• Gene duplication
• Genetic complexity
• Neofunctionalization
• Non-functionalization
• Protein-encoding genes
• Subfunctionalization
• Zebrafish

• Animals
• Zebrafish/genetics
• Zebrafish/metabolism
• Gene Duplication
• Evolution, Molecular
• Genes, Duplicate
• Gene Regulatory Networks

• R15 HD098969 NICHD NIH HHS
• R15HD098969 Eunice Kennedy Shriver National Institute of Child Health and Human Development

• COPD
• Inflammation
• circCeNETs
• circRNAs
• ncRNAs

• Pulmonary Disease, Chronic Obstructive/genetics
• Humans
• RNA, Circular/genetics
• Gene Regulatory Networks
• MicroRNAs/genetics
• Animals
• Biomarkers/metabolism
• Epithelial-Mesenchymal Transition/genetics
• RNA, Competitive Endogenous

• MicroRNA (miR)
• breast cancer (BC)
• competing endogenous RNA (ceRNA)
• ethical and legal challenges
• non-coding RNA
• personalized medicine

• breast cancer
• long non-coding rnas

• Humans
• Female
• Breast Neoplasms/genetics
• Pseudogenes/genetics
• RNA, Competitive Endogenous
• MicroRNAs/genetics
• MCF-7 Cells

Noncoding RNAs have been shown with powerful ability in post-transcriptional regulation, enabling intertwined RNA crosstalk and global molecular interaction in a large amount of dysfunctional conditions including cancer. Competing endogenous RNAs (ceRNAs) are those competitively binding with shared microRNAs (miRNAs), freeing their counterparts from miRNA-induced degradation, thus actively influencing and connecting with each other. Constantly updated analytical approaches boost outstanding advancement achieved in this burgeoning hotspot in multilayered intracellular communication, providing new insights into pathogenesis and clinical treatment. Here, we summarize the mechanisms and correlated factors under this RNA interplay and deregulated transcription profile in neoplasm and tumor progression, underscoring the great significance of ceRNAs for diagnostic values, monitoring biomarkers, and prognosis evaluation in cancer.

• ANXA2P2
• Norcantharidin
• Pathological scars
• STAT3
• UBAP2L

• Cancer
• ESC-GEMM
• Genetically engineered mouse model
• Pseudogene

• Animals
• Cell Line, Tumor
• Drug Resistance, Microbial/genetics
• Embryonic Stem Cells
• Gene Expression Regulation
• Genes, Synthetic
• Heterografts
• Humans
• Mice
• Mice, Transgenic
• Molecular Targeted Therapy
• Neoplasm Transplantation
• Neoplasms, Experimental/genetics
• Promoter Regions, Genetic
• Pseudogenes/genetics
• RNA Interference
• Recombinant Proteins/biosynthesis
• Recombinant Proteins/genetics
• Species Specificity
• Tetracycline/pharmacology
• Up-Regulation

• HMGA1 pseudogenes
• ceRNA
• transgenic mouse models

Gene duplication is a major driver of organismal evolution. One of the main mechanisms of gene duplications is retroposition, a process in which mRNA is first transcribed into DNA and then reintegrated into the genome. Most gene retrocopies are depleted of the regulatory regions. Nevertheless, examples of functional retrogenes are rapidly increasing. These functions come from the gain of new spatio-temporal expression patterns, imposed by the content of the genomic sequence surrounding inserted cDNA and/or by selectively advantageous mutations, which may lead to the switch from protein coding to regulatory RNA. As recent studies have shown, these genes may lead to new protein domain formation through fusion with other genes, new regulatory RNAs or other regulatory elements. We utilized existing data from high-throughput technologies to create a complex description of retrogenes functionality. Our analysis led to the identification of human retroposed genes that substantially contributed to transcriptome and proteome. These retrocopies demonstrated the potential to encode proteins or short peptides, act as cis- and trans- Natural Antisense Transcripts (NATs), regulate their progenitors’ expression by competing for the same microRNAs, and provide a sequence to lncRNA and novel exons to existing protein-coding genes. Our study also revealed that retrocopies, similarly to retrotransposons, may act as recombination hot spots. To our best knowledge this is the first complex analysis of these functions of retrocopies.

• antisense transcript
• lncRNA
• miRNA sponge
• pseudogenes
• recombination.
• retroposition

• classification
• diagnosis
• function
• prognosis
• pseudogene
• therapeutics

Long thought “relics” of evolution, not until recently have pseudogenes been of medical interest regarding regulation in cancer. Often, these regulatory roles are a direct by-product of their close sequence homology to protein-coding genes. Novel pseudogene-gene (PGG) functional associations can be identified through the integration of biomedical data, such as sequence homology, functional pathways, gene expression, pseudogene expression, and microRNA expression. However, not all of the information has been integrated, and almost all previous pseudogene studies relied on 1:1 pseudogene–parent gene relationships without leveraging other homologous genes/pseudogenes.

We produce PGG families that expand beyond the current 1:1 paradigm. First, we construct expansive PGG databases by (i) CUDAlign graphics processing unit (GPU) accelerated local alignment of all pseudogenes to gene families (totaling 1.6 billion individual local alignments and >40,000 GPU hours) and (ii) BLAST-based assignment of pseudogenes to gene families. Second, we create an open-source web application (PseudoFuN [Pseudogene Functional Networks]) to search for integrative functional relationships of sequence homology, microRNA expression, gene expression, pseudogene expression, and gene ontology. We produce four “flavors” of CUDAlign-based databases (>462,000,000 PGG pairwise alignments and 133,770 PGG families) that can be queried and downloaded using PseudoFuN. These databases are consistent with previous 1:1 PGG annotation and also are much more powerful including millions of de novo PGG associations. For example, we find multiple known (e.g., miR-20a-PTEN-PTENP1) and novel (e.g., miR-375-SOX15-PPP4R1L) microRNA-gene-pseudogene associations in prostate cancer. PseudoFuN provides a “one stop shop” for identifying and visualizing thousands of potential regulatory relationships related to pseudogenes in The Cancer Genome Atlas cancers.

Thousands of new PGG associations can be explored in the context of microRNA-gene-pseudogene co-expression and differential expression with a simple-to-use online tool by bioinformaticians and oncologists alike.

• competing endogenous RNA
• database
• functional prediction
• gene regulation
• graphics processing unit
• high-performance computing
• network analysis
• pseudogenes

• Competing endogenous RNAs
• RNA-RNA crosstalk
• Shared MREs
• Sponge effect
• ceRNETs
• miRNAs

• Animals
• Gene Regulatory Networks
• Gene Silencing
• Humans
• MicroRNAs/genetics
• MicroRNAs/metabolism
• RNA, Messenger/chemistry
• RNA, Messenger/genetics
• RNA, Messenger/metabolism

• breast cancer
• ceRNA
• ceRNET
• ceRnome
• ncRNAs

• Breast cancer
• Cancer
• Stem cells
• miRNA

Pseudogenes have been considered as non-functional transcriptional relics of human genomic for long time. However, recent studies revealed that they play a plethora of roles in diverse physiological and pathological processes, especially in cancer, and many pseudogenes are transcribed into long noncoding RNAs and emerging as a novel class of lncRNAs. However, the biological roles and underlying mechanism of pseudogenes in the pathogenesis of non small cell lung cancer are still incompletely elucidated. This study identifies a putative oncogenic pseudogene DUXAP10 in NSCLC, which is located in 14q11.2 and 2398 nt in length. Firstly, we found that DUXAP10 was significantly up-regulated in 93 human NSCLC tissues and cell lines, and increased DUXAP10 was associated with patients poorer prognosis and short survival time. Furthermore, the loss and gain of functional studies including growth curves, migration, invasion assays and in vivo studies verify the oncogenic roles of DUXAP10 in NSCLC. Finally, the mechanistic experiments indicate that DUXAP10 could interact with Histone demethylase Lysine specific demethylase1 (LSD1) and repress tumor suppressors Large tumor suppressor 2 (LATS2) and Ras-related associated with diabetes (RRAD) transcription in NSCLC cells. Taken together, these findings demonstrate DUXAP10 exerts the oncogenic roles through binding with LSD1 and epigenetic silencing LATS2 and RRAD expression. Our investigation reveals the novel roles of pseudogene in NSCLC, which may serve as new target for NSCLC diagnosis and therapy.

• DUXAP10
• LSD1
• migration and invasion
• proliferation
• pseudogene

Accumulating evidence indicates that deregulation of cancer-associated pseudogene is involved in the pathogenesis of cancer. In the study, we demonstrated that pseudogene CTNNAP1, for the CTNNA1 gene, was dysregulated in colorectal cancer and the degree of dysregulation was remarkably associated with tumor node metastasis (TNM) stage (P<0.05). The mechanistic experiments revealed that pseudogene CTNNAP1 played a pivotal role in the regulation of its cognate gene CTNNA1 by competition for microRNA-141. Moreover, gain-of-function approaches showed that overexpression of CTNNAP1 or CTNNA1 significantly inhibited cell proliferation and tumor growth in vitro and in vivo by inducing G0/G1 cell cycle arrest. Our findings add a new regulatory circuit via competing endogenous RNA (ceRNA) cross-talk between pseudogene CTNNAP1 and its cognate gene CTNNA1, and provide new insights into potential diagnostic biomarker for monitoring human colorectal cancer.

• CCK-8
• CRC
• ceRNA
• lncRNA
• qRT-PCR

• Biomarker
• Cancer
• CellMiner
• Pseudogene
• miRNA

• Biomarkers, Tumor/genetics
• Biomarkers, Tumor/metabolism
• Databases, Nucleic Acid
• Gene Expression Regulation, Neoplastic
• Humans
• MicroRNAs/genetics
• MicroRNAs/metabolism
• Neoplasms/diagnosis
• Neoplasms/genetics
• Neoplasms/therapy
• Oncogenes
• Pseudogenes

• cancer
• competing endogenous RNA
• lncRNA
• miRNAs
• pseudogene

• Anti-miRNA oligonucleotide
• Circular RNA
• Competing endogenous RNA
• Gene therapy
• Nanoparticle
• miRNA sponge

• Breast cancer
• CKS1BP7
• IGF1R
• Quantitative multi-gene fluorescence in situ hybridization

• DUXAP8
• EGR1
• NSCLC
• RHOB
• invasion
• proliferation
• pseudogene

• Apoptosis/genetics
• Carcinoma, Non-Small-Cell Lung/genetics
• Carcinoma, Non-Small-Cell Lung/mortality
• Cell Cycle/genetics
• Cell Line, Tumor
• Cell Proliferation
• Cell Transformation, Neoplastic/genetics
• Cluster Analysis
• ERG1 Potassium Channel/genetics
• ERG1 Potassium Channel/metabolism
• Enhancer of Zeste Homolog 2 Protein/metabolism
• Epigenesis, Genetic
• Gene Expression Profiling
• Gene Expression Regulation, Neoplastic
• Gene Knockdown Techniques
• Gene Silencing
• Histone Demethylases/metabolism
• Humans
• Lung Neoplasms/genetics
• Lung Neoplasms/mortality
• Prognosis
• Protein Binding
• Pseudogenes/genetics
• rhoB GTP-Binding Protein/genetics
• rhoB GTP-Binding Protein/metabolism

• ceRNA
• gene expression
• microRNA
• pseudogene

• Animals
• Gene Expression/genetics
• Gene Regulatory Networks/genetics
• Humans
• Pseudogenes/genetics
• RNA/genetics
• Response Elements/genetics

Recent studies have revealed that pseudogene transcripts can function as competing endogenous RNAs, and thereby can also contribute to cancer when dysregulated. We have recently identified two pseudogenes, HMGA1P6 and HMGA1P7 for the HMGA1 gene whose overexpression has a critical role in cancer progression. These pseudogenes work as competitive endogenous RNA decoys for HMGA1 and other cancer related genes suggesting their role in carcinogenesis. Looking for new HMGA1 pseudogene ceRNAs, we performed RNA sequencing technology on mouse embryonic fibroblasts deriving from transgenic mice overexpressing HMGA1P7. Here, we report that HMGA1P7 mRNA sustains the H19 and Igf2 overexpression by acting as miRNA decoy. Lastly, the expression of HMGA1P7 was significantly correlated with H19 and IGF2 levels in human breast cancer thereby suggesting a role for HMGA1P7 deregulation in this neoplasia.

• Drosophila suzukii
• adaptation
• comparative genomics
• odorant receptors

Noncoding RNAs (ncRNAs) have attracted much attention in cancer research field. They are involved in cellular development, proliferation, differentiation and apoptosis. The dysregulation of ncRNAs has been reported in tumor initiation, progression, invasion and metastasis in various cancers, including gastric cancer (GC). In the past few years, an accumulating body of evidence has deepened our understanding of ncRNAs, and several emerging ncRNAs have been identified, such as PIWI-interacting RNAs (piRNAs) and circular RNAs (circRNAs). The competing endogenous RNA (ceRNA) networks include mRNAs, microRNAs, long ncRNAs (lncRNAs) and circRNAs, which play critical roles in the tumorigenesis of GC. This review summarizes the recent hotspots of ncRNAs involved in GC pathobiology and their potential applications in GC. Finally, we briefly discuss the advances in the ceRNA network in GC.

• Noncoding RNAs
• Gastric cancer
• MicroRNA
• Long ncRNAs
• PIWI-interacting RNAs
• Competing endogenous RNA

• Humans
• RNA/physiology
• RNA, Circular
• RNA, Untranslated/physiology
• Stomach Neoplasms/drug therapy
• Stomach Neoplasms/etiology
• Stomach Neoplasms/genetics

• African American
• Breast Cancer
• Disparities
• Luminal A

• cell invasion
• lentivirus
• pancreatic cancer
• siRNA
• target therapy
• zinc finger protein 91 pseudogene

• Cancer
• Pseudogenes
• RNA

Recent advances in the analysis of RNA sequencing data have shown that pseudogenes are highly specific markers of cell identity and can be used as diagnostic and prognostic markers. Furthermore, genetically engineered mouse models have recently provided compelling support for a causal link between altered pseudogene expression and cancer. In this review, we discuss the most recent milestones reached in the pseudogene field and the use of pseudogenes as cancer classifiers.

• animal models of cancer
• cancer
• ceRNAs
• diagnostic markers
• mutagenic factors
• prognostic markers
• pseudogenes

• Cell biology
• Clinical genetics
• MicroRNA
• Molecular genetics

While RNA-sequencing (RNA-seq) is becoming a powerful technology in transcriptome profiling, one significant shortcoming of the first-generation RNA-seq protocol is that it does not retain the strand specificity of origin for each transcript. Without strand information it is difficult and sometimes impossible to accurately quantify gene expression levels for genes with overlapping genomic loci that are transcribed from opposite strands. It has recently become possible to retain the strand information by modifying the RNA-seq protocol, known as strand-specific or stranded RNA-seq. Here, we evaluated the advantages of stranded RNA-seq in transcriptome profiling of whole blood RNA samples compared with non-stranded RNA-seq, and investigated the influence of gene overlaps on gene expression profiling results based on practical RNA-seq datasets and also from a theoretical perspective.

Our results demonstrated a substantial impact of stranded RNA-seq on transcriptome profiling and gene expression measurements. As many as 1751 genes in Gencode Release 19 were identified to be differentially expressed when comparing stranded and non-stranded RNA-seq whole blood samples. Antisense and pseudogenes were significantly enriched in differential expression analyses. Because stranded RNA-seq retains strand information of a read, we can resolve read ambiguity in overlapping genes transcribed from opposite strands, which provides a more accurate quantification of gene expression levels compared with traditional non-stranded RNA-seq. In the human genome, it is not uncommon to find genomic loci where both strands encode distinct genes. Among the over 57,800 annotated genes in Gencode release 19, there are an estimated 19 % (about 11,000) of overlapping genes transcribed from the opposite strands. Based on our whole blood mRNA-seq datasets, the fraction of overlapping nucleotide bases on the same and opposite strands were estimated at 2.94 % and 3.1 %, respectively. The corresponding theoretical estimations are 3 % and 3.6 %, well in agreement with our own findings.

Stranded RNA-seq provides a more accurate estimate of transcript expression compared with non-stranded RNA-seq, and is therefore the recommended RNA-seq approach for future mRNA-seq studies.

The online version of this article (doi:10.1186/s12864-015-1876-7) contains supplementary material, which is available to authorized users.