microRNA-target Pairs Research Articles

O-137 Mapping microRNA profiling and dysregulated pathways in non-obstructive azoospermia cases with maturation arrest: A systematic review and in-silico analysis of the affected pathways

Abstract Study question Could microRNA profiling be a useful tool towards better understanding the pathophysiological mechanisms leading to non-obstructive azoospermia (NOA) due to maturation arrest? Summary answer MicroRNA profiling may be an efficient method towards unveiling maturation arrest pathophysiology as microRNAs constitute master posttranscriptional regulators of cell-cycle control during spermatogenesis. What is known already Non-obstructive azoospermia constitutes the most severe form of male factor infertility, affecting approximately 10% of infertile men. According to the histological subtype, NOA is classified into three main categories namely hypospermatogenesis, maturation arrest, and Sertoli-cell only syndrome. Maturation arrest is one of the most complex forms of NOA characterized by failure of spermatogenesis. Despite advances, the pathophysiology of maturation arrest remains a conundrum rendering management complex. Recent studies indicate that alterations on microRNA expression patterns could lead to maturation arrest. Mapping microRNA profiling and highlighting dysregulated pathways of maturation arrest cases may lead the way forward. Study design, size, duration A systematic review was performed in PubMed/Medline and Embase up to April 2022. Only full-length original studies in humans were included. Strict inclusion-exclusion criteria were applied aiming to isolate studies comparing microRNA profiling between maturation arrest cases versus normal fertile men, and/or men with obstructive azoospermia (OA). Following study selection, data on altered microRNA expression patterns were analyzed to underline differences between the abovementioned groups. Subsequently, in-silico analysis was performed to compare affected gene pathways. Participants/materials, setting, methods The studied population consisted of maturation arrest cases. Control groups consisted of men with normal spermatogenesis and/or men with OA. Predicted microRNA–target pairs were retrieved from microT-CDS, while a 0.8 cutoff threshold was applied. The GTEx repository was used to identify microRNA-targeted genes in the testis. Annotations derived from Ensembl and miRbase. Gene-set enrichment analysis was performed employing the KEGG-database. Fisher’s exact test was performed in R package limma, setting a 0.01 p-value threshold. Main results and the role of chance Ten studies reported altered microRNA expression patterns in maturation arrest versus normal spermatogenesis cases and six studies in maturation arrest versus OA cases. Considering the maturation arrest-normal spermatogenesis arm, analysis revealed that eight microRNAs, which were upregulated in maturation arrest cases, namely hsa-miR-449a, hsa-miR-370-3p, hsa-miR-10b-3p, hsa-miR-539-5p, hsa-miR-22-5p, hsa-miR-605-5p, hsa-miR-491-3p and hsa-miR-302d-3p, affected 106 statistically significant gene-targets in the testis. The three most significantly affected pathways included the “microRNAs in cancer” pathway (55 affected genes, p-value <0.001), the “EGFR tyrosine kinase inhibitor resistance pathway” (29 affected genes, p-value = 0.007), and the “Hedgehog signaling pathway” (22 affected genes, p-value=0.008). Regarding the second arm of maturation arrest-OA, functional analysis indicated that four microRNAs, presenting to be downregulated in maturation arrest cases, namely hsa-miR-181a-5p, hsa-miR-449a, hsa-miR-182-5p and hsa-miR-138-5p, affected 421 statistically significant gene-targets in testis. The three most significantly affected pathways included the “pathways in cancer” pathway (86 affected genes, p-value =0.009), the “microRNAs in cancer” pathway (48 affected genes, p-value < 0.001), and the “ cGMP-PKG signaling” pathway (36 affected genes, p-value=0.008). In summary, microRNAs affect the expression of master genes regulating cell-cycle and maturation processes during spermatogenesis, leading to maturation arrest as well as to other associated pathologies, including cancer. Limitations, reasons for caution The limited number of the included studies, as well as the small size population characterizing the great majority of them, constitute the main limitations of this study. Another reason for caution is the great heterogeneity observed among the studies regarding the molecular methods employed for microRNA profiling. Wider implications of the findings Data presented herein indicate that microRNA functional analysis may be a significant tool towards better understanding the pathophysiological basis of spermatogenesis maturation arrest, indicating future personalized diagnostic and therapeutic targets. Moreover, microRNA analysis may also constitute an efficient method of evaluating predisposition of NOA patients to other pathologies including cancer. Trial registration number Not applicable

P-099 Alterations in microRNA expression profiles may be implicated in increased prevalence of cancer in Sertoli cell-only syndrome cases: A systematic review and in-silico analysis

Abstract Study question Could microRNA dysregulation be an underlying molecular mechanism leading to the observed increased prevalence of cancer in patients with Sertoli-cell only syndrome (SCOS)? Summary answer Patients with SCOS are characterized by altered microRNA profiles and dysregulated gene pathways involved in SCOS pathophysiology and in cell-cycle control and therefore in carcinogenesis. What is known already Sertoli cell-only syndrome constitutes a histopathological subtype of non-obstructive azoospermia, affecting 26.3–57.8% of azoospermia patients. It is characterized by partial or complete absence of active spermatogenesis due to germ cell aplasia. Except from infertility, SCOS is associated with increased risk of testicular nodules and cancer, rendering research on the topic essential. Despite advances, the underlying molecular mechanisms connecting SCOS with cancer remain unknown. Data demonstrates that microRNAs could play crucial roles in both SCOS pathophysiology and carcinogenesis. Identifying relevant microRNAs and conducting in-silico analysis on affected pathways may lead to mapping the way forward. Study design, size, duration A systematic review was performed in PubMed/Medline and Embase up to April 2022. Only full-length original studies in humans were included. Strict inclusion-exclusion criteria were applied aiming to select studies comparing microRNA profiling between SCOS cases versus men with normal spermatogenesis or men with proven fertility. Following study selection, data on altered microRNA expression patterns were analyzed to underline differences between the abovementioned groups. Subsequently, in-silico functional analysis was performed to compare affected gene pathways. Participants/materials, setting, methods The studied population consisted of SCOS cases. Men with normal spermatogenesis or proven fertility served as the control group. Predicted microRNA–target pairs were retrieved from microT-CDS, while a 0.8 cutoff threshold was applied. The GTEx repository was used to identify microRNA-targeted genes in the testis. Annotations derived from Ensembl and miRbase. Gene-set enrichment analysis was performed employing the KEGG-database. Fisher’s exact test was performed in R package limma, setting a 0.01 p-value threshold. Main results and the role of chance Four studies reported altered microRNA expression profiles in SCOS (n = 45) versus normal spermatogenesis cases or men of proven fertility (n = 16). Functional analysis revealed that six microRNAs, which were downregulated in the SCOS cases, namely hsa-miR-34b-5p, hsa-miR-202-3p, hsa-miR-34c-5p, hsa-miR-449a, hsa-miR-141-3p, and hsa-miR-34b-3p, affected 66 statistically significant gene-targets in the testis. Two pathways were reported to be statistically significantly dysregulated from these microRNAs, namely the ‘’microRNAs in cancer’’ pathway (40 affected genes, p-value = 0.004), and the ‘’TGF-beta signaling’’ pathway (26 affected genes, p-value = 0.01). Furthermore, four microRNAs, namely hsa-miR-10b-5p, hsa-miR-4270, hsa-miR-181c-5p, and hsa-miR-605-3p, reported to be upregulated in the SCOS group. These microRNAs had 108 statistically significant gene-targets in the testis. Three pathways were statistically significantly dysregulated from these microRNAs, namely the ‘’Herpes simplex virus 1 infection’’ pathway (61 affected genes, p-value = 0.01), the ‘’microRNAs in cancer’’ pathway (28 affected genes, p-value = 0.01), and the ‘’longevity regulating’’ pathway (19 affected genes, p-value = 0.01). The molecular role of the affected gene pathways in proper cell-cycle regulation and germ cell differentiation is herein underlined as critical. In the disrupted testicular microenvironment of the SCOS cases these disrupted genes may act as inducers of carcinogenic mechanisms. Limitations, reasons for caution The main limitation is the small number of the included studies and the small number of participants investigated per study, especially with regards to the control group. Moreover, the observed heterogeneity among the studies regarding the molecular tools employed for the microRNA profiling is another reason for caution. Wider implications of the findings Our data suggest that the dysregulation of microRNAs affecting several gene pathways that control cell-cycle and differentiation may lead to increased cancer risk in SCOS cases. Further studies employing our findings as a starting point will indicate whether microRNA profiling can serve as an effective evaluation tool for cancer predisposition. Trial registration number Not applicable

Identification of Sex Differentiation-Related microRNAs in Spinach Female and Male Flower.

Sex determination and differentiation is an important biological process for unisexual flower development. Spinach is a model plant to study the mechanism of sex determination and differentiation of dioecious plant. Till now, little is known about spinach sex determination and differentiation mechanism. MicroRNAs are key factors in flower development. Herein, small RNA sequencing was performed to explore the roles of microRNAs in spinach sex determination and differentiation. As a result, 92 known and 3402 novel microRNAs were identified in 18 spinach female and male flower samples. 74 differentially expressed microRNAs were identified between female and male flowers, including 20 female-biased and 48 male-biased expression microRNAs. Target prediction identified 22 sex-biased microRNA-target pairs, which may be involved in spinach sex determination or differentiation. Among the differentially expressed microRNAs between FNS and M03, 55 microRNAs were found to reside in sex chromosome; one of them, sol-miR2550n, was functionally studied via genetic transformation. Silencing of sol-miR2550n resulted in abnormal anther while overexpression of sol-miR2550n induced early flowering, indicating sol-miR2550n was a male-promoting factor and validating the reliability of our small RNA sequencing data. Conclusively, this work can supply valuable information for exploring spinach sex determination and differentiation and provide a new insight in studying unisexual flower development.

Transcriptome-wide identification of microRNAs and functional insights inferred from microRNA—target pairs in Physalis angulata L

ABSTRACTPhysalis angulata L., a member of the family Solanaceae, is widely used as the folk medicine in various countries. Continuous research efforts are devoted to the discovery of the effective medicinal ingredients from Physalis angulata. However, due to the limited resources of genome and transcriptome sequencing data, only a few studies have been performed at the gene regulatory level. In this study, the transcriptomes of five organs (roots, stems, leaves, flowers and fruits) of Physalis angulata were reported. Based on the transcriptome assembly containing 196,117 unique transcripts, a total of 17,556 SSRs (simple sequence repeats) were identified, which could be useful RNA-based barcoding for discrimination of the plants closely relative to Physalis angulata. Additionally, 24 transcripts were discovered to be the potential microRNA (miRNA) precursors which encode a total of 31 distinct mature miRNAs. Some of these precursors showed organ-specific expression patterns. Target prediction revealed 116 miRNA–target pairs, involving 31 miRNAs and 83 target transcripts in Physalis angulata. Taken together, our results could serve as the data resource for in-depth studies on the molecular regulatory mechanisms related to the production of medicinal ingredients in Physalis angulata.

MicroRNA expression profiling and bioinformatics analysis of dysregulated microRNAs in obstructive sleep apnea patients.

Obstructive sleep apnea (OSA) is a common chronic obstructive sleep disease in clinic. The purpose of our study was to use bioinformatics analysis to identify microRNAs (miRNAs) that are differentially expressed between OSA patients and healthy controls.Serum samples were collected from OSA patients and healthy controls. To better reveal the sample specificity of differentially expressed microRNAs, supervised hierarchical clustering was conducted. We used the microT-CDS and TargetScan databases to predict target genes of the differentially expressed microRNAs and selected the common genes. The Search Tool for the Retrieval of Interacting Genes (STRING) was used to evaluate many coexpression relationships. Moreover, we used these potential microRNA-target pairs and coexpression relationships to construct a regulatory coexpression network using Cytoscape software. Functional analysis of microRNA target genes was conducted with FunRich.A total of 104 microRNAs that were differentially expressed between OSA patients and healthy controls were identified. Supervised hierarchical clustering was conducted based on the expression of the 104 microRNAs in the OSA patients and healthy controls. Overall, 6621 potential target genes were predicted, and 119 target genes were screened based on coexpression coefficients in the STRING database. A regulatory coexpression network was constructed that included 23 differentially expressed microRNAs and 18 of the most related potential target genes. Metabolic signaling pathways were the most highly enriched category. Differentially expressed microRNAs, such as hsa-miR-485-5p, hsa-miR-107, hsa-miR-574-5p, and hsa-miR-199-3p, might participate in OSA. The target gene CAD might also be closely related to OSA.Our results may provide a basis for the pathogenesis of OSA and the study of disease diagnosis, prevention, and treatment. However, more experiments are needed to verify these predictions.

Evolutionary Transitions of MicroRNA-Target Pairs.

How newly generated microRNA (miRNA) genes are integrated into gene regulatory networks during evolution is fundamental in understanding the molecular and evolutionary bases of robustness and plasticity in gene regulation. A recent model proposed that after the birth of a miRNA, the miRNA is generally integrated into the network by decreasing the number of target genes during evolution. However, this decreasing model remains to be carefully examined by considering in vivo conditions. In this study, we therefore compared the number of target genes among miRNAs with different ages, combining experiments with bioinformatics predictions. First, we focused on three Drosophila miRNAs with different ages. As a result, we found that an older miRNA has a greater number of target genes than a younger miRNA, suggesting the increasing number of targets for each miRNA during evolution (increasing model). To further confirm our results, we also predicted all target genes for all miRNAs in D. melanogaster, considering co-expression of miRNAs and mRNAs in vivo. The results obtained also do not support the decreasing model but are reasonably consistent with the increasing model of miRNA-target pairs. Furthermore, our large-scale analyses of currently available experimental data of miRNA-target pairs also showed a weak but the same trend in humans. These results indicate that the current decreasing model of miRNA-target pairs should be reconsidered and the increasing model may be more appropriate to explain the evolutionary transitions of miRNA-target pairs in many organisms.

Improving microRNA target prediction by modeling with unambiguously identified microRNA-target pairs from CLIP-ligation studies.

MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in many physiological and disease processes. One major challenge in miRNA studies is the identification of genes targeted by miRNAs. Currently, most researchers rely on computational programs to initially identify target candidates for subsequent validation. Although considerable progress has been made in recent years for computational target prediction, there is still significant room for algorithmic improvement. Here, we present an improved target prediction algorithm, which was developed by modeling high-throughput profiling data from recent CLIPL (crosslinking and immunoprecipitation followed by RNA ligation) sequencing studies. In these CLIPL-seq studies, the RNA sequences in each miRNA-target pair were covalently linked and unambiguously determined experimentally. By analyzing the CLIPL data, many known and novel features relevant to target recognition were identified and then used to build a computational model for target prediction. Comparative analysis showed that the new algorithm had improved performance over existing algorithms when applied to independent experimental data. All the target prediction data as well as the prediction tool can be accessed at miRDB (http://mirdb.org). xwang@radonc.wustl.edu.

Abstract P640: Endogenous microRNAs in Human Microvascular Endothelial Cells Regulate mRNAs Encoded by Hypertension-Related Genes and Are Functionally Important

Relatively few miRNA-target pairs have been shown to be involved in hypertension or physiological processes related to blood pressure regulation. The goal of the present study was to systematically identify endogenous microRNAs in endothelial cells that regulate mRNAs encoded by genes relevant to hypertension. Small RNA deep sequencing was performed in cultured human microvascular endothelial cells (HMVEC-D) to identify abundant miRNAs. Of the 50 most abundant microRNAs identified, 30 had predicted target mRNAs encoded by genes with known involvement in hypertension or blood pressure regulation. HMVEC-D were transfected with anti-miR oligonucleotides to inhibit each of the 30 microRNAs and the mRNA abundance of predicted targets was measured by qRT-PCR. Of 95 microRNA-target pairs examined, the target mRNAs were significantly up-regulated in 35 pairs and paradoxically down-regulated in 8 pairs. The functional relevance of miRNAs targeting JAG1 (miR-21-5p) and NOX4 (miR-92a-3p, miR-92b-3p, miR-100-5p, and miR-99b-5p), was tested in in vivo and in vitro models, respectively. Blood pressure was measured with radiotelemetry in C57BL/6J mice receiving LNA anti-miR-21 or scrambled LNA anti-miR (n=4/group; 10mg/kg; i.p.). LNA anti-miR-21 induced a transient increase in arterial pressure in mice fed a 0.4% NaCl diet, but a significant and sustained reduction of 24 hour averaged mean arterial pressure on a 4.0% NaCl diet, reaching 96.3 ± 4.0 mmHg compared to 105.3 ± 1.6 mmHg (mean ± SEM) in mice treated with scrambled anti-miR (p<0.05). The release of H 2 O 2 from HMVEC-D was measured by Amplex Red assay 48 hours after transfection with anti-miRs identified to increase NOX4 mRNA abundance or scrambled anti-miR (n=6-12/group). The release of H 2 O 2 from HMVEC-D was significantly increased following transfection of anti-miRs for miR-92a-3p, miR-92b-3p, miR-99b-5p, and miR-100b-5p by 82.2% to 139.6%. These findings indicate widespread, tonic control of mRNA abundance of genes relevant to blood pressure regulation by endothelial microRNAs that are functionally significant.

Regulation of Hypertension‐Related Genes by Endogenous microRNAs in Human Microvascular Endothelial Cells

The goal of the present study was to systematically identify endogenous microRNAs in human vascular endothelial cells that regulate genes related to hypertension or blood pressure regulation. Small RNA deep sequencing was performed to identify the 30 most abundant microRNAs in cultured human microvascular endothelial cells. Each of the 30 microRNAs was knocked down using anti-miR oligonucleotides, and the abundance of up to 9 predicted target genes known to be related to hypertension or blood pressure regulation was examined for each microRNA. Of 93 microRNA-target pairs examined, the target genes were significantly up-regulated in 35 pairs in response to microRNA knockdown and paradoxically down-regulated in 7 pairs. The result indicated significant suppression of the expression of FGF5 by the endogenous let-7 family in human endothelial cells, GOSR2 by miR-27a-3p, JAG1 by miR-21-5p, SH2B3 by miR-30a-5p, miR-98, miR-181a-5p, and the miR-125 family, ADM by miR-181a-5p, miR-26a-5p, and the miR-92 family, ADRA1B by miR-22-3p, CAT by miR-30a, EDNRB by the miR-92 family, Furin by miR-125a-5p, NOX4 by the miR-92 family, miR-100-5p, and miR-99b-5p, TBX3 by miR-92 family and miR-100-5p, ATP2B1 by miR-27b-5p, ADRA2A by miR-30a-5p and miR-30e-5p, and ADRA2B by miR-30e-5p, miR-181a-5p, and miR-181b-5p (n=3-9, P<0.05 vs. scrambled anti-miR). The study has identified several microRNAs that play a tonic role in regulating the expression of hypertension-related genes in human microvascular endothelial cells. Support R01 HL121233, P01 HL082798-6186, and 8UL1TR000055

Identification of potential microRNA–target pairs associated with osteopetrosis by deep sequencing, iTRAQ proteomics and bioinformatics

MicroRNAs aberrantly express in many human diseases including some metabolic bone disorders. They have been found to be associated with osteoclast differentiation and function, which makes them attractive candidates for the therapy of bone. However, the potential clinical application of microRNAs in therapeutics rests heavily upon our in-depth understanding of microRNAs and their targets. To identify potential microRNA-target pairs associated with osteopetrosis, we performed a system approach including deep sequencing, iTRAQ quantitative proteomics, and bioinformatics in the peripheral blood mononuclear cells (PBMCs) taken from patients with osteopetrosis and health donors. Notably, 123 differently expressed microRNAs, 173 differently expressed proteins, and 117 computationally predicted microRNA-target pairs with reciprocally expressed level in PBMCs were found in the two sample groups. Functional annotation identified that the microRNA-target pairs were involved in cell growth, differentiation, cellular signaling network, and the network highlighted the microRNA-target pair of has-miR-320a and ADP ribosylation factor 1 (Arf1) potentially associated with CLCN7 mutations in osteopetrosis. The pair of has-miR-320a and Arf1 was further verified by real-time PCR, western blot, and the interaction between has-miR-320a and its targeted sequence on the Arf1 mRNAs was confirmed by luciferase assay. Collectively, the present study established a new system approach for the investigation of microRNAs, and the microRNA-target pairs, particular has-miR-320a and Arf1, may have important roles in osteopetrosis.

RFMirTarget: Predicting Human MicroRNA Target Genes with a Random Forest Classifier

MicroRNAs are key regulators of eukaryotic gene expression whose fundamental role has already been identified in many cell pathways. The correct identification of miRNAs targets is still a major challenge in bioinformatics and has motivated the development of several computational methods to overcome inherent limitations of experimental analysis. Indeed, the best results reported so far in terms of specificity and sensitivity are associated to machine learning-based methods for microRNA-target prediction. Following this trend, in the current paper we discuss and explore a microRNA-target prediction method based on a random forest classifier, namely RFMirTarget. Despite its well-known robustness regarding general classifying tasks, to the best of our knowledge, random forest have not been deeply explored for the specific context of predicting microRNAs targets. Our framework first analyzes alignments between candidate microRNA-target pairs and extracts a set of structural, thermodynamics, alignment, seed and position-based features, upon which classification is performed. Experiments have shown that RFMirTarget outperforms several well-known classifiers with statistical significance, and that its performance is not impaired by the class imbalance problem or features correlation. Moreover, comparing it against other algorithms for microRNA target prediction using independent test data sets from TarBase and starBase, we observe a very promising performance, with higher sensitivity in relation to other methods. Finally, tests performed with RFMirTarget show the benefits of feature selection even for a classifier with embedded feature importance analysis, and the consistency between relevant features identified and important biological properties for effective microRNA-target gene alignment.

MicroRNA-target pairs in human renal epithelial cells treated with transforming growth factor β1: a novel role of miR-382

We reported previously an approach for identifying microRNA (miRNA)-target pairs by combining miRNA and proteomic analyses. The approach was applied in the present study to examine human renal epithelial cells treated with transforming growth factor β1 (TGFβ1), a model of epithelial–mesenchymal transition important for the development of renal interstitial fibrosis. Treatment of human renal epithelial cells with TGFβ1 resulted in upregulation of 16 miRNAs and 18 proteins and downregulation of 17 miRNAs and 16 proteins. Of the miRNAs and proteins that exhibited reciprocal changes in expression, 77 pairs met the sequence criteria for miRNA–target interactions. Knockdown of miR-382, which was up-regulated by TGFβ1, attenuated TGFβ1-induced loss of the epithelial marker E-cadherin. miR-382 was confirmed by 3′-untranslated region reporter assay to target five genes that were downregulated at the protein level by TGFβ1, including superoxide dismutase 2 (SOD2). Knockdown of miR-382 attenuated TGFβ1-induced downregulation of SOD2. Overexpression of SOD2 ameliorated TGFβ1-induced loss of the epithelial marker. The study provided experimental evidence in the form of reciprocal expression at the protein level for a large number of predicted miRNA-target pairs and discovered a novel role of miR-382 and SOD2 in the loss of epithelial characteristics induced by TGFβ1.

MicroRNAs and their targets from Arabidopsis to rice: half conserved and half diverged

MicroRNAs are 21to 24-nucleotide long, endogenous non-coding RNAs in eukaryotes (Hannon, 2002). Mature microRNAs generated by Dicer are incorporated into an RNA-induced silencing complex (RISC), resulting in gene silencing via the cleavage of a target mRNA or the repression of target mRNA translation (Qi et al, 2005). Thus, microRNAs play a key role in post-transcriptional gene silencing, and microRNA-based gene silencing pathways are critical in developmental regulation, biotic and abiotic adaptations, and hormone responses in plants (Baulcombe, 2004; Jones-Rhoades et al., 2006). In microRNA-based gene silencing, the microRNAtarget mRNA pair determines the specificity of the biological effect. Hundreds of microRNAs have been identified in plants by cloning and deep genomic sequencing (Griffiths-Jones et al., 2008). Thus, a key step in determining the biological function of a microRNA is to identify its target. However, our knowledge of microRNA targets is incomplete due to limitations imposed by the methods used to identify microRNA targets. Traditionally, microRNA targets have been identified from computational predictions based on sequence matching between a microRNA and its target mRNA (Rhoades et al., 2002). Thus, a new approach is needed to facilitate the identification of microRNA targets on a global scale. Degradome sequencing is a new approach that integrates high-throughput sequencing, experimental approaches, and bioinformatic analyses (German et al., 2009). More than 100 microRNA targets in Arabidopsis have been isolated using this method (Addo-Quaye et al., 2008; German et al., 2008), suggesting that degradome sequencing is a powerful tool for microRNA-target pair identification. The isolation and experimental validation of microRNAtarget pairs from the monocot model plant rice using a degradome sequencing approach was reported in this issue by Dr. Xiaofeng Cao’s group (Zhou et al., 2010). They identified 177 mRNAs that were targeted by 87 unique microRNAs (Zhou et al., 2010). Among them, microRNAs known to be conserved in the plant kingdom targeted about half of the identified target mRNAs, and, interestingly, about 70% of the target mRNAs encoded transcription factors (Zhou et al., 2010). One example is the mi156SBP-box gene mRNA pair (Fig. 1A). The Arabidopsis genome encodes thirteen SBP-box genes (SPLs), ten of which are mi156 targets (Schwab et al., 2005; Wu et al., 2009; Wang et al., 2009). The mi156-SPL pathway regulates the vegetative-phase transition, flowering, leaf initiation, and apical dominance in Arabidopsis (Schwab et al., 2005; Wu et al., 2009; Wang et al., 2009). Consistent with the microRNA-target of the mi156-SPL mRNA pairs in Arabidopsis, eleven SPL mRNAs are mi156 targets in rice (Zhou et al., 2010). These conserved microRNA-target pairs may represent common regulatory nodes for the regulation of fundamental developmental processes and responses to environmental signals in the plant kingdom. The second half of the identified target genes were found to be targeted by non-conserved microRNAs (Zhou et al., 2010). These non-conserved microRNA-target pairs may be involved in riceor grass-specific processes or responses, such as osa-miR528/Os0738290 interaction (Fig. 1B). Interestingly, a large proportion of the nonconserved microRNAs targeted the 5’or 3’-untranslated region of their target mRNAs (Zhou et al., 2010). Thus, these non-conserved microRNAs may regulate gene expression via manners other than mRNA cleavage, and translational repression by microRNAs is more common in rice than in Arabidopsis. Therefore, rice is a better model than Arabidopsis to use in determining the mechanism of microRNA-mediated translational repression in plants. What will be the next step after this useful and much needed atlas of microRNA-target interactions is completed? First, it will be possible to address the biological functions of microRNA-target transcript pairs in rice. The genetic manipulation of microRNA-mRNA pairs in planta Received December 19, 2009; accepted December 23, 2009

Genome-wide survey of rice microRNAs and microRNA–target pairs in the root of a novel auxin-resistant mutant

Auxin is one of the central hormones in plants, and auxin response factor (ARF) is a key regulator in the early auxin response. MicroRNAs (miRNAs) play an essential role in auxin signal transduction, but knowledge remains limited about the regulatory network between miRNAs and protein-coding genes (e.g. ARFs) involved in auxin signalling. In this study, we used a novel auxin-resistant rice mutant with plethoric root defects to investigate the miRNA expression patterns using microarray analysis. A number of miRNAs showed reduced auxin sensitivity in the mutant compared with the wild type, consistent with the auxin-resistant phenotype of the mutant. Four miRNAs with significantly altered expression patterns in the mutant were further confirmed by Northern blot, which supported our microarray data. Clustering analysis revealed some novel auxin-sensitive miRNAs in roots. Analysis of miRNA duplication and expression patterns suggested the evolutionary conservation between miRNAs and protein-coding genes. MiRNA promoter analysis suggested the possibility that most plant miRNAs might share the similar transcriptional mechanisms with other non-plant eukaryotic genes transcribed by RNA polymerase II. Auxin response elements were proved to be more frequently present in auxin-related miRNA promoters. Comparative analysis of miRNA and protein-coding gene expression datasets uncovered many reciprocally expressed miRNA-target pairs, which could provide some hints for miRNA downstream analysis. Based on these findings, we also proposed a feedback circuit between miRNA(s) and ARF(s). The results presented here could serve as the basis for further in-depth studies of plant miRNAs involved in auxin signalling.

MicroRNA expression pattern in different stages of nonalcoholic fatty liver disease

To explore the unique microRNA expression pattern of nonalcoholic fatty liver disease in a rat model, and search for targets of certain dysregulated microRNAs. Microarray and stem-loop RT-PCR were utilized to detect dysregulated microRNAs in a rat model. Significance Analysis of Microarray, Prediction Analysis of Microarray and clustering analysis were implemented to calculate significantly aberrantly expressed microRNAs. TargetScan, miRanda and PicTar were jointly used to predict targets of microRNAs. Confirmed by Significance Analysis of Microarray and predicted by Prediction Analysis of Microarray, portfolios of 27 and 21 microRNAs were selected as an accurate molecular signature in distinguishing steatosis and steatohepatitis from normal rat liver. Besides, a panel of microRNA-target pairs that may be involved in lipid and glucose metabolism and inflammation process was delineated. This is by far the first report on the dysregulated microRNAs expression pattern in nonalcoholic fatty liver disease. The successful differentiation of steatosis and steatohepatitis from normal liver hints to the potential of using lists of dysregulated microRNAs for diagnosis, though many problems need to be solved. Besides, these data will guide further studies of the contribution of microRNAs to the pathogenesis of nonalcoholic fatty liver disease while disease-specific microRNAs might become potential targets for therapeutic intervention.

MicroRNA-target pairs in the rat kidney identified by microRNA microarray, proteomic, and bioinformatic analysis.

Mammalian genomes contain several hundred highly conserved genes encoding microRNAs. In silico analysis has predicted that a typical microRNA may regulate the expression of hundreds of target genes, suggesting miRNAs might have broad biological significance. A major challenge is to obtain experimental evidence for predicted microRNA-target pairs. We reasoned that reciprocal expression of a microRNA and a predicted target within a physiological context would support the presence and relevance of a microRNA-target pair. We used microRNA microarray and proteomic techniques to analyze the cortex and the medulla of rat kidneys. Of the 377 microRNAs analyzed, we identified 6 as enriched in the renal cortex and 11 in the renal medulla. From approximately 2100 detectable protein spots in two-dimensional gels, we identified 58 proteins as more abundant in the renal cortex and 72 in the renal medulla. The differential expression of several microRNAs and proteins was verified by real-time PCR and Western blot analyses, respectively. Several pairs of reciprocally expressed microRNAs and proteins were predicted to be microRNA-target pairs by TargetScan, PicTar, or miRanda. Seven pairs were predicted by two algorithms and two pairs by all three algorithms. The identification of reciprocal expression of microRNAs and their computationally predicted targets in the rat kidney provides a unique molecular basis for further exploring the biological role of microRNA. In addition, this study establishes a differential profile of microRNA expression between the renal cortex and the renal medulla and greatly expands the known differential proteome profiles between the two kidney regions.