Conditional splicing system for tight control of viral overlapping genes.

Viral genomes frequently harbor overlapping genes, complicating the development of virus-vectored vaccines and gene therapies. This study introduces a novel conditional splicing system to precisely control the expression of such overlapping genes through recombinase-mediated conditional splicing. We refined site-specific recombinase (SSR) conditional splicing systems and explored their mechanisms. The systems demonstrated exceptional inducibility (116,700-fold increase) with negligible background expression, facilitating the conditional expression of overlapping genes in adenovirus-associated virus (AAV) and human immunodeficiency virus type 1. Notably, this approach enabled the establishment of stable AAV producer cell lines, encapsulating all necessary packaging genes. Our findings underscore the potential of the SSR-conditional splicing system to significantly advance vector engineering, enhancing the efficacy and scalability of viral-vector-based therapies and vaccines. IMPORTANCE: Regulating overlapping genes is vital for gene therapy and vaccine development using viral vectors. The regulation of overlapping genes presents challenges, including cytotoxicity and impacts on vector capacity and genome stability, which restrict stable packaging cell line development and broad application. To address these challenges, we present a "loxp-splice-loxp"-based conditional splicing system, offering a novel solution for conditional expression of overlapping genes and stable cell line establishment. This system may also regulate other cytotoxic genes, representing a significant advancement in cell engineering and gene therapy as well as biomass production.

Revealing the pharmacological effects of Remodelin against osteosarcoma based on network pharmacology, acRIP-seq and experimental validation.

Osteosarcoma (OS) is the most common primary malignant tumor of bone. Remodelin, an inhibitor of the N (4)-Acetylcytidine (ac4C) acetylation modifying enzyme N-acetyltransferase 10 (NAT10), has been shown to have therapeutic effects on cancer in several studies, and our previous studies have confirmed the inhibitory effect of Remodelin on OS cells, however, the mechanism of action has not yet been elucidated. We used network pharmacological analysis to quantify the therapeutic targets of Remodelin against OS. acRIP-seq and RNA-seq were performed to investigate the inhibitory activity of Remodelin on acetylation and its effect on the transcriptome after intervening in OS cells U2OS with Remodelin in vitro. Key target genes were deduced based on their pharmacological properties, combined with network pharmacology results and sequencing results. Finally, the deduced target genes were validated with vitro experiments. Network pharmacological analysis showed that 2291 OS-related target genes and 369 Remodelin-related target genes were obtained, and 116 overlapping genes were identified as Remodelin targets for OS treatment. Sequencing results showed that a total of 13,736 statistically significant ac4C modification peaks were detected by acRIP-seq, including 6938 hypoacetylation modifications and 6798 hyperacetylation modifications. A total of 2350 statistically significant mRNAs were detected by RNA-seq, of which 830 were up-regulated and 1520 were down-regulated. Association analyses identified a total of 382 genes that were Hypoacetylated-down, consistent with inhibition of mRNA acetylation and expression by Remodelin. Five genes, CASP3, ESR2, FGFR2, IGF1 and MAPK1, were identified as key therapeutic targets of Remodelin against OS. Finally, in vitro experiments, CCK-8 and qRT-PCR demonstrated that Remodelin indeed inhibited the proliferation of OS cells and reduced the expression of three genes: ESR2, IGF1, and MAPK1. In conclusion, ESR2, IGF1 and MAPK1 were identified as key therapeutic targets of Remodelin against OS. This reveals the target of Remodelin's pharmacological action on OS and provides new ideas for the treatment of OS.

Identification of immunogenic cell death-related genes involved in Alzheimer's disease.

Alzheimer's disease (AD) is the leading cause of dementia worldwide, with recent studies highlighting the potential role of immunogenic cell death (ICD) in the pathogenesis of this neurodegenerative disorder. A total of 52 healthy controls and 64 patients with AD were included. Compared to the controls, the patients with AD exhibited 2392 differentially expressed genes (DEGs), of which 1015 and 1377 were upregulated and downregulated genes, respectively. Among them, nine common genes were identified by intersecting the AD-related module genes with the DEGs and ICD-associated genes. Gene ontology (GO)analysis further revealed "positive regulation of cytokine production" as the most significant term. Moreover, the enriched molecular functions were primarily related to the inflammatory body complex, while the overlapping genes were significantly enriched in lipopolysaccharide binding. Kyoto encyclopedia of genes and genomes (KEGG) analysis also indicated that these overlapping genes were mainly enriched in immunity, inflammation, and lipid metabolism pathways. Furthermore, the following four hub genes were detected using machine learning algorithms: P2RX7, HSP90AA1, NT5E, and NLRP3. These genes demonstrated significant differences in expression between the AD and healthy control groups (P < 0.05). Additionally, the area under the curve values of these four genes were all > 0.7, indicating their potential diagnostic value for AD. We further validated the protein levels of these four genes in the hippocampus of 3xTg-AD and C57BL/6J mice, showing P2RX7 and HSP90AA1 expression levels consistent with the previously analyzed trends. Finally, the single-sample gene set enrichment analysis (ssGSEA) algorithm provided additional evidence by demonstrating the crucial role of immune cell infiltration and its link with the hub genes in AD progression. Our study results suggest that ICD-mediated elevation of HSP90AA1 and P2RX7 levels and the resulting induction of tau hyperphosphorylation and neuroinflammation are vital in the AD pathogenic mechanism.

Bioinformatics-led discovery of liver-specific genes and macrophage infiltration in acute liver injury.

Background: Acute liver injury (ALI) is an important global health concern, primarily caused by widespread hepatocyte cell death, coupled with a complex immune response and a lack of effective remedies. This study explores the underlying mechanisms, immune infiltration patterns, and potential targets for intervention and treatment ALI. Methods: The datasets of acetaminophen (APAP), carbon tetrachloride (CCl4), and lipopolysaccharide (LPS)-induced ALI were obtained from the GEO database. Differentially expressed genes (DEGs) were individually identified using the limma packages. Functional enrichment analysis was performed using KEGG, GO, and GSEA methods. The overlapping genes were extracted from the three datasets, and hub genes were identified using MCODE and CytoHubba algorithms. Additionally, PPI networks were constructed based on the String database. Immune cell infiltration analysis was conducted using ImmuCellAI, and the correlation between hub genes and immune cells was determined using the Spearman method. The relationship between hub genes, immune cells, and biochemical indicators of liver function (ALT, AST) was validated using APAP and triptolide (TP) -induced ALI mouse models. Results: Functional enrichment analysis indicated that all three ALI models were enriched in pathways linked to fatty acid metabolism, drug metabolism, inflammatory response, and immune regulation. Immune analysis revealed a significant rise in macrophage infiltration. A total of 79 overlapping genes were obtained, and 10 hub genes were identified that were consistent with the results of the biological information analysis after screening and validation. Among them, Clec4n, Ms4a6d, and Lilrb4 exhibited strong associations with macrophage infiltration and ALI.

Exploring the shared molecular mechanisms between systemic lupus erythematosus and primary Sjögren's syndrome based on integrated bioinformatics and single-cell RNA-seq analysis.

Background: Systemic lupus erythematosus (SLE) and primary Sjögren's syndrome (pSS) are common systemic autoimmune diseases that share a wide range of clinical manifestations and serological features. This study investigates genes, signaling pathways, and transcription factors (TFs) shared between SLE and pSS. Methods: Gene expression profiles of SLE and pSS were obtained from the Gene Expression Omnibus (GEO). Weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis were conducted to identify shared genes related to SLE and pSS. Overlapping genes were then subject to Gene Ontology (GO) and protein-protein interaction (PPI) network analyses. Cytoscape plugins cytoHubba and iRegulon were subsequently used to screen shared hub genes and predict TFs. In addition, gene set variation analysis (GSVA) and CIBERSORTx were used to calculate the correlations between hub genes and immune cells as well as related pathways. To confirm these results, hub genes and TFs were verified in microarray and single-cell RNA sequencing (scRNA-seq) datasets. Results: Following WGCNA and limma analysis, 152 shared genes were identified. These genes were involved in interferon (IFN) response and cytokine-mediated signaling pathway. Moreover, we screened six shared genes, namely IFI44L, ISG15, IFIT1, USP18, RSAD2 and ITGB2, out of which three genes, namely IFI44L, ISG15 and ITGB2 were found to be highly expressed in both microarray and scRNA-seq datasets. IFN response and ITGB2 signaling pathway were identified as potentially relevant pathways. In addition, STAT1 and IRF7 were identified as common TFs in both diseases. Conclusion: This study revealed IFI44L, ISG15 and ITGB2 as the shared genes and identified STAT1 and IRF7 as the common TFs of SLE and pSS. Notably, the IFN response and ITGB2 signaling pathway played vital roles in both diseases. Our study revealed common pathogenetic characteristics of SLE and pSS. The particular roles of these pivotal genes and mutually overlapping pathways may provide a basis for further mechanistic research.

Comparative transcriptome analysis of unfractionated peripheral blood leukocytes after exercise in human.

Exercise has profound but variable effects on the immune system. However, only limited information exists about the changes of exercise-induced gene expression in whole immune cells. The aim of this study is to unravel the potential molecular changes of genes which are related to immunity after exercise. The raw expression data and corresponding clinical of GSE18966 were downloaded from Gene Expression Omnibus database. The differentially expressed genes between control group and treat groups were performed by in-house developed perl scripts. A total of 83 differentially expressed genes (DEGs) (|log2 FC|> 1, FDR < 0.05) were identified between control and treat group 1 (0 h after exercise), 128 DEGs (|log2 FC|> 1, FDR < 0.05) between control and treat group 2 (4 h after exercise), and there was no significant difference between control and treat group 3 (20 h after exercise). Next, we identified 51 overlapping genes between treat group 1 (0 h after exercise) and treat group 2 (4 h after exercise) using Venn analysis. Protein-protein interaction (PPI) network was constructed by Cytoscape 3.7.2, and nine hub genes (S100A12, FCGR3B, FPR1, VNN2, AQP9, MMP9, OSM, NCF4, HP) were identified. Finally, 9 hub genes were identified as the potential biomarkers of exercise using validation set (GSE83578) verification analysis. These hub genes might serve as potential molecular targets of monitoring exercise and training processes in the further.

Prolonging genetic circuit stability through adaptive evolution of overlapping genes.

The development of synthetic biological circuits that maintain functionality over application-relevant time scales remains a significant challenge. Here, we employed synthetic overlapping sequences in which one gene is encoded or 'entangled' entirely within an alternative reading frame of another gene. In this design, the toxin-encoding relE was entangled within ilvA, which encodes threonine deaminase, an enzyme essential for isoleucine biosynthesis. A functional entanglement construct was obtained upon modification of the ribosome-binding site of the internal relE gene. Using this optimized design, we found that the selection pressure to maintain functional IlvA stabilized the production of burdensome RelE for >130 generations, which compares favorably with the most stable kill-switch circuits developed to date. This stabilizing effect was achieved through a complete alteration of the allowable landscape of mutations such that mutations inactivating the entangled genes were disfavored. Instead, the majority of lineages accumulated mutations within the regulatory region of ilvA. By reducing baseline relE expression, these more 'benign' mutations lowered circuit burden, which suppressed the accumulation of relE-inactivating mutations, thereby prolonging kill-switch function. Overall, this work demonstrates the utility of sequence entanglement paired with an adaptive laboratory evolution campaign to increase the evolutionary stability of burdensome synthetic circuits.

Contribution of labor related gene subtype classification on heterogeneity of polycystic ovary syndrome.

OBJECTIVE: As one of the most common endocrine disorders in women of reproductive age, polycystic ovary syndrome (PCOS) is highly heterogeneous with varied clinical features and diverse gestational complications among individuals. The patients with PCOS have 2-fold higher risk of preterm labor which is associated with substantial infant morbidity and mortality and great socioeconomic cost. The study was designated to identify molecular subtypes and the related hub genes to facilitate the susceptibility assessment of preterm labor in women with PCOS. METHODS: Four mRNA datasets (GSE84958, GSE5090, GSE43264 and GSE98421) were obtained from Gene Expression Omnibus database. Twenty-eight candidate genes related to preterm labor or labor were yielded from the researches and our unpublished data. Then, we utilized unsupervised clustering to identify molecular subtypes in PCOS based on the expression of above candidate genes. Key modules were generated with weighted gene co-expression network analysis R package, and their hub genes were generated with CytoHubba. The probable biological function and mechanism were explored through Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis. In addition, STRING and Cytoscape software were used to identify the protein-protein interaction (PPI) network, and the molecular complex detection (MCODE) was used to identify the hub genes. Then the overlapping hub genes were predicted. RESULTS: Two molecular subtypes were found in women with PCOS based on the expression similarity of preterm labor or labor-related genes, in which two modules were highlighted. The key modules and PPI network have five overlapping five hub genes, two of which, GTF2F2 and MYO6 gene, were further confirmed by the comparison between clustering subgroups according to the expression of hub genes. CONCLUSIONS: Distinct PCOS molecular subtypes were identified with preterm labor or labor-related genes, which might uncover the potential mechanism underlying heterogeneity of clinical pregnancy complications in women with PCOS.

Transcriptomic analysis reveals the potential crosstalk genes and immune relationship between IgA nephropathy and periodontitis.

Background: It is well known that periodontitis has an important impact on systemic diseases. The aim of this study was to investigate potential crosstalk genes, pathways and immune cells between periodontitis and IgA nephropathy (IgAN). Methods: We downloaded periodontitis and IgAN data from the Gene Expression Omnibus (GEO) database. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were used to identify shared genes. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the shared genes. Hub genes were further screened using least absolute shrinkage and selection operator (LASSO) regression, and a receiver operating characteristic (ROC) curve was drawn according to the screening results. Finally, single-sample GSEA (ssGSEA) was used to analyze the infiltration level of 28 immune cells in the expression profile and its relationship with shared hub genes. Results: By taking the intersection of WGCNA important module genes and DEGs, we found that the SPAG4, CCDC69, KRT10, CXCL12, HPGD, CLDN20 and CCL187 genes were the most important cross-talk genes between periodontitis and IgAN. GO analysis showed that the shard genes were most significantly enriched in kinase regulator activity. The LASSO analysis results showed that two overlapping genes (CCDC69 and CXCL12) were the optimal shared diagnostic biomarkers for periodontitis and IgAN. The immune infiltration results revealed that T cells and B cells play an important role in the pathogenesis of periodontitis and IgAN. Conclusion: This study is the first to use bioinformatics tools to explore the close genetic relationship between periodontitis and IgAN. The SPAG4, CCDC69, KRT10, CXCL12, HPGD, CLDN20 and CCL187 genes were the most important cross-talk genes between periodontitis and IgAN. T-cell and B-cell-driven immune responses may play an important role in the association between periodontitis and IgAN.

Three Novel Antisense Overlapping Genes in E. coli O157:H7 EDL933.

The abundance of long overlapping genes in prokaryotic genomes is likely to be significantly underestimated. To date, only a few examples of such genes are fully established. Using RNA sequencing and ribosome profiling, we found expression of novel overlapping open reading frames in Escherichia coli O157:H7 EDL933 (EHEC). Indeed, the overlapping candidate genes are equipped with typical structural elements required for transcription and translation, i.e., promoters, transcription start sites, as well as terminators, all of which were experimentally verified. Translationally arrested mutants, unable to produce the overlapping encoded protein, were found to have a growth disadvantage when grown competitively against the wild type. Thus, the phenotypes found imply biological functionality of the genes at the level of proteins produced. The addition of 3 more examples of prokaryotic overlapping genes to the currently limited, yet constantly growing pool of such genes emphasizes the underestimated coding capacity of bacterial genomes. IMPORTANCE The abundance of long overlapping genes in prokaryotic genomes is likely to be significantly underestimated, since such genes are not allowed in genome annotations. However, ribosome profiling catches mRNA in the moment of being template for protein production. Using this technique and subsequent experiments, we verified 3 novel overlapping genes encoded in antisense of known genes. This adds more examples of prokaryotic overlapping genes to the currently limited, yet constantly growing pool of such genes.

Overlapping gene dependencies for PARP inhibitors and carboplatin response identified by functional CRISPR-Cas9 screening in ovarian cancer.

PARP inhibitors (PARPi) have revolutionized the therapeutic landscape of epithelial ovarian cancer (EOC) treatment with outstanding benefits in regard to progression-free survival, especially in patients either carrying BRCA1/2 mutations or harboring defects in the homologous recombination repair system. Yet, it remains uncertain which PARPi to apply and how to predict responders when platinum sensitivity is unknown. To shed light on the predictive power of genes previously suggested to be associated with PARPi response, we systematically reviewed the literature and identified 79 publications investigating a total of 93 genes. The top candidate genes were further tested using a comprehensive CRISPR-Cas9 mutagenesis screening in combination with olaparib treatment. Therefore, we generated six constitutive Cas9+ EOC cell lines and profiled 33 genes in a CRISPR-Cas9 cell competition assay using non-essential (AAVS1) and essential (RPA3 and PCNA) genes for cell fitness as negative and positive controls, respectively. We identified only ATM, MUS81, NBN, BRCA2, and RAD51B as predictive markers for olaparib response. As the major survival benefit of PARPi treatment was reported in platinum-sensitive tumors, we next assessed nine top candidate genes in combination with three PARPi and carboplatin. Interestingly, we observed similar dropout rates in a gene and compound independent manner, supporting the strong correlation of cancer cell response to compounds that rely on DNA repair for their effectiveness. In addition, we report on CDK12 as a common vulnerability for EOC cell survival and proliferation without altering the olaparib response, highlighting its potential as a therapeutic target in EOC.

Constrained evolution of overlapping genes in viral host adaptation: Acquisition of glycosylation motifs in hepadnaviral precore/core genes.

Hepadnaviruses use extensively overlapping genes to expand their coding capacity, especially the precore/core genes encode the precore and core proteins with mostly identical sequences but distinct functions. The precore protein of the woodchuck hepatitis virus (WHV) is N-glycosylated, in contrast to the precore of the human hepatitis B virus (HBV) that lacks N-glycosylation. To explore the roles of the N-linked glycosylation sites in precore and core functions, we substituted T77 and T92 in the WHV precore/core N-glycosylation motifs (75NIT77 and 90NDT92) with the corresponding HBV residues (E77 and N92) to eliminate the sequons. Conversely, these N-glycosylation sequons were introduced into the HBV precore/core gene by E77T and N92T substitutions. We found that N-glycosylation increased the levels of secreted precore gene products from both HBV and WHV. However, the HBV core (HBc) protein carrying the E77T substitution was defective in supporting virion secretion, and during infection, the HBc E77T and N92T substitutions impaired the formation of the covalently closed circular DNA (cccDNA), the critical viral DNA molecule responsible for establishing and maintaining infection. In cross-species complementation assays, both HBc and WHV core (WHc) proteins supported all steps of intracellular replication of the heterologous virus while WHc, with or without the N-glycosylation sequons, failed to interact with HBV envelope proteins for virion secretion. Interestingly, WHc supported more efficiently intracellular cccDNA amplification than HBc in the context of either HBV or WHV. These findings reveal novel determinants of precore secretion and core functions and illustrate strong constraints during viral host adaptation resulting from their compact genome and extensive use of overlapping genes.

Using networks to analyze and visualize the distribution of overlapping genes in virus genomes.

Gene overlap occurs when two or more genes are encoded by the same nucleotides. This phenomenon is found in all taxonomic domains, but is particularly common in viruses, where it may increase the information content of compact genomes or influence the creation of new genes. Here we report a global comparative study of overlapping open reading frames (OvRFs) of 12,609 virus reference genomes in the NCBI database. We retrieved metadata associated with all annotated open reading frames (ORFs) in each genome record to calculate the number, length, and frameshift of OvRFs. Our results show that while the number of OvRFs increases with genome length, they tend to be shorter in longer genomes. The majority of overlaps involve +2 frameshifts, predominantly found in dsDNA viruses. Antisense overlaps in which one of the ORFs was encoded in the same frame on the opposite strand (-0) tend to be longer. Next, we develop a new graph-based representation of the distribution of overlaps among the ORFs of genomes in a given virus family. In the absence of an unambiguous partition of ORFs by homology at this taxonomic level, we used an alignment-free k-mer based approach to cluster protein coding sequences by similarity. We connect these clusters with two types of directed edges to indicate (1) that constituent ORFs are adjacent in one or more genomes, and (2) that these ORFs overlap. These adjacency graphs not only provide a natural visualization scheme, but also a novel statistical framework for analyzing the effects of gene- and genome-level attributes on the frequencies of overlaps.

Are There Hidden Genes in DNA/RNA Vaccines?

Due to the fast global spreading of the Severe Acute Respiratory Syndrome Coronavirus - 2 (SARS-CoV-2), prevention and treatment options are direly needed in order to control infection-related morbidity, mortality, and economic losses. Although drug and inactivated and attenuated virus vaccine development can require significant amounts of time and resources, DNA and RNA vaccines offer a quick, simple, and cheap treatment alternative, even when produced on a large scale. The spike protein, which has been shown as the most antigenic SARS-CoV-2 protein, has been widely selected as the target of choice for DNA/RNA vaccines. Vaccination campaigns have reported high vaccination rates and protection, but numerous unintended effects, ranging from muscle pain to death, have led to concerns about the safety of RNA/DNA vaccines. In parallel to these studies, several open reading frames (ORFs) have been found to be overlapping SARS-CoV-2 accessory genes, two of which, ORF2b and ORF-Sh, overlap the spike protein sequence. Thus, the presence of these, and potentially other ORFs on SARS-CoV-2 DNA/RNA vaccines, could lead to the translation of undesired proteins during vaccination. Herein, we discuss the translation of overlapping genes in connection with DNA/RNA vaccines. Two mRNA vaccine spike protein sequences, which have been made publicly-available, were compared to the wild-type sequence in order to uncover possible differences in putative overlapping ORFs. Notably, the Moderna mRNA-1273 vaccine sequence is predicted to contain no frameshifted ORFs on the positive sense strand, which highlights the utility of codon optimization in DNA/RNA vaccine design to remove undesired overlapping ORFs. Since little information is available on ORF2b or ORF-Sh, we use structural bioinformatics techniques to investigate the structure-function relationship of these proteins. The presence of putative ORFs on DNA/RNA vaccine candidates implies that overlapping genes may contribute to the translation of smaller peptides, potentially leading to unintended clinical outcomes, and that the protein-coding potential of DNA/RNA vaccines should be rigorously examined prior to administration.

Immune microenvironment infiltration landscape and immune-related subtypes in prostate cancer.

Background: The tumor microenvironment (TME) primarily comprises cancer cells, cancer-infiltrating immune cells, and stromal cells. The tumor cells alter the TME by secreting signaling molecules to induce immune tolerance. The immune cell infiltrating the TME influences the prognosis of patients with cancers. However, immune cell infiltration (ICI) in the TME of patients with prostate cancer (PC) has not yet been studied. Methods: In this study, we used Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) and Estimation of Stromal and Immune cells in Malignant Tumors using Expression data (ESTIMATE) algorithms to identify three ICI clusters based on 1,099 genes associated with ICI in the TME. The patients were classified into three distinct ICI gene clusters based on overlapping differentially expressed genes in ICI clusters. Furthermore, the ICI scores were calculated using principal component analysis. Results: The results revealed that patients with high ICI scores had poor prognoses and reduced expression of immune-checkpoint genes and immune-related genes. Furthermore, the transforming growth factor-beta (TGF-ß) and WNT-ß signaling pathways were enriched in the high ICI score subgroup, which suggests that suppression of T cells could contribute to poor prognosis of patients with PC. A positive correlation was observed between the high-ICI-score subgroup and the high tumor mutation burden (TMB) value. Patients with low ICI scores could benefit from immunotherapy, indicating that the ICI score could be used to predict the efficacy of immunotherapeutic response. Conclusions: In summary, we provide a comprehensive overview of the landscape of ICI in PC, which could aid in designing the strategies for immunotherapy for patients with PC.

Computational methods for inferring location and genealogy of overlapping genes in virus genomes: approaches and applications.

Viruses may evolve to increase the amount of encoded genetic information by means of overlapping genes, which utilize several reading frames. Such overlapping genes may be especially impactful for genomes of small size, often serving a source of novel accessory proteins, some of which play a crucial role in viral pathogenicity or in promoting the systemic spread of virus. Diverse genome-based metrics were proposed to facilitate recognition of overlapping genes that otherwise may be overlooked during genome annotation. They can detect the atypical codon bias associated with the overlap (e.g. a statistically significant reduction in variability at synonymous sites) or other sequence-composition features peculiar to overlapping genes. In this review, I compare nine computational methods, discuss their strengths and limitations, and survey how they were applied to detect candidate overlapping genes in the genome of SARS-CoV-2, the etiological agent of COVID-19 pandemic.

Blood RNA sequencing shows overlapping gene expression across COPD phenotype domains.

RATIONALE: COPD can be assessed using multidimensional grading systems with components from three domains: pulmonary function tests, symptoms and systemic features. Clinically, measures may be used interchangeably, though it is not known if they share similar pathobiology. OBJECTIVE: To use RNA sequencing (RNA-seq) to determine if there is an overlap in the underlying biological mechanisms and consequences driving different components of the multidimensional grading systems. METHODS: Whole blood was collected for RNA-seq from current and former smokers in the Genetic Epidemiology of COPD study. We tested the overlap in gene expression and biological pathways associated with case-control status and quantitative COPD phenotypes within and between the three domains. RESULTS: In 2647 subjects, there were 3030 genes differentially expressed in any of the three domains or case-control status. There were five genes that overlapped between the three domains and case-control status, including G protein-coupled receptor 15(GPR15), sestrin 1 (SESN1) and interferon-induced guanylate-binding protein 1 (GBP1), which were associated with longitudinal decline in FEV1. The overlap between the three domains was enriched for pathways related to cellular components. CONCLUSIONS: We identified gene sets and pathways that overlap between 12 COPD-related phenotypes and case-control status. There were no pathways represented in the overlap between the three domains and case-control status, but we identified multiple genes that demonstrated a consistent pattern of expression across several of the phenotypes. Patterns of gene expression correlation were generally similar to the correlation of clinical phenotypes in the PFT and symptom domains but not the systemic features.

Overlapping genes in natural and engineered genomes.

Modern genome-scale methods that identify new genes, such as proteogenomics and ribosome profiling, have revealed, to the surprise of many, that overlap in genes, open reading frames and even coding sequences is widespread and functionally integrated into prokaryotic, eukaryotic and viral genomes. In parallel, the constraints that overlapping regions place on genome sequences and their evolution can be harnessed in bioengineering to build more robust synthetic strains and constructs. With a focus on overlapping protein-coding and RNA-coding genes, this Review examines their discovery, topology and biogenesis in the context of their genome biology. We highlight exciting new uses for sequence overlap to control translation, compress synthetic genetic constructs, and protect against mutation.

Biological factors in the synthetic construction of overlapping genes.

BACKGROUND: Overlapping genes (OLGs) with long protein-coding overlapping sequences are disallowed by standard genome annotation programs, outside of viruses. Recently however they have been discovered in Archaea, diverse Bacteria, and Mammals. The biological factors underlying life's ability to create overlapping genes require more study, and may have important applications in understanding evolution and in biotechnology. A previous study claimed that protein domains from viruses were much better suited to forming overlaps than those from other cellular organisms - in this study we assessed this claim, in order to discover what might underlie taxonomic differences in the creation of gene overlaps. RESULTS: After overlapping arbitrary Pfam domain pairs and evaluating them with Hidden Markov Models we find OLG construction to be much less constrained than expected. For instance, close to 10% of the constructed sequences cannot be distinguished from typical sequences in their protein family. Most are also indistinguishable from natural protein sequences regarding identity and secondary structure. Surprisingly, contrary to a previous study, virus domains were much less suitable for designing OLGs than bacterial or eukaryotic domains were. In general, the amount of amino acid change required to force a domain to overlap is approximately equal to the variation observed within a typical domain family. The resulting high similarity between natural sequences and those altered so as to overlap is mostly due to the combination of high redundancy in the genetic code and the evolutionary exchangeability of many amino acids. CONCLUSIONS: Synthetic overlapping genes which closely resemble natural gene sequences, as measured by HMM profiles, are remarkably easy to construct, and most arbitrary domain pairs can be altered so as to overlap while retaining high similarity to the original sequences. Future work however will need to assess important factors not considered such as intragenic interactions which affect protein folding. While the analysis here is not sufficient to guarantee functional folding proteins, further analysis of constructed OLGs will improve our understanding of the origin of these remarkable genetic elements across life and opens up exciting possibilities for synthetic biology.

Prediction of two novel overlapping ORFs in the genome of SARS-CoV-2.

Six candidate overlapping genes have been detected in SARS-CoV-2, yet current methods struggle to detect overlapping genes that recently originated. However, such genes might encode proteins beneficial to the virus, and provide a model system to understand gene birth. To complement existing detection methods, I first demonstrated that selection pressure to avoid stop codons in alternative reading frames is a driving force in the origin and retention of overlapping genes. I then built a detection method, CodScr, based on this selection pressure. Finally, I combined CodScr with methods that detect other properties of overlapping genes, such as a biased nucleotide and amino acid composition. I detected two novel ORFs (ORF-Sh and ORF-Mh), overlapping the spike and membrane genes respectively, which are under selection pressure and may be beneficial to SARS-CoV-2. ORF-Sh and ORF-Mh are present, as ORF uninterrupted by stop codons, in 100% and 95% of the SARS-CoV-2 genomes, respectively.