection of transcriptome-wide microRNA–target interactions in single cells with agoTRIBE

MicroRNAs (miRNAs) exert their gene regulatory effects on numerous biological processes based on their selection of target transcripts. Current experimental methods available to identify miRNA targets are laborious and require millions of cells. Here we have overcome these limitations by fusing the miRNA effector protein Argonaute2 to the RNA editing domain of ADAR2, allowing the detection of miRNA targets transcriptome-wide in single cells. miRNAs guide the fusion protein to their natural target transcripts, causing them to undergo A>I editing, which can be detected by sensitive single-cell RNA sequencing. We show that agoTRIBE identifies functional miRNA targets, which are supported by evolutionary sequence conservation. In one application of the method we study microRNA interactions in single cells and identify substantial differential targeting across the cell cycle. AgoTRIBE also provides transcriptome-wide measurements of RNA abundance and allows the deconvolution of miRNA targeting in complex tissues at the single-cell level.

An ensemble of stacking classifiers for improved prediction of miRNA–mRNA interactions

MicroRNAs (miRNAs) are small non-coding RNA molecules that play a crucial role in regulating gene expression at the post-transcriptional level by binding to potential target sites of messenger RNAs (mRNAs), facilitated by the Argonaute family of proteins. Selecting the conservative candidate target sites (CTS) is a challenging step, considering that most of the existing computational algorithms primarily focus on canonical site types, which is a time-consuming and inefficient utilization of miRNA target site interactions. We developed a stacking classifier algorithm that addresses the CTS selection criteria using feature-encoding techniques that generates feature vectors, including k-mer nucleotide composition, dinucleotide composition, pseudo-nucleotide composition, and sequence order coupling. This innovative stacking classifier algorithm surpassed previous state-of-the-art algorithms in predicting functional miRNA targets. We evaluated the performance of the proposed model on 10 independent test datasets and obtained an average accuracy of 79.77%, which is a significant improvement of 7.26 % over previous models. This improvement shows that the proposed method has great potential for distinguishing highly functional miRNA targets and can serve as a valuable tool in biomedical and drug development research.

Identification of miRNAs as Biomarkers of Cardiac Protection in Non-Genetically Modified Primary Human Cardiomyocytes Exposed to Halogenated Hypnotics in an In Vitro Model of Transfection and Ischemia/Reperfusion: A New Model in Translational Anesthesia.

Many clinical studies have identified some circulating micro-RNAs (miRNAs) as potential biomarkers with regard to the cardioprotective effects of halogenated agents administered perioperatively during myocardial conditioning procedures. However, there is a major methodological difficulty in identifying these potential miRNA targets in cardiac cells. We developed an in vitro protocol to analyze the differential expression of target miRNAs at the intracellular level in non-genetically modified primary human cardiomyocytes (HCMs) through their exposure to different hypnotic compounds (i.e., halogenated versus non-halogenated). For this purpose, we performed a validated in vitro model of "ischemia and reperfusion" with the transfection of specific miRNA mimics (MIMICs) designed to simulate naturally occurring mature miRNAs as a functional study. Afterwards, next-generation sequencing (NGS) was used to identify and quantify miRNAs and elucidate their function. The differences in miRNA expression between HCMs exposed to different hypnotic drugs, along with the prediction of functional miRNA targets, were assessed using a meticulous in-house bioinformatics pipeline in order to derive diagnostic biomarkers and possible therapeutic targets. In brief, this methodological procedure was designed to investigate whether the cardioprotective effects of halogenated agents are a phenomenon mediated by either the activation or the suppression of miRNAs targeted by halogenated anesthetics.

Integrated analysis of microRNA and mRNA expression profiles in Crassostrea gigas to reveal functional miRNA and miRNA-targets regulating shell pigmentation

MicroRNAs (miRNAs) regulate post-transcription gene expression by targeting genes and play crucial roles in diverse biological processes involving body color formation. However, miRNAs and miRNA-targets underlying shell color polymorphism remain largely unknown in mollusca. Using four shell colors full-sib families of the Pacific oyster Crassostrea gigas, we systematically identified miRNAs and miRNA-targets in the mantles, which organ could produce white, golden, black or partially pigmented shell. RNA sequencing and analysis identified a total of 53 known miRNA and 91 novel miRNAs, 47 of which were detected to differentially express among six pairwise groups. By integrating miRNA and mRNA expression profiles, a total of 870 genes were predicted as targets of differentially expressed miRNAs, mainly involving in biomineralization and pigmentation through functional enrichment. Furthermore, a total of four miRNAs and their target mRNAs were predicted to involve in synthesis of melanin, carotenoid or tetrapyrrole. Of them, lgi-miR-317 and its targets peroxidase and lncRNA TCONS_00951105 are implicated in acting as the competing endogenous RNA to regulate melanogenesis. Our studies revealed the systematic characterization of miRNAs profiles expressed in oyster mantle, which might facilitate understanding the intricate molecular regulation of shell color polymorphism and provide new insights into breeding research in oyster.

An integrated analysis of testis miRNA and mRNA transcriptome reveals important functional miRNA-targets in reproduction traits of roosters

The reproductive efficiency of roosters is an important trait in poultry production; however, the molecular mechanisms underlying this trait are not clearly understood. Here, we compared the mRNA and microRNA (miRNA) transcriptomes of testis from roosters with divergent sperm motility. A total of 302 differentially expressed genes (DEGs), including 182 upregulated genes and 120 downregulated genes, were identified in high sperm motility groups compared with low sperm motility groups. A subset of these DEGs related to steroid hormone biosynthesis and thus could be important for spermatogenesis. Additionally, we detected 13 differentially expressed miRNAs (DEMs) between two groups, and target gene prediction indicated seven of these could be associated with spermatogenesis. Based on a comprehensive analysis of these transcriptomes, miRNA–mRNA interaction networks were constructed. Six DEGs were predicted to be regulated by DEMs. Subsequently, we validated the negative regulation of family with sequence similarity 84, member A (FAM84A) by miR-215 using a dual-luciferase reporter system. These results provide new insights into the molecular profile of the testis and identify genes that may determine sperm motility in chickens.

Integrated Analysis of miRNA and mRNA Expression Profiles Reveals Functional miRNA-Targets in Development Testes of Small Tail Han Sheep.

Small Tail Han Sheep is a highly valued local breed in China because of their precocity, perennial estrus, and high fecundity. The average annual lambing rate of ewes is as high as 180–270%, the semen of ram has characteristics of high yield, high density, and good motility. To reveal the key miRNAs and miRNA-targets underlying testis development and spermatogenesis in male Small Tail Han Sheep, integrated analysis of miRNA and mRNA expression profiles in 2-, 6-, and 12-month-old testes was performed by RNA-seq technology and bioinformatics methods. The results showed that total of 153 known sheep miRNAs and 2712 novel miRNAs were obtained in 2-,6 - and 12-month-old Small Tail Han Sheep testes; 5, 1, and 4 differentially expressed (DE) known sheep miRNAs, and 132, 105, and 24 DE novel miRNAs were identified in 2- vs. 6-, 6- vs. 12-, and 2- vs. 12-month-old testes, respectively. We combined miRNA results of this study and the mRNA results obtained in our previous study to predict the target mRNAs of DE known sheep miRNAs; 131, 10, and 15 target mRNAs of DE known sheep miRNAs and 76, 1, and 11 DE miRNA–targets were identified in the three groups, respectively. GO and KEGG analyses showed that: in 2- vs. 6-month-olds, the target genes of DE known sheep miRNAs were involved in 100 biological processes and 11 signaling pathways; in 6- vs. 12-month-olds, the target genes of DE known sheep miRNAs were involved in 4 biological processes; and in 2- vs. 12-month-olds, the target genes of DE known sheep miRNAs were involved in 17 biological processes and 4 signaling pathways. Three miR–target regulatory networks were constructed based on these DE miRNA–targets. The key miRNA-Targets involved in testis development and spermatogenesis were screened. 6 known sheep miRNAs and 6 novel miRNAs were selected to validate the accuracy of miRNA sequencing data by qRT-PCR. The binding sites of oar-miR-379-5p with WNT8A was validated by a dual luciferase reporter gene detection system.

Identification of MicroRNA Targets of Capsicum spp. Using MiRTrans-a Trans-Omics Approach.

The microRNA (miRNA) can regulate the transcripts that are involved in eukaryotic cell proliferation, differentiation, and metabolism. Especially for plants, our understanding of miRNA targets, is still limited. Early attempts of prediction on sequence alignments have been plagued by enormous false positives. It is helpful to improve target prediction specificity by incorporating the other data sources such as the dependency between miRNA and transcript expression or even cleaved transcripts by miRNA regulations, which are referred to as trans-omics data. In this paper, we developed MiRTrans (Prediction of MiRNA targets by Trans-omics data) to explore miRNA targets by incorporating miRNA sequencing, transcriptome sequencing, and degradome sequencing. MiRTrans consisted of three major steps. First, the target transcripts of miRNAs were predicted by scrutinizing their sequence characteristics and collected as an initial potential targets pool. Second, false positive targets were eliminated if the expression of miRNA and its targets were weakly correlated by lasso regression. Third, degradome sequencing was utilized to capture the miRNA targets by examining the cleaved transcripts that regulated by miRNAs. Finally, the predicted targets from the second and third step were combined by Fisher's combination test. MiRTrans was applied to identify the miRNA targets for Capsicum spp. (i.e., pepper). It can generate more functional miRNA targets than sequence-based predictions by evaluating functional enrichment. MiRTrans identified 58 miRNA-transcript pairs with high confidence from 18 miRNA families conserved in eudicots. Most of these targets were transcription factors; this lent support to the role of miRNA as key regulator in pepper. To our best knowledge, this work is the first attempt to investigate the miRNA targets of pepper, as well as their regulatory networks. Surprisingly, only a small proportion of miRNA-transcript pairs were shared between degradome sequencing and expression dependency predictions, suggesting that miRNA targets predicted by a single technology alone may be prone to report false negatives.

BayMiR: inferring evidence for endogenous miRNA-induced gene repression from mRNA expression profiles

BackgroundPopular miRNA target prediction techniques use sequence features to determine the functional miRNA target sites. These techniques commonly ignore the cellular conditions in which miRNAs interact with their targets in vivo. Gene expression data are rich resources that can complement sequence features to take into account the context dependency of miRNAs.ResultsWe introduce BayMiR, a new computational method, that predicts the functionality of potential miRNA target sites using the activity level of the miRNAs inferred from genome-wide mRNA expression profiles. We also found that mRNA expression variation can be used as another predictor of functional miRNA targets. We benchmarked BayMiR, the expression variation, Cometa, and the TargetScan “context scores” on two tasks: predicting independently validated miRNA targets and predicting the decrease in mRNA abundance in miRNA overexpression assays. BayMiR performed better than all other methods in both benchmarks and, surprisingly, the variation index performed better than Cometa and some individual determinants of the TargetScan context scores. Furthermore, BayMiR predicted miRNA target sets are more consistently annotated with GO and KEGG terms than similar sized random subsets of genes with conserved miRNA seed regions. BayMiR gives higher scores to target sites residing near the poly(A) tail which strongly favors mRNA degradation using poly(A) shortening. Our work also suggests that modeling multiplicative interactions among miRNAs is important to predict endogenous mRNA targets.ConclusionsWe develop a new computational method for predicting the target mRNAs of miRNAs. BayMiR applies a large number of mRNA expression profiles and successfully identifies the mRNA targets and miRNA activities without using miRNA expression data. The BayMiR package is publicly available and can be readily applied to any mRNA expression data sets.

The majority of endogenous microRNA targets within Alu elements avoid the microRNA machinery

The massive spread of repetitive elements in the human genome presents a substantial challenge to the organism, as such elements may accidentally contain seemingly functional motifs. A striking example is offered by the roughly one million copies of Alu repeats in the genome, of which ∼0.5% reside within genes' untranslated regions (UTRs), presenting ∼30 000 novel potential targets for highly conserved microRNAs (miRNAs). Here, we examine the functionality of miRNA targets within Alu elements in 3'UTRs in the human genome. Using a comprehensive dataset of miRNA overexpression assays, we show that mRNAs with miRNA targets within Alus are significantly less responsive to the miRNA effects compared with mRNAs that have the same targets outside Alus. Using Ago2-binding mRNA profiling, we confirm that the miRNA machinery avoids miRNA targets within Alus, as opposed to the highly efficient binding of targets outside Alus. We propose three features that prevent potential miRNA sites within Alus from being recognized by the miRNA machinery: (i) Alu repeats that contain miRNA targets and genuine functional miRNA targets appear to reside in distinct mutually exclusive territories within 3'UTRs; (ii) Alus have tight secondary structure that may limit access to the miRNA machinery; and (iii) A-to-I editing of Alu-derived mRNA sequences may divert miRNA targets. The combination of these features is proposed to allow toleration of Alu insertions into mRNAs. Nonetheless, a subset of miRNA targets within Alus appears not to possess any of the aforementioned features, and thus may represent cases where Alu insertion in the genome has introduced novel functional miRNA targets. Supplementary data are available at Bioinformatics online.

Identification of Novel Targets for miR-29a Using miRNA Proteomics

MicroRNAs (miRNAs) are short regulatory RNA molecules that interfere with the expression of target mRNA by binding to complementary sequences. Currently, the most common method for identification of targets of miRNAs is computational prediction based on free energy change calculations, target site accessibility and conservation. Such algorithms predict hundreds of targets for each miRNA, necessitating tedious experimentation to identify the few functional targets. Here we explore the utility of miRNA-proteomics as an approach to identifying functional miRNA targets. We used Stable Isotope Labeling by amino acids in cell culture (SILAC) based proteomics to detect differences in protein expression induced by the over-expression of miR-34a and miR-29a. Over-expression of miR-29a, a miRNA expressed in the brain and in cells of the blood lineage, resulted in the differential expression of a set of proteins. Gene Ontology based classification showed that a significant sub-set of these targets, including Voltage Dependent Anion Channel 1 and 2 (VDAC1 and VDAC2) and ATP synthetase, were mitochondrial proteins involved in apoptosis. Using reporter assays, we established that miR-29a targets the 3′ Untranslated Regions (3′ UTR) of VDAC1 and VDAC2. However, due to the limited number of proteins identified using this approach and the inability to differentiate between primary and secondary effects we conclude that miRNA-proteomics is of limited utility as a high-throughput alternative for sensitive and unbiased miRNA target identification. However, this approach was valuable for rapid assessment of the impact of the miRNAs on the cellular proteome and its biological role in apoptosis.

MiRNA-dependent gene silencing involving Ago2-mediated cleavage of a circular antisense RNA

MicroRNAs (miRNAs) are ∼22 nt non-coding RNAs that typically bind to the 3' UTR of target mRNAs in the cytoplasm, resulting in mRNA destabilization and translational repression. Here, we report that miRNAs can also regulate gene expression by targeting non-coding antisense transcripts in human cells. Specifically, we show that miR-671 directs cleavage of a circular antisense transcript of the Cerebellar Degeneration-Related protein 1 (CDR1) locus in an Ago2-slicer-dependent manner. The resulting downregulation of circular antisense has a concomitant decrease in CDR1 mRNA levels, independently of heterochromatin formation. This study provides the first evidence for non-coding antisense transcripts as functional miRNA targets, and a novel regulatory mechanism involving a positive correlation between mRNA and antisense circular RNA levels.

Target site effects in the RNA interference and microRNA pathways

In RNAi (RNA interference), siRNAs (small interfering RNAs) are loaded into the RISC (RNA-induced silencing complex), which then mediates endonucleolytic cleavage of complementary target RNAs. Although RNAi has become one of the most powerful tools in molecular biology to assess gene function, there remains a great number of ineffective siRNAs. It is already known that the assembly and activation of RISC is a crucial determinant of RNAi activity, but downstream effects such as target accessibility have not been analysed extensively. Therefore we assessed the effect of target site accessibility and found that it significantly improves the potency of siRNAs. Similarly, miRNAs (microRNAs) act by repressing protein synthesis through imperfect base-pairing to the 3'-UTR (untranslated region) of target mRNAs. We found that predicted target sites reside in regions of high accessibility and tested whether this criterion could be used in the search of functional miRNA targets. In addition, we performed reporter gene assays to test whether accessibility correlates with measured mRNA suppression levels. The results of our initial study suggest that secondary structures might add a so far underrepresented layer of complexity in the recognition of RNA targets by miRNAs.

Isolation of microRNA targets by miRNP immunopurification

microRNAs (miRNAs) serve as post-transcriptional regulators of gene expression, by guiding effector complexes (miRNPs) to target RNAs. Although considerable progress has been made in computational methods to identify miRNA targets, only a relatively limited assessment of their ability to function in vivo has been reported. Here we describe an alternative approach to miRNA target identification based on a biochemical method for purifying miRNP complexes with associated miRNAs and bound mRNA targets. Microarray analysis revealed a high degree of enrichment for miRNA complementary sites in the 3'UTRs of the miRNP-associated mRNAs. mRNAs specifically associated with an individual miRNA were identified by comparing the miRNP-associated mRNAs from wild-type flies and mutant flies lacking miR-1, and their regulation by the miRNA was validated. This approach provides a means to identify functional miRNA targets based on their physical interaction in vivo.

Bayesian Inference of MicroRNA Targets from Sequence and Expression Data

MicroRNAs (miRNAs) regulate a large proportion of mammalian genes by hybridizing to targeted messenger RNAs (mRNAs) and down-regulating their translation into protein. Although much work has been done in the genome-wide computational prediction of miRNA genes and their target mRNAs, an open question is how to efficiently obtain functional miRNA targets from a large number of candidate miRNA targets predicted by existing computational algorithms. In this paper, we propose a novel Bayesian model and learning algorithm, GenMiR++ (Generative model for miRNA regulation), that accounts for patterns of gene expression using miRNA expression data and a set of candidate miRNA targets. A set of high-confidence functional miRNA targets are then obtained from the data using a Bayesian learning algorithm. Our model scores 467 high-confidence miRNA targets out of 1,770 targets obtained from TargetScanS in mouse at a false detection rate of 2.5%: several confirmed miRNA targets appear in our high-confidence set, such as the interactions between miR-92 and the signal transduction gene MAP2K4, as well as the relationship between miR-16 and BCL2, an anti-apoptotic gene which has been implicated in chronic lymphocytic leukemia. We present results on the robustness of our model showing that our learning algorithm is not sensitive to various perturbations of the data. Our high-confidence targets represent a significant increase in the number of miRNA targets and represent a starting point for a global understanding of gene regulation.

L(ou)sy miRNA targets?

MicroRNAs (miRNAs) are noncoding small RNAs thought to post-transcriptionally regulate many metazoan genes by binding to partially complementary sites in target messenger RNAs. In this issue, Didiano and Hobert examine known and predicted targets of the nematode lsy-6 miRNA, question the general validity of previously proposed rules about miRNA-target interactions and suggest that many functional miRNA targets might be context dependent, as seen in metazoan gene regulation by transcription factors.