miRNA Target Prediction Research Articles

In Silico Identification of Cassava Genome-Encoded MicroRNAs with Predicted Potential for Targeting the ICMV-Kerala Begomoviral Pathogen of Cassava.

Cassava mosaic disease (CMD) is caused by several divergent species belonging to the genus Begomovirus (Geminiviridae) transmitted by the whitefly Bemisia tabaci cryptic species group. In India and other parts of Asia, the Indian cassava mosaic virus-Kerala (ICMV-Ker) is an emergent begomovirus of cassava causing damage that results in reduced yield loss and tuber quality. Double-stranded RNA-mediated interference (RNAi) is an evolutionary conserved mechanism in eukaryotes and highly effective, innate defense system to inhibit plant viral replication and/or translation. The objective of this study was to identify and characterize cassava genome-encoded microRNAs (mes-miRNA) that are predicted to target ICMV-Ker ssDNA-encoded mRNAs, based on four in silico algorithms: miRanda, RNA22, Tapirhybrid, and psRNA. The goal is to deploy the predicted miRNAs to trigger RNAi and develop cassava plants with resistance to ICMV-Ker. Experimentally validated mature cassava miRNA sequences (n = 175) were downloaded from the miRBase biological database and aligned with the ICMV-Ker genome. The miRNAs were evaluated for base-pairing with the cassava miRNA seed regions and to complementary binding sites within target viral mRNAs. Among the 175 locus-derived mes-miRNAs evaluated, one cassava miRNA homolog, mes-miR1446a, was identified to have a predicted miRNA target binding site, at position 2053 of the ICMV-Ker genome. To predict whether the cassava miRNA might bind predicted ICMV-Ker mRNA target(s) that could disrupt viral infection of cassava plants, a cassava locus-derived miRNA-mRNA regulatory network was constructed using Circos software. The in silico-predicted cassava locus-derived mes-miRNA-mRNA network corroborated interactions between cassava mature miRNAs and the ICMV-Ker genome that warrant in vivo analysis, which could lead to the development of ICMV-Ker resistant cassava plants.

A passage-dependent network for estimating the in vitro senescence of mesenchymal stromal/stem cells using microarray, bulk and single cell RNA sequencing.

Long-term in vitro culture of human mesenchymal stem cells (MSCs) leads to cell lifespan shortening and growth stagnation due to cell senescence. Here, using sequencing data generated in the public domain, we have established a specific regulatory network of "transcription factor (TF)-microRNA (miRNA)-Target" to provide key molecules for evaluating the passage-dependent replicative senescence of mesenchymal stem cells for the quality control and status evaluation of mesenchymal stem cells prepared by different procedures. Short time-series expression miner (STEM) analysis was performed on the RNA-seq and miRNA-seq databases of mesenchymal stem cells from various passages to reveal the dynamic passage-related changes of miRNAs and mRNAs. Potential miRNA targets were predicted using seven miRNA target prediction databases, including TargetScan, miRTarBase, miRDB, miRWalk, RNA22, RNAinter, and TargetMiner. Then use the TransmiR v2.0 database to obtain experimental-supported transcription factor for regulating the selected miRNA. More than ten sequencing data related to mesenchymal stem cells or mesenchymal stem cells reprogramming were used to validate key miRNAs and mRNAs. And gene set variation analysis (GSVA) was performed to calculate the passage-dependent signature. The results showed that during the passage of mesenchymal stem cells, a total of 29 miRNAs were gradually downregulated and 210 mRNA were gradually upregulated. Enrichment analysis showed that the 29 miRNAs acted as multipotent regulatory factors of stem cells and participated in a variety of signaling pathways, including TGF-beta, HIPPO and oxygen related pathways. 210 mRNAs were involved in cell senescence. According to the target prediction results, the targets of these key miRNAs and mRNAs intersect to form a regulatory network of "TF-miRNA-Target" related to replicative senescence of cultured mesenchymal stem cells, across 35 transcription factor, 7 miRNAs (has-mir-454-3p, has-mir-196b-5p, has-mir-130b-5p, has-mir-1271-5p, has-let-7i-5p, has-let-7a-5p, and has-let-7b-5p) and 7 predicted targets (PRUNE2, DIO2, CPA4, PRKAA2, DMD, DDAH1, and GATA6). This network was further validated by analyzing datasets from a variety of mesenchymal stem cells subculture and lineage reprogramming studies, as well as qPCR analysis of early passages mesenchymal stem cells versus mesenchymal stem cells with senescence morphologies (SA-β-Gal+). The "TF-miRNA-Target" regulatory network constructed in this study reveals the functional mechanism of miRNAs in promoting the senescence of MSCs during in vitro expansion and provides indicators for monitoring the quality of functional mesenchymal stem cells during the preparation and clinical application.

Nf-core/circrna: a portable workflow for the quantification, miRNA target prediction and differential expression analysis of circular RNAs

BackgroundCircular RNAs (circRNAs) are a class of covalenty closed non-coding RNAs that have garnered increased attention from the research community due to their stability, tissue-specific expression and role as transcriptional modulators via sequestration of miRNAs. Currently, multiple quantification tools capable of detecting circRNAs exist, yet none delineate circRNA–miRNA interactions, and only one employs differential expression analysis. Efforts have been made to bridge this gap by way of circRNA workflows, however these workflows are limited by both the types of analyses available and computational skills required to run them.ResultsWe present nf-core/circrna, a multi-functional, automated high-throughput pipeline implemented in nextflow that allows users to characterise the role of circRNAs in RNA Sequencing datasets via three analysis modules: (1) circRNA quantification, robust filtering and annotation (2) miRNA target prediction of the mature spliced sequence and (3) differential expression analysis. nf-core/circrna has been developed within the nf-core framework, ensuring robust portability across computing environments via containerisation, parallel deployment on cluster/cloud-based infrastructures, comprehensive documentation and maintenance support.Conclusionnf-core/circrna reduces the barrier to entry for researchers by providing an easy-to-use, platform-independent and scalable workflow for circRNA analyses. Source code, documentation and installation instructions are freely available at https://nf-co.re/circrna and https://github.com/nf-core/circrna.

Genome-Wide Identification of BTB Domain-Containing Gene Family in Grapevine (Vitis vinifera L.)

BTB (broad-complex, tram track and bric-a-brac) proteins have broad functions in different growth processes and biotic and abiotic stresses. However, the biological role of these proteins has not yet been explored in grapevine, which draws our attention towards the BTB gene family. Herein, we identified 69 BTB genes (VvBTB) in the Vitis vinifera genome and performed comprehensive in silico analysis. Phylogenetic analysis classified VvBTB proteins into five groups, and further domain analysis revealed the presence of other additional functional domains. The majority of BTB proteins were localized in the nucleus. We also performed differential expression analysis by harnessing RNA- seq data of 10 developmental stages and different biotic and abiotic stresses. Our findings revealed the plausible roles of the BTB gene family in developmental stages; Fifty VvBTB were differentially expressed at different developmental stages. In addition, 47 and 16 VvBTB were responsive towards abiotic and biotic stresses, respectively. Interestingly, 13 VvBTB genes exhibited differential expression in at least one of the developmental stages and biotic and abiotic stresses. Further, miRNA target prediction of 13 VvBTB genes revealed that vvi-miR482 targets VvBTB56, and multiple miRNAs, such as vvi-miR172, vvi-miR169 and vvi-miR399, target VvBTB24, which provides an insight into the essential role of the BTB family in the grapevine. Our study provides the first comprehensive analysis and essential information that can potentially be used for further functional investigation of BTB genes in this economically important fruit crop.

DDX3-mediated miR-34 expression inhibits autophagy and HBV replication in hepatic cells.

HBV entry to the host cells and its successful infection depends on its ability to modulate the host restriction factors. DEAD box RNA helicase, DDX3, is shown to inhibit HBV replication. However, the exact mechanism of inhibition still remains unclear. DDX3 is involved in multitude or RNA metabolism processes including biogenesis of miRNAs. In this study, we sought to determine the mechanism involved in DDX3-mediated HBV inhibition. First, we observed that HBx protein of HBV downregulated DDX3 expression in HBV-infected cells. Overexpression of DDX3 inhibited HBx, HBsAg and total viral load, while its knockdown reversed the result in Hep G2.2.15 cells. Expression of miR-34 was downregulated in HBV-infected cells. Overexpression of pHBV1.3 further confirmed that HBV downregulates miR-34 expression. Consistent with the previous finding that DDX3 is involved in miRNA biogenesis, we observed that expression of miR-34 positively corelated with DDX3 expression. miRNA target prediction tools showed that miR-34 can target autophagy pathway which is hijacked by HBV for the benefit of its own replication. Indeed, transfection with miR-34 oligos downregulated the expression of autophagy marker proteins in HBV-expressing cells. Overexpression of DDX3 in HBV-expressing cells, downregulated expression of autophagy proteins while silencing of DDX3 reversed the results. These results led us to conclude that DDX3 upregulates miR-34 expression and thus inhibits autophagy in HBV-expressing cells while HBx helps HBV evade DDX3-mediated inhibition by downregulating DDX3 expression in HBV-infected cells.

P-TarPmiR accurately predicts plant-specific miRNA targets

microRNAs (miRNAs) are small non-coding ribonucleic acids that post-transcriptionally regulate gene expression through the targeting of messenger RNA (mRNAs). Most miRNA target predictors have focused on animal species and prediction performance drops substantially when applied to plant species. Several rule-based miRNA target predictors have been developed in plant species, but they often fail to discover new miRNA targets with non-canonical miRNA–mRNA binding. Here, the recently published TarDB database of plant miRNA–mRNA data is leveraged to retrain the TarPmiR miRNA target predictor for application on plant species. Rigorous experiment design across four plant test species demonstrates that animal-trained predictors fail to sustain performance on plant species, and that the use of plant-specific training data improves accuracy depending on the quantity of plant training data used. Surprisingly, our results indicate that the complete exclusion of animal training data leads to the most accurate plant-specific miRNA target predictor indicating that animal-based data may detract from miRNA target prediction in plants. Our final plant-specific miRNA prediction method, dubbed P-TarPmiR, is freely available for use at http://ptarpmir.cu-bic.ca. The final P-TarPmiR method is used to predict targets for all miRNA within the soybean genome. Those ranked predictions, together with GO term enrichment, are shared with the research community.

ERVWE1 Reduces Hippocampal Neuron Density and Impairs Dendritic Spine Morphology through Inhibiting Wnt/JNK Non-Canonical Pathway via miR-141-3p in Schizophrenia.

Human endogenous retroviruses (HERVs) are remnants of ancestral germline infections by exogenous retroviruses. Human endogenous retroviruses W family envelope gene (HERV-W env, also called ERVWE1), located on chromosome 7q21-22, encodes an envelope glycoprotein from the HERV-W family. Mounting evidence suggests that aberrant expression of ERVWE1 involves the etiology of schizophrenia. Moreover, the genetic and morphological studies indicate that dendritic spine deficits may contribute to the onset of schizophrenia. Here, we reported that ERVWE1 changed the density and morphology of the dendritic spine through inhibiting Wingless-type (Wnt)/c-Jun N-terminal kinases (JNK) non-canonical pathway via miR-141-3p in schizophrenia. In this paper, we found elevated levels of miR-141-3p and a significant positive correlation with ERVWE1 in schizophrenia. Moreover, serum Wnt5a and actin-related protein 2 (Arp2) levels decreased and demonstrated a significant negative correlation with ERVWE1 in schizophrenia. In vitro experiments disclosed that ERVWE1 up-regulated miR-141-3p expression by interacting with transcription factor (TF) Yin Yang 1 (YY1). YY1 modulated miR-141-3p expression by binding to its promoter. The luciferase assay revealed that YY1 enhanced the promoter activity of miR-141-3p. Using the miRNA target prediction databases and luciferase reporter assays, we demonstrated that miR-141-3p targeted Wnt5a at its 3' untranslated region (3' UTR). Furthermore, ERVWE1 suppressed the expression of Arp2 through non-canonical pathway, Wnt5a/JNK signaling pathway. In addition, ERVWE1 inhibited Wnt5a/JNK/Arp2 signal pathway through miR-141-3p. Finally, functional assays showed that ERVWE1 induced the abnormalities in hippocampal neuron morphology and spine density through inhibiting Wnt/JNK non-canonical pathway via miR-141-3p in schizophrenia. Our findings indicated that miR-141-3p, Wnt5a, and Arp2 might be potential clinical blood-based biomarkers or therapeutic targets for schizophrenia. Our work also provided new insight into the role of ERVWE1 in schizophrenia pathogenesis.

Determinants of Functional MicroRNA Targeting.

MicroRNAs (miRNAs) play cardinal roles in regulating biological pathways and processes, resulting in significant physiological effects. To understand the complex regulatory network of miRNAs, previous studies have utilized massivescale datasets of miRNA targeting and attempted to computationally predict the functional targets of miRNAs. Many miRNA target prediction tools have been developed and are widely used by scientists from various fields of biology and medicine. Most of these tools consider seed pairing between miRNAs and their mRNA targets and additionally consider other determinants to improve prediction accuracy. However, these tools exhibit limited prediction accuracy and high false positive rates. The utilization of additional determinants, such as RNA modifications and RNA-binding protein binding sites, may further improve miRNA target prediction. In this review, we discuss the determinants of functional miRNA targeting that are currently used in miRNA target prediction and the potentially predictive but unappreciated determinants that may improve prediction accuracy.

Insilco prediction of the role of the FriZZled5 gene in colorectal cancer

IntroductionIn this study, we aimed to elucidate the crosstalk between the Wnt/β-catenin signaling pathway and colorectal cancer (CRC) associated with inflammatory bowel disease (IBD) using a bioinformatics analysis of putative common biomarkers and a systems biology approach. Materials and methodsThe following criteria were used to search the GEO and ArrayExpress databases for terms related to CRC and IBD: 1. The dataset containing the transcriptomic data, and 2. Untreated samples by medications or drugs. A total of 42 datasets were selected for additional analysis. The GEO2R identified the differentially expressed genes. The genes involved in the Wnt signaling pathway were extracted from the KEGG database. Enrichment analysis and miRNA target prediction were conducted through the ToppGene online tool. ResultsIn CRC datasets, there were 1168 up- and 998 down-regulated probes, whereas, in IBD datasets, there were 256 up- and 200 down-regulated probes. There were 65 upregulated and 57 downregulated genes shared by CRC and IBD. According to KEGG, there were 166 genes in the Wnt pathway. FriZZled5 (FZD5) was a down-regulated gene in both CRC and IBD, as determined by the intersection of CRC- and IBD-related DEGs with the Wnt pathway. It was also demonstrated that miR-191, miR-885-5p, miR-378a-3p, and miR-396-3p affect the FriZZled5 gene expression. ConclusionIt is possible that increased expression of miR-191 and miR-885-5p, or decreased expression of miR-378a -3p and miR396-3, in IBD and CRC results in decreased expression of the FZD5 gene. Based on the function of this gene, FZD5 may be a potential therapeutic target in IBD that progresses to CRC.

Abstract C058: Deregulated microRNA-mRNA reciprocal pairs as novel precision biomarkers and therapeutic targets for African American prostate cancer

Abstract Prostate cancer (PCa) is the most frequently diagnosed cancer and second leading cause of cancer death among American men. Notably, African American (AA) men exhibit 1.6-fold higher incidence rate and 2.4-fold higher mortality rate when compared to European American (EA) men. Besides socioeconomic factors, accumulating genomic data suggest that intrinsic genetic risk elements also play critical roles in promoting PCa disparities. MicroRNAs (miRNAs) are involved in epigenetic mechanisms regulating mRNA expression in various human diseases, including cancers. In this study, we have applied a systems biology approach (by integrating mRNA and miRNA profiling data, target prediction, and pathway analysis) to identify critical signaling networks differentially regulated between AA and EA PCa. Using miRNA-drive algorithm mirPath V.3 coupled with mRNA mapping, and global test algorithm coupled with miRNA mapping, we identified several cancer pathways, such as ERBB, mTOR, HIF, and VEGF signaling, that are significantly regulated by AA-depleted/enriched miRNAs and mRNAs. Specifically, reciprocal miRNA-mRNA pairs miR-34a-5p/HIF1A, miR-34a-5p/PIK3CB, miR-34a-5p/IGFBP2, and miR-99b-5p/MTOR (downregulated/upregulated in AA vs. EA PCa), and miR-96-5p/MAPKAPK2 (upregulated/downregulated in AA vs. EA PCa) were identified as core miRNA/mRNA regulators in activation of mTOR and VEGF signaling in AA PCa. RT-qPCR, Western blotting, and immunohistochemistry assays in AA and EA PCa cell lines and patient samples have confirmed that these miRNAs and mRNAs are differentially expressed in AA and EA PCa. Furthermore, molecular targeting miRNA/mRNA pairings using miR-34a-5p, miR-99b-5p mimics and/or miR-96-5p antagomir consequently reduced cell proliferation and enhanced docetaxel-induced cytotoxicity in AA PCa cells. In summary, these results suggest that deregulated miRNA/mRNA reciprocal pairs play critical roles in promoting cancer aggressiveness and chemoresistance in AA PCa. Further development of these miRNA/mRNA pairings as precision diagnostic/prognostic biomarkers and novel therapeutic targets may pave a new path for PCa diagnosis and treatment. Citation Format: Himali Gujrati, Siyoung Ha, Bi-Dar Wang. Deregulated microRNA-mRNA reciprocal pairs as novel precision biomarkers and therapeutic targets for African American prostate cancer [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr C058.

Sequential expression of miR-221-3p and miR-338-3p in Schwann cells as a therapeutic strategy to promote nerve regeneration and functional recovery.

The functional properties of endogenous Schwann cells (SCs) during nerve repair are dynamic. Optimizing the functional properties of SCs at different stages of nerve repair may have therapeutic benefit in improving the repair of damaged nerves. Previous studies showed that miR-221-3p promotes the proliferation and migration of SCs, and miR-338-3p promotes the myelination of SCs. In this study, we established rat models of sciatic nerve injury by bridging the transected sciatic nerve with a silicone tube. We injected a miR-221 lentiviral vector system together with a doxycycline-inducible Tet-On miR-338 lentiviral vector system into the cavity of nerve conduits of nerve stumps to sequentially regulate the biological function of endogenous SCs at different stages of nerve regeneration. We found that the biological function of SCs was sequentially regulated, the diameter and density of myelinated axons were increased, the expression levels of NF200 and myelin basic protein were increased, and the function of injured peripheral nerve was improved using this system. miRNA Target Prediction Database prediction, Nanopore whole transcriptome sequencing, quantitative PCR, and dual luciferase reporter gene assay results predicted and verified Cdkn1b and Nrp1 as target genes of miR-221-3p and miR-338-3p, respectively, and their regulatory effects on SCs were confirmed in vitro. In conclusion, here we established a new method to enhance nerve regeneration through sequential regulation of biological functions of endogenous SCs, which establishes a new concept and model for the treatment of peripheral nerve injury. The findings from this study will provide direct guiding significance for clinical treatment of sciatic nerve injury.

Overview of Computational and Experimental Methods to Identify Tissue-Specific MicroRNA Targets.

As ubiquitous posttranscriptional regulators of gene expression, microRNAs (miRNAs) play key roles in cell physiology and function across taxa. In the last two decades, we have gained a good understanding about miRNA biogenesis pathways, modes of action, and consequences of miRNA-mediated gene regulation. More recently, research has focused on exploring causes for miRNA dysregulation, miRNA-mediated crosstalk between genes and signaling pathways, and the role of miRNAs in disease.This chapter discusses methods for the identification of miRNA-target interactions and causes for tissue-specific miRNA-target regulation. Computational approaches for predicting miRNA target sites and assessing tissue-specific target regulation are discussed. Moreover, there is an emphasis on features that affect miRNA target recognition and how high-throughput sequencing protocols can help in assessing miRNA-mediated gene regulation on a genome-wide scale. In addition, this chapter introduces some experimental approaches for the validation of miRNA targets as well as web-based resources sharing predicted and validated miRNA-target interactions.

MicroRNA-Target Identification: A Combinatorial In Silico Approach.

Contemporary computational target prediction tools with their distinctive properties and stringency have been playing a vital role in pursuing putative targets for a solitary miRNA or a subcategory of miRNAs. These tools utilize a defined set of probabilistic algorithms, machine learning techniques, and information of experimentally validated miRNA targets to provide the best selection. However, there are numerous false-positive predictions, and a method to choose an archetypal approach and put the data provided by the prediction tools into context is still lacking. Moreover, sensitivity, specificity, and overall efficiency of a single tool have not yet been achieved. Therefore, a systematic combination of selective online tools combining elementary and advanced factors of miRNA target identification might reinforce the current target prediction regime. The focus of this study was to build a comprehensive workflow by combining six available online tools to facilitate the current understanding of miRNA-target prediction.

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

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

Small RNA Targets: Advances in Prediction Tools and High-Throughput Profiling.

MicroRNAs (miRNAs) are an abundant class of small non-coding RNAs that regulate gene expression at the post-transcriptional level. They are suggested to be involved in most biological processes of the cell primarily by targeting messenger RNAs (mRNAs) for cleavage or translational repression. Their binding to their target sites is mediated by the Argonaute (AGO) family of proteins. Thus, miRNA target prediction is pivotal for research and clinical applications. Moreover, transfer-RNA-derived fragments (tRFs) and other types of small RNAs have been found to be potent regulators of Ago-mediated gene expression. Their role in mRNA regulation is still to be fully elucidated, and advancements in the computational prediction of their targets are in their infancy. To shed light on these complex RNA-RNA interactions, the availability of good quality high-throughput data and reliable computational methods is of utmost importance. Even though the arsenal of computational approaches in the field has been enriched in the last decade, there is still a degree of discrepancy between the results they yield. This review offers an overview of the relevant advancements in the field of bioinformatics and machine learning and summarizes the key strategies utilized for small RNA target prediction. Furthermore, we report the recent development of high-throughput sequencing technologies, and explore the role of non-miRNA AGO driver sequences.

MiRBind: A Deep Learning Method for miRNA Binding Classification

The binding of microRNAs (miRNAs) to their target sites is a complex process, mediated by the Argonaute (Ago) family of proteins. The prediction of miRNA:target site binding is an important first step for any miRNA target prediction algorithm. To date, the potential for miRNA:target site binding is evaluated using either co-folding free energy measures or heuristic approaches, based on the identification of binding 'seeds', i.e., continuous stretches of binding corresponding to specific parts of the miRNA. The limitations of both these families of methods have produced generations of miRNA target prediction algorithms that are primarily focused on 'canonical' seed targets, even though unbiased experimental methods have shown that only approximately half of in vivo miRNA targets are 'canonical'. Herein, we present miRBind, a deep learning method and web server that can be used to accurately predict the potential of miRNA:target site binding. We trained our method using seed-agnostic experimental data and show that our method outperforms both seed-based approaches and co-fold free energy approaches. The full code for the development of miRBind and a freely accessible web server are freely available.

Exosomal microRNAs in the DLK1-DIO3 imprinted region derived from cancer-associated fibroblasts promote progression of hepatocellular carcinoma by targeting hedgehog interacting protein.

Hepatocellular carcinoma (HCC) is the sixth most commonly diagnosed cancer and third leading cause of cancer-related death worldwide in 2020. Exosomes derived from cancer-associated fibroblasts (CAFs-exo) can promote tumor progression in various human cancers. However, the underlying regulatory mechanism controlling how CAFs-exo can promote HCC progression remains poorly understood. CAFs and para-cancer fibroblasts (PAFs) were isolated from HCC tissues and corresponding para-cancer tissues, then were cultured in vitro. CAFs and PAFs were characterized by immunofluorescence and western blot (WB) assays. Exosomes were isolated by ultracentrifugation, and characterized by transmission electron microscopy, nanoflow cytometry, and WB assay. The internalization of exosomes by HCC cells was observed under a fluorescence microscope. Cell Counting Kit-8 (CCK-8) assay was used to evaluate cell proliferation. Wound healing and transwell assays were used for migration and invasion experiments. RT-PCR assay was used to examine differentially expressed microRNAs (miRNAs) in exosomes and HCC cells. The TargetScan database was used to predict miRNA target genes. Hedgehog interacting protein (HHIP) expression analysis, prognostic analysis, and enrichment analysis of HHIP-related co-expressed genes were performed using the TIMER, UALCAN, Kaplan-Meier plotter, and LinkedOmics databases. CAFs-exo were internalized by HCC cells. CAFs-exo contributed to the aggressive phenotype of HCC cells, while inhibiting exosome secretion reversed these effects. Mechanistically, miRNAs in the DLK1-DIO3 imprinted region (miR-329-3p, miR-380-3p, miR-410-5p, miR-431-5p) were increased in HCC cells co-cultured with CAFs-exo compared with PAFs-exo. Expression of HHIP, a possible miR-431-5p target gene, was significantly downregulated in HCC cells. Low HHIP expression level in tumor tissues could predict poor prognosis in HCC patients. HHIP-related co-expressed genes were mainly associated with cell adhesion molecules. CAFs-exo can promote HCC progression by delivering miRNAs in the DLK1-DIO3 imprinted region to HCC cells, subsequently inhibiting HHIP expression. HHIP is a potential prognostic biomarker in HCC.

Genome-Wide Analysis of SQUAMOSA-Promoter-Binding Protein-like Family in Flowering Pleioblastus pygmaeus.

SQUAMOSA Promoter-Binding Protein-Like (SPL) family is well-known for playing an important role in plant growth and development, specifically in the reproductive process. Bamboo plants have special reproductive characteristics with a prolonged vegetative phase and uncertain flowering time. However, the underlying functions of SPL genes in reproductive growth are undisclosed in bamboo plants. In the study, a total of 28 SPLs were screened from an ornamental dwarf bamboo species, Pleioblastus pygmaeus. Phylogenetic analysis indicates that 183 SPLs from eight plant species can be classified into nine subfamilies, and the 28 PpSPLs are distributed among eight subfamilies. Homologous analysis shows that as many as 32 pairs of homologous genes were found between P. pygmaeus and rice, and 83 pairs were found between P. pygmaeus and Moso bamboo, whose Ka/Ks values are all <1. MiRNA target prediction reveals that 13 out of the 28 PpSPLs have recognition sites complementary to miRNA156. To screen the SPLs involved in the reproductive growth of bamboo plants, the mRNA abundance of the 28 PpSPLs was profiled in the different tissues of flowering P. pygmaeus and non-flowering plants by RNA-Seq. Moreover, the relative expression level of eight PpSPLs is significantly higher in flowering P. pygmaeus than that in non-flowering plants, which was also validated by RT-qPCR. Combined with phylogenetic analysis and homologous analysis, the eight significant, differentially expressed PpSPLs were identified to be associated with the reproductive process and flower organ development. Among them, there are four potential miRNA156-targeting PpSPLs involved in the flowering process. Of significant interest in the study is the identification of 28 SPLs and the exploration of four key flowering-related SPLs from P. pygmaeus, which provides a theoretic basis for revealing the underlying functions of SPLs in the reproductive growth of bamboo plants.

LncRNA KCNQ1OT1 accelerates ovarian cancer progression via miR-125b-5p/CD147 axis.

Ovarian cancer (OC) is one of the most common gynecological malignancies with a high incidence. Researches showed that lncRNA KCNQ1OT1 (KCNQ1OT1) was involved various tumors progression, including OC. However, the precise mechanism of KCNQ1OT1 in OC needs to be further clarified. For investigate the underlying mechanism of KCNQ1OT1 regulating OC progression. CCK-8 assay, colony formation assay, Transwell assay, Western blot and quantitative real-time PCR (qRT-PCR) were performed to examine viability, proliferation, migration and invasion, genes and proteins' level. To identify KCNQ1OT1 as a regulator of miR-125b-5p and miR-125b-5p as a regulator of CD147, we used miRNA target prediction algorithms, Pearson's correlation analysis and dual-luciferase reporter gene assay. KCNQ1OT1 was high expression and miR-125b-5p was low expression in OC, and KCNQ1OT1 was negatively correlated with that of miR-125b-5p in OC specimens. KCNQ1OT1 promoted OC cell proliferation and metastasis by binding to miR-125b-5p. miR-125b-5p targeted CD147, and which was negatively correlated with that of miR-125b-5p in OC specimens. KCNQ1OT1 was positively correlated with that of CD147 in OC specimens, and KCNQ1OT1 accelerated OC progression via miR-125b-5p/CD147 axis. KCNQ1OT1 accelerated OC progression via miR-125b-5p/CD147 axis indicating KCNQ1OT1 serve as a novel biomarker for OC treatment. Our research provides a new direction for OC treatment.

SCRAP: a bioinformatic pipeline for the analysis of small chimeric RNA-seq data.

MicroRNAs (miRNAs) are small non-coding RNAs (sncRNAs) that function in post-transcriptional gene regulation through imperfect base pairing with mRNA targets which results in inhibition of translation and typically destabilization of bound transcripts. Sequence-based algorithms historically used to predict miRNA targets face inherent challenges in reliably reflecting in vivo interactions. Recent strategies have directly profiled miRNA-target interactions by crosslinking and ligation of sncRNAs to their targets within the RNA-induced silencing complex (RISC), followed by high throughput sequencing of the chimeric sncRNA:target RNAs. Despite the strength of these direct profiling approaches, standardized pipelines for effectively analyzing the resulting chimeric sncRNA:target RNA sequencing data are not readily available. Here we present SCRAP, a robust Small Chimeric RNA Analysis Pipeline for the bioinformatic processing of chimeric sncRNA:target RNA sequencing data. SCRAP consists of two parts, each of which are specifically optimized for the distinctive characteristics of chimeric small RNA sequencing reads: first, read processing and alignment and second, peak calling and annotation. We apply SCRAP to benchmark chimeric sncRNA:target RNA sequencing datasets generated by distinct molecular approaches, and compare SCRAP to existing chimeric RNA analysis pipelines. SCRAP has minimal hardware requirements, is cross-platform, and contains extensive annotation to broaden accessibility for processing small chimeric RNA sequencing data and enable insights about the targets of small non-coding RNAs in regulating diverse biological systems.