Are pseudogene counted as a subtype of long non-coding RNA genes?

Are pseudogenes regarded as a subtype of the genes for long non-coding RNAs?

I could not find the answer to this question in an internet search.

A note on nomenclature in modern biology

As it stands, this question seems to assume there is some legal commission, Académie française, or the like that is devoted to continually determining scientific nomenclature, and that those in the field obediently follow it. While organizations like IUPAC - The International Union of Pure and Applied Chemistry - do exist for standardization, they move very slowly, and only come out when the dust has settled (so to speak). So if I write an article about genes I can classify them as suits my purpose. I may wish to distinguish just between coding or non-coding; or between structural, informational, regulatory and junk etc. etc. Nobody is going to throw me in gaol if they disagree.

Is it scientific to classify pseudogenes in this way?

By this, I mean do the genes (for that is what we can compare) for long non-coding RNAs (ncRNAs or lncRNAs) have enough general features shared by pseudogenes that it would be useful to sub-type pseudogenes in this way. In my opinion, No. Pseudogenes are generally regarded as non-functional - remnants of unsuccessful or uncompleted gene duplication, or of reverse transcription of mature mRNAs into the germ-line DNA. In many cases they are not even transcribed. There may not be a single function for those gene-products termed lncRNAs but in general they are transcribed and thought to have functions concerned with gene regulation. There are no structural similarities with pseudogenes, so that all the genes have in common is that they are, well, long, so to that idea I would say “So long!”

How do the genome annotators regard this?

The people that make the rules, de facto - and revise them as science advances - are the ones with the job of annotating sequenced genomes. I haven't made a general survey of genomes, and am restricting myself to the genome of the fruit fly, Drosophila melanogaster, with which I am familiar. The distinct Biotypes for genes in the data at FlyBase are currently (2019) as follows:

  • ncRNA (aka lncRNA)
  • protein coding
  • pseudogene
  • snRNA
  • tRNA
  • rRNA
  • snoRNA
  • pre miRNA

I suspect that this is standard among the large genome databases, and it can be seen that pseudogene and ncRNA are regarded as distinct categories.

Of course, one can argue with this classification - where are the SINES and LINES and Drosophila-specific mobile elements, for example? But that just illustrates what I have written above.

DUXAP8, a pseudogene derived lncRNA, promotes growth of pancreatic carcinoma cells by epigenetically silencing CDKN1A and KLF2

Recent studies highlight pseudogene derived long non-coding RNAs (lncRNAs) as key regulators of cancer biology. However, few of them have been well characterized in pancreatic cancer. Here, we aimed to identify the association between pseudogene derived lncRNA DUXAP8 and growth of pancreatic cancer cells.


We screened for pseudogene derived lncRNAs associated with human pancreatic cancer by comparative analysis of three independent datasets from GEO. Quantitative real-time reverse transcription polymerase chain reaction was used to assess the relative expression of DUXAP8 in pancreatic cancer tissues and cells. Loss-of-function approaches were used to investigate the potential functional roles of DUXAP8 in pancreatic cancer cell proliferation and apoptosis in vitro and in vivo. RNA immunoprecipitation, chromosome immunoprecipitation assay and rescue experiments were performed to analyze the association of DUXAP8 with target proteins and genes in pancreatic cancer cells.


Pancreatic cancer tissues had significantly higher DUXAP8 levels than paired adjacent normal tissues. High DUXAP8 expression was associated with a larger tumor size, advanced pathological stage and shorter overall survival of pancreatic cancer patients. Moreover, silencing DUXAP8 expression by siRNA or shRNA inhibited pancreatic cancer cell proliferation and promoted apoptosis in vitro and in vivo. Mechanistic analyses indicated that DUXAP8 regulates PC cell proliferation partly through downregulation of tumor suppressor CDKN1A and KLF2 expression.


Our results suggest that tumor expression of pseudogene derived lncRNA DUXAP8 plays an important role in pancreatic cancer progression. DUXAP8 may serve as a candidate biomarker and represent a novel therapeutic target of pancreatic cancer.


Colorectal carcinoma (CRC) is a common type of cancer in American and China, thus representing a major public health problem 1, 2 . It accounts for over 9% of all malignancy incidence, with estimated 1.4 million cases occurring in 2012 worldwide 3, 4 . Moreover, the global burden is expected to further increase due to the growth and aging of the population and the adoption of westernized behaviors and lifestyle 3 . Colorectal carcinogenesis is a complicated biological process that results from the dysregulation of many cancer-related genes. Therefore, a greater understanding of the molecular mechanisms involved in the development and progression of colorectal cancer is essential to develop targeted strategies that could alleviate the burden of the disease.

In the past decade, the significance of nonprotein-coding functional elements in the human genome has emerged from the water and been identified as an important revelation in post-genomic biology 5,6,7 . Recently, benefiting from the improvement of bioinformatics methods and large scale sequencing technique, tens of thousands of pseudogenes as well as numerous long non-coding RNA (lncRNA) genes were identified 8, 9 . Briefly, pseudogenes are the results of duplicated genes, which have lost their protein-coding capacity through molecular events such as point or frameshift mutations 8 . Interestingly, it is becoming apparent that many pseudogenes are transcribed into long non-coding RNAs, with proven biological functions 10 . They play a plethora of roles at multiple levels (DNA, RNA or protein) in diverse pathological processes, especially in carcinogenesis 11, 12 . In the recent reported study by Ma H and colleagues, the pseudogene derived from long non-coding RNA DUXAP8 can promote gastric cancer cell proliferation and tumorigenesis through epigenetically silencing PLEKHO1 transcription 13 . In addition, the pseudogene-expressed lncRNA RSU1P2 was found to be significantly up-regulated in cervical cancer, and functioned as an oncogene in cervical cancer cells 14 . Therefore, pseudogene-expressed lncRNAs have been highlighted as key factors in cancer research.

DUXAP10 is previously found to be overexpressed in non small cell lung cancer (NSCLC) and promotes NSCLC cells proliferation. However, the biological functions and underline mechanism of DUXAP10 in the control of CRC tumorigenes is have not been documented. These prompted us to explore the role of DUXAP10 in human CRC 15 . In the present study, we investigated that pseudogene-expressed lncRNA DUXAP10 was aberrantly expressed in CRC and positively associated with tumor size, pathological stage and lymphatic metastasis. Furthermore, functional analysis revealed that DUXAP10 could promote CRC cell growth both in vitro and in vivo. Mechanism studies indicated that DUXAP10 is an oncogenic pseudogene-expressed lncRNA that promotes tumorigenesis through epigenetically silencing p21 and PTEN expression.


Pseudogenes are genomic sequences with high sequence similarity to functional genes but have been presumed to be “non-functional” [1]–[3]. By definition, pseudogenes derived from protein-coding genes have lost their protein-coding capacity due to deleterious disruptions (e.g., premature stop codons or frame shift mutations) in their hypothetical open reading frames. Based on distinct generation mechanisms, pseudogenes are separated into processed pseudogenes (generated by retrotransposition) and duplicated pseudogenes (from gene duplication). This separation is primarily based on examination of sequence features, with the lack of introns as strong evidence for retrotransposition, whereas older pseudogenes with extensive structure degeneration are sometimes classified as pseudogene fragments due to ambiguity. The functional gene with the “highest” sequence similarity to a pseudogene is often operationally referred as its parental gene, which is also used in the current study.

Thousands of pseudogenes are found in the human genome some of them have been suggested to have critical regulatory functions [4]–[7]. Historically, pseudogenes are considered to be mostly transcriptionally inactive because they are presumably lacking either a functional promoter or auxiliary regulatory elements. However, recent studies have found that a substantial portion of pseudogenes can actually be transcribed to stable RNAs [8]–[12]. Furthermore, accumulating lines of evidence suggest that pseudogenes, via their non-coding RNA (ncRNA) products, may play regulatory roles in modulating the expression of their parental genes, as well as non-parental genes [1], [3], [13]–[21]. For example, short interfering RNAs (siRNAs) derived from pseudogenes, through their complementary interactions with mRNAs of the parental genes, were found to down regulate parental gene expression in mouse oocytes by a Dicer-dependent RNAi process [22], [23]. Our recent analysis of millions of small RNAs from multiple rice tissues also supports the idea that high eukaryotic pseudogenes can produce endogenous siRNAs (endo-siRNAs) that are mostly tissue and development-stage specific [24]. Moreover, many of those pseudogene-derived endo-siRNAs share similar features with plant repeat-associated siRNAs that can mediate RNA-directed DNA methylation and heterochromatin formation [24]. Whether mammalian pseudogenes can play a similar role in modulating epigenetic repression at pseudogene loci (i.e., cis-effect) has not yet been investigated, although trans-effects have been suggested. For example, the Oct4 pseudogene ncRNA was shown to direct epigenetic remodeling complexes to the Oct4 parent gene [25].

Pseudogene transcripts functioning by other mechanisms have also been reported [8], [14], [19], [20], [26]–[29], including acting as antisense transcripts [25], [30]. PTENP1, a pseudogene derived from the tumor suppressor gene PTEN, was first shown to act as a competitive decoy for several miRNAs that target PTEN mRNA, thus stabilize expression of its parental PTEN gene [28]. The recent discovery of antisense ncRNAs from PTENP1 and their role in regulating PTEN [31], furthermore, indicates that functional interaction between pseudogenes and their parents can be complex and multilayered. Given the wide range of biological functions potentially carried out by ncRNAs [32]–[34], and the high sequence similarity between pseudogenes and their protein-coding paralogs, it is conceivable that pseudogene-derived ncRNAs may also have a variety of molecular and cellular effects on normal cell growth, human disease, and cancer [12], [19], [35]–[37].

In this study, we have surveyed the landscape of pseudogene transcription across a large number of human tissues and cell lines and begun to explore potential functional and cellular activities of pseudogene ncRNAs from several perspectives. We found that a few thousand human pseudogenes were transcribed and their transcription was overall correlated with increased expression levels and expression diversity of their parental genes. Some pseudogenes, on the other hand, displayed evidence of siRNA production and function, potentially by either interfering with parental gene expression or mediating local epigenetic silencing. Taken together, our results suggest that pseudogene transcription is likely an important process that has provided novel ncRNA elements for modulating the transcriptional fluctuation of protein-coding genes.


Identification of lncRNA that are regulated by TNFα

We hypothesized that NF-κB regulates the expression of lncRNAs just as it regulates the expression of coding genes and microRNAs (Boldin and Baltimore, 2012). To determine whether NF-κB regulates the expression of lncRNAs, we performed paired-end directional RNA-seq on wildtype (WT) MEFs before treatment and after treatment for 1.5, 6 and 24 hr with 20 ng/ml of TNFα. On average, more than 20 million reads were mapped to the mouse genome (mm9 assembly) for each treatment condition (Supplementary file 1A). First, reads were mapped to the mouse mm9 reference genome using TopHat (Trapnell et al., 2009). Using an in-house generated script, RefSeq and Ensemble annotated transcripts’ expression in the form of RPKM (reads per kilobase of exon model per million) were obtained and those transcripts with at least a twofold change in expression and an average RPKM > 1, were defined as significant. Reference based de novo transcriptome assembly of mapped reads was performed using two methods. Raw reads were mapped using TopHat and de novo transcriptome assembly of mapped reads was performed using, Cufflinks (Trapnell et al., 2010) and Scripture (Guttman et al., 2010) in parallel. RefSeq and Ensemble annotated transcripts were downloaded from UCSC table browser, and these annotated transcripts were filtered out from Scripture and Cufflinks-assembled transcriptomes to yield about 1500 novel de novo isoforms that are expressed at an RPKM > 1. Because many isoforms mapped to a single locus, we further filtered the list of novel transcripts by applying promoter regions as defined by H3K4me3 via chromatin immunoprecipitation sequencing (ChIP-Seq), which yielded 184 novel loci. To further refine the candidate transcripts, we extracted the raw reads that mapped to those 184 loci, processed a de novo transcript assembly through Trinity (Grabherr et al., 2011) and determined the Coding Potential Calculator (CPC) score of each transcript (Kong et al., 2007) to identify 64 novel de novo lncRNAs (Figure 1A, Supplementary file 1B).

TNFα regulates the transcription of many coding and noncoding genes.

(A) Workflow for strategy for discovery of NF-κB regulated lncRNAs. (B) 3596 RefSeq protein coding genes are regulated by TNFα. Values are normalized to the 0 hr time point. (C) 244 RefSeq ncRNAs are regulated by TNFα. (D) 64 de novo lncRNAs are regulated by TNFα. (E) The fraction of all RefSeq ncRNAs for each class of transcript. (F) 54 pseudogene lncRNAs are regulated by TNFα.

In this way, 3596 protein coding transcripts, 244 ncRNAs and 64 de novo lncRNAs were detected in these experiments. Many RefSeq protein coding genes that had been shown to be regulated by NF-κB were induced by TNFα including Gadd45b, Sod2, Nfkbia, Relb, Cdkn2a, and Il6. Additionally, the RNA-seq data showed the expected oscillatory gene expression pattern of NF-κB dependent gene expression, and notably the dynamic range by RNA-seq is greater than previously observed with microarrays (Kawahara et al., 2011). Interestingly, the 244 RefSeq ncRNAs showed a similar expression pattern as the protein coding genes, where peak expression or repression levels were observed at 1.5 and 24 hr post stimulation. A subset also showed maximal repression at 6 hr in both classes. 84 ncRNAs were at least twofold upregulated when compare to untreated at a least one time point. In contrast, the vast majority (59 out of 64) of de novo lncRNAs were primarily repressed upon TNFα treatment (Figure 1B–D, Supplementary file 1B–D). A similar result in which most de novo lncRNAs were down regulated after treatment was seen in response to estrogen in breast cancer cells (Hah et al., 2011).

Next, we divided the RefSeq ncRNAs by their RefSeq annotation into four classes, pri-miRNAs (40%), RNaseP, SnoRNA, ScaRNA (19%), pseudogene lncRNA (22%) and annotated lncRNAs (19%) (Figure 1E). Interestingly, only 11 of 96 pri-miRNAs were upregulated with TNFα treatment. In contrast about 23 of 45 housekeeping RNAs (RNaseP, scaRNA, snoRNA) and 37 of 54 pseudogene lncRNAs were upregulated. Finally, 12 out of 48 annotated lncRNA were upregulated, mirroring what we see in the de novo lncRNAs. To further examine the pseudogene component of the lncRNAs, we created a heatmap of pseudogene lncRNA, and observed the same oscillatory gene expression pattern that was observed in the protein coding genes (Figure 1F and Supplementary file 1E). We determined that the pseudogene Rps15a-ps4 (herein named Lethe), had the highest expression changes of any pseudogene with an RPKM > 1. Additionally, we observed that Gapdh had seven pseudogenes that were identified as induced by TNFα, but we were unable to validate this result with qRT-PCR.

We selected Refseq genes with significant differential expression over the time course (FDR < 0.05, SAMseq) and varied by at least twofold, yielding 3690 significant transcripts (Supplementary file 1F). We organized their patterns of temporal expression by mean-centered hierarchical clustering (Figure 1—figure supplement 1), and determined which lncRNAs clustered with known NF-κB regulated genes. From our list, we chose to validate and further characterize Cox2 Divergent, Gp96 Convergent, H2-T23/24AS, HoxA11AS, Lethe, Pbrm1 Convergent, Scripture 16,612 and Scripture 60,588.

LncRNAs distinguish distinct inflammatory stimuli

Our directional paired-end RNA-Seq data revealed TNFα regulation of many lncRNA transcripts which include divergent, antisense, convergent, and intergenic transcripts. Since the functional relationship between genomic organization and expression is unknown, we chose to validate and further characterize the lncRNAs expression alongside the closest protein coding gene under a variety of different stimuli by qRT-PCR. In our subset of lncRNAs, we found that most lncRNAs are co-regulated with their protein-coding gene. This is not surprising since we chose to validate lncRNAs that were close to genes that were regulated by TNFα. One notable exception was Lethe. Although the Lethe is expressed from the same strand as Gmeb1 and close to the 3′ terminus of Gmeb1, qRT-PCR showed that Lethe was specifically induced by TNFα and IL-1β, whereas Gmeb1 expression did not significantly change, confirming that the Lethe is not an extension of the 3′ UTR of Gmeb1 (Figure 2A).

LncRNAs distinguish between different stimuli and are regulated by NF-κB.

(A) Validation of lncRNAs expression alongside the closest protein coding gene under a variety of different stimuli by qRT-PCR. Genomic organization is shown below. MEFs were treated with 20 ng/ml TNFα for 0 and 6 hr. Quantitative Taqman real time RT-PCR of the indicated RNAs is normalized to Actin levels (mean ± SD). (B) LncRNAs are regulated by RelA. qRT-PCR in WT and RelA−/− littermate cells under a variety of different stimuli. MEFs were treated with 20 ng/ml TNFα for 0 and 6 hr. Quantitative Taqman real time RT-PCR of the indicated RNAs is normalized to Actin levels (mean ± SD). (C) Endogenous RelA is recruited to the promoters of lncRNAs. MEFs were treated with 20 ng/ml TNFα for 0 and 15 min. ChIP with α-RelA antibodies was performed and RelA percent enrichment relative to input is shown (mean ± SD, Nkfbia, p<0.0518 Gp96 Convergent, p<0.007 Lethe, p<0.002). (D) LncRNAs are found throughout the cell. Cellular fractionation was performed and fraction found in the chromatin, nucleus and cytoplasm is shown. MEFs were treated with 20 ng/ml TNFα for 6 hr. Quantitative Taqman real time RT-PCR of the indicated RNAs is shown (mean ± SD is shown). (E) LncRNAs are found on the chromatin. MEFs were treated with 20 ng/ml TNFα for 6 hr. RNA-IP with α-H3 antibodies was performed. RNA was isolated and Quantitative Taqman real time RT-PCR of the indicated RNAs is shown (mean ± SD, Lethe p<0.004).

NF-κB signaling can be initiated in response to many different stimuli including in response to proinflammatory cytokines like TNFα and IL-1β as well as in response to microbial components via the TLR family (Hayden and Ghosh, 2012). Therefore, we validated our lncRNA candidates in response to TNFα, IL-1β, and agonists of Toll like receptors (TLR) 1, 2, 3, 4, or 7 (Figure 2A–B). TLRs are pattern-recognition receptors for pathogen components from bacteria, fungi, or viruses, and play key roles in controlling the innate and adaptive immunity (Kawai and Akira, 2010). Indeed, we found that many of the lncRNAs are upregulated in response to distinct stimuli. Most notable, Cox2 Divergent is upregulated in response to proinflammatory cytokines and TLR1-4 agonists. In contrast, Gp96 Convergent is only expressed in response to TNFα. H2-T32/24AS is responsive to only TNFα and TLR3 agonists, whereas HoxA11AS is expressed in response to TLR3 agonists and actually down regulated by TNFα stimulation. Lethe is upregulated in response to the proinflammatory cytokines TNFα and IL-1β, but not TLR agonists, indicating it may have a function in inflammation, but not in native immunity. Pbrm1 Convergent is highly upregulated in response to IL-1β, and to a lesser extent TNFα, and TLR4 and 7 agonists. These results demonstrate that lncRNAs are dynamically and specifically regulated in response to different stimuli, suggesting that the pattern of lncRNAs can serve as an internal representation of a cell’s exposure to distinct inflammatory and pathogenic signals.

LncRNAs are directly regulated by NF-κB

Next, we wanted to determine if the lncRNAs were directly regulated by NF-κB. To address this question, we used two different methods. First, we performed qRT-PCR in RelA−/− littermate cells alongside WT cells (Figure 2—figure supplement 1). Cox2 Divergent is dramatically upregulated in response to proinflammatory cytokines and TLR1-4 agonists in WT and to an even larger extent, in RelA−/− cells indicating that it is not directly regulated by NF-κB component RelA. Additionally, HoxA11AS, H2-T23/24AS, Gp96 Convergent and Scripture 16,612 all show some induction in RelA−/− cells. In contrast, induction of Lethe, Pbrm1 Convergent and Scripture 60,588 is largely abrogated in RelA−/− cells, indicating that RelA is required to induce these lncRNAs (Figure 2B). Second, we performed RelA chromatin immunoprecipitation (ChIP) in WT MEFs. Upon TNFα signaling, RelA was found to bind to the promoters of Nfkbia, Gp96 Convergent and Lethe, but was not detected on the promoters of Cox2 Divergent or Pbrm1 Convergent, or Dll1, a negative control (Figure 2C). These results indicate that Lethe and Gp96 Convergent are directly transcriptional targets of RelA, with Lethe being particularly dependent on RelA for induction.

Lethe lncRNA is largely nuclear and on chromatin

To determine where our candidate genes are located within the cell we performed subcellular fractionation on cells stimulated with TNFα for 6 hr. We found that the subcellular distribution of TNFα−induced lncRNAs vary in a transcript-specific manner. Gapdh was tested as a control and found to be evenly distributed between the nucleus and cytoplasm with little transcript found on the chromatin. Likewise, Cox2 Divergent, Gp96 Convergent, and H2-T23/24AS were evenly distributed between nucleus and cytoplasm. HoxA11AS was mostly nuclear with some transcript found in the cytoplasm, but not on the chromatin. Interestingly, Lethe, Pbrm1 Convergent, Scripture 16,612 and Scripture 60,588 were found mostly on the chromatin, with a smaller fraction in the nucleus. These results indicate that Lethe, Pbrm1, Scripture 16,612 and Scripture 60,588 may be directly involved in gene regulation by interacting with the chromatin (Figure 2D). To further determine if it is the nascent transcript or processed transcript that is found on the chromatin, we performed polyA selection on our subcellular fractions and analyzed the results by qRT-PCR. Interestingly, polyadenylated Lethe RNA is still preferentially associated with chromatin compared to two control mRNAs, Actin and Nfkbia (Figure 2—figure supplement 1), indicating that full length Lethe is associated with chromatin. Finally, we performed H3-RNA immunoprecipitation (RIP) to directly test if lncRNAs are found on the chromatin after cells were stimulated with TNFα for 6 hr. We found that Lethe and Pbrm1 Convergent are both found on the chromatin, while Cox2 Divergent and Gp96 Convergent were not detected, confirming our fractionation results (Figure 2E). Results from Figure 2 are summarized in Table 1.

Classification of TNF regulated lncRNAs

Cox2 Divergent++++++n.d.n.d.n.d.
Gp96 Convergent+n.d.n.d.n.d.n.d.n.d.n.d.n.d.+n.d.
Pbrm1 Convergent+++−/++
Scripture 16,612+++n.d.n.t.
Scripture 60,588n.d.n.t.

These results demonstrate that lncRNAs are regulated by diverse and specific stimuli. Additionally, lncRNAs are directly regulated by NF-κB. Finallyp, the subcellular distribution of TNFα−induced lncRNAs varies by transcript. n.d., not detectable. n.t., not tested.

Lethe is a pseudogene of Rps15a

Since Lethe is an Rps15a pseudogene, we wanted to determine if there are other pseudogenes that are directly regulated by TNFα. We obtained Taqman probes against non-repetitive sequences unique to each pseudogene member, and examined Rps15a pseudogene family members as well as Rps15a to determine if they are regulated by TNFα (Figure 3A, Figure 3—figure supplement 1). qRT-PCR analysis showed that Nfkbia (a positive control) is dynamically regulated in response to TNFα, as is Lethe. Rps15a and Rps15a-ps6, another Rps15a pseudogene lncRNA, are both transcribed but are not regulated by TNFα (Figure 3B).

Lethe is a pseudogene lncRNAs that is regulated by NF-κB, Glucocorticoid Receptor and in aging.

(A) Gene structure, homology and Taqman probe design of Rps15a and pseudogene family members. (B) Lethe is induced by TNFα, but other family members are not. MEFs were treated with 20 ng/ml TNFα for 0 and 1.5 hr. Quantitative Taqman real time RT-PCR of the indicated RNAs is shown normalized to Actin levels (mean ± SD, p<0.012). (C) Genomic organization of Lethe with RNA-Seq data at time 0, 1.5, 6 and 24 hr post TNFα treatment. Lethe is located on mouse chromosome 4 between Gmeb1 and Ythd2. Gmeb1 and Ythd2 are not induced by TNFα stimulation. (D) Lethe is induced by dexamethasone treatment, but not other nuclear hormone receptor agonists. MEFs were treated with either 10 nM vitamin D, 100 nM methyltrienolone, 100 nM estradiol, or 1 μM dexamethasone for 0 and 6 hr. Quantitative Taqman real time RT-PCR of the indicated RNAs is shown normalized to Actin levels (mean ± SD, p<0.003). (E) Lethe is down-regulated in aged mice. Lethe is expressed in young spleen from male and female mice. Five mice were used for each sex and time point. Quantitative Taqman real time RT-PCR of the indicated RNAs is shown normalized to Actin levels (mean ± SD, Lethe p<0.001, Gmeb1 p<0.003). ANOVA analysis was performed to determine significance.

Lethe is 697 bp long unspliced lncRNA, and its locus on chromosome four lays approximately 500 bp downstream of Gmeb1 and 8 kb upstream of Ythdf2 on the minus strand (Figure 3C). Lethe is dramatically induced upon TNFα stimulation at 1.5 hr and 24 hr and repressed at 6 hr, in an expression pattern that is characteristic of other NF-κB regulated transcripts. Importantly, expression of its two neighbor mRNA genes was not changed by TNFα stimulation (Figure 3C), indicating that Lethe is independently regulated.

Lethe is induced by the glucocorticoid receptor

It is known that glucocorticoid receptor (GR) and NF-κB share many target gene sites (Rao et al., 2011). Therefore we tested whether Lethe could be induced upon stimulation with a number of nuclear hormone agonists including the GR agonist, dexamethasone. We found that Lethe is upregulated in response to anti-inflammatory agent, dexamethasone, but not in response to other nuclear hormone receptor agonists examined, including Vitamin D (Vitamin D Receptor), methyltrienolone (Androgen Receptor) and estradiol (Estrogen Receptor) (Figure 3D). Thus, Lethe is a pseudogene lncRNA that is induced by both inflammatory stimuli and an anti-inflammatory therapeutic.

Lethe is downregulated in aged mice

Recent work has shown that the transcription factor binding motif most strongly associated with aging is NF-κB (Adler et al., 2007). To determine if Lethe is expressed in old tissue as a result of constant NF-κB signaling, we tested a panel of tissues, including liver, lung, kidney, skin, spleen, cortex (brain), and skeletal muscle. Lethe is expressed in male and female spleen, but not detectable in other tissues. Interestingly, Lethe is downregulated with age: 20-fold and 160-fold in males and females respectively (Figure 3E). Neither Nfkbia nor Gmeb1 expression changes with age or sex.

Lethe inhibits NF-κB activity

We hypothesized that Lethe acts in trans to regulate NF-κB function. Therefore we performed loss-of-function experiments and measuring expression of canonical NF-κB members. We used chemically modified chimeric antisense oligonucleotides (ASO) which have been shown to be effective at knocking-down expression of nuclear ncRNAs (Ideue et al., 2009). ASO blockade inhibited the TNFα induction of Lethe, and we monitored the induction of two NF-κB target genes by qRT-PCR. Nfkbia level was significantly higher than TNFα stimulated ASO control in one of the two ASOs tested, while Nfkb2 was induced significantly for both ASOs tested (Figure 4A). This result indicates that Lethe may act as a repressor of NF-κB activity.

Lethe Binds to RelA and inhibits RelA occupancy of DNA.

(A) Increased expression of NF-κB regulated genes in Lethe knockdown cells. Quantitative Taqman real time RT-PCR of the indicated RNAs is shown normalized to Actin levels (mean ± SD, p<0.05 is shown) (B) Lethe inhibits TNFα induced reporter gene expression. RLU of 3x-κB reporter activity and mutant reporter activity (mean ± SD, p<0.05 is shown) in CMV_Lethe transfected 293T cells. Reporter constructs are diagrammed above. (C) Endogenous RelA recruitment to the promoters of target genes is reduced in the presence of Lethe. 293T expressing CMV_GFP or CMV_Lethe were treated with 20 ng/ml TNFα for 15 min. ChIP with α-RelA antibodies was performed and RelA percent enrichment relative to input is shown (mean ± SD Il6, p<0.033 Sod2, p<0.001 Il8, p<0.003 Nfkbia, p<0.015). (D) Lethe binds to RelA. MEFs were treated with 20 ng/ml TNFα for 6 hr. RNA-IP with α-RelA antibodies was performed. RNA was isolated and Quantitative Taqman real time RT-PCR of the indicated RNAs is shown (mean ± SD, p<0.020). (E) Lethe expression blocks DNA binding of the RelA homodimer to its target. NF-κB EMSA of GFP or Lethe transfected 293T nuclear extracts treated with 20 ng/ml TNFα for 15 min. Extracts were pretreated with unlabeled NF-κB (specific) or CREB (nonspecific competitor), or α-RelA antibodies for 15 min prior to incubation with probe. (F) Model for Lethe regulation of gene expression. Upon addition of TNFα or dexamthasone, Lethe is transcribed. Lethe can then bind to RelA–RelA homodimers and block binding to other NF-κB response elements, inhibiting NF-κB.

Conversely, we overexpressed Lethe or GFP in the presence of an NF-κB luciferase reporter gene after TNFα stimulation. Lethe expression, but not GFP expression, repressed NF-κB reporter gene activity. Additionally, Lethe can increase the repression NF-κB luciferase reporter gene expression in a dose dependent manner. To determine if Lethe’s effect on reporter gene activity was specific to NF-κB mediated reporter gene expression, we mutated the κB binding sites out of the reporter plasmid. As expected, the repression was no longer observed, indicating that Lethe requires NF-κB to repress reporter gene expression (Figure 4B).

The TNFα inducible repression of NF-κB luciferase reporter gene expression indicates that Lethe may affect the ability of RelA to bind to target promoters. To test this possibility, 293T cells were transfected with Lethe and ChIP was performed with RelA antibodies or IgG. In response to TNFα, Lethe expression significantly decreased RelA occupancy of several NF-κB target genes including Il6, Sod2, Il8, and Nfkbia (Figure 4C). Immunoblot analysis confirmed that that Lethe does not lower RelA protein level (Figure 4C). These results indicate that Lethe acts to inhibit NF-κB binding to the chromatin.

Lethe Binds to RelA and inhibits RelA occupancy of DNA

We reasoned that Lethe may bind RelA directly. RelA-RIP retrieved Lethe, but not Gapdh in MEFs stimulated with TNFα for 6 hr. Interestingly, other lncRNAs, Cox2 Divergent and Gp96 Convergent did not bind to RelA (Figure 4D). To further explore the relationship between Lethe and RelA, NF-κB DNA binding was assessed by electro mobility shift assays (EMSA). 293T cells were transfected with either CMV_GFP or CMV_Lethe. 48 hours post transfection cells were stimulated with TNFα for 15 min before nuclear lysates were prepared. As expected, TNF-stimulated extracts contained NF-κB activity, which are shifted by radiolabelled NF-κB probes, specifically competed away by cold NF-κB probes, and supershifted by anti-RelA antibody. Notably Lethe expression blocks DNA binding of the RelA homodimer, but not other isoforms (Figure 4E). These results indicate that Lethe may act as an inhibitor of NF-κB by binding directly to the RelA homodimer, and blocking RelA’s ability to bind DNA (Figure 4F).


F.A.C. is supported by a Special Research Fund (BOF) scholarship of Ghent University (BOF.DOC.2017.0026.01). R.C. is supported by the Fonds Wetenschappelijk Onderzoek (11Y6218N). T.-W.C. is supported by grants from the Ministry of Science and Technology, Taiwan (MOST-109-2311-B-009 −002). A.U. is supported by research funding from the National Health and Medical Research Council (Australia) and the Leukemia & Lymphoma Society, the Leukemia Foundation and the Snowdome Foundation. G.A. is supported by a postgraduate scholarship from the Translational Cancer Research Network. M.R.W. and N.P.D. acknowledge support from the National Collaborative Research Infrastructure Strategy program, administered by Bioplatforms Australia. We thank N. Yigit, A. Barr, S. Pathak, L. Way and A. Mai for their contributions in library preparation and A. Yunghans, E. Jaeger and A. Moshrefi for their assistance in library organization and sequencing/tracking/data management. This project was funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreements 668858 and 826121 to P.M., P.S. and J. Koster and the Concerted Research Action of Ghent University (BOF/GOA 01G00819) to P.M. and K.B.

4 Discussion

In this study, we identified one up-regulated lncRNA, RACGAP1P, in the breast cancer tissue using LncRNA Expression Microarray, and its high expression was positively correlated with lymph node metastasis, distance metastasis, TNM stage, and shorter survival time. Further experiments showed that the overexpression of RACGAP1P could enhance mitochondrial fission by up-regulating its parental gene RACGAP1 via competitively binding to miR-345-5p and thus increase the invasive ability of breast cancer cells. The results revealed the regulatory mechanism of RACGAP1P in the invasion and metastasis of breast cancer (Fig. 7).

LncRNAs have emerged to exhibit important biological function in cancer development and progression, involving in tumor cell proliferation [ [30] ], metabolism [ [31] ], migration, invasion [ [32] ], and even non-coding RNA transfer [ [33, 34] ]. A previous study showed that overexpression of lncRNA RACGAP1P enhanced cell proliferation and migration, thus promoting hepatocellular carcinoma early recurrence [ [18] ]. Our results demonstrated that the up-regulation of RACGAP1P was a commonly oncogenic event in breast cancer, which is correlated with lymph node metastasis, distance metastasis, TNM stage, and poor prognosis of breast cancer patients. Accordingly, functional experiments in vivo and in vitro confirmed that RACGAP1P promoted breast cancer cell migration, invasion, and metastasis, but had no significant effect on breast cancer cell proliferation. Consistently, we did not observe statistically significant relevance between RACGAP1P and tumor size in 102 breast cancer patients. As for the different effects on cell proliferation in hepatocellular carcinoma and breast cancer, we speculate that it may be due to the heterogeneity of breast cancer. Further investigation in cell biological behaviors involving RACGAP1P is needed.

Mitochondrial fission has been recognized as an important metastatic driver as the fragmentation of mitochondria helps the distribution of mitochondria by subcellular trafficking to the leading edge of migrating direction where energy is highly demanded to form lamellipodia during the process of migration and subsequent invasion [ [35] ]. Mitochondrial fragmentation is mainly regulated by the dynamin 1-like protein (Drp1). Overexpression or enhanced activation of Drp1 mediates the mitochondrial fission in metastatic breast cancer [ [25] ], pancreatic cancer [ [9] ], and glioblastoma cells [ [36] ]. Drp1 activity is mainly regulated by post-translational modifications, phosphorylation at serine (Ser) 616 residue site [ [37] ]. Moreover, several studies also showed that lncRNAs might play roles in mitochondrial function [ [38-40] ]. In this study, we found that the overexpression of RACGAP1P led to increased phosphorylation of Drp1-S616 and promoted mitochondrial fission. While mitochondrial fission inhibitor Mdivi-1 could diminish the invasive ability of RACGAP1P overexpression cells. Collectively, RACGAP1P promoted mitochondrial fission, which is required for breast cancer cell invasion via Drp1 activity enhancement.

Accumulating evidence suggests that RNA crosstalk plays a vital role in gene regulatory networks, and is implicated in cancer [ [41] ]. Pseudogenes are relicts of parental genes that lost the function of encoding for full-length functional proteins during the evolutionary process [ [42] ]. Considering the homolog of pseudogenes with parental genes, pseudogenes have defined roles in regulating the expression of the parental genes through sequestering common miRNAs and releasing expression inhibition [ [43] ]. According to the NCBI database, RACGAP1P is the pseudogene of RACGAP1. Notably, RACGAP1P co-expressed with RACGAP1 in breast cancer. Further experiments showed that RACGAP1P could regulate RACGAP1 expression by endogenously competitive binding with miR-345-5p. Previous studies demonstrated that RACGAP1 was a cancer-promoting gene overexpressed in various cancers [ [44-46] ]. Importantly, RACGAP1 was identified as a metastatic driver in uterine carcinosarcoma [ [47] ]. Besides, RACGAP1 was also considered as a poor prognosis marker in high-risk early breast cancer [ [48] ]. Consistent with these findings, we found that RACGAP1 could induce breast cancer cell invasion.

A great many of studies demonstrated RACGAP1 could enhance the phosphorylation level of Erk and activate Rho/Erk signaling [ [18, 49, 50] ]. Interestingly, the MAPK signal pathway was reported to be involved in mitochondrial fission that Erk1/2 could phosphorylate Drp1 on Ser616 [ [9] ]. Combined with our results, we speculate that RACGAP1P could promote mitochondrial fission through RACGAP1/Erk /Drp1 signaling axis.

Nuclear Factor κB Signaling and Its Related Non-coding RNAs in Cancer Therapy

Xiaomin Liu , . Zhongliang Ma , in Molecular Therapy - Nucleic Acids , 2020

Other ncRNAs and NF-κB Signal Transduction

lncRNA has been found to play a vital part in pathological and physiological processes, containing tumor formation and metastasis. Different lncRNAs have different molecular mechanisms that play different biological functions. 81 The activation of NF-κB is also related with lncRNA.

Tumor-associated NF-κB activation and lncRNA overexpression are most directly related to the inhibition of IκB, which acts as a negative regulator of NF-κB signaling. Liu et al. 82 found that NKILA (NF-κB interacting lncRNA) binds to NF-κB, which is upregulated by inflammatory factors in breast cancer. NKILA inhibits activation of the NF-κB signaling pathway by masking the location of phosphorylation of IκB for IKK phosphorylation suppression. Further studies revealed that there are two hairpin structures, A and B, at 300–500 nt of NKILA. Hairpin A binds to the DNA-binding region of NF-κB, and hairpin B binds to S51-R73 of p65, preventing IκBα detachment that forming a stable NKILA/NF-κB/IκBα complex. Yang et al. 83 found that FTH1P3 (long non-protein coding RNA ferritin heavy chain 1 pseudogene 3) regulated metastasis and invasion through SP1 (specificity protein 1)/NF-κB (p65) in esophageal squamous cell carcinoma (ESCC). The mechanism of lncRNAs has been studied. A deeper understanding of the molecular mechanisms and biological functions of lncRNA will help to find new effective anticancer strategies in tumorigenesis.

miRNAs and lncRNAs have been demonstrated to play an irreplaceable role in the NF-κB signaling pathway. In addition, other types of ncRNAs, such as circRNA and piRNA, are also involved in the regulation of tumor-associated signaling pathways. Studies have shown that miR-7 sponge circRNA (ciRS-7) has more than 70 conserved miR-7 binding sites, which can effectively sponge miR-7 and suppress the inhibition of miR-7 target genes, promoting the correlation of gene expression and activating NF-κB signaling pathways. 84 , 85 There are few reports on piRNA in cancer. Leng et al. 86 found that piR-DQ590027, miR-377, and miR-153 in glioma-conditioned endothelial cells (GECs) had lower expression. piR-DQ590027 bound to MIR17HG. FOXR2 was a downstream target of miR-377 and miR-153. This study proved that the piR-DQ590027/MIR17HG/miR-153(miR-377)/FOXR2 pathway plays a crucial role in regulating the permeability of glioma-conditioned normal blood-brain barrier (BBB). Another study has shown that piR-021285 can induce the methylation of genes in breast cancer. 87 The roles of these ncRNAs in tumors remain to be further explored.


Recently, pseudogenes have emerged as new players in tumour biology 5,10 . However, a crucial question remains unclear: does pseudogene expression, as a whole, represent a biologically meaningful dimension that can characterize tumour heterogeneity and provide clinical applications? Here, we performed a Pan-Cancer analysis of pseudogene expression for what is, to our knowledge, the largest number of cancer patient samples (

3,000) in one such analysis. Utilizing TCGA patient cohorts with a sufficient sample size, we show the predictive power of pseudogene expression in classifying established tumour types and the high concordance of tumour subtypes based on pseudogene expression with other molecular subtypes as well as clinically established biomarkers (such as ER and PR status in breast cancer). It should be emphasized that a large number of tumour lineage-specific pseudogenes identified through between-disease comparisons 10 do not imply our findings through the within-disease analyses. Because many tumour lineage- or cancer-specific pseudogenes could arise from tissue-related rather than tumorigenesis-related effects, they may or may not have the power to differentiate tumour subtypes.

Strikingly, our analysis reveals an unexpected prognostic power of pseudogene expression in kidney cancer: pseudogene expression subtypes not only correlate with patient survival but also confer additional prognostic powers for a group of patients whose survival times cannot be well predicted based on conventional clinical variables. This finding implies a novel prognostic strategy that incorporates both the risk scores defined by the clinical-variable model and the tumour subtypes revealed by pseudogene expression (subtype 1 and subtype 2): among medium-risk patients, patients of subtype 2 may benefit from earlier, more aggressive therapies. Interestingly, although the tumour subtypes defined by other molecular data (for example, mRNA and miRNA) show high concordance with the pseudogene expression subtypes based on the whole patient cohort, they do not confer additional prognostic power based on the medium-risk patient subset. These aggregate results provide a strong rationale for further investigation of the clinical utility of pseudogene expression, which has been understudied in the field. Since TCGA patient samples were collected for the purpose of comprehensive molecular profiling and were collected from different institutions, this practice might introduce some bias. In addition, the resulting clinical annotation of patient samples and related records may not be as rigorous and complete as those obtained from standard clinical trials. Therefore, further efforts should be made to validate the clinical utility of pseudogene expression in a more formal clinical setting (for example, clinical trials).

Although our study primarily focused on the biomedical significance and clinical relevance of pseudogene expression as a whole (that is, the subtypes that collectively represent the information of many pseudogenes), an intriguing question is how individual pseudogenes are functionally involved in tumorigenesis. This is a challenging but exciting topic since pseudogenes may affect their WT-coding genes or unrelated genes through multiple mechanisms such as microRNA decoys and antisense transcripts. From a systems biology point of view, the informative behaviour of pseudogenes may originate from a role such as ‘regulator.’ Our preliminary analysis here revealed some candidates of potential interest. Further efforts are required to elucidate how these pseudogenes functionally contribute to tumour initiation and development and how they are regulated through the complex gene regulatory network.

Author information


CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3, 1090, Vienna, Austria

Aleksandra E. Kornienko, Philipp M. Guenzl, Robert Kralovics, Florian M. Pauler & Denise P. Barlow

Present Address: Institute of Science and Technology Austria, Lab Building East, Am Campus 1, A-3400, Klosterneuburg, Austria

Department of Internal Medicine I, Division of Hematology and Blood Coagulation, Medical University of Vienna, Vienna, Austria

Watch the video: Pseudogenes. What Are Pseudogenes. Junk DNA (November 2021).