Detecting transcription of ribosomal protein pseudogenes in diverse human tissues from RNA-seq data

Ribosomal dysregulation: A conserved pathophysiological mechanism in human depression and mouse chronic stress

The underlying biological mechanisms that contribute to the heterogeneity of major depressive disorder (MDD) presentation remain poorly understood, highlighting the need for a conceptual framework that can explain this variability and bridge the gap between animal models and clinical endpoints. Here, we hypothesize that comparative analysis of molecular data from different experimental systems of chronic stress, and MDD has the potential to provide insight into these mechanisms and address this gap. Thus, we compared transcriptomic profiles of brain tissue from postmortem MDD subjects and from mice exposed to chronic variable stress (CVS) to identify orthologous genes. Ribosomal protein genes (RPGs) were down-regulated, and associated ribosomal protein (RP) pseudogenes were up-regulated in both conditions. A seeded gene co-expression analysis using altered RPGs common between the MDD and CVS groups revealed that down-regulated RPGs homeostatically regulated the synaptic changes in both groups through a RP-pseudogene-driven mechanism. In vitro analysis demonstrated that the RPG dysregulation was a glucocorticoid-driven endocrine response to stress. In silico analysis further demonstrated that the dysregulation was reversed during remission from MDD and selectively responded to ketamine but not to imipramine. This study provides the first evidence that ribosomal dysregulation during stress is a conserved phenotype in human MDD and chronic stress-exposed mouse. Our results establish a foundation for the hypothesis that stress-induced alterations in RPGs and, consequently, ribosomes contribute to the synaptic dysregulation underlying MDD and chronic stress-related mood disorders. We discuss the role of ribosomal heterogeneity in the variable presentations of depression and other mood disorders.

Biological role and diagnostic utility of ribosomal protein L23a pseudogene 53 in cutaneous melanoma

Background

Skin melanoma is one of the deadliest types of skin cancer and develops from melanocytes. The genetic aberrations in protein-coding genes are well characterized, but little is known about changes in non-coding RNAs (ncRNAs) such as pseudogenes. Ribosomal protein pseudogenes (RPPs) have been described as the largest group of pseudogenes which are dispersed in the human genome.

Materials and methids

We looked deeply at the role of one of them, ribosomal protein L23a pseudogene 53 (RPL23AP53), and its potential diagnostic use. The expression level of RPL23AP53 was profiled in melanoma cell lines using real time quantitative reverse transcription polymerase chain reaction (qRT-PCR) and analyzed based on the Cancer Genome Atlas (TCGA) data depending on BRAF status and clinicopathological parameters. Cellular phenotype, which was associated with RPL23AP53 levels, was described based on the REACTOME pathway browser, Gene Set Enrichment Analysis (GSEA) analysis as well as Immune and ESTIMATE Scores.

Results

We indicted in vitro changes in RPL23AP53 level depending on a cell line, and based on in silico analysis of TCGA samples demonstrated significant differences in RPL23AP53 expression between primary and metastatic melanoma, as well as correlation between RPL23AP53 and overall survival. No differences depending on BRAF status were observed. RPL23AP53 is associated with several signaling pathways and cellular processes.

Conclusions

This study showed that patients with higher expression of RPL23AP53 displayed changed infiltration of lymphocytes, macrophages, and neutrophils compared to groups with lower expression of RPL23AP53. RPL23AP53 pseudogene is differently expressed in melanoma compared with normal tissue and its expression is associated with cellular proliferation. Thus, it may be considered as an indicator of patients' survival and a marker for the immune profile assessment.

Specialized Ribosomes in Health and Disease

Ribosomal heterogeneity exists within cells and between different cell types, at specific developmental stages, and occurs in response to environmental stimuli. Mounting evidence supports the existence of specialized ribosomes, or specific changes to the ribosome that regulate the translation of a specific group of transcripts. These alterations have been shown to affect the affinity of ribosomes for certain mRNAs or change the cotranslational folding of nascent polypeptides at the exit tunnel. The identification of specialized ribosomes requires evidence of the incorporation of different ribosomal proteins or of modifications to rRNA and/or protein that lead(s) to physiologically relevant changes in translation. In this review, we summarize ribosomal heterogeneity and specialization in mammals and discuss their relevance to several human diseases.

Long Non-Coding RNAs as Epigenetic Regulators of Immune Checkpoints in Cancer Immunity

In recent years, cancer treatment has undergone significant changes, predominantly in the shift towards immunotherapeutic strategies using immune checkpoint inhibitors. Despite the clinical efficacy of many of these inhibitors, the overall response rate remains modest, and immunotherapies for many cancers have proved ineffective, highlighting the importance of knowing the tumor microenvironment and heterogeneity of each malignancy in patients. Long non-coding RNAs (lncRNAs) have attracted increasing attention for their ability to control various biological processes by targeting different molecular pathways. Some lncRNAs have a regulatory role in immune checkpoints, suggesting they might be utilized as a target for immune checkpoint treatment. The focus of this review is to describe relevant lncRNAs and their targets and functions to understand key regulatory mechanisms that may contribute in regulating immune checkpoints. We also provide the state of the art on super-enhancers lncRNAs (selncRNAs) and circular RNAs (circRNAs), which have recently been reported as modulators of immune checkpoint molecules within the framework of human cancer. Other feasible mechanisms of interaction between lncRNAs and immune checkpoints are also reported, along with the use of miRNAs and circRNAs, in generating new tumor immune microenvironments, which can further help avoid tumor evasion.

A genome-wide epistatic network underlies the molecular architecture of continuous color variation of body extremities

Deciphering the molecular architecture of coat coloration for a better understanding of the biological mechanisms underlying pigmentation still remains a challenge. We took advantage of a rabbit French experimental population in which both a pattern and a gradient of coloration from white to brown segregated within the himalayan phenotype. The whole experimental design was genotyped using the high density Affymetrix® AxiomOrcun™ SNP Array and phenotyped into 6 different groups ordered from the lighter to the darker. Genome-wide association analyses pinpointed an oligogenic determinism, under recessive and additive inheritance, involving genes already known in melanogenesis (ASIP, KIT, MC1R, TYR), and likely processed pseudogenes linked to ribosomal function, RPS20 and RPS14. We also identified (i) gene-gene interactions through ASIP:MC1R affecting light cream/beige phenotypes while KIT:RPS responsible of dark chocolate/brown colors and (ii) a genome-wide epistatic network involving several others coloration genes such as POT1 or HPS5. Finally, we determined the recessive inheritance of the English spotting phenotype likely involving a copy number variation affecting at least the end of the coding sequence of the KIT gene. Our analyses of coloration as a continuous trait allowed us to go beyond much of the established knowledge through the detection of additional genes and gene-gene interactions that may contribute to the molecular architecture of the coloration phenotype.

The impact of physical frailty on the response to inactivated influenza vaccine in older adults

Physical frailty's impact on hemagglutination inhibition antibody titers (HAI) and peripheral blood mononuclear cell (PBMC) transcriptional responses after influenza vaccination is unclear. Physical frailty was assessed using the 5-item Fried frailty phenotype in 168 community- and assisted-living adults ≥55 years of age during an observational study. Blood was drawn before, 3, 7, and 28 days post-vaccination with the 2017-2018 inactivated influenza vaccine. HAI response to the A/H1N1 strain was measured at Days 0 and 28 using seropositivity, seroconversion, log2 HAI titers, and fold-rise in log2 HAI titers. RNA sequencing of PBMCs from Days 0, 3 and 7 was measured in 28 participants and compared using pathway analyses. Frailty was not significantly associated with any HAI outcome in multivariable models. Compared with non-frail participants, frail participants expressed decreased cell proliferation, metabolism, antibody production, and interferon signaling genes. Conversely, frail participants showed elevated gene expression in IL-8 signaling, T-cell exhaustion, and oxidative stress pathways compared with non-frail participants. These results suggest that reduced effectiveness of influenza vaccine among older, frail individuals may be attributed to immunosenescence-related changes in PBMCs that are not reflected in antibody levels.

MYC-regulated pseudogene HMGA1P6 promotes ovarian cancer malignancy via augmenting the oncogenic HMGA1/2

Pseudogenes have long been considered as nonfunctional genomic sequences. Recent studies have shown that they can potentially regulate the expression of protein-coding genes and are dysregulated in diseases including cancer. However, the potential roles of pseudogenes in ovarian cancer have not been well studied. Here we characterized the pseudogene expression profile in HGSOC (high-grade serous ovarian carcinoma) by microarray. We identified 577 dysregulated pseudogenes and most of them were up-regulated (538 of 577). HMGA1P6 (High mobility group AT-hook 1 pseudogene 6) was one of the overexpressed pseudogenes and its expression was inversely correlated with patient survival. Mechanistically, HMGA1P6 promoted ovarian cancer cell malignancy by acting as a ceRNA (competitive endogenous RNA) that led to enhanced HMGA1 and HMGA2 expression. Importantly, HMGA1P6 was transcriptionally activated by oncogene MYC in ovarian cancer. Our findings reveal that MYC may contribute to oncogenesis through transcriptional regulation of pseudogene HMGA1P6 in ovarian cancer.

Translational regulation contributes to the secretory response of chondrocytic cells following exposure to interleukin-1β

Osteoarthritis is a chronic disease characterized by the loss of articular cartilage in synovial joints through a process of extracellular matrix destruction that is strongly associated with inflammatory stimuli. Chondrocytes undergo changes to their protein translational capacity during osteoarthritis, but a study of how disease-relevant signals affect chondrocyte protein translation at the transcriptomic level has not previously been performed. In this study, we describe how the inflammatory cytokine interleukin 1-β (IL-1β) rapidly affects protein translation in the chondrocytic cell line SW1353. Using ribosome profiling we demonstrate that IL-1β induced altered translation of inflammatory-associated transcripts such as NFKB1, TNFAIP2, MMP13, CCL2, and CCL7, as well as a number of ribosome-associated transcripts, through differential translation and the use of multiple open reading frames. Proteomic analysis of the cellular layer and the conditioned media of these cells identified changes in a number of the proteins that were differentially translated. Translationally regulated secreted proteins included a number of chemokines and cytokines, underlining the rapid, translationally mediated inflammatory cascade that is initiated by IL-1β. Although fewer cellular proteins were found to be regulated in both ribosome profiling and proteomic data sets, we did find increased levels of SOD2, indicative of redox changes within SW1353 cells being modulated at the translational level. In conclusion, we have produced combined ribosome profiling and proteomic data sets that provide a valuable resource in understanding the processes that occur during cytokine stimulation of chondrocytic cells.

Pan-Cancer Analysis of TCGA Data Revealed Promising Reference Genes for qPCR Normalization

Quantitative PCR (qPCR) remains the most widely used technique for gene expression evaluation. Obtaining reliable data using this method requires reference genes (RGs) with stable mRNA level under experimental conditions. This issue is especially crucial in cancer studies because each tumor has a unique molecular portrait. The Cancer Genome Atlas (TCGA) project provides RNA-Seq data for thousands of samples corresponding to dozens of cancers and presents the basis for assessment of the suitability of genes as reference ones for qPCR data normalization. Using TCGA RNA-Seq data and previously developed CrossHub tool, we evaluated mRNA level of 32 traditionally used RGs in 12 cancer types, including those of lung, breast, prostate, kidney, and colon. We developed an 11-component scoring system for the assessment of gene expression stability. Among the 32 genes, PUM1 was one of the most stably expressed in the majority of examined cancers, whereas GAPDH, which is widely used as a RG, showed significant mRNA level alterations in more than a half of cases. For each of 12 cancer types, we suggested a pair of genes that are the most suitable for use as reference ones. These genes are characterized by high expression stability and absence of correlation between their mRNA levels. Next, the scoring system was expanded with several features of a gene: mutation rate, number of transcript isoforms and pseudogenes, participation in cancer-related processes on the basis of Gene Ontology, and mentions in PubMed-indexed articles. All the genes covered by RNA-Seq data in TCGA were analyzed using the expanded scoring system that allowed us to reveal novel promising RGs for each examined cancer type and identify several "universal" pan-cancer RG candidates, including SF3A1, CIAO1, and SFRS4. The choice of RGs is the basis for precise gene expression evaluation by qPCR. Here, we suggested optimal pairs of traditionally used RGs for 12 cancer types and identified novel promising RGs that demonstrate high expression stability and other features of reliable and convenient RGs (high expression level, low mutation rate, non-involvement in cancer-related processes, single transcript isoform, and absence of pseudogenes).

Genetic Separation of Listeria monocytogenes Causing Central Nervous System Infections in Animals

Listeria monocytogenes is a foodborne pathogen that causes abortion, septicemia, gastroenteritis and central nervous system (CNS) infections in ruminants and humans. L. monocytogenes strains mainly belong to two distinct phylogenetic groups, named lineages I and II. In general, clinical cases in humans and animals, in particular CNS infections, are caused by lineage I strains, while most of the environmental and food strains belong to lineage II. Little is known about why lineage I is more virulent than lineage II, even though various molecular factors and mechanisms associated with pathogenesis are known. In this study, we have used a variety of whole genome sequence analyses and comparative genomic tools in order to find characteristics that distinguish lineage I from lineage II strains and CNS infection strains from non-CNS strains. We analyzed 225 strains and identified single nucleotide variants between lineages I and II, as well as differences in the gene content. Using a novel approach based on Reads Per Kilobase per Million Mapped (RPKM), we identified 167 genes predominantly absent in lineage II but present in lineage I. These genes are mostly encoding for membrane-associated proteins. Additionally, we found 77 genes that are largely absent in the non-CNS associated strains, while 39 genes are especially lacking in our defined “non-clinical” group. Based on the RPKM analysis and the metadata linked to the L. monocytogenes strains, we identified 6 genes potentially associated with CNS cases, which include a transcriptional regulator, an ABC transporter and a non-coding RNA. Although there is not a clear separation between pathogenic and non-pathogenic strains based on phylogenetic lineages, the presence of the genes identified in our study reveals potential pathogenesis traits in ruminant L. monocytogenes strains. Ultimately, the differences that we have found in our study will help steer future studies in understanding the virulence mechanisms of the most pathogenic L. monocytogenes strains.

Hypoglycemic mechanisms of Ganoderma lucidum polysaccharides F31 in db/db mice via RNA-seq and iTRAQ

This study provides insight into the system-level hypoglycemic mechanisms of Ganoderma lucidum polysaccharides F31 by the integrative analysis of transcriptomics and proteomics data.

Transcriptomic Analysis of Young and Old Erythrocytes of Fish

Understanding gene expression changes over the lifespan of cells is of fundamental interest and gives important insights into processes related to maturation and aging. This study was undertaken to understand the global transcriptome changes associated with aging in fish erythrocytes. Fish erythrocytes retain their nuclei throughout their lifetime and they are transcriptionally and translationally active. However, they lose important functions during their lifespan in the circulation. We separated rainbow trout (Oncorhynchus mykiss) erythrocytes into young and old fractions using fixed angle-centrifugation and analyzed transcriptome changes using RNA sequencing (RNA-seq) technology and quantitative real-time PCR. We found 930 differentially expressed between young and old erythrocyte fractions; 889 of these showed higher transcript levels in young, while only 34 protein-coding genes had higher transcript levels in old erythrocytes. In particular genes involved in ion binding, signal transduction, membrane transport, and those encoding various enzyme classes are affected in old erythrocytes. The transcripts with higher levels in old erythrocytes were associated with seven different GO terms within biological processes and nine within molecular functions and cellular components, respectively. Our study furthermore found several highly abundant transcripts as well as a number of differentially expressed genes (DEGs) for which the protein products are currently not known revealing the gaps of knowledge in most non-mammalian vertebrates. Our data provide the first insight into changes involved in aging on the transcriptional level and thus opens new perspectives for the study of maturation processes in fish erythrocytes.

Relevance of iPSC-derived human PGC-like cells at the surface of embryoid bodies to prechemotaxis migrating PGCs

Human primordial germ cell-like cells (hPGCLCs) generated from pluripotent stem cells in vitro hold promise, with broad applications for studies of human germline cells. We show that hPGCLCs generated using several distinct protocols are transcriptomally comparable and that primed pluripotency human iPSCs gain competence to generate hPGCLCs after only 72 hours of reprogramming toward ERK-independent state-naïve pluripotency. hPGCLCs were localized in the outermost surface layer of embryoid bodies and strongly expressed CXCR4. Live cell imaging showed active migratory activity of hPGCLCs, and their exposure to the CXCR4 ligand CXCL12/SDF-1 induced enriched expression of promigratory genes and antiapoptotic genes. These results support the resemblance of hPGCLCs to prechemotaxis human embryonic primordial germ cells migrating in the midline region of embryos.

Pluripotent stem cell-derived human primordial germ cell-like cells (hPGCLCs) provide important opportunities to study primordial germ cells (PGCs). We robustly produced CD38⁺ hPGCLCs [∼43% of FACS-sorted embryoid body (EB) cells] from primed-state induced pluripotent stem cells (iPSCs) after a 72-hour transient incubation in the four chemical inhibitors (4i)-naïve reprogramming medium and showed transcriptional consistency of our hPGCLCs with hPGCLCs generated in previous studies using various and distinct protocols. Both CD38⁺ hPGCLCs and CD38⁻ EB cells significantly expressed PRDM1 and TFAP2C, although PRDM1 mRNA in CD38⁻ cells lacked the 3′-UTR harboring miRNA binding sites regulating mRNA stability. Genes up-regulated in hPGCLCs were enriched for cell migration genes, and their promoters were enriched for the binding motifs of TFAP2 (which was identified in promoters of T, NANOS3, and SOX17) and the RREB-1 cell adhesion regulator. In EBs, hPGCLCs were identified exclusively in the outermost surface monolayer as dispersed cells or cell aggregates with strong and specific expression of POU5F1/OCT4 protein. Time-lapse live cell imaging revealed active migration of hPGCLCs on Matrigel. Whereas all hPGCLCs strongly expressed the CXCR4 chemotaxis receptor, its ligand CXCL12/SDF1 was not significantly expressed in the whole EBs. Exposure of hPGCLCs to CXCL12/SDF1 induced cell migration genes and antiapoptosis genes. Thus, our study shows that transcriptionally consistent hPGCLCs can be readily produced from hiPSCs after transition of their pluripotency from the primed state using various methods and that hPGCLCs resemble the early-stage PGCs randomly migrating in the midline region of human embryos before initiation of the CXCL12/SDF1-guided chemotaxis.

The pseudogene derived from long non-coding RNA DUXAP10 promotes colorectal cancer cell growth through epigenetically silencing of p21 and PTEN

Recently, substantial evidence has demonstrated that pseudogene derived lncRNAs are crucial regulators of cancer development and progression. DUXAP10,a pseudogene derived long non-coding RNA(lncRNA), is overexpression in colorectal cancer (CRC), but its expression pattern, biological function and underlying mechanism in CRC is still undetermined. In this study, we observed that DUXAP10 was up-regulated in CRC tissues which was positively correlated with advanced pathological stages, larger tumor sizes and lymph node metastasis. Additionally, knockdown of DUXAP10 inhibited cell proliferation, induced cell apoptosis and increase the number of G0/G1 cells significantly in the HCT116 and SW480 cell lines. Moreover, DUXAP10 silencing inhibited tumor growth in vivo. Further mechanism study showed that, by binding to histone demethylase lysine-specific demethylase 1 (LSD1), DUXAP10 promote CRC cell growth and reduced cell apoptosis through silencing the expression of p21 and phosphatase and tensin homolog (PTEN) tumor suppressor. Our findings suggested that the pseudogene-derived from lncRNA DUXAP10 promotes the biological progression of CRC and is likely to be a potential therapeutic target for CRC intervention.

Efficient Approach to Correct Read Alignment for Pseudogene Abundance Estimates

RNA-Sequencing has been the leading technology to quantify expression of thousands of genes simultaneously. The data analysis of an RNA-Seq experiment starts from aligning short reads to the reference genome/transcriptome or reconstructed transcriptome. However, current aligners lack the sensitivity to distinguish reads that come from homologous regions of an genome. One group of these homologies is the paralog pseudogenes. Pseudogenes arise from duplication of a set of protein coding genes, and have been considered as degraded paralogs in the genome due to their lost of functionality. Recent studies have provided evidence to support their novel regulatory roles in biological processes. With the growing interests in quantifying the expression level of pseudogenes at different tissues or cell lines, it is critical to have a sensitive method that can correctly align ambiguous reads and accurately estimate the expression level among homologous genes. Previously in PseudoLasso, we proposed a linear regression approach to learn read alignment behaviors, and to leverage this knowledge for abundance estimation and alignment correction. In this paper, we extend the work of PseudoLasso by grouping the homologous genomic regions into different communities using a community detection algorithm, followed by building a linear regression model separately for each community. The results show that this approach is able to retain the same accuracy as PseudoLasso. By breaking the genome into smaller homologous communities, the running time is improved from quadratic growth to linear with respect to the number of genes.

eMERGE Phenome-Wide Association Study (PheWAS) identifies clinical associations and pleiotropy for stop-gain variants

BACKGROUND

We explored premature stop-gain variants to test the hypothesis that variants, which are likely to have a consequence on protein structure and function, will reveal important insights with respect to the phenotypes associated with them. We performed a phenome-wide association study (PheWAS) exploring the association between a selected list of functional stop-gain genetic variants (variation resulting in truncated proteins or in nonsense-mediated decay) and an extensive group of diagnoses to identify novel associations and uncover potential pleiotropy.

RESULTS

In this study, we selected 25 stop-gain variants: 5 stop-gain variants with previously reported phenotypic associations, and a set of 20 putative stop-gain variants identified using dbSNP. For the PheWAS, we used data from the electronic MEdical Records and GEnomics (eMERGE) Network across 9 sites with a total of 41,057 unrelated patients. We divided all these samples into two datasets by equal proportion of eMERGE site, sex, race, and genotyping platform. We calculated single effect associations between these 25 stop-gain variants and ICD-9 defined case-control diagnoses. We also performed stratified analyses for samples of European and African ancestry. Associations were adjusted for sex, site, genotyping platform and the first three principal components to account for global ancestry. We identified previously known associations, such as variants in LPL associated with hyperglyceridemia indicating that our approach was robust. We also found a total of three significant associations with p < 0.01 in both datasets, with the most significant replicating result being LPL SNP rs328 and ICD-9 code 272.1 "Disorder of Lipoid metabolism" (pdiscovery = 2.59x10-6, preplicating = 2.7x10-4). The other two significant replicated associations identified by this study are: variant rs1137617 in KCNH2 gene associated with ICD-9 code category 244 "Acquired Hypothyroidism" (pdiscovery = 5.31x103, preplicating = 1.15x10-3) and variant rs12060879 in DPT gene associated with ICD-9 code category 996 "Complications peculiar to certain specified procedures" (pdiscovery = 8.65x103, preplicating = 4.16x10-3).

CONCLUSION

In conclusion, this PheWAS revealed novel associations of stop-gained variants with interesting phenotypes (ICD-9 codes) along with pleiotropic effects.

MeSiC: A Model-Based Method for Estimating 5 mC Levels at Single-CpG Resolution from MeDIP-seq

As the fifth base in mammalian genome, 5-methylcytosine (5 mC) is essential for many biological processes including normal development and disease. Methylated DNA immunoprecipitation sequencing (MeDIP-seq), which uses anti-5 mC antibodies to enrich for methylated fraction of the genome, is widely used to investigate methylome at a resolution of 100–500 bp. Considering the CpG density-dependent bias and limited resolution of MeDIP-seq, we developed a Random Forest Regression (RFR) model method, MeSiC, to estimate DNA methylation levels at single-base resolution. MeSiC integrated MeDIP-seq signals of CpG sites and their surrounding neighbors as well as genomic features to construct genomic element-dependent RFR models. In the H1 cell line, a high correlation was observed between MeSiC predictions and actual 5 mC levels. Meanwhile, MeSiC enabled to calibrate CpG density-dependent bias of MeDIP-seq signals. Importantly, we found that MeSiC models constructed in the H1 cell line could be used to accurately predict DNA methylation levels for other cell types. Comparisons with methylCRF and MEDIPS showed that MeSiC achieved comparable and even better performance. These demonstrate that MeSiC can provide accurate estimations of 5 mC levels at single-CpG resolution using MeDIP-seq data alone.

Ribosomal proteins as novel players in tumorigenesis

Ribosome biogenesis is the most demanding energetic and metabolic expenditure of the cell. The nucleolus, a nuclear compartment, coordinates rRNA transcription, maturation, and assembly into ribosome subunits. The transcription process is highly coordinated with ribosome biogenesis. In this context, ribosomal proteins (RPs) play a crucial role. In the last decade, an increasing number of studies have associated RPs with extraribosomal functions related to proliferation. Importantly, the expression of RPs appears to be deregulated in several human disorders due, at least in part, to genetic mutations. Although the deregulation of RPs in human malignancies is commonly observed, a more complex mechanism is believed to be involved, favoring the tumorigenic process, its progression and metastasis. This review explores the roles of the most frequently mutated oncogenes and tumor suppressor genes in human cancer that modulate ribosome biogenesis, including their interaction with RPs. In this regard, we propose a new focus for novel therapies.

Pseudogenes transcribed in breast invasive carcinoma show subtype-specific expression and ceRNA potential

Background

Recent studies have shown that some pseudogenes are transcribed and contribute to cancer when dysregulated. In particular, pseudogene transcripts can function as competing endogenous RNAs (ceRNAs). The high similarity of gene and pseudogene nucleotide sequence has hindered experimental investigation of these mechanisms using RNA-seq. Furthermore, previous studies of pseudogenes in breast cancer have not integrated miRNA expression data in order to perform large-scale analysis of ceRNA potential. Thus, knowledge of both pseudogene ceRNA function and the role of pseudogene expression in cancer are restricted to isolated examples.

Results

To investigate whether transcribed pseudogenes play a pervasive regulatory role in cancer, we developed a novel bioinformatic method for measuring pseudogene transcription from RNA-seq data. We applied this method to 819 breast cancer samples from The Cancer Genome Atlas (TCGA) project. We then clustered the samples using pseudogene expression levels and integrated sample-paired pseudogene, gene and miRNA expression data with miRNA target prediction to determine whether more pseudogenes have ceRNA potential than expected by chance.

Conclusions

Our analysis identifies with high confidence a set of 440 pseudogenes that are transcribed in breast cancer tissue. Of this set, 309 pseudogenes exhibit significant differential expression among breast cancer subtypes. Hierarchical clustering using only pseudogene expression levels accurately separates tumor samples from normal samples and discriminates the Basal subtype from the Luminal and Her2 subtypes. Correlation analysis shows more positively correlated pseudogene-parent gene pairs and negatively correlated pseudogene-miRNA pairs than expected by chance. Furthermore, 177 transcribed pseudogenes possess binding sites for co-expressed miRNAs that are also predicted to target their parent genes. Taken together, these results increase the catalog of putative pseudogene ceRNAs and suggest that pseudogene transcription in breast cancer may play a larger role than previously appreciated.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1227-8) contains supplementary material, which is available to authorized users.

The zinc finger protein ZNF658 regulates the transcription of genes involved in zinc homeostasis and affects ribosome biogenesis through the zinc transcriptional regulatory element

We previously identified the ZTRE (zinc transcriptional regulatory element) in genes involved in zinc homeostasis and showed that it mediates transcriptional repression in response to zinc. We now report that ZNF658 acts at the ZTRE. ZNF658 was identified by matrix-assisted laser desorption ionization-time of flight mass spectrometry of a band excised after electrophoretic mobility shift assay using a ZTRE probe. The protein contains a KRAB domain and 21 zinc fingers. It has similarity with ZAP1 from Saccharomyces cerevisiae, which regulates the response to zinc restriction, including a conserved DNA binding region we show to be functional also in ZNF658. Small interfering RNA (siRNA) targeted to ZNF658 abrogated the zinc-induced, ZTRE-dependent reduction in SLC30A5 (ZnT5 gene), SLC30A10 (ZnT10 gene), and CBWD transcripts in human Caco-2 cells and the ability of zinc to repress reporter gene expression from corresponding promoter-reporter constructs. Microarray analysis of the effect of reducing ZNF658 expression by siRNA uncovered a large decrease in rRNA. We find that ZTREs are clustered within the 45S rRNA precursor. We also saw effects on expression of multiple ribosomal proteins. ZNF658 thus links zinc homeostasis with ribosome biogenesis, the most active transcriptional, and hence zinc-demanding, process in the cell. ZNF658 is thus a novel transcriptional regulator that plays a fundamental role in the orchestrated cellular response to zinc availability.

Advanced Datamining Using RNAseq Data

In recent years, RNA sequencing (RNAseq) technology has experienced a rapid rise in popularity. Often seen as a competitor of and the ultimate successor to microarray technology given its more accurate and quantitative gene expression measurement, RNAseq also offers a wealth of additional information that is often overlooked, and given the massive accumulation of RNAseq data available in public data repositories over the past few years, these data are ripe for discovery. Abundant opportunities exist for researchers to conduct in-depth, non-traditional analyses that take advantage of these secondary uses and for bioinformaticians to develop tools to make these data more accessible. This is discussed in this chapter.

Contribution of pseudogenes to sequence diversity

Pseudogenes are very common in the genomes of a wide range of organisms and, although they were originally considered as genetic junk, now several functions have been attributed to them. One important function of pseudogenes, as discussed in this chapter, is to provide material for genetic diversity. This is most prominent in the case of immunological recognition molecules such as immunoglobulins and B- and T-cell receptors, as well as in the case of antigenic variation in intracellular pathogens. Other examples discussed are olfactory receptors, ribosomal proteins, cytochrome P450s, and pseudokinases.

Hepatic signaling by the mechanistic target of rapamycin complex 2 (mTORC2)

The mechanistic target of rapamycin (mTOR) exists in two complexes that regulate diverse cellular processes. mTOR complex 1 (mTORC1), the canonical target of rapamycin, has been well studied, whereas the physiological role of mTORC2 remains relatively uncharacterized. In mice in which the mTORC2 component Rictor is deleted in liver [Rictor-knockout (RKO) mice], we used genomic and phosphoproteomic analyses to characterize the role of hepatic mTORC2 in vivo. Overnight food withdrawal followed by refeeding was used to activate mTOR signaling. Rapamycin was administered before refeeding to specify mTORC2-mediated events. Hepatic mTORC2 regulated a complex gene expression and post-translational network that affects intermediary metabolism, ribosomal biogenesis, and proteasomal biogenesis. Nearly all changes in genes related to intermediary metabolic regulation were replicated in cultured fetal hepatocytes, indicating a cell-autonomous effect of mTORC2 signaling. Phosphoproteomic profiling identified mTORC2-related signaling to 144 proteins, among which were metabolic enzymes and regulators. A reduction of p38 MAPK signaling in the RKO mice represents a link between our phosphoproteomic and gene expression results. We conclude that hepatic mTORC2 exerts a broad spectrum of biological effects under physiological conditions. Our findings provide a context for the development of targeted therapies to modulate mTORC2 signaling.

Pseudogenes: pseudo or real functional elements?

Pseudogenes are genomic remnants of ancient protein-coding genes which have lost their coding potentials through evolution. Although broadly existed, pseudogenes used to be considered as junk or relics of genomes which have not drawn enough attentions of biologists until recent years. With the broad applications of high-throughput experimental techniques, growing lines of evidence have strongly suggested that some pseudogenes possess special functions, including regulating parental gene expression and participating in the regulation of many biological processes. In this review, we summarize some basic features of pseudogenes and their functions in regulating development and diseases. All of these observations indicate that pseudogenes are not purely dead fossils of genomes, but warrant further exploration in their distribution, expression regulation and functions. A new nomenclature is desirable for the currently called 'pseudogenes' to better describe their functions.