miRTarBase 2020: updates to the experimentally validated microRNA–target interaction database

Huang, Hsi‐Yuan; Lin, Yang-Chi-Dung; Li, Jing; Huang, Kai-Yao; Shrestha, Sirjana; Hong, Hsiao-Chin; Tang, Yun; Chen, Yigang; Jin, Chen-Nan; Yu, Yuan; Xu, Jianhong; Li, Yueming; Cai, Xiaoxuan; Zhou, Zhenyu; Chen, Xiao-Hang; Pei, Yuanyuan; Hu, Liang; Su, Jinjiang; Cui, Shidong; Wang, Fei; Xie, Yueyang; Ding, Si-Yuan; Luo, Meng-Fan; Chou, Chih‐Hung; Chang, Nen Chung; Chen, Kaiwen; Cheng, Yu-Hsiang; Wan, Xinhong; Hsu, Wen-Lian; Lee, Tzong-Yi; Wei, Fengxiang; Huang, Hsien-Da

doi:10.1093/nar/gkz896

Cited by 958 publications

(998 citation statements)

References 58 publications

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“…Novel datasets were obtained to build our enrichment categories, consisting of Gene Ontology [25], miRTarBase 8.0 [15], KEGG [26], miRandola 2017 [22], miRPathDB 2.0 [16], TissueAtlas [17], MNDR v2.0 [19], NPInter 4.0 [27], RNALocate v2.0 [21], TAM 2.0 [13], and TransmiR v2.0 [20]. Other pre-existing datasets have been updated, including HMDD v3.0 [18] and miRBase v22.1 [28].…”

Section: Data Collectionmentioning

confidence: 99%

“…All kinds of enrichment tools rely on high quality sets of miRNA categories that were either obtained by curation of scientific literature or collected from specific databases. For instance, curated miRNA annotations can be obtained from miRBase or miRCarta [14], miRNA-target interactions from miRTarBase [15], miRNA-pathway associations from miRPathDB [16], tissuespecific miRNAs from the human TissueAtlas [17], or miRNA-disease associations from HMDD [18] or MNDR [19], many of which were updated in the last two years. Further specialised annotations like miRNA and transcription factor interactions provided by TransmiR [20], miRNA sub-cellular localisations collected in RNALocate [21], or extra-cellular circulating miRNAs contained in miRandola [22] provide target categories for integrated enrichment analysis.…”

Section: Introductionmentioning

confidence: 99%

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miEAA 2.0: Integrating multi-species microRNA enrichment analysis and workflow management systems

Kern

Fehlmann

Solomon

et al. 2020

Preprint

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AbstractGene set enrichment analysis has become one of the most frequently used applications in molecular biology research. Originally developed for gene sets, the same statistical principles are now available for all omics types. In 2016, we published the miRNA enrichment analysis and annotation tool (miEAA) for human precursor and mature miRNAs.Here, we present miEAA 2.0, supporting miRNA input from Homo sapiens, Mus musculus, and Rattus norvegicus. To facilitate inclusion of miEAA in workflow systems, we implemented an Application Programming Interface (API). Users can perform miRNA set enrichment analysis using either the web-interface, a dedicated Python package, or custom remote clients. Moreover, the number of category sets was raised by an order of magnitude. We implemented novel categories like annotation confidence level or localisation in biological compartments. In combination with the miR-Base miRNA-version and miRNA-to-precursor converters, miEAA supports research settings where older releases of miRBase are in use. The web server also offers novel comprehensive visualisations such as heatmaps and running sum curves with background distributions. Lastly, additional methods to correct for multiple hypothesis testing were implemented. We demonstrate the new features using case studies for human kidney cancer and mouse samples. The tool is freely accessible at: https://www.ccb.uni-saarland.de/mieaa2.

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Section: Data Collectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

miEAA 2.0: Integrating multi-species microRNA enrichment analysis and workflow management systems

Kern

Fehlmann

Solomon

et al. 2020

Preprint

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“…We extracted the experimentally validated target genes of human miRNAs from miRTarBase database [46].…”

Section: Obtaining Human Mirnas Target Genesmentioning

confidence: 99%

Lung biopsy cells transcriptional landscape from COVID-19 patient stratified lung injury in SARS-CoV-2 infection through impaired pulmonary surfactant metabolism

Islam

Khan

2020

Preprint

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Clinical management of COVID-19 is still complicated due to the lack of therapeutic interventions to reduce the breathing problems, respiratory complications and acute lung injury -which are the major complications of most of the mild to critically affected patients and the molecular mechanisms behind these clinical features are still largely unknown. In this study, we have used the RNA-seq gene expression pattern in the COVID-19 affected lung biopsy cells and compared it with the effects observed in typical cell lines infected with SARS-CoV-2 and SARS-CoV. We performed functional overrepresentation analyses using these differentially expressed genes to signify the processes/pathways which could be deregulated during SARS-CoV-2 infection resulting in the symptomatic impairments observed in COVID-19. Our results showed that the significantly altered processes include inflammatory responses, antiviral cytokine signaling, interferon responses, and interleukin signaling etc. along with downmodulated processes related to lung's functionality likeresponses to hypoxia, lung development, respiratory processes, cholesterol biosynthesis and surfactant metabolism. We also found that the viral protein interacting host's proteins involved in similar pathways like: respiratory failure, lung diseases, asthma, and hypoxia responses etc., suggesting viral proteins might be deregulating the processes related to acute lung injury/breathing complications in COVID-19 patients. Protein-protein interaction networks of these processes and map of gene expression of deregulated genes revealed that several viral proteins can directly or indirectly modulate the host genes/proteins of those lung related processes along with several host transcription factors and miRNAs. Surfactant proteins and their regulators SPD, SPC, TTF1 etc. which maintains the stability of the pulmonary tissue are found to be downregulated through viral NSP5, NSP12 that could lead to deficient gaseous exchange by the surface films. Mitochondrial dysfunction owing to the aberration of NDUFA10, NDUFAF5, SAMM50 etc. by NSP12; abnormal thrombosis in lungs through atypical PLAT, EGR1 functions by viral ORF8, NSP12; dulled hypoxia responses due to unusual shift in HIF-1 downstream signaling might be the causative elements behind the acute lung injury in COVID-19 patients. Our study put forward a distinct mechanism of probable virus induced lung damage apart from cytokine storm and advocate the need of further research for alternate therapy in this direction.

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“…MiRTarBase uses curated data from over 10,000 publications to make validated predictions on miRNA-target interactions (MTIs) (42,43). Out of 1154 upregulated genes in human Ishikawa DICER1 -/cells, 885 were MTIs for the 193 downregulated miRNAs.…”

Section: Unique Transcriptomic Profile With Loss Of Two Alleles Of DImentioning

confidence: 99%

PtenandDicer1loss causes poorly-differentiated endometrial adenocarcinoma in mice

Wang

Wendel

Emerson

et al. 2020

Preprint

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Endometrial cancer remains the most common gynecological malignancy in the UnitedStates. While the loss of the tumor suppressor, PTEN (phosphatase and tensin homolog), is well studied in endometrial cancer, recent studies suggest that DICER1, the endoribonuclease responsible for miRNA genesis, also plays a significant role in endometrial adenocarcinoma. In an endometrial adenocarcinoma mouse model, which has a conditional uterine deletion of Pten, Dicer1 was also conditionally deleted.Conditional uterine deletion of Dicer1 and Pten resulted in high-penetrance, poorlydifferentiated endometrial adenocarcinomas. Poorly-differentiated endometrial adenocarcinomas expressed known markers of clear-cell adenocarcinoma, including Napsin A and HNF1B (hepatocyte nuclear factor 1 homeobox B). Adenocarcinomas were hormone-independent, and treatment with long-term progesterone did not mitigate poorly-differentiated adenocarcinoma, nor did it affect adnexal metastasis.Transcriptomic analyses of uteri or Ishikawa cells with deletion of DICER1 revealed unique transcriptomic profiles and global downregulation of miRNAs. Integration of downregulated miRNAs with upregulated mRNA targets revealed deregulated let-7 and miR-16 target genes, similar to published human DICER1-mutant endometrial cancers from TCGA (The Cancer Genome Atlas). Importantly, these miRNA-target genes, involved in ephrin-receptor and transforming growth factor-beta signaling, represent potential clinical targets for rare, yet deadly, poorly-differentiated endometrial adenocarcinomas in women. This mouse model represents poorly-differentiated endometrial adenocarcinoma and will allow for the discovery of novel mechanisms of hormone-independent endometrial adenocarcinoma from atrophic endometrium. Significance StatementEndometrial cancer is one of the few cancers with an increasing death rate in the United States. The most significant risk factor associated with death is high tumor grade, which occurs most frequently in postmenopausal women, where it develops within an atrophic endometrium. Here, we present a mouse model with conditional deletion of Dicer1, a key enzyme in miRNA genesis, and Pten, a tumor suppressor, that develops poorlydifferentiated, steroid hormone-independent, endometrial adenocarcinoma with adnexal metastasis. These high-grade adenocarcinomas develop from an atrophic endometrium and share molecular features with DICER1-mutant human endometrial adenocarcinomas. We anticipate that this preclinical model represents a move toward the discovery of novel mechanisms of hormone-independent development of endometrial adenocarcinoma from atrophic endometrium.

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miRTarBase 2020: updates to the experimentally validated microRNA–target interaction database

Cited by 958 publications

References 58 publications

miEAA 2.0: Integrating multi-species microRNA enrichment analysis and workflow management systems

miEAA 2.0: Integrating multi-species microRNA enrichment analysis and workflow management systems

Lung biopsy cells transcriptional landscape from COVID-19 patient stratified lung injury in SARS-CoV-2 infection through impaired pulmonary surfactant metabolism

PtenandDicer1loss causes poorly-differentiated endometrial adenocarcinoma in mice

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