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Scientific Reports May 2023Accumulating evidence shows that pseudogenes can function as microRNAs (miRNAs) sponges and regulate gene expression. Mining potential interactions between pseudogenes...
Accumulating evidence shows that pseudogenes can function as microRNAs (miRNAs) sponges and regulate gene expression. Mining potential interactions between pseudogenes and miRNAs will facilitate the clinical diagnosis and treatment of complex diseases. However, identifying their interactions through biological experiments is time-consuming and labor intensive. In this study, an ensemble learning framework with similarity kernel fusion is proposed to predict pseudogene-miRNA associations, named ELPMA. First, four pseudogene similarity profiles and five miRNA similarity profiles are measured based on the biological and topology properties. Subsequently, similarity kernel fusion method is used to integrate the similarity profiles. Then, the feature representation for pseudogenes and miRNAs is obtained by combining the pseudogene-pseudogene similarities, miRNA-miRNA similarities. Lastly, individual learners are performed on each training subset, and the soft voting is used to yield final decision based on the prediction results of individual learners. The k-fold cross validation is implemented to evaluate the prediction performance of ELPMA method. Besides, case studies are conducted on three investigated pseudogenes to validate the predict performance of ELPMA method for predicting pseudogene-miRNA interactions. Therefore, all experiment results show that ELPMA model is a feasible and effective tool to predict interactions between pseudogenes and miRNAs.
Topics: MicroRNAs; Pseudogenes; Machine Learning; Computational Biology; Algorithms
PubMed: 37258695
DOI: 10.1038/s41598-023-36054-y -
Nature Communications Mar 2020Tumor cells often reprogram their metabolism for rapid proliferation. The roles of long noncoding RNAs (lncRNAs) in metabolism remodeling and the underlying mechanisms...
Tumor cells often reprogram their metabolism for rapid proliferation. The roles of long noncoding RNAs (lncRNAs) in metabolism remodeling and the underlying mechanisms remain elusive. Through screening, we found that the lncRNA Actin Gamma 1 Pseudogene (AGPG) is required for increased glycolysis activity and cell proliferation in esophageal squamous cell carcinoma (ESCC). Mechanistically, AGPG binds to and stabilizes 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3). By preventing APC/C-mediated ubiquitination, AGPG protects PFKFB3 from proteasomal degradation, leading to the accumulation of PFKFB3 in cancer cells, which subsequently activates glycolytic flux and promotes cell cycle progression. AGPG is also a transcriptional target of p53; loss or mutation of TP53 triggers the marked upregulation of AGPG. Notably, inhibiting AGPG dramatically impaired tumor growth in patient-derived xenograft (PDX) models. Clinically, AGPG is highly expressed in many cancers, and high AGPG expression levels are correlated with poor prognosis, suggesting that AGPG is a potential biomarker and cancer therapeutic target.
Topics: Animals; Cell Line, Tumor; Cell Proliferation; Cellular Reprogramming; Esophageal Squamous Cell Carcinoma; Female; Gene Knockout Techniques; Glycolysis; Humans; Mice, Inbred BALB C; Mice, Nude; Phosphofructokinase-2; Pseudogenes; RNA, Long Noncoding; Up-Regulation; Xenograft Model Antitumor Assays
PubMed: 32198345
DOI: 10.1038/s41467-020-15112-3 -
Methods in Molecular Biology (Clifton,... 2021Pseudogenes have long been considered nonfunctional elements. The influx of large-scale sequencing projects over the last decade have provided rich sources of evidence...
Pseudogenes have long been considered nonfunctional elements. The influx of large-scale sequencing projects over the last decade have provided rich sources of evidence that pseudogenes can play key evolutionary and regulatory roles, highlighting the need for high quality annotation for both human and key model organisms. To date, GENCODE has completed the manual annotation of pseudogenes in human and has undertaken the task to curate and characterize pseudogenes in the mouse reference genome. Capitalizing on available high-quality annotations as well as on the functional-genomics, evolutionary, and phenotypical data, we were able to create a comprehensive picture of both the human and mouse pseudogene complements' creation, development, and activity. Thus, we found that while human pseudogenes were created through a single burst of retrotransposition events, the active transposable element content in mouse allows for a continuous renewal of the pseudogene pool. Despite their differences, the two organisms share a number of similarities in terms of pseudogene activity, with ~10% of pseudogenes being transcribed. Finally, we highlight a variety of resources developed based on the available GENCODE annotations that help shed light on pseudogene biology.
Topics: Animals; Computational Biology; Databases, Genetic; Evolution, Molecular; Genomics; Humans; Mice; Molecular Sequence Annotation; Pseudogenes; Retroelements; Sequence Analysis, DNA; Transcription, Genetic
PubMed: 34165709
DOI: 10.1007/978-1-0716-1503-4_5 -
Pathology, Research and Practice Jan 2024This review examines and compares the diagnostic and prognostic capabilities of miRNAs and lncRNAs derived from pseudogenes in cancer patients. Additionally, it delves... (Review)
Review
This review examines and compares the diagnostic and prognostic capabilities of miRNAs and lncRNAs derived from pseudogenes in cancer patients. Additionally, it delves into their roles in cancer pathogenesis. Both miRNAs and pseudogene-derived lncRNAs have undergone thorough investigation as remarkably sensitive and specific cancer biomarkers, offering significant potential for cancer detection and monitoring. . Extensive research is essential to gain a complete understanding of the precise roles these non-coding RNAs play in cancer, allowing the development of novel targeted therapies and biomarkers for improved cancer detection and treatment approaches.
Topics: Humans; MicroRNAs; RNA, Long Noncoding; Pseudogenes; Neoplasms; Prognosis; Biomarkers, Tumor
PubMed: 38128189
DOI: 10.1016/j.prp.2023.155014 -
Journal of Cellular Physiology Dec 2019The pseudogene DUXAP10 is overexpressed in numerous types of human cancers. However, the diagnostic and prognostic value of DUXAP10 in cancers has yet to be...
The pseudogene DUXAP10 is overexpressed in numerous types of human cancers. However, the diagnostic and prognostic value of DUXAP10 in cancers has yet to be characterized. PubMed, EMBASE, Web of Science, the Cancer Genome Atlas (TCGA), and Gene Expression Omnibus databases were comprehensively searched in this study. A total of 50 studies comprising 11,292 patients were collected in this integrated analysis. DUXAP10 was confirmed to be significantly overexpressed in various human cancers (p < .05). Summary receiver operating characteristic (SROC) curve analysis was implemented, which indicated that DUXAP10 was a potential diagnostic biomarker for human cancers (area under the curve [AUC] of SROC curve = 0.81 [0.77-0.84]; pooled sensitivity = 0.69 [0.62-0.75]; pooled specificity = 0.81 [0.73-0.87]). In addition, hazard ratios (HRs) with 95% confidence intervals (CIs) were obtained to evaluate the association of DUXAP10 expression with overall survival (OS) time of cancer patients. Outcomes of meta-analysis suggested that upregulation of DUXAP10 was closely associated with poor OS (pooled HR = 1.11 [1.03-1.18]). Our study revealed that the pseudogene DUXAP10 was upregulated in multiple types of cancers and could be a potential biomarker with good diagnostic and prognostic value for human cancers.
Topics: Biomarkers, Tumor; Databases, Genetic; Gene Expression Regulation, Neoplastic; Humans; Neoplasms; Prognosis; Pseudogenes; RNA, Long Noncoding
PubMed: 31169303
DOI: 10.1002/jcp.28937 -
BMC Genomics 2015Over the last decade, methods have been developed for the reconstruction of gene trees that take into account the species tree. Many of these methods have been based on...
Over the last decade, methods have been developed for the reconstruction of gene trees that take into account the species tree. Many of these methods have been based on the probabilistic duplication-loss model, which describes how a gene-tree evolves over a species-tree with respect to duplication and losses, as well as extension of this model, e.g., the DLRS (Duplication, Loss, Rate and Sequence evolution) model that also includes sequence evolution under relaxed molecular clock. A disjoint, almost as recent, and very important line of research has been focused on non protein-coding, but yet, functional DNA. For instance, DNA sequences being pseudogenes in the sense that they are not translated, may still be transcribed and the thereby produced RNA may be functional.
Topics: DNA; Evolution, Molecular; Gene Duplication; Phylogeny; Pseudogenes
PubMed: 26449131
DOI: 10.1186/1471-2164-16-S10-S12 -
Nature Methods Apr 2015HISAT (hierarchical indexing for spliced alignment of transcripts) is a highly efficient system for aligning reads from RNA sequencing experiments. HISAT uses an...
HISAT (hierarchical indexing for spliced alignment of transcripts) is a highly efficient system for aligning reads from RNA sequencing experiments. HISAT uses an indexing scheme based on the Burrows-Wheeler transform and the Ferragina-Manzini (FM) index, employing two types of indexes for alignment: a whole-genome FM index to anchor each alignment and numerous local FM indexes for very rapid extensions of these alignments. HISAT's hierarchical index for the human genome contains 48,000 local FM indexes, each representing a genomic region of ∼64,000 bp. Tests on real and simulated data sets showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method. Despite its large number of indexes, HISAT requires only 4.3 gigabytes of memory. HISAT supports genomes of any size, including those larger than 4 billion bases.
Topics: Humans; Limit of Detection; Pseudogenes; Sequence Alignment; Sequence Analysis, DNA; Sequence Analysis, RNA
PubMed: 25751142
DOI: 10.1038/nmeth.3317 -
Proceedings of the National Academy of... May 2011Pseudogenes have been shown to acquire unique regulatory roles from more and more organisms. We report the observation of a cluster of siRNAs derived from pseudogenes of...
Pseudogenes have been shown to acquire unique regulatory roles from more and more organisms. We report the observation of a cluster of siRNAs derived from pseudogenes of African Trypanosoma brucei using high through-put analysis. We show that these pseudogene-derived siRNAs suppress gene expression through RNA interference. The discovery that siRNAs may originate from pseudogenes and regulate gene expression in a unicellular eukaryote provides insights into the functional roles of pseudogenes and into the origin of noncoding small RNAs.
Topics: Gene Expression Regulation; Genes, Protozoan; Pseudogenes; RNA, Small Interfering; Trypanosoma brucei brucei
PubMed: 21531904
DOI: 10.1073/pnas.1103894108 -
Oxidative Medicine and Cellular... 2022Research over the past decade has suggested important roles for pseudogenes in gliomas. Our previous study found that the RPL4P4 pseudogene is highly expressed in...
OBJECTIVE
Research over the past decade has suggested important roles for pseudogenes in gliomas. Our previous study found that the RPL4P4 pseudogene is highly expressed in gliomas. However, its biological function in gliomas remains unclear.
METHODS
In this study, we analyzed clinical data on patients with glioma obtained from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), the Genotype-Tissue Expression (GTEx), and the GEPIA2 databases. We used the R language for the main analysis. Correlations among RPL4P4 expression, pathological characteristics, clinical outcome, and biological function were evaluated. In addition, the correlations of RPL4P4 expression with immune cell infiltration and glioma progression were analyzed. Finally, wound healing, Transwell, and CCK-8 assays were performed to analyze the function of RPL4P4 in glioma cells.
RESULT
We found that RPL4P4 is highly expressed in glioma tissues and is associated with poor prognosis, IDH1 wild type, codeletion of 1p19q, and age. Multivariate analysis and the nomogram model showed that high RPL4P4 expression was an independent risk factor for glioma prognosis and had better prognostic prediction power. Moreover, high RPL4P4 expression correlated with immune cell infiltration, which showed a significant positive association with M2-type macrophages. Finally, RPL4P4 knockdown in glioma cell lines caused decreased glioma cell proliferation, invasion, and migration capacity.
CONCLUSION
Our data suggest that RPL4P4 can function as an independent prognostic predictor of glioma. It also shows that RPL4P4 expression correlates with immune cell infiltration and that targeting RPL4P4 may be a new strategy for the treatment of glioma patients.
Topics: Biomarkers; Brain Neoplasms; Glioma; Humans; Prognosis; Pseudogenes; Ribosomal Proteins
PubMed: 35993018
DOI: 10.1155/2022/7967722 -
Aging Dec 2019Ovarian cancer is one of the most common and lethal cancer types in women. The molecular mechanism of ovarian cancer progression is still unclear.
OBJECTIVE
Ovarian cancer is one of the most common and lethal cancer types in women. The molecular mechanism of ovarian cancer progression is still unclear.
RESULTS
Here, we first reported that expression levels of three genes, GJB2, S100A2 and SPOCK2, were significantly higher in advanced stage than that in early stage of ovarian cancer, and upregulation of them indicated poor prognosis of patients with ovarian cancer. Subsequently, 8, 6 and 20 miRNAs were predicted to target GJB2, S100A2 and SPOCK2, respectively. Among these miRNA-mRNA pairs, hsa-miR-363-3p-SPOCK2 axis was the most potential in suppressing progression of ovarian cancer. Mechanistically, we found that hsa-miR-363-3p-SPOCK2 axis was involved in regulation of actin cytoskeleton. Moreover, 6 pseudogenes and 8 lncRNAs were identified to potentially inhibit hsa-miR-363-3p-SPOCK2 axis in ovarian cancer.
CONCLUSIONS
Collectively, we elucidate a regulatory role of pseudogene/lncRNA-hsa-miR-363-3p-SPOCK2 pathway in progression of ovarian cancer, which may provide effective therapeutic approaches and promising prognostic biomarkers for ovarian cancer.
MATERIALS AND METHODS
Differentially expressed genes (DEGs) in ovarian cancer were first screened using GSE12470, after which DEGs expression were validated using GEPIA. Kaplan-Meier analysis was employed to assess the prognostic values. Potential miRNAs were predicted by seven target prediction databases, and upstream lncRNAs and pseudogenes of hsa-miR-363-3p were forecasted through miRNet or starBase. UALCAN and starBase were used to obtain the co-expressed genes of SPOCK. Enrichment analysis for these co-expressed genes was performed by Enrichr.
Topics: Female; Gene Expression Regulation, Neoplastic; Humans; MicroRNAs; Oligonucleotide Array Sequence Analysis; Ovarian Neoplasms; Proteoglycans; Pseudogenes; RNA, Long Noncoding; Transcriptome
PubMed: 31794425
DOI: 10.18632/aging.102538