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MicroRNAs (miRNAs) are a class of important small non-coding RNAs with critical molecular functions in almost all biological processes, and thus, they play important roles in disease diagnosis and therapy. Human MicroRNA Disease Database (HMDD) represents an important and comprehensive resource for biomedical researchers in miRNA-related medicine. Here, we introduce HMDD v4.0, which curates 53530 miRNA-disease association entries from literatures. In comparison to HMDD v3.0 released five years ago, HMDD v4.0 contains 1.5 times more entries. In addition, some new categories have been curated, including exosomal miRNAs implicated in diseases, virus-encoded miRNAs involved in human diseases, and entries containing miRNA-circRNA interactions. We also curated sex-biased miRNAs in diseases. Furthermore, in a case study, disease similarity analysis successfully revealed that sex-biased miRNAs related to developmental anomalies are associated with a number of human diseases with sex bias. HMDD can be freely visited at http://www.cuilab.cn/hmdd., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Abdominal aortic aneurysm (AAA) is a permanent dilatation of the abdominal aorta and is highly lethal. The main purpose of the current study is to search for noninvasive medical therapies for AAA, for which there is currently no effective drug therapy. Network medicine represents a cutting-edge technology, as analysis and modeling of disease networks can provide critical clues regarding the etiology of specific diseases and therapeutics that may be effective. Here, we proposed a novel algorithm to quantify disease relations based on a large accumulated microRNA-disease association dataset and then built a disease network covering 15 disease classes and 304 diseases. Analysis revealed some patterns for these diseases. For instance, diseases tended to be clustered and coherent in the network. Surprisingly, we found that AAA showed the strongest similarity with rheumatoid arthritis and systemic lupus erythematosus, both of which are autoimmune diseases, suggesting that AAA could be one type of autoimmune diseases in etiology. Based on this observation, we further hypothesized that drugs for autoimmune diseases could be repurposed for the prevention and therapy of AAA. Finally, animal experiments confirmed that methotrexate, a drug for autoimmune diseases, was able to alleviate the formation and development of AAA., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Breast cancer is the most prevalent cancer in the world. Currently, the main treatments for breast cancer are radiotherapy, chemotherapy, targeted therapy and surgery. The treatment measures for breast cancer depend on the molecular subtype. Thus, the exploration of the underlying molecular mechanisms and therapeutic targets for breast cancer remains a hotspot in research. In breast cancer, a high level of expression of DNMTs is highly correlated with poor prognosis, that is, the abnormal methylation of tumor suppressor genes usually promotes tumorigenesis and progression. MiRNAs, as non-coding RNAs, have been identified to play key roles in breast cancer. The aberrant methylation of miRNAs could lead to drug resistance during the aforementioned treatment. Therefore, the regulation of miRNA methylation might serve as a therapeutic target in breast cancer. In this paper, we reviewed studies on the regulatory mechanisms of miRNA and DNA methylation in breast cancer from the last decade, focusing on the promoter region of tumor suppressor miRNAs methylated by DNMTs and the highly expressed oncogenic miRNAs inhibited by DNMTs or activating TETs.

G protein-coupled receptors (GPCRs) are the largest family of druggable targets, and their biological functions depend on different ligands and intracellular interactomes. Some microRNAs (miRNAs) bind as ligands to RNA-sensitive toll-like receptor 7 to regulate the inflammatory response, thereby contributing to the pathogenesis of cancer or neurodegeneration. It is unknown whether miRNAs bind to angiotensin II (Ang II) type 2 receptor (AGTR2), a critical protective GPCR in cardiovascular diseases, as ligands or intracellular interactomes. Here, screening for miRNAs that bind to AGTR2, we identified and confirmed that the pre-miRNA hsa-let-7a-2 non-competitively binds to the intracellular third loop of AGTR2. Functionally, intracellular hsa-let-7a-2 overexpression suppressed the Ang II-induced AGTR2 effects such as cAMP lowering, RhoA inhibition, and activation of Src homology 2 domain-containing protein-tyrosine phosphatase 1, whereas hsa-let-7a-2 knockdown enhanced these effects. Consistently, overexpressed hsa-let-7a-2 restrained the AGTR2-induced antiproliferation, antimigration, and proapoptosis of cells, and vasodilation of mesenteric arteries. Our findings demonstrated that hsa-let-7a-2 is a novel intracellular partner of AGTR2 that negatively regulates AGTR2-activated signals., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

MicroRNAs (miRNAs) are associated with various complex human diseases and some miRNAs can be directly involved in the mechanisms of disease. Identifying disease-causative miRNAs can provide novel insight in disease pathogenesis from a miRNA perspective and facilitate disease treatment. To date, various computational models have been developed to predict general miRNA-disease associations, but few models are available to further prioritize causal miRNA-disease associations from non-causal associations. Therefore, in this study, we constructed a Levenshtein-Distance-Enhanced miRNA-disease Causal Association Predictor (LE-MDCAP), to predict potential causal miRNA-disease associations. Specifically, Levenshtein distance matrixes covering the sequence, expression and functional miRNA similarities were introduced to enhance the previous Gaussian interaction profile kernel-based similarity matrix. LE-MDCAP integrated miRNA similarity matrices, disease semantic similarity matrix and known causal miRNA-disease associations to make predictions. For regular causal vs. non-disease association discrimination task, LF-MDCAP achieved area under the receiver operating characteristic curve (AUROC) of 0.911 and 0.906 in 10-fold cross-validation and independent test, respectively. More importantly, LE-MDCAP prominently outperformed the previous MDCAP model in distinguishing causal versus non-causal miRNA-disease associations (AUROC 0.820 vs. 0.695). Case studies performed on diabetic retinopathy and hsa-mir-361 also validated the accuracy of our model. In summary, LE-MDCAP could be useful for screening causal miRNA-disease associations from general miRNA-disease associations.

Animal models have a certain degree of similarity with human in genes and physiological processes, which leads them to be valuable tools for studying human diseases and for assisting drug development. However, translational researches adopting animal models are largely restricted by the species heterogeneity, which is also a major reason for the failure of drug research. Currently, computational method for exploring the functional differences between orthologous genes is still insufficient. For this purpose, here, we presented an algorithm, functional divergence score (FDS), by comprehensively evaluating the functional differences between the microRNAs regulating the paired orthologous genes. Given that mouse is one of the most popular model animals, currently, FDS was designed to dissect the functional divergence of orthologous genes between human and mouse. The results showed that gene FDS value is significantly associated with gene evolutionary characteristics and can discover expression divergence of human-mouse orthologous genes. Moreover, FDS performed well in distinguishing the targets of approved drugs and the failed ones. These results suggest that FDS is a valuable tool to evaluate the functional divergence of paired human and mouse orthologous genes. In addition, for each orthologous gene pair, FDS can provide detailed differences in functions and phenotypes. Our study provided a useful tool for quantifying the functional difference between human and mouse, and the presented framework is easily to be extended to the orthologous genes between human and other species. An online server of FDS is available at http://www.cuilab.cn/fds/., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

tRNA-derived fragments (tRFs), which by definition are cleaved from tRNAs, comprise a novel class of regulatory small non-coding RNAs. Recent evidence has revealed that tRFs can be loaded onto Argonaute (AGO) family proteins to perform post-transcriptional regulations via substantial tRF-target gene interactions (TGIs). However, there is no resource that systematically profiles potential AGO-mediated TGIs. To this end, we performed a systemic computational screening of potential AGO-mediated TGIs by a re-analysis of 146 crosslinking-immunoprecipitation and high-throughput sequencing (CLIP-seq) datasets in which 920,690 TGIs between 12,102 tRFs and 5,688 target genes were identified. The predicted TGIs have superior signal-to-noise ratio and good consistency with TGIs identified from an orthogonal technique. AGO-bound tRFs are not evenly distributed, where the 5'-tRF and 3'-tRF are enriched and some commonly expressed tRFs are also overrepresented. The tRFs tend to target conserved regions of transcripts and co-express with their target genes. Filtering TGIs with consistent co-expression with target genes results in a set of regulatory TGIs that contains 25,281 tRF-target pairs. Together, our results unveiled the extensive regulatory interactions between tRFs and target genes. Finally, the CLIP-derived TGIs were incorporated in a user-friendly online platform termed as tRFTar, where various functions like custom searching, co-expressed TGI filtering, genome browser and TGI-based tRF functional enrichment analysis are enabled to help users to investigate the functions of tRFs. The tRFTar is freely available at http://www.rnanut.net/tRFTar/., (Copyright © 2020 Elsevier Inc. All rights reserved.)

It is known that many microRNAs (miRNAs) stably exist in various body fluids, however, the relationship of body fluids miRNAs (BF-miRNAs) with those from tissues (T-miRNAs) remains largely unclear but is important for understanding the potential of BF-miRNAs to be biomarkers of specific diseases. Here by analyzing miRNA expression data from 40 human healthy tissues and those from human body fluids, including plasma, serum, urine, bile, and feces, we revealed a positive correlation between BF-miRNAs and T-miRNAs. Moreover, plasma and serum have the most communication with pericardium, adipose, liver, and spleen. Urinary miRNAs show the highest correlation with kidney miRNAs. For fecal miRNAs, gastrointestinal tract (colon, ileum, jejunum, small intestine, stomach, proximal colon, duodenum, and distal colon) miRNAs show the strongest correlation. Moreover, miRNA set enrichment analysis revealed that highly expressed fecal miRNAs are mostly associated with gastric and colon cancers etc. Additionally, bile miRNAs from suspected cholangiocarcinoma patients show a positive correlation with the cholangiocarcinoma tumor tissue. Interestingly, the relationship of BF-miRNAs and T-miRNAs shows significant sex differences. Serum miRNAs showed higher correlation with T-miRNAs in males, whereas plasma miRNAs and urine miRNAs showed higher correlations with T-miRNAs in females. These findings together indicate a potential role of BF-miRNAs as biomarkers to monitor corresponding specific human diseases.

Physiological and pathophysiological differences exist between the left and right kidneys; however, the molecular bases for these differences remain unknown. Since miRNAs are involved in kidney function and the development of kidney diseases, we examined their differential expression through miRNA profiling of the left and right kidneys of normal mice. We find that 36 miRNAs exhibit higher expression, whereas 22 miRNAs show lower expression in the left than the right kidneys in mice under physiological condition. Ten miRNAs were further examined by quantitative PCR assays, and four of them with high expression level were confirmed by Northern blot. Through bioinformatic analysis, we dissected the function and network of the differentially expressed miRNAs, providing insights into the physiological and pathophysiological differences between the left and the right kidneys., (© 2019 Federation of European Biochemical Societies.)

Triple-negative breast cancer (TNBC) is the most aggressive, prevalent, and distinct subtype of breast cancer characterized by high recurrence rates and poor clinical prognosis, devoid of both predictive markers and potential therapeutic targets. MicroRNAs (miRNA/miR) are a family of small, endogenous, non-coding, single-stranded regulatory RNAs that bind to the 3'-untranslated region (3'-UTR) complementary sequences and downregulate the translation of target mRNAs as post-transcriptional regulators. Dysregulation miRNAs are involved in broad spectrum cellular processes of TNBC, exerting their function as oncogenes or tumor suppressors depending on their cellular target involved in tumor initiation, promotion, malignant conversion, and metastasis. In this review, we emphasize on masses of miRNAs that act as oncogenes or tumor suppressors involved in epithelial-mesenchymal transition (EMT), maintenance of stemness, tumor invasion and metastasis, cell proliferation, and apoptosis. We also discuss miRNAs as the targets or as the regulators of dysregulation epigenetic modulation in the carcinogenesis process of TNBC. Furthermore, we show that miRNAs used as potential classification, prognostic, chemotherapy and radiotherapy resistance markers in TNBC. Finally, we present the perspective on miRNA therapeutics with mimics or antagonists, and focus on the challenges of miRNA therapy. This study offers an insight into the role of miRNA in pathology progression of TNBC., Competing Interests: The authors declare no conflicts of interest.

Background: A series of miRNA-disease association prediction methods have been proposed to prioritize potential disease-associated miRNAs. Independent benchmarking of these methods is warranted to assess their effectiveness and robustness., Results: Based on more than 8000 novel miRNA-disease associations from the latest HMDD v3.1 database, we perform systematic comparison among 36 readily available prediction methods. Their overall performances are evaluated with rigorous precision-recall curve analysis, where 13 methods show acceptable accuracy (AUPRC > 0.200) while the top two methods achieve a promising AUPRC over 0.300, and most of these methods are also highly ranked when considering only the causal miRNA-disease associations as the positive samples. The potential of performance improvement is demonstrated by combining different predictors or adopting a more updated miRNA similarity matrix, which would result in up to 16% and 46% of AUPRC augmentations compared to the best single predictor and the predictors using the previous similarity matrix, respectively. Our analysis suggests a common issue of the available methods, which is that the prediction results are severely biased toward well-annotated diseases with many associated miRNAs known and cannot further stratify the positive samples by discriminating the causal miRNA-disease associations from the general miRNA-disease associations., Conclusion: Our benchmarking results not only provide a reference for biomedical researchers to choose appropriate miRNA-disease association predictors for their purpose, but also suggest the future directions for the development of more robust miRNA-disease association predictors.

MicroRNAs (miRNAs) are one class of important small non-coding RNA molecules and play critical roles in health and disease. Therefore, it is important and necessary to evaluate the functional relationship of miRNAs and then predict novel miRNA-disease associations. For this purpose, here we developed the updated web server MISIM (miRNA similarity) v2.0. Besides a 3-fold increase in data content compared with MISIM v1.0, MISIM v2.0 improved the original MISIM algorithm by implementing both positive and negative miRNA-disease associations. That is, the MISIM v2.0 scores could be positive or negative, whereas MISIM v1.0 only produced positive scores. Moreover, MISIM v2.0 achieved an algorithm for novel miRNA-disease prediction based on MISIM v2.0 scores. Finally, MISIM v2.0 provided network visualization and functional enrichment analysis for functionally paired miRNAs. The MISIM v2.0 web server is freely accessible at http://www.lirmed.com/misim/., (© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Endothelial NO synthase (eNOS) expression is regulated by a number of transcriptional and post-transcriptional mechanisms, but the effects of competing endogenous RNAs (ceRNAs) on eNOS mRNA and the underlying mechanisms are still unknown. Our bioinformatic analysis revealed three highly expressed eNOS-targeting miRNAs (miR-15b, miR-16, and miR-30b) in human endothelial cells (ECs). Among the 1103 mRNA targets of these three miRNAs, 15 mRNAs share a common disease association with eNOS. Gene expression and correlation analysis in patients with cardiovascular diseases identified insulin receptor substrate 2 (IRS2) as the most correlated eNOS-ceRNA. The expression levels of eNOS and IRS2 were coincidentally increased by application of laminar shear but reduced with eNOS or IRS2 siRNA transfection in human ECs, which was impeded by Dicer siRNA treatment. Moreover, luciferase reporter assay showed that these three miRNAs directly target the 3'UTR of eNOS and IRS2. Overexpression of these three miRNAs decreased, whereas inhibition of them increased, both mRNA and protein levels of eNOS and IRS2. Functionally, silencing eNOS suppressed the Akt signal pathway, while IRS2 knockdown reduced NO production in ECs. Thus, we identified eNOS and IRS2 as ceRNAs and revealed a novel mechanism explaining the coincidence of metabolic and cardiovascular diseases., (© The Author(s) (2018). Published by Oxford University Press on behalf of Journal of Molecular Cell Biology, IBCB, SIBS, CAS. All rights reserved.)

MicroRNAs (miRNAs) are important post-transcriptional regulators of gene expression and play vital roles in various biological processes. It has been reported that aberrant regulation of miRNAs was associated with the development and progression of various diseases, but the underlying mechanisms are not fully deciphered. Here, we described our updated TransmiR v2.0 database for more comprehensive information about transcription factor (TF)-miRNA regulations. 3730 TF-miRNA regulations among 19 species from 1349 reports were manually curated by surveying >8000 publications, and more than 1.7 million tissue-specific TF-miRNA regulations were further incorporated based on ChIP-seq data. Besides, we constructed a 'Predict' module to query the predicted TF-miRNA regulations in human based on binding motifs of TFs. To facilitate the community, we provided a 'Network' module to visualize TF-miRNA regulations for each TF and miRNA, or for a specific disease. An 'Enrichment analysis' module was also included to predict TFs that are likely to regulate a miRNA list of interest. In conclusion, with improved data coverage and webserver functionalities, TransmiR v2.0 would be a useful resource for investigating the regulation of miRNAs. TransmiR v2.0 is freely accessible at http://www.cuilab.cn/transmir.

Comprehensive databases of microRNA-disease associations are continuously demanded in biomedical researches. The recently launched version 3.0 of Human MicroRNA Disease Database (HMDD v3.0) manually collects a significant number of miRNA-disease association entries from literature. Comparing to HMDD v2.0, this new version contains 2-fold more entries. Besides, the associations have been more accurately classified based on literature-derived evidence code, which results in six generalized categories (genetics, epigenetics, target, circulation, tissue and other) covering 20 types of detailed evidence code. Furthermore, we added new functionalities like network visualization on the web interface. To exemplify the utility of the database, we compared the disease spectrum width of miRNAs (DSW) and the miRNA spectrum width of human diseases (MSW) between version 3.0 and 2.0 of HMDD. HMDD is freely accessible at http://www.cuilab.cn/hmdd. With accumulating evidence of miRNA-disease associations, HMDD database will keep on growing in the future.

Colorectal cancer (CRC) is responsible for one of the major cancer incidence and mortality worldwide. It is well known that MicroRNAs (miRNAs) play vital roles in maintaining the cell development and other physiological processes, as well as, the aberrant expression of numerous miRNAs involved in CRC progression. MiRNAs are a class of small, endogenous, non-coding, single-stranded RNAs that bind to the 3'-untranslated region (3'-UTR) complementary sequences of their target mRNA, resulting in mRNA degradation or inhibition of its translation as a post-transcriptional regulators. Moreover, miRNAs also can target the long non-coding RNA (lncRNA) to regulate the expression of its target genes involved in proliferation and metastasis of CRC. The functions of these dysregulated miRNAs appear to be context specific, with evidence of having a dual role in both oncogenes and tumor suppression depending on the cellular environment in which they are expressed. Therefore, the unique expression profiles of miRNAs relate to the diagnosis, prognosis, and therapeutic outcome in CRC. In this review, we focused on several oncogenic and tumor-suppressive miRNAs specific to CRC, and assess their functions to uncover the molecular mechanisms of tumor initiation and progression in CRC. These data promised that miRNAs can be used as early detection biomarkers and potential therapeutic target in CRC patients.

With the rapid accumulation of high-throughput microRNA (miRNA) expression profile, the up-to-date resource for analyzing the functional and disease associations of miRNAs is increasingly demanded. We here describe the updated server TAM 2.0 for miRNA set enrichment analysis. Through manual curation of over 9000 papers, a more than two-fold growth of reference miRNA sets has been achieved in comparison with previous TAM, which covers 9945 and 1584 newly collected miRNA-disease and miRNA-function associations, respectively. Moreover, TAM 2.0 allows users not only to test the functional and disease annotations of miRNAs by overrepresentation analysis, but also to compare the input de-regulated miRNAs with those de-regulated in other disease conditions via correlation analysis. Finally, the functions for miRNA set query and result visualization are also enabled in the TAM 2.0 server to facilitate the community. The TAM 2.0 web server is freely accessible at http://www.scse.hebut.edu.cn/tam/ or http://www.lirmed.com/tam2/.

Sex differences are widely observed under various circumstances ranging from physiological processes to therapeutic responses, and a myriad of sex-biased genes have been identified. In recent years, transcriptomic datasets of microRNAs (miRNAs), an important class of non-coding RNAs, become increasingly accessible. However, comprehensive analysis of sex difference in miRNA expression has not been performed. Here, we identified the differentially-expressed miRNAs between males and females by examining the transcriptomic datasets available in public databases and conducted a systemic analysis of their biological characteristics. Consequently, we identified 73 female-biased miRNAs (FmiRs) and 163 male-biased miRNAs (MmiRs) across four tissues including brain, colorectal mucosa, peripheral blood, and cord blood. Our results suggest that compared to FmiRs, MmiRs tend to be clustered in the human genome and exhibit higher evolutionary rate, higher expression tissue specificity, and lower disease spectrum width. In addition, functional enrichment analysis of miRNAs show that FmiR genes are significantly associated with metabolism process and cell cycle process, whereas MmiR genes tend to be enriched for functions like histone modification and circadian rhythm. In all, the identification and analysis of sex-biased miRNAs together could provide new insights into the biological differences between females and males and facilitate the exploration of sex-biased disease susceptibility and therapy., (Copyright © 2018 The Authors. Production and hosting by Elsevier B.V. All rights reserved.)

Hepatic FAM3A expression is repressed under obese conditions, but the underlying mechanism remains unknown. This study determined the role and mechanism of miR-423-5p in hepatic glucose and lipid metabolism by repressing FAM3A expression. miR-423-5p expression was increased in the livers of obese diabetic mice and in patients with nonalcoholic fatty liver disease (NAFLD) with decreased FAM3A expression. miR-423-5p directly targeted FAM3A mRNA to repress its expression and the FAM3A-ATP-Akt pathway in cultured hepatocytes. Hepatic miR-423-5p inhibition suppressed gluconeogenesis and improved insulin resistance, hyperglycemia, and fatty liver in obese diabetic mice. In contrast, hepatic miR-423-5p overexpression promoted gluconeogenesis and hyperglycemia and increased lipid deposition in normal mice. miR-423-5p inhibition activated the FAM3A-ATP-Akt pathway and repressed gluconeogenic and lipogenic gene expression in diabetic mouse livers. The miR-423 precursor gene was further shown to be a target gene of NFE2, which induced miR-423-5p expression to repress the FAM3A-ATP-Akt pathway in cultured hepatocytes. Hepatic NFE2 overexpression upregulated miR-423-5p to repress the FAM3A-ATP-Akt pathway, promoting gluconeogenesis and lipid deposition and causing hyperglycemia in normal mice. In conclusion, under the obese condition, activation of the hepatic NFE2/miR-423-5p axis plays important roles in the progression of type 2 diabetes and NAFLD by repressing the FAM3A-ATP-Akt signaling pathway., (© 2017 by the American Diabetes Association.)

Cellular senescence is an important protective mechanism against cell proliferation and has critical roles in aging and aging-related disease. Recently, one interesting observation is that the protein abundance is higher in senescent cells than that in young cells. So far, some factors were presented to interpret this observation, such as active protein synthesis linked with autophagy, mTOR, and oxidative stress. Here, applying bioinformatic analysis of microRNA profiles in young cells and aging cells, we revealed that globally senescent cells show lower miRNA abundance than that in young cells, suggesting that the repression of protein synthesis by miRNA in senescent cells could be largely attenuated. This finding provides clues that protein accumulation in cellular senescence could be associated with lower miRNA abundance in aging cells.

Circulating microRNAs presented in venous plasma have been demonstrated as powerful biomarkers for the complex diseases like cancer. Nevertheless, those presented in arterial plasma remained largely unexplored. Here, using microarray technique, we compared microRNA expression profiles of the matched arterial and venous plasma samples from the same male rats. Though the microRNA profiles were largely similar, we identified 24 differentially expressed microRNAs, including 10 arterial highly expressed microRNAs and 14 venous highly expressed microRNAs. The differentially expressed microRNAs were validated by qRT-PCR. Computational analysis of these microRNAs and their targets indicated that arterial highly expressed microRNAs were overrepresented for functional terms like hematopoiesis and diseases like Crohn's Disease and leukemia; while venous highly expressed microRNAs were enriched for cell differentiation function, and diseases like distal myopathies and heart failure. Our analysis also suggested significant correlations between plasma microRNA expression and tissue microRNA expression. Four arterial highly expressed microRNAs also showed enriched expression in specific tissues and would be novel biomarker candidates.

MicroRNA-375 is involved in many types of alimentary system cancers. Our previous studies showed that microRNA-375 was significantly down-regulated in carcinoma tissues compared with para-carcinoma tissues, which strongly indicates that microRNA-375 might suppress the occurrence and development of colorectal cancer. However, the mechanism underlying the microRNA-375 regulation in colorectal cancer remains unclear. In this study, we first sorted out jak2, map3k8 and atg7 as microRNA-375 targeted genes from multiple databases, and found that jak2, map3k8 and their downstream genes stat3 and erk were up-regulated in carcinoma tissues. Secondly, we over-expressed microRNA-375 in colorectal cancer cell lines (HCT116, Caco2 and HT29). Our results showed that in microRNA-375 over-expressing cells, JAK2/STAT3 and MAP3K8/ERK proteins were down-regulated, cell proliferation was inhibited, cell migration rate did not change. There was no significant difference on ATG7 expression between the control group and microRNA-375 over-expressing HT29/Caco2 cells, whereas microRNA-375 down-regulated ATG7 specifically in HCT116 cells. Finally, we demonstrated that expressing microRNA-375 suppressed tumor formation in nude mice. In conclusion, microRNA-375 might function as a tumor-repressive gene to inhibit cell proliferation, mainly through targeting both JAK2/STAT3 and MAP3K8/ERK signaling pathways in colorectal cancer. These findings suggest miR-375 as a promising diagnostic marker and a therapeutic drug for colorectal cancer.

LncRNAs represent a large class of noncoding RNA molecules that have important functions and play key roles in a variety of human diseases. There is an urgent need to develop bioinformatics tools as to gain insight into lncRNAs. This study developed a sequence-based bioinformatics method, LncDisease, to predict the lncRNA-disease associations based on the crosstalk between lncRNAs and miRNAs. Using LncDisease, we predicted the lncRNAs associated with breast cancer and hypertension. The breast-cancer-associated lncRNAs were studied in two breast tumor cell lines, MCF-7 and MDA-MB-231. The qRT-PCR results showed that 11 (91.7%) of the 12 predicted lncRNAs could be validated in both breast cancer cell lines. The hypertension-associated lncRNAs were further evaluated in human vascular smooth muscle cells (VSMCs) stimulated with angiotensin II (Ang II). The qRT-PCR results showed that 3 (75.0%) of the 4 predicted lncRNAs could be validated in Ang II-treated human VSMCs. In addition, we predicted 6 diseases associated with the lncRNA GAS5 and validated 4 (66.7%) of them by literature mining. These results greatly support the specificity and efficacy of LncDisease in the study of lncRNAs in human diseases. The LncDisease software is freely available on the Software Page: http://www.cuilab.cn/., (© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Cigarette smoking is a world-wide habit and an important risk factor for cancer. It was known that cigarette smoking can change the expression of circulating microRNAs (miRNAs) in healthy middle-aged adults. However, it remains unclear whether cigarette smoking can change the levels of circulating miRNAs in young healthy smokers and whether there are differences in cancer susceptibility for the two cases. In this study, the miRNA expression profiles of 28 smokers and 12 non-smokers were determined by Agilent human MicroRNA array. We further performed bioinformatics analysis for the differentially expressed miRNAs. The result showed that 35 miRNAs were differentially expressed. Among them, 24 miRNAs were up-regulated and 11 miRNAs were down-regulated in smokers. Functional enrichment analysis showed that the deregulated miRNAs are related to immune system and hormones regulation. Strikingly, the up-regulated miRNAs are mostly associated with hematologic cancers, such as lymphoma, leukemia. As a comparison, the up-regulated plasma miRNAs in middle-aged smokers are mostly associated with solid cancers, such as hepatocellular carcinoma and lung cancer, suggesting that smoking could have different influences on young adults and middle-aged adults. In a conclusion, we identified the circulating miRNAs deregulated by cigarette smoking and revealed that the age-dependent deregulated miRNAs tend to be mainly involved in different types of human cancers., Competing Interests: The authors declare that there is no conflict of interests.

Alzheimer's disease (AD) is a serious neurodegenerative disease, and microRNAs (miRNAs) have been linked to its pathogenesis. miR-603, a novel primate-specific miRNA and an intronic miRNA of a human brain highly expressed gene KIAA1217, is implicated in the risk and pathogenesis of AD. The rs11014002 single nucleotide polymorphism (SNP) (C/U), which locates in miR-603 precursor (pre-miR-603), exhibits a protective effect towards AD risk. Additionally, the rs11014002 SNP promotes the biogenesis of mature miR-603. miR-603 downregulates LRPAP1 mRNA and protein levels through directly binding the 3' untranslated region (3'UTR) of LRPAP1. Moreover, miR-603 increases LRP1 protein expression. LRPAP1 and LRP1, playing opposite roles, are involved in Aβ clearance and pathogenesis of AD. Strikingly, miR-603 exhibits a relatively higher expression and there is a loss of a negative correlation between miR-603 and LRPAP1/RND1 mRNA levels in the hippocampi of patients with AD. In addition, miR-603 directly downregulates a key neuronal apoptotic component-E2F1, and prevents HeLa cells from undergoing H2O2-induced apoptosis. This work suggests that miR-603 may be a novel AD-relevant miRNA and that its rs11014002 SNP may serve as a protective factor against AD.

Historically, owing to not changing amino acid composition of protein sequences, synonymous mutations are commonly assumed to be neutral during evolution and therefore have no effect on the phenotype and disease. Here, based on observations from large-scale analysis of genomic data, we predicted the putative synonymous SNPs that could result in functional consequences and disease risk through changing the microRNA-mediated gene regulation. We found that nearly half of the synonymous SNPs could affect protein expression by changing microRNA regulation in human genome and these SNPs significantly prefer to be associated with human diseases and traits. The synonymous SNPs changing microRNA-mediated gene regulation tend to be more under recent positive selection, prefer to affect gene expression, and implicate in human disease. We conclude that the miRNA-mediated regulation changes could be a potential mechanism for the contributions of synonymous SNPs to protein functions and disease risks.

The Human microRNA Disease Database (HMDD; available via the Web site at http://cmbi.bjmu.edu.cn/hmdd and http://202.38.126.151/hmdd/tools/hmdd2.html) is a collection of experimentally supported human microRNA (miRNA) and disease associations. Here, we describe the HMDD v2.0 update that presented several novel options for users to facilitate exploration of the data in the database. In the updated database, miRNA-disease association data were annotated in more details. For example, miRNA-disease association data from genetics, epigenetics, circulating miRNAs and miRNA-target interactions were integrated into the database. In addition, HMDD v2.0 presented more data that were generated based on concepts derived from the miRNA-disease association data, including disease spectrum width of miRNAs and miRNA spectrum width of human diseases. Moreover, we provided users a link to download all the data in the HMDD v2.0 and a link to submit novel data into the database. Meanwhile, we also maintained the old version of HMDD. By keeping data sets up-to-date, HMDD should continue to serve as a valuable resource for investigating the roles of miRNAs in human disease.

Background: MiR-499 is a cardiac-abundant miRNA. However, the biological functions of miR-499 in differentiated cardiomyocytes or in the cardiomyocyte differentiation process is not very clear. Sox6 is believed to be one of its targets, and is also believed to play a role in cardiac differentiation. Therefore, our aim was to investigate the association between Sox6 and miR-499 during cardiac differentiation., Methodology/principal Findings: Using a well-established in vitro cardiomyocyte differentiation system, mouse P19CL6 cells, we found that miR-499 was highly expressed in the late stage of cardiac differentiation. In cells stably transfected with miR-499 (P-499 cells), it was found that miR-499 could promote the differentiation into cardiomyocytes at the early stage of cardiac differentiation. Notably, cell viability assay, EdU incorporation assay, and cell cycle profile analysis all showed that the P-499 cells displayed the distinctive feature of hyperplastic growth. Further investigation confirmed that miR-499 could promote neonatal rat cardiomyocyte proliferation. MiR-499 knock-down enhanced apoptosis in the late differentiation stage in P19CL6 cells, but overexpression of miR-499 resulted in a decrease in the apoptosis rate. Sox6 was identified as a direct target of miR-499 and its expression was detected from day 8 or day 10 of cardiac differentiation of P19CL6 cells. Sox6 played a role in cell viability, inhibited cell proliferation and promoted cell apoptosis in P19CL6 cells and cardiomyocytes. The overexpression of Sox6 could reverse the proliferation and anti-apoptosis effects of miR-499. It was also found that miR-499 might exert its function by regulating cyclin D1 via its influence on Sox6., Conclusions/significance: miR-499 probably regulates the proliferation and apoptosis of P19CL6 cells in the late stage of cardiac differentiation via its effects on Sox6 and cyclin D1.

While recent insights indicate that the transcription factor Krüppel-like factor 4 (KLF4) is indispensable for vascular homeostasis, its exact role in proliferation and angiogenesis and how it functions remain unresolved. Thus, the aim of the present study was to evaluate the role of KLF4 in the proliferations of endothelial and vascular smooth muscle cells, as well as the angiogenesis. The overexpression of KLF4 in endothelial cells significantly impaired tube formation. KLF4 inhibited the formation of a vascular network in implanted Matrigel plugs in nude mice. Importantly, we found that KLF4 significantly upregulated the miR-15a expression in endothelial cells and vascular smooth muscle cells, and conversely, KLF4 depletion reduced the amount of miR-15a. Furthermore, KLF4 blocked cell cycle progression and decreased cyclin D1 expression in endothelial cells and vascular smooth muscle cells through the induction of miR-15a. Intriguingly, the delivery of a miR-15a antagomir to nude mice resulted in marked attenuation of the anti-angiogenic effect of KLF4. Collectively, our present study provide the first evidence that miR-15a as a direct transcriptional target of KLF4 that mediates the anti-proliferative and anti-angiogenic actions of KLF4, which indicates that KLF4 upregulation of miR-15a may represent a therapeutic option to suppress proliferative vascular disorders., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Background: MicroRNAs (miRNAs) are endogenously encoded small RNAs that post-transcriptionally regulate gene expression and play essential roles in numerous developmental and physiological processes. Currently, little information on the transcriptome and tissue-specific expression of miRNAs is available in the model non-edible oilseed crop castor bean (Ricinus communis L.), one of the most important non-edible oilseed crops cultivated worldwide. Recent advances in sequencing technologies have allowed the identification of conserved and novel miRNAs in many plant species. Here, we used high-throughput sequencing technologies to identify and characterize the miRNAs in castor bean., Results: Five small RNA libraries were constructed for deep sequencing from root tips, leaves, developing seeds (at the initial stage, seed1; and at the fast oil accumulation stage, seed2) and endosperms in castor bean. High-throughput sequencing generated a large number of sequence reads of small RNAs in this study. In total, 86 conserved miRNAs were identified, including 63 known and 23 newly identified. Sixteen miRNA isoform variants in length were found from the conserved miRNAs of castor bean. MiRNAs displayed diverse organ-specific expression levels among five libraries. Combined with criteria for miRNA annotation and a RT-PCR approach, 72 novel miRNAs and their potential precursors were annotated and 20 miRNAs newly identified were validated. In addition, new target candidates for miRNAs newly identified in this study were proposed., Conclusions: The current study presents the first high-throughput small RNA sequencing study performed in castor bean to identify its miRNA population. It characterizes and increases the number of miRNAs and their isoforms identified in castor bean. The miRNA expression analysis provides a foundation for understanding castor bean miRNA organ-specific expression patterns. The present study offers an expanded picture of miRNAs for castor bean and other members in the family Euphorbiaceae.

The roles of circulating miRNAs in disease therapy remain largely unclear, but recent data suggests a role for these molecules in cancer. In patients with cancer, the levels of circulating miRNAs with tumor-suppressing capabilities increase and those with oncogenic activity decrease. In addition, the population of circulating miRNAs correlates highly with immune response, suggesting that circulating miRNAs could be driving anticancer effects through active immune defense and might be a novel strategy for cancer therapy., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Increasing studies have shown that microRNA (miRNA) stability plays important roles in physiology. However, the global picture of miRNA stability remains largely unknown. Here, we had analyzed genome-wide miRNA stability across 10 diverse cell types using miRNA arrays. We found that miRNA stability shows high dynamics and diversity both within individual cells and across cell types. Strikingly, we observed a negative correlation between miRNA stability and miRNA expression level, which is different from current findings on other biological molecules such as proteins and mRNAs that show positive and not negative correlations between stability and expression level. This finding indicates that miRNA has a distinct action mode, which we called "rapid production, rapid turnover; slow production, slow turnover." This mode further suggests that high expression miRNAs normally degrade fast and may endow the cell with special properties that facilitate cellular status-transition. Moreover, we revealed that the stability of miRNAs is affected by cohorts of factors that include miRNA targets, transcription factors, nucleotide content, evolution, associated disease, and environmental factors. Together, our results provided an extensive description of the global landscape, dynamics, and distinct mode of human miRNA stability, which provide help in investigating their functions in physiology and pathophysiology.

With the rapid accumulation of microRNA (miRNAs), a class of newly identified small noncoding RNAs, in silico inference of miRNA functions has become one of the central tasks in miRNA bioinformatics. Traditional methods have helped in the understanding of miRNAs, but they also have limitations. In this paper, we first gave a brief review for the progress of bioinformatic methods in miRNA function inference and next presented a new framework (miRUPnet) for inferring the functions of miRNAs by functional analysis of a novel dimension of miRNA network, the context of its transcription factors (TFs) in a protein-protein interaction network. This dimension represents specific biological processes initiated by TF combinations and therefore differs from traditional methods in concept. To validate the accuracy of our method, we first comprehensively mined literature-reported miRNA functions and then made a comparison with the prediction result. The results show that even using the stringent TFBS rule, our method has independently predicted 68.2% of the literature reported miRNA functions, suggesting that miRUPnet has a high accuracy. Moreover, our approach successfully predicted specific functions that could not be inferred for given miRNAs using traditional methods. More importantly, it can distinguish miRNAs from the same family, as well as those present in multiple copies that cannot be differentiated through traditional methods. This study presents a new concept and dimension for miRNA function inference. miRUPnet represents an important and novel method for inferring the function of miRNAs. miRUPnet is available at http://cmbi.bjmu.edu.cn/mirupnet.

Increasing studies have shown that the interactions between microRNAs (miRNAs) and environmental factors (EFs) play critical roles in determining phenotypes and diseases. In this study, we revealed a number of important biological insights by analyzing and modeling of miRNA-EF interactions and their relationships with human diseases. We demonstrated that the miRNA signatures of EFs could provide new information on EFs. More importantly, we quantitatively showed that the miRNA signatures of drug/radiation could be used as indicators for evaluating the results of cancer treatments. Finally, we developed a computational model that could efficiently identify the possible relationship between EF and human diseases. Meanwhile, we provided a website (http://cmbi.hsc.pku.edu.cn/miren) for the main results of this study. This study elucidates the mechanisms of EFs, presents a framework for predicting the results of cancer treatments, and develops a model that illustrates the relationships between EFs and human diseases.

Unlabelled: The interaction between genetic factors and environmental factors has critical roles in determining the phenotype of an organism. In recent years, a number of studies have reported that the dysfunctions on microRNA (miRNAs), environmental factors and their interactions have strong effects on phenotypes and even may result in abnormal phenotypes and diseases, whereas there has been no a database linking miRNAs, environmental factors and phenotypes. Such a resource platform is believed to be of great value in the understanding of miRNAs, environmental factors, especially drugs and diseases. In this study, we constructed the miREnvironment database, which contains a comprehensive collection and curation of experimentally supported interactions among miRNAs, environmental factors and phenotypes. The names of miRNAs, phenotypes, environmental factors, conditions of environmental factors, samples, species, evidence and references were further annotated. miREnvironment represents a biomedical resource for researches on miRNAs, environmental factors and diseases., Availability: http://cmbi.bjmu.edu.cn/miren., Contact: cuiqinghua@hsc.pku.edu.cn.

Background: In recent years, a number of tools have been developed to explore microRNAs (miRNAs) by analyzing their target genes. However, a reverse problem, that is, inferring patterns of protein-coding genes through their miRNA regulators, has not been explored. As various miRNA annotation data become available, exploring gene patterns by analyzing the prior knowledge of their miRNA regulators is becoming more feasible., Results: In this study, we developed a tool, miR2Gene, for this purpose. Various sets of miRNAs, according to prior rules such as function, associated disease, tissue specificity, family, and cluster, were integrated with miR2Gene. For given genes, miR2Gene evaluates the enrichment of the predicted miRNAs that regulate them in each miRNA set. This tool can be used for single genes, multiple genes, and KEGG pathways. For the KEGG pathway, genes with enriched miRNA sets are highlighted according to various rules. We confirmed the usefulness of miR2Gene through case studies., Conclusions: miR2Gene represents a novel and useful tool that integrates miRNA knowledge for protein-coding gene analysis. miR2Gene is freely available at http://cmbi.hsc.pku.edu.cn/mir2gene.

MicroRNAs (miRNAs) are small noncoding RNAs which play essential roles in many important biological processes. Therefore, their dysfunction is associated with a variety of human diseases, including cancer. Increasing evidence shows that miRNAs can act as oncogenes or tumor suppressors, and although there is great interest in research into these cancer-associated miRNAs, little is known about them. In this study, we performed a comprehensive analysis of putative human miRNA oncogenes and tumor suppressors. We found that miRNA oncogenes and tumor suppressors clearly show different patterns in function, evolutionary rate, expression, chromosome distribution, molecule size, free energy, transcription factors, and targets. For example, miRNA oncogenes are located mainly in the amplified regions in human cancers, whereas miRNA tumor suppressors are located mainly in the deleted regions. miRNA oncogenes tend to cleave target mRNAs more frequently than miRNA tumor suppressors. These results indicate that these two types of cancer-associated miRNAs play different roles in cancer formation and development. Moreover, the patterns identified here can discriminate novel miRNA oncogenes and tumor suppressors with a high degree of accuracy. This study represents the first large-scale bioinformatic analysis of human miRNA oncogenes and tumor suppressors. Our findings provide help for not only understanding of miRNAs in cancer but also for the specific identification of novel miRNAs as miRNA oncogenes and tumor suppressors. In addition, the data presented in this study will be valuable for the study of both miRNAs and cancer.

Background: MicroRNAs (miRNAs) are a class of important gene regulators. The number of identified miRNAs has been increasing dramatically in recent years. An emerging major challenge is the interpretation of the genome-scale miRNA datasets, including those derived from microarray and deep-sequencing. It is interesting and important to know the common rules or patterns behind a list of miRNAs, (i.e. the deregulated miRNAs resulted from an experiment of miRNA microarray or deep-sequencing)., Results: For the above purpose, this study presents a method and develops a tool (TAM) for annotations of meaningful human miRNAs categories. We first integrated miRNAs into various meaningful categories according to prior knowledge, such as miRNA family, miRNA cluster, miRNA function, miRNA associated diseases, and tissue specificity. Using TAM, given lists of miRNAs can be rapidly annotated and summarized according to the integrated miRNA categorical data. Moreover, given a list of miRNAs, TAM can be used to predict novel related miRNAs. Finally, we confirmed the usefulness and reliability of TAM by applying it to deregulated miRNAs in acute myocardial infarction (AMI) from two independent experiments., Conclusion: TAM can efficiently identify meaningful categories for given miRNAs. In addition, TAM can be used to identify novel miRNA biomarkers. TAM tool, source codes, and miRNA category data are freely available at http://cmbi.bjmu.edu.cn/tam.

Motivation: It is popular to explore meaningful molecular targets and infer new functions of genes through gene functional similarity measuring and gene functional network construction. However, little work is available in this field for microRNA (miRNA) genes due to limited miRNA functional annotations. With the rapid accumulation of miRNAs, it is increasingly needed to uncover their functional relationships in a systems level., Results: It is known that genes with similar functions are often associated with similar diseases, and the relationship of different diseases can be represented by a structure of directed acyclic graph (DAG). This is also true for miRNA genes. Therefore, it is feasible to infer miRNA functional similarity by measuring the similarity of their associated disease DAG. Based on the above observations and the rapidly accumulated human miRNA-disease association data, we presented a method to infer the pairwise functional similarity and functional network for human miRNAs based on the structures of their disease relationships. Comparisons showed that the calculated miRNA functional similarity is well associated with prior knowledge of miRNA functional relationship. More importantly, this method can also be used to predict novel miRNA biomarkers and to infer novel potential functions or associated diseases for miRNAs. In addition, this method can be easily extended to other species when sufficient miRNA-associated disease data are available for specific species., Availability: The online tool is available at http://cmbi.bjmu.edu.cn/misim, Contact: cuiqinghua@hsc.pku.edu.cn, Supplementary Information: Supplementary data are available at Bioinformatics online.

Background: microRNAs (miRNAs) are important cellular components. The understanding of their evolution is of critical importance for the understanding of their function. Although some specific evolutionary rules of miRNAs have been revealed, the rules of miRNA evolution in cellular networks remain largely unexplored. According to knowledge from protein-coding genes, the investigations of gene evolution in the context of biological networks often generate valuable observations that cannot be obtained by traditional approaches., Results: Here, we conducted the first systems-level analysis of miRNA evolution in a human transcription factor (TF)-miRNA regulatory network that describes the regulatory relations among TFs, miRNAs, and target genes. We found that the architectural structure of the network provides constraints and functional innovations for miRNA evolution and that miRNAs showed different and even opposite evolutionary patterns from TFs and other protein-coding genes. For example, miRNAs preferentially coevolved with their activators but not with their inhibitors. During transcription, rapidly evolving TFs frequently activated but rarely repressed miRNAs. In addition, conserved miRNAs tended to regulate rapidly evolving targets, and upstream miRNAs evolved more rapidly than downstream miRNAs., Conclusions: In this study, we performed the first systems level analysis of miRNA evolution. The findings suggest that miRNAs have a unique evolution process and thus may have unique functions and roles in various biological processes and diseases. Additionally, the network presented here is the first TF-miRNA regulatory network, which will be a valuable platform of systems biology.

Endothelial cells (ECs) respond to changes in mechanical forces, leading to the modulation of signaling networks and cell function; an example is the inhibition of EC proliferation by steady laminar flow. MicroRNAs (miRs) are short noncoding 20-22 nucleotide RNAs that negatively regulate the expression of target genes at the posttranscriptional level. This study demonstrates that miRs are involved in the flow regulation of gene expression in ECs. With the use of microRNA chip array, we found that laminar shear stress (12 dyn/cm(2), 12 h) regulated the EC expression of many miRs, including miR-19a. We further showed that stable transfection of miR-19a significantly decreased the expression of a reporter gene controlled by a conserved 3'-untranslated region of the cyclinD1 gene and also the protein level of cyclin D1, leading to an arrest of cell cycle at G1/S transition. Laminar flow suppressed cyclin D1 protein level, and this suppressive effect was diminished when the endogenous miR-19a was inhibited. In conclusion, we demonstrated that miR-19a plays an important role in the flow regulation of cyclin D1 expression. These results revealed a mechanism by which mechanical forces modulate endothelial gene expression.

MicroRNAs (miRNAs) regulate gene expression at the posttranscriptional level and are therefore important cellular components. As is true for protein-coding genes, the transcription of miRNAs is regulated by transcription factors (TFs), an important class of gene regulators that act at the transcriptional level. The correct regulation of miRNAs by TFs is critical, and increasing evidence indicates that aberrant regulation of miRNAs by TFs can cause phenotypic variations and diseases. Therefore, a TF-miRNA regulation database would be helpful for understanding the mechanisms by which TFs regulate miRNAs and understanding their contribution to diseases. In this study, we manually surveyed approximately 5000 reports in the literature and identified 243 TF-miRNA regulatory relationships, which were supported experimentally from 86 publications. We used these data to build a TF-miRNA regulatory database (TransmiR, http://cmbi.bjmu.edu.cn/transmir), which contains 82 TFs and 100 miRNAs with 243 regulatory pairs between TFs and miRNAs. In addition, we included references to the published literature (PubMed ID) information about the organism in which the relationship was found, whether the TFs and miRNAs are involved with tumors, miRNA function annotation and miRNA-associated disease annotation. TransmiR provides a user-friendly interface by which interested parties can easily retrieve TF-miRNA regulatory pairs by searching for either a miRNA or a TF.

The fact that microRNAs play a role in almost all biological processes is well established, as is the importance of recombination in generating genome variability. However, the association between microRNAs and recombination remains largely unknown. In order to investigate the recombination patterns of microRNAs, we performed a comprehensive analysis of the recombination rate of human microRNAs. We observed that microRNAs that are expressed in several tissues tend to have lower recombination rates than tissue-specific microRNAs. Additionally, microRNAs that are associated with a number of diseases are also likely to have lower recombination rates. Furthermore, microRNAs with higher expression levels are found to have fewer recombination events. These findings reveal patterns in recombination rates of microRNAs that could help in understanding the function, evolution, and disease-related roles of microRNAs.

Identifying the tissues in which a microRNA is expressed could enhance the understanding of the functions, the biological processes, and the diseases associated with that microRNA. However, the mechanisms of microRNA biogenesis and expression remain largely unclear and the identification of the tissues in which a microRNA is expressed is limited. Here, we present a machine learning based approach to predict whether an intronic microRNA show high co-expression with its host gene, by doing so, we could infer the tissues in which a microRNA is high expressed through the expression profile of its host gene. Our approach is able to achieve an accuracy of 79% in the leave-one-out cross validation and 95% on an independent testing dataset. We further estimated our method through comparing the predicted tissue specific microRNAs and the tissue specific microRNAs identified by biological experiments. This study presented a valuable tool to predict the co-expression patterns between human intronic microRNAs and their host genes, which would also help to understand the microRNA expression and regulation mechanisms. Finally, this framework can be easily extended to other species.

It has been reported that increasingly microRNAs are associated with diseases. However, the patterns among the microRNA-disease associations remain largely unclear. In this study, in order to dissect the patterns of microRNA-disease associations, we performed a comprehensive analysis to the human microRNA-disease association data, which is manually collected from publications. We built a human microRNA associated disease network. Interestingly, microRNAs tend to show similar or different dysfunctional evidences for the similar or different disease clusters, respectively. A negative correlation between the tissue-specificity of a microRNA and the number of diseases it associated was uncovered. Furthermore, we observed an association between microRNA conservation and disease. Finally, we uncovered that microRNAs associated with the same disease tend to emerge as predefined microRNA groups. These findings can not only provide help in understanding the associations between microRNAs and human diseases but also suggest a new way to identify novel disease-associated microRNAs.

MicroRNAs (miRNAs) modulate expression of their target genes in various tissues and at different developmental stages, but it is unclear whether they drive cross-species variation in gene expression. By comparing data from mammal and fly species we found that the cross-species expression variation of miRNA targets is significantly lower than that of other genes. This implies that miRNAs can affect gene expression by reducing stochastic noise, buffering cross-species variation and constraining evolutionary gene expression variation.

Over the past few years, microRNAs (miRNAs) have emerged as a new prominent class of gene regulatory factors that negatively regulate expression of approximately one-third of the genes in animal genomes at post-transcriptional level. However, it is still unclear why some genes are regulated by miRNAs but others are not, i.e. what principles govern miRNA regulation in animal genomes. In this study, we systematically analyzed the relationship between transcription factors (TFs) and miRNAs in gene regulation. We found that the genes with more TF-binding sites have a higher probability of being targeted by miRNAs and have more miRNA-binding sites on average. This observation reveals that the genes with higher cis-regulation complexity are more coordinately regulated by TFs at the transcriptional level and by miRNAs at the post-transcriptional level. This is a potentially novel discovery of mechanism for coordinated regulation of gene expression. Gene ontology analysis further demonstrated that such coordinated regulation is more popular in the developmental genes.

MicroRNAs (miRNAs) are endogenous approximately 22-nucleotide RNAs, which suppress gene expression by selectively binding to the 3'-noncoding region of specific messenger RNAs through base-pairing. Given the diversity and abundance of miRNA targets, miRNAs appear to functionally interact with various components of many cellular networks. By analyzing the interactions between miRNAs and a human cellular signaling network, we found that miRNAs predominantly target positive regulatory motifs, highly connected scaffolds and most downstream network components such as signaling transcription factors, but less frequently target negative regulatory motifs, common components of basic cellular machines and most upstream network components such as ligands. In addition, when an adaptor has potential to recruit more downstream components, these components are more frequently targeted by miRNAs. This work uncovers the principles of miRNA regulation of signal transduction networks and implies a potential function of miRNAs for facilitating robust transitions of cellular response to extracellular signals and maintaining cellular homeostasis.