Pericentromeric Transcription of Novel Pathogen-Related Human GPS Genes in Cancers is Regulated by C19MC miRNAs, CEBPB, IFN-γ, and IFN-β

Pericentromeric Transcription of Novel Pathogen-Related Human GPS Genes in Cancers is Regulated by C19MC miRNAs, CEBPB, IFN-γ, and IFN-β | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Pericentromeric Transcription of Novel Pathogen-Related Human GPS Genes in Cancers is Regulated by C19MC miRNAs, CEBPB, IFN-γ, and IFN-β Goodwin Jinesh, Isha Godwin, Marco Napoli, Elsa Flores, Andrew Brohl This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8621807/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Pericentromeric transcription is unique to testis, and oocytes among the normal tissues. However, its regulation in cancer is not well-understood. Here, we discover a novel human, intron-less, coding, pericentromeric GPS gene family in cancer cells, with protein-level homology to microbial proteins from Plasmodium , Staphylococcus, Streptococcus , and Mycobacterium tuberculosis . GPS proteins harbor a conserved FPFP-motif, characteristic of a Mycobacterial protein that hijacks the host ERK-1/2 phosphorylation. We examined the two most expressed GPS family genes ( C6GPS , and C17GPS ) in cancer cells and discovered that the pericentromeric transcription is regulated by interferon-γ and interferon-β, CEBPB-LAP, and antiviral C19MC-miRNAs. Furthermore, GPS mRNAs are suppressed by truncation mutations, and nonsense-mediated decay (NMD). Thus, we discovered a novel pathogen-related GPS gene family in the human genome, and its pericentromeric transcription-regulatory network. This discovery will help to understand the role of GPS pericentromeric transcription in the biology, immunotherapy, and host-pathogen relationships of cancers in the future. Biological sciences/Genetics/Genome/Open reading frames Biological sciences/Genetics/Genotype Biological sciences/Immunology/Antimicrobial responses Biological sciences/Immunology/Cytokines/Interferons Biological sciences/Immunology/Tumour immunology GPS: Genes at Pericentromeric-repeat Sequences Pericentromeric transcription C6GPS C17GPS CEBPB-LAP Nonsense-mediated decay (NMD) IFN-γ IFN-β Plasmodium ovale wallikeri Staphylococcus hominis Streptococcus pneumoniae Streptomyces sp. Miniopterus natalensis Vibrio vulnificus Salmonella enterica C19MC miR-519D miR-520G miR-526B Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Summary Pericentromeric transcription is unique to testis, and oocytes among the normal tissues. However, its regulation in cancer is not well-understood. Here, we discover a novel human, intron-less, coding, pericentromeric GPS gene family in cancer cells, with protein-level homology to microbial proteins from , , and . GPS proteins harbor a conserved FPFP-motif, characteristic of a protein that hijacks the host ERK-1/2 phosphorylation. We examined the two most expressed GPS family genes (, and ) in cancer cells and discovered that the pericentromeric transcription is regulated by interferon-γ and interferon-β, CEBPB-LAP, and antiviral C19MC-miRNAs. Furthermore, GPS mRNAs are suppressed by truncation mutations, and nonsense-mediated decay (NMD). Thus, we discovered a novel pathogen-related GPS gene family in the human genome, and its pericentromeric transcription-regulatory network. This discovery will help to understand the role of GPS pericentromeric transcription in the biology, immunotherapy, and host-pathogen relationships of cancers in the future. Introduction Human centromeres, and pericentromeres are highly enriched with repetitive sequences 1 – 5 , and the presence of coding genes within these regions is rare. Although centromeres, and pericentromeres constitute a large portion of the non-coding region within the human genome, transcription of non-coding RNA genes and a few coding genes does happen within centromeric, and pericentromeric regions 6 , 7 resulting in clearly defined functions such as meiosis 8 – 10 , mitosis 11 , self-renewal in senescent cells 1 , centromeric cohesion 12 , CENP-A targeting to the centromere 13 , and drug resistance 14 . Therefore, centromeric and pericentromeric transcription is important for the chromosome dynamics during cell division 12 , and can serve as a basic mechanism related to chromosomal instability or stability 15 . However, regulation of the human pericentromeric transcription is not well-understood except that it is repressed in most normal human tissues, excluding testis 7 , and mature oocytes 3 , indicating a developmental role, which was demonstrated in mice 16 , 17 in addition to gametogenesis. Pericentromeric chromatin differs from centromeric chromatin by having predominant H3K27me3 methylation mark through transcript-directed recruitment of methylation factors to the pericentromeric region 18 . H3K27me3 mark is also associated with PRC-1 and PRC-2-dependant chromatin compaction and heterochromatinization to repress genes 19 . Hypomethylation of pericentromeric chromatin leads to interferon (IFN) response 20 . Interestingly, the IFN-β promoter tends to associate with pericentromeric heterochromatin, and which dissociates from pericentromeric chromatin upon viral infection to promote IFN expression 21 . IFN signaling is tightly associated with the viral response of the host 22 , and viruses stimulate an antiviral response miRNA cluster from chromosome-19 (Chromosome-19 miRNA cluster: C19MC) 23 – 28 , which is widely expressed in human cancers with critical functions 19 , 29 – 32 . Importantly, we uncovered the role of C19MC in nuclear division without nuclear envelope breakdown (NEBD) during a novel meiosis-III that happens in multiple human cancers 29 . Of note, meiosis is also related to pericentromeric transcription 8 – 10 , testis, and oocyte development 33 , 34 . The biological context and regulation of pericentromeric transcription during C19MC viral response, and interferon immune responses are not understood to date. Human pathogens (such as multiple viruses 35 , 36 , Plasmodium 37 , 38 , Staphylococcus 39 , 40 , Streptococcus 41 – 43 , Mycobacterium tuberculosis 44 , 45 , and Salmonella 46 ) are capable of eliciting interferon response in hosts. IFN signals through STATs, and extracellular signal-regulated kinases-1 and 2 (popularly referred to as ERK-1/2) to activate CCAAAT/Enhancer-binding Protein-β (CEBPB)-dependent transcription 47 . CEBPB is often co-expressed with antiviral C19MC in human cancers 31 and modulates transcription in response to C19MC miRNA/IFN-γ 25 and has cooperative functions with C19MC miRNAs 28 . In the context of chronic/persistent infections pathogens disable IFN signaling at multiple level 36 , including the inhibition of ERK signaling. For example, the FPFP motif of the Mce3E protein of Mycobacterium tuberculosis binds to and inhibits host/human ERK signaling in the context of persistent Mycobacterium tuberculosis infection 48 . However, the relationship between human pathogens, interferon signaling, CEBPB, and C19MC miRNAs in the pericentromeric transcription context remains unknown. Nonsense-mediated decay (NMD) is a mechanism of RNA catabolism where the unwanted transcripts such as mutated/translation truncated mRNAs are degraded using exonucleases, and endonucleases. Viruses 49 and other pathogens influence the host NMD mechanism, or have their own NMD mechanism to remodel the transcriptome 50 . A widespread absence of pericentromeric transcripts in normal tissues 7 suggests that either a strong transcriptional repression at the pericentromeric region such as heterochromatinization, or an RNA decay mechanism such as NMD, might suppress the pericentromeric transcripts, but this is not understood to date. Here, we discovered and characterized a novel intron-less, coding, pericentromeric GPS ( G enes at P ericentromeric-repeat S equences) human gene family with protein-level homology to proteins from Plasmodium ovale/walkeri , Staphylococcus hominis, Streptococcus pneumoniae, Streptomyces kurssanovii, Mycobacterium tuberculosis , Salmonella enterica , and other pathogens, expressed in human cancer cells. We identify a highly conserved FPFP motif within the entire GPS gene family member proteins along with multiple proteins from various human pathogens, and a bat genus that often serves as a reservoir for viruses ( Miniopterus ). We further found that the pericentromeric transcription is regulated by IFN-γ, IFN-β, CEBPB-LAP, miR-519D, miR-520G, and miR-526B (C19MC-miRNAs). Finally, we uncovered that the pericentromeric GPS mRNA transcripts are suppressed by nonsense-mediated decay (NMD). Thus, our study sheds light on the role of GPS pericentromeric transcription in the biology of cancers, especially in the contexts of immune (interferons), antiviral response (C19MC miRNAs), transcription (CEBPB), mutation and NMD, and paves the way to better understand antiviral, pathogen-induced, and pericentromeric transcription-directed signaling in human host cells in future. Results Discovery and characterization of C6GPS, a pericentromeric intron-less gene To understand pericentromeric transcription, we scanned the pericentromeric regions of the human genome for the H3K27ac mark using the UCSC genome browser. We identified a strong H3K27ac mark that falls within the repetitive DNA region but closely outside the centromere of the chromosome-6 at the p-arm side (Figure-1A). Notably, this region is not conserved and is specific to humans among the 100 vertebrate genomes of the PhyloP set (Figure-1A). We refer to this locus as the c hromosome- 6 g ene at the p ericentromeric s equence ( C6GPS ) based on the findings below. To confirm the pericentromeric nature and transcription competent potential, we examined the MCF-7 ChIP-seq data of H3K27ac (transcription potential), p300 (transcription potential), and H3K27me3 (pericentromeric mark) and found that the C6GPS locus is indeed at the pericentromeric transcriptional region (Figure-1B). We chose the MCF-7 cell line for its known phenotypic features in meiosis-III 29 . We also found that c-Jun transcription factor can bind to the C6GPS locus in MCF-7 cells (Figure-1C). Considering multiple transcription factors (c-Jun and p300) can bind to the C6GPS locus, we examined this region for any potential open reading frames (ORF) and found an ORF of 624 nucleotides in length with start, and stop codons (Figure-1D). The annotated protein sequence of this ORF indicated that C6GPS is a 207 amino acid long protein with a predicted molecular weight of 22.77 kDa and an isoelectric pH of 9.63, enriched in tyrosine, serine, and threonine residues, suggesting that C6GPS could be regulated by both receptor tyrosine kinases (RTKs), and serine/threonine kinases (STKs) (Figure-1E). Sequence homology search using BLASTp has shown that C6GPS has strong similarities to pathogen proteins such as 9APIC of Plasmodium falciparum , and STAHO of Staphylococcus hominis , among many others (see below) (Figure-1E). To determine if C6GPS is transcribed into mRNA, we performed RT-PCR in MCF-7 cells and found a feeble product of the expected size (~ 813 base pairs). To confirm its identity and to understand if it has undergone splicing, we reamplified this product and subjected it to Sanger sequencing (Figure-1F). The sequencing data revealed that C6GPS is an intronless gene and its mRNA is not subjected to splicing (Figure-1F and Figure-S1). Taken these data together, C6GPS is an intronless pericentromeric gene with protein-level homology to proteins from human pathogens, and is transcribed in MCF-7 cells without splicing. Discovery and characterization of C17GPS, a pericentromeric intron-less gene To further investigate the pericentromeric transcription we undertook a nucleotide sequence-based search of C6GPS within the human genome and found no strong homologous genes. However, when we further examined the pericentromeric regions of the human genome for the H3K27ac mark, we identified another strong H3K27ac mark that falls within the repetitive DNA region but closely outside the centromere (pericentromeric region) of the chromosome-17 at the p-arm side (Figure-2A). Notably, this region is not conserved and is specific to humans among the 100 vertebrate genomes of the PhyloP set (Figure-2A). We refer to this locus as the c hromosome- 17 g ene at the p ericentromeric s equence ( C17GPS ) based on the findings below. To confirm the pericentromeric nature and transcription competent potential, we examined the MCF-7 ChIP-seq data of H3K27ac (transcription potential), p300 (transcription potential), and H3K27me3 (pericentromeric mark) and found that the C17GPS locus is indeed bound by p300 but had feeble H3K27ac and H3K27me3 marks in MCF-7 cells (Figure-1B). However, the K562 cell line exhibited strong H3K27ac and H3K27me3 marks, indicating that the C17GPS locus is in a potentially transcription-competent pericentromeric region (Figure-1C). We also found that c-Jun transcription factor can bind to the C17GPS locus in MCF-7 cells (Figure-1D). We examined both C6GPS and C17GPS loci for E2F1 binding (a meiosis-promoting transcription factor) and found that E2F1 can bind to both genes (Figure-1E). We examined the C17GPS locus for any potential open reading frames (ORF) and found an ORF of 792 nucleotides length with start, and stop codons (Figure-1F). The annotated protein sequence from this ORF indicated that C17GPS is a 263 amino acid long protein with a predicted molecular weight of 28.93 kDa and an isoelectric pH of 10.1, enriched in tyrosine, serine, and threonine residues suggesting that C17GPS could be regulated by both receptor tyrosine kinases (RTKs), and serine/threonine kinases (STKs) (Figure-1G). Sequence homology search using BLASTp has shown that the N-terminal half of C17GPS has strong similarities to pathogen proteins of Plasmodium ovale , Staphylococcus hominis, Mycobacterium tuberculosis, Streptococcus pneumoniae, and Streptomyces , among many others (see below) (Figure-1H). Though our C6GPS nucleotide-based search did not identify C17GPS, their proteins had strong conserved motifs indicating the existence of a protein-level homology despite having a low homology at the nucleotide-level (Figure-2I). To determine if C17GPS is transcribed into mRNA, we performed RT-PCR in MCF-7 cells and obtained a feeble product of the expected size (~ 969 base pairs). To confirm its identity and to understand if it has undergone splicing, we reamplified this product and subjected it to Sanger sequencing (Figure-1J). The sequencing data revealed that C17GPS is also an intronless gene and its mRNA is not subjected to splicing (Figure-1J and Figure-S2). Taken these data together, C17GPS is an intronless pericentromeric gene with protein-level homology to proteins from human pathogens, and is transcribed in MCF-7 cells without splicing. Discovery and characterization of pathogen-related GPS family of pericentromeric intron-less genes: the conserved FPFP motif and its truncation in cancer cells Identification of C6GPS and C17GPS at the pericentromeric region of different chromosomes prompted us to search for additional similar genes within the human genome. A nucleotide sequence-based search of C17GPS within the human genome resulted in the identification of 27 other homologous intronless genes, all located at the pericentromeric region of human chromosomes, with the exception of two genes that are located at the non-pericentromeric regions of chromosome-9 (Figure-3A). Notably, we did not identify pericentromeric genes at chromosomes-4, 13, and 22 based on C17GPS sequence similarity search (Figure-3A). We named these genes based on the chromosomes in which they are located, for example if the gene is localized to chromosome-1, then we named it as C1GPS , and so on. At this point, we called these genes collectively as the “GPS gene family”. Chromosome-Y harbors 5 GPS genes ( CYGPS1-5 ) which are identical in sequence and located close to each other suggesting that this could be due to the result of repetitive DNA expansion (Figure-3B). On the other hand, C9GPS1 and C9GPS2 were also identical but not located at the pericentromeric repeats (Figure-3B). At the nucleotide level, all GPS gene family genes showed considerable homology except C6GPS (Figure-3B). All wild-type nucleotide sequences of the ORFs of the GPS gene family members are provided in Supplementary table-1. At the protein level, about half of the GPS gene family members shown close homology to C17GPS (Figure-3B). All wild-type protein sequences of the GPS gene family members are provided in Supplementary table-2. Again, C6GPS stood out as different among all the GPS family members (Figure-3B) despite having conserved motifs with C17GPS (Figure-2I). Conserved peptide motif analysis among all GPS gene family members revealed the presence of a conserved 12–13 amino acid sequence. Homology search of this sequence using BLASTp revealed that this motif is also conserved with the proteins from multiple human pathogens including Plasmodium ovale, Mycobacterium tuberculosis, Staphylococcus hominis, Escherichia coli, Vibrio sp., Salmonella sp., Acinetobacter sp., Cronobacter sp., Lactobacillus crispatus , and others (Figure-3C). While this stretch of 12–13 amino acid sequence is well conserved, an FPFP motif within this sequence is notable as its function is known in the case of Mycobacterium tuberculosis FPFP motif of Mce3E protein, which binds to and inhibits host/human ERK phosphorylation-based signaling in the context of persistent infection 48 (Figure-3C). Among the human proteins, the FPFP motif is also present in a handful of proteins (Figure-3C), notably in human chorionic gonadotrophin (hCG), a known meiosis stimulator 29 . We next investigated the potential role of the FPFP motif of GPS genes in cancer. Sanger sequencing of C17GPS mRNA from MCF-7 cells revealed multiple mutations compared to the UCSC human reference genome, ranging from silent, substitution, to truncation mutations (Figure-3D). The truncation mutation identified was at codon G132Stop, which could potentially result in the loss of FPFP motif from the translation product (Figure-3D). To check if these mutations are specific to MCF-7 cells or also present in other cancer cells, we examined C17GPS mRNA in Hep3B cells. C17GPS mRNA of Hep3B cells harbored identical (codons F42V, K97R, P129P silent, V131A, N153K, R163T, N180K, I222V, S249S silent, A252P, and L253P) as well as unique (F13V, N133K, and R215R silent) mutations compared to the MCF-7 cell line (Figure-3E). Of note, these alterations could be due to de novo mutations or polymorphisms and understanding of which requires population-based studies. Importantly, the truncation mutation was identical to the MCF-7 C17GPS mRNA (G132Stop) (Figure-3E). Thus, the truncation mutation resulting in the loss of FPFP motif of GPS genes in cancer could be a common mechanism. Taken together, these data demonstrate that GPS genes are a family of pericentromeric intronless genes located in most human chromosomes with a homologous FPFP ERK-1/2 inhibitory motif at their protein sequences, which are lost due to truncation mutations in MCF-7 and Hep3B cell lines. Antiviral C19MC miRNAs are expressed with pericentromeric GPS genes in the Interferon context Considering the role of the FPFP motif in ERK-1/2 signaling and the role of ERK-1/2 in IFN-γ production, an essential role of interferons in the GPS gene family expression is conceivable. ERK-1/2 regulate the transcription of IFN-γ through the transcription factor CCAAAT/Enhancer-binding Protein-β (hereafter referred to as CEBPB) 47 in addition to its other targets, and IFN-γ is involved in the antiviral immunity 51 , 52 . Furthermore, multiple human pathogenic viruses are capable of eliciting C19MC miRNA response 26 , 27 as well as interferon response in hosts 35 , 36 . Therefore, we evaluated whether GPS mRNAs co-express with C19MC miRNAs. For this purpose, we first evaluated the expression of GPS gene mRNAs in 100 human cancer cell lines and found that GPS gene mRNAs are widely expressed in human cancer cell lines (Figure-4A). C6GPS and C17GPS mRNAs were the most expressed GPS family genes, followed by C9GPS1 and C9GPS2 mRNAs, which are not in fact pericentromeric genes but driven by non-coding RNA (ncRNA) host genes (Figure-4B). We matched the 100 cell line GPS gene expression data with C19MC miRNA data (miRNA-seq) and found that C19MC expression is tightly associated with GPS mRNA expression (Figure-4C). However, GPS gene mRNAs were also expressed in a small subset of cell lines without C19MC miRNA expression suggesting that the GPS gene family mRNAs could also be regulated independent of C19MC miRNA expression context. To understand the signaling context between the co-expression of C19MC miRNAs and GPS gene family mRNAs, we performed differential gene expression profiling of RNA-seq data of cell lines that co-express both GPS mRNAs plus C19MC miRNAs versus cells that do not express both RNAs (Figure-4C-D). While the results are enriched with interferon-related genes, we identify that the IFN-γ response geneset, and STAT-1/IRF1 as the most significantly enriched as well as most networked transcription factors (Figure-4E-F). Interferons, C19MC miRNAs, all-trans retinoic acid (ATRA), and NMD regulate pericentromeric transcription and mRNA levels of the GPS family genes Many of the IFN-γ pathway genes are also related to the IFN-β pathway, which is also involved in antiviral response, and were upregulated in C19MC plus GPS gene expression positive cell lines (Figure-5A). Some of the top downregulated genes were also a direct target of IFN-β regulated genes: for example, Ankyrin repeat gene ANK1 product is a target for IKBKE kinase, which usually targets ankyrin repeats (Figure-5A). We examined two transcription factors, STAT-1 and IRF-1 binding to make sure interferon-regulated transcription factors can bind to the C6GPS locus using MCF-7 ChIP-seq data. Both STAT-1 and IRF-1 can bind to the C6GPS locus (Figure-5B). Therefore, we examined if IFN-γ and IFN-β could modulate the pericentromeric transcription of C6GPS and C17GPS in MCF-7 cells. The results revealed that both IFN-γ and IFN-β at 1 nM final concentrations can induce the pericentromeric transcription of both C6GPS and C17GPS genes at 24 hours, and their combination had an additive effect on C6GPS gene transcript compared to C17GPS (Figure-5C). This result suggested that both IFN-γ and IFN-β could use independent as well as overlapping pathways to regulate pericentromeric transcription to achieve the additive effect. Next, we examined the effect of stable overexpression of antiviral C19MC miRNAs in MCF-7 cells. While we attempted three individual C19MC miRNAs (miR-519D, miR-520G, and miR-526B), we could generate stable cells only for miR-519D, and miR-526B. The C19MC miR-519D strongly induced the pericentromeric transcription of C17GPS compared to the C6GPS gene, whereas miR-526B did not have any effect (Figure-5D). This correlated with the sickle nuclear meiosis-III phenotype (Figure-5D), which we identified previously in response to miR-519D in MCF-7 cells 29 . As all-trans retinoic acid, a stimulator of meiosis-III in cancer cells 23 , which signals through one of its many receptors RAR-α (RARA), we examined the available RARA-ChIP-seq data to find whether RAR-α can bind to the C6GPS locus and found that RAR-α binds to the C6GPS locus in HepG2 cells (Figure-5E). Usage of all-trans retinoic acid (ATRA) in MCF-7 cells induced the pericentromeric transcription of both C6GPS and C17GPS mRNAs, and the usage of nonsense-mediated decay (NMD) inhibitor caffeine with ATRA further increased the levels of C6GPS and C17GPS mRNAs, indicating that the pericentromeric mRNAs are also subjected to NMD (Figure-5F). The inability of ATRA to induce pericentromeric C6GPS and C17GPS mRNAs in the presence of transcription inhibitor actinomycin-D indicated that fresh transcription is involved in the induction of pericentromeric transcripts by ATRA as a single agent (Figure-5F). Taken together, these results demonstrate that the pericentromeric transcription is regulated by IFN-γ, IFN-β, antiviral C19MC miRNAs, and ATRA in the meiosis-III context, and that these transcripts are subjected to nonsense-mediated decay. IFN-γ, CEBPB-LAP, and C19MC miRNAs cooperate to regulate pericentromeric GPS gene transcription CEBPB liver-enriched activator protein (CEBPB-LAP isoform) modulates the transcriptional outcome of MYO18B gene by IFN-γ in the context of C19MC miRNAs in the liver context 25 . Therefore, we examined if CEBPB can bind to the C6GPS locus in HepG2 ChIP-seq data. CEBPB binding to the C6GPS locus is induced by CEBPB activating stimulus (Forskolin) and is the strongest among all CEBPB binding sites in the entire chromosome-6 (Figure-6A). Stable overexpression of CEBPB-LAP isoform in Hep3B cells (Hep3B cells express basal C19MC miRNAs, and GPS gene expression: Figure-4C-D, and lack basal IFN-γ expression 25 ) by itself induced the pericentromeric transcription of C6GPS and C17GPS mRNAs (Figure-6B). As Hep3B cells lack basal expression of IFN-γ but not its receptors 25 , we examined the effect of exogenous IFN-γ in pericentromeric transcription. 1 nM IFN-γ in CEBPB-LAP stably overexpressed cells boosted the pericentromeric transcription of C6GPS and to a lesser extent of C17GPS genes (Figure-6C). Furthermore, stable overexpression of individual C19MC miRNAs miR-519D, miR-520G, and miR-526B induced the pericentromeric transcription of C17GPS and to a lesser extent C6GPS genes (Figure-6D). Finally, we asked the question whether the IFN-γ induced hyper-pericentromeric transcription of C6GPS in CEBPB-LAP overexpressed cells involve C19MC miRNAs. Quantitative real-time PCR analysis of C19MC miRNAs in this context revealed that an approximately 100-fold induction of endogenous miR-526B (and possibly more miRNAs from the C19MC) over the basal expression is accompanied with the hyper-pericentromeric transcription of C6GPS in CEBPB-LAP overexpressed cells in IFN-γ treated condition (Figure-6E). Therefore, we conclude that the CEBPB-LAP transcription factor cooperates with IFN-γ, and C19MC miRNAs to induce pericentromeric transcription. Discussion Cancers are known for rapid proliferation, which is mediated by mitotic cell division. Meiosis is confined to gametogenic tissues such as testis and ovary. However, non-germ line cancer cells from multiple cancer types exhibit spermatogenesis gene expression signature and exhibit a novel meiosis-III in the context of antiviral C19MC miRNA expression 29 . Pericentromeric transcription is restricted to testis 7 , and matured oocytes 3 and is repressed in other normal tissues. Pericentromeric transcription is associated with IFN signaling 20 and the IFN-β promoter tends to associate with pericentromeric heterochromatin, which dissociates from pericentromeric chromatin upon viral infection to promote IFN expression 21 . Here, we discovered a pericentromeric intron-less GPS gene family (Figure-7A-B) and identified that the pericentromeric transcription of these genes is regulated by cooperative interactions of IFN-γ, IFN-β, CEBPB-LAP, and C19MC miRNAs (Figure-7C). Homology of GPS family protein FPFP motifs to various proteins from microbes, including Plasmodium , and Mycobacterium tuberculosis , sheds more insight on the functions of GPS family genes (Figure-7B). For example, Plasmodium -driven malaria is resisted by sickle cell disease and bacterial coinfections 53 – 55 , and the sickling pattern is strikingly similar to meiotic sickle cell-like morphological features upon miR-519D overexpression in MCF-7 cells 29 (Figure-5D). Induction of pericentromeric transcription by meiotic inducer ATRA further supports this result (Figure-5E-F). Mycobacterium tuberculosis Mce3E protein FPFP motif is implicated in the ERK-1/2 phosphorylation 48 (Figure-7C). The truncation mutation in the C6GPS , and C17GPS genes in cell lines can potentially remove the FPFP motif in these gene products. However, any other GPS gene products could still contribute to the FPFP motif-mediated influence of ERK-1/2 signaling. The level of FPFP motif and its flanking sequence homology to various human pathogenic microbial proteins to GPS family proteins (Figure-7B) indicates the importance of pericentromeric transcription of GPS genes. Although the GPS genes are not conserved among 100 vertebrate genomes at the nucleotide level (Figures- 1 A and 2 A), their FPFP motif homology to proteins from the bat Miniopterus suggests a protein level conservation could exist among vertebrates. FPFP motif homology in Miniopterus is consistent with the fact that this bat is a reservoir for human pathogenic viruses 56 (Figures- 3 C and 7 B). Miniopterus natalensis bats are found in South Africa 57 , a place prone to HIV-1 epidemics 58 . Miniopterus natalensis bats have a mysterious chimera of CCR5 and CCR2 chemokine genes responsible for HIV-1 infection/entry 59 . This scenario is further complicated by increased maternal death associated with recent pregnancy (C19MC miRNAs express during pregnancy) by Mycobacterium tuberculosis in South Africa 60 . To add more spice, C19MC antiviral miRNA expression is strongly associated with HIV-infection signature in human cancers 29 . Therefore, the human GPS gene family and its homologous proteins of Miniopterus natalensis, Mycobacterium tuberculosis might play an important role in HIV-infection, and cancer biology in the context of C19MC miRNAs and interferons. While the truncation mutation precluding the translation of FPFP motifs from C6GPS and C17GPS, unusual stop codons are also capable of triggering nonsense-mediated decay (NMD) of target RNAs. As expected, we found that the pericentromeric mRNAs of C6GPS , and C17GPS are undergoing NMD (Figure-5F). Therefore, this could be a mechanism to keep these mRNAs in check, or a mechanism to prevent the inhibition of ERK-1/2, as cancers heavily depend on ERK-1/2 for oncogene-driven tumorigenesis 61 . In summary, our study uncovers a novel family of pericentromeric GPS genes that are related to various human pathogenic microbes, and their regulation by a cooperative network involving IFN-γ, IFN-β, CEBPB-LAP, and C19MC miRNAs. Further studies will help to understand the role of GPS pericentromeric transcription in the biology, immunotherapy, and host-pathogen relationships of cancers in the future. Materials and Methods Cell lines: culture and authentication by DNA fingerprinting. Human Hep3B hepatocellular carcinoma cells (ATCC # HB-8064), and MCF-7 (HTB22) human breast cancer cells were cultured in MEM containing L-Glutamine and Sodium bi-carbonate (Sigma #M4655), with 10% FBS (Sigma#F0926), vitamins (Gibco Life Technologies #11120052), sodium pyruvate (Gibco Life Technologies #11360070), non-essential amino acids (Gibco Life Technologies #11140050), and penicillin-streptomycin (Gibco Life Technologies #15140122). The cells were identity confirmed by STR fingerprinting as per institutional/lab standards. Fresh revived cells were used after every 6 months or after ~25 passages. The cells in culture were periodically tested for mycoplasma using MycoAlert Kit (Lonza). Plasmids: C19MC miRNAs, CEBPB-LAP, and their controls Glycerol stocks of mammalian expression vectors such as pMIR-CMV (Control), pMIR-CMV-519D (CR215546), pMIR-CMV-520G (CR215781), and pMIR-CMV-526B (CR215142) were purchased from Vigene Biosciences (Rockville, MD USA) and described previously 24 . The control pLenti-GIII-CMV-RFP-2A-Puro (Cat# LV084) and the LAP isoform-CEBPB pLenti-GIII-CMV-human-CEBPB-RFP-2A-Puro (Cat# LV796074) vectors were purchased from Applied Biological Materials Inc., Richmond, BC, Canada and described previously 25 . All plasmids were isolated using Qiagen MIDI prep kit (#12143) as per manufacturer’s instructions. Stable cell line generation and authentication Hep3B stable cells with C19MC miRNA overexpression (miR-519D, miR-520G, and miR-526B) is described previously 24 . Briefly, the transfections were done using plasmids (not viruses) and Lipofectamine 2000 (Life Technologies # 11668019) and selected using 4 mg/ml puromycin (Invitrogen # A1113803) for 2 months while GFP/RFP positive clones were picked, expanded and frozen. MCF-7 stable cells with C19MC miRNA overexpression (miR-519D, and miR-526B) is generated as described above but with gradual increase in puromycin, where the miR-520G failed to grow as cell line after transfection, and the cells were sorted for GFP positivity instead of clone picking. The FACS sorted cells were further subjected to STR fingerprinting to make sure the identity of MCF-7 cells and to rule out cross contamination of cells. Hep3B stable cells with CEBPB-LAP and its control plasmid overexpression is described previously 25 . Briefly, the cells were transfected using plasmids (not viruses) and Lipofectamine 2000 (Life Technologies # 11668019) as per manufacturer’s protocol, and selected using 4 mg/ml puromycin (Invitrogen # A1113803) for 2 months before colony picking by RFP positivity. The overexpression of CEBPB-LAP was confirmed by LAP-specific RT-PCR (See below for primer details). Reagents and treatment doses Kits: High-Capacity cDNA Reverse Transcription kit (ABI, Cat.# 4368814), Plasmid isolation MIDI-prep kit (Qiagen, Cat.# 12143), and Illustra GFX PCR DNA and Gel Band Purification Kit (GE Healthcare, Cat.# 28903470), Trizol RNA isolation reagent (ThermoFisher Scientific, Cat.# 15596018), miRNeasy Mini Kit (50) (Qiagen, Cat.# 217004). Cytokines and treatment conditions: IFN-γ (R&D Systems, Cat.# 285-IF-100, 1nM / 17 ng/ml for 24 h.), IFN-β (R&D Systems, Cat.# 8499-IF-010, 1nM / 20 ng/ml for 24 h.). Chemical reagents and treatment conditions: All-trans retinoic acid (ATRA) (Cayman Chemicals, Cat.# 11017, 1mM for 24 h.), betaine (5M stock: Sigma # B0300-1VL, St. Louis, MO, USA), and Caffeine (Cayman Chemicals, Cat.# 14118, 10mM for 24 h.). RT-PCR and sequencing primers Target mRNA Primer sequence Annealing C6GPS-Forward * † 5' ‐ TGCTCTATCAAGAGAAATGTTCCACC ‐ 3' 60 ˚ C C6GPS-Reverse * † 5' ‐ GAAAAGGGAATATCTTTCCATAAAAGG ‐ 3' 60 ˚ C C17GPS-Forward * 5' ‐ CAACGAGAGTTTCCAAAGTGCTCTC ‐ 3' 60 ˚ C C17GPS-Reverse * 5' ‐ GGGATAACTGCACCTAACTACACGG ‐ 3' 60 ˚ C MTCO1-Forward ** 5' ‐ ATGAGCTGGAGTCCTAGGCACAGC ‐ 3' 60 ˚ C MTCO1-Reverse ** 5' ‐ AACCTGTTCCTGCTCCGGCCTCC ‐ 3' 60 ˚ C CEBPB-LAP-Forward ** 5' ‐ AACGCCTGGTGGCCTGGGACCC ‐ 3' 60 ˚ C CEBPB-LAP-Reverse ** 5' ‐ AAGAGGTCGGAGAGGAAGTCGTGG ‐ 3' 60 ˚ C * Sequencing & RT-PCR primers used in this study ; ** Published previously 25 ; † G.G.J personal order. RNA isolation and Reverse transcriptase PCRs Total RNAs were isolated from cells were isolated from cells using either Trizol reagent, or using miRNeasy kit with RNAse-free DNAse digestion step as per manufacturer’s instructions. 20 ml complementary DNA (cDNA) synthesis reactions were performed using 1000 ng RNA and High-Capacity cDNA Reverse Transcription Kit with 1.5M final concentration of betaine (from 5M stock). The temperature steps for cDNA synthesis were, 25°C for 10m, 37°C for 120m and 85°C for 5m. The cDNAs were further diluted with 30 ml of nuclease free water and then 2.5 ml was used for each PCR reaction. For PCR reactions 1M betaine (final conc.) was used along with regular PCR reaction components ( Per reaction: 10X PCR buffer without MgCl 2 : 2.5 ml; 25 mM MgCl 2 : 1ml; 5M Betaine: 5 ml; dNTP mix [2.5 mM each]: 1 ml; Taq polymerase: 1.25 U; DEPC water: 12.5 ml). The primer sequences were indicated above and each primer (forward and reverse) are used at 1 ml per reaction from a 10 mM stock. All PCR reactions were subjected to an initial denaturation of 3 minutes, and cycling denaturation (95°C) time of 1-minute, annealing temperature of 60°C (30 seconds) and 1 minute of extension time (72°C), with 34 cycles. A final extension time of 5 minutes was given for complete product synthesis. The PCR reactions were run on 2% agarose gels with GeneRuler 100 bp DNA Ladder (ThermoFisher Scientific #SM0243). The gels were imaged using LI-COR Odyssey Fc imager (Lincoln, NE, USA). The expected product sizes were indicated in the figures. Sanger sequencing of C6GPS and C17GPS: mutation, and splicing analyses Initial RT-PCR amplificons of C6GPS, and C17GPS were reamplified for Sanger sequencing purposes. The reamplified products were GFX-column purified as per manufacturer’s instructions, and 5-10ng of purified products were submitted to paired-end Sanger sequencing PCR reaction with 1M betaine and single primer (forward or reverse) at Azenta (Genewiz/Azenta, USA). The sequences were analyzed using FinchTV chromatogram reader for mutations and splicing by comparing the corresponding UCSC human genome hg19 build as reference (The coordinates are indicated in the figures). The following mutant sequences (compared to the reference genome sequence of the ORF) were submitted to GenBank: C6GPS of MCF-7 cells (Accession: PX444937), C17GPS of MCF-7 cells (Accession: PX444936), C17GPS of Hep3B cells (Accession: PX444938). Bioinformatic ORF identification of C6GPS and C17GPS genes, protein annotation Pericentromeric human chromosome-6 and 17 regions were examined for H3K27Ac and H3K27me3 marks by enabling corresponding ChIP-seq layers in addition to repetitive DNA and centromeric DNA layers in UCSC genome browser (Hg19 build). DNA sequences that harbor H3K27Ac and H3K27me3 marks at the pericentromeric repetitive regions were subjected to 6-frame open reading frame analysis (ORF) in NCBI-ORF finder (https://www.ncbi.nlm.nih.gov/orffinder/) with ATG and alternative initiation codon, maximum ORF length, and standard genetic code options on. The ORFs were annotated to protein sequence using single letter amino acid code, to obtain calculated molecular weight using 110 Daltons weight for average amino acid. GPS gene epigenetic and transcription factor binding analysis: ChIP-seq Transcription factor binding to GPS gene family loci (CEBPB, RARA, Jun, Fos, E2F1, EP300/p300, STAT-1 and IRF-1) and epigenetic histone regulatory marks (H3K27Ac, and H3K27me3) were examined using cell line ChIP-seq data. All ChIP-seq data were accessed from Encyclopedia of DNA Elements (ENCODE) 64 or from UCSC Genome Browser (if indicated). CEBPB ChIP-seq data sets with or without forskolin induction in HepG2 cells [ENCODE: ENCSR000EEX file: ENCFF000XPP (fold change over control hg19) and ENCSR000BQI file: ENCFF321NDM (fold change over control hg19)] were examined for CEBPB binding at whole chromosome-6 as well as at the C6GPS locus and visualized using Integrative Genomics Viewer (IGV: BROAD institute, version 2.4.10) as peaks or as heatmap. The data range was kept constant (500) for both uninduced and forskolin induced peak tracks whereas the data range was represented as scale for heatmap. Other ChIP-seq data used were: RARA HepG2 (ENCSR500WXT: fold change over control; data range FC: 0-15), Jun MCF-7 (ENCFF513YRC: Signal p-Value; data range FC: 0-10, 0-30, 0-60), Fos MCF-7 (ENCFF950XOS: Signal p-Value; data range FC: 0-10, 0-30, 0-60), E2F1 MCF-7 (ENCFF000ZLB: signal; data range FC: 0-800), EP300 MCF-7 (ENCSR000BTR: fold change over control; data range FC: 0-5), H3K27Ac MCF-7 (ENCSR752UOD: fold change over control; data range FC: 0-5), H3K27me3 MCF-7 (ENCSR000EWP: fold change over control; data range FC: 0-5), STAT-1 K562: IFN-γ treated for 6 hours (ENCSR000EHJ: Signal p-Value; data range FC: 0-20), IRF-1 K562: IFN-γ treated for 6 hours (ENCSR000EGT: Signal p-Value; data range FC: 0-20), H3K27Ac K562 [from UCSC Genome Browser], and H3K27me3 K562 [from UCSC Genome Browser]. These ChIP-seq data sets were examined for binding at whole chromosome or C6GPS or C17GPS loci and visualized using Integrative Genomics Viewer (IGV: BROAD institute, version 2.4.10) as peaks or as heatmap. BLASTn and BLASTp homology search and nomenclature of GPS gene family members The C6GPS ORF was subjected to human genome contig and RefSeq transcriptome BLASTn searches in NCBI site (https://blast.ncbi.nlm.nih.gov/Blast.cgi) and no considerable matches were found. A similar search for C17GPS ORF yielded multiple ORFs with significant homology to C17GPS and predominantly localized to human pericentromeric regions. These genes are named based on the chromosome number in which it is located (For example, C3 if it is located on chromosome-3), and numbered if more than one such genes are located at same chromosomes (For example, six genes located on chromosome-Y: CYGPS1-6). Annotated protein sequences of GPS family members were subjected to non-redundant protein search across all proteins from multiple organisms including humans using BLASTp (https://blast.ncbi.nlm.nih.gov/Blast.cgi) and the matching reference protein sequences (RefSeq) were collected for further phylogenetic analysis (See below). A similar search and reference sequence collection was also done for nucleotide sequences of GPS family genes. GPS family gene mapping to human genome (Circos) Genomic visualization of GPS family genes was done using Circa software (http://omgenomics.com/circa) as described previously 28 . Genomic coordinates of GPS genes were collected based on the ATG start position of each gene (Hg19) from UCSC genome browser and layered along with the coordinates for centromeres, and Giemsa positivity of DNA. The circos plot was then composited and labelled in Adobe Photoshop CS5. GPS family nucleotide and protein similarity distance analysis (iTOL) Both nucleotide and protein BLAST matching sequences were subjected to sequence homology analysis using EMBL-EBI Clustal Omega (protein/nucleotide options) (https://www.ebi.ac.uk/jdispatcher/msa/clustalo?stype=protein). iTOL (https://itol.embl.de/). The cladograms were composited, and labelled in Adobe Photoshop CS5. The cladogram homology/identity scale is read based on the circular but not radial lines. A similar analysis, and compositing were done for FPFP motif matching proteins. GPS gene family mRNA and C19MC miRNA expression and differential gene expression analysis in CCLE cell lines: 100 cell lines that have miRNA-seq and RNA-seq datasets from Cancer Cell Line Encyclopedia (CCLE: https://sites.broadinstitute.org/ccle/) database were integrated by matching the cell lines, and examined for all GPS mRNA expressions in RNA-seq BAM files. Maximum reads at single point (MRSP) within the GPS gene ORF was considered as expression level. To get the expression level of an individual GPS gene, the reads of that gene across all 100 cell lines were added up to get a combined score. To get an expression level of overall GPS gene family, all reads of GPS family per cell line were added up to get a GPS score. The GPS score is then integrated with the cumulative C19MC miRNA expression and sorted based on C19MC expression before generating heatmap. From these 100 CCLE cell lines, high C19MC+GPS RNA expressing 12 cell lines, and an equal number of cell lines that lack C19MC+GPS RNAs were grouped (of GPS+C19MC-RNA Positive and GPS+C19MC-RNA Negative groups) for differential gene expression analysis. The differentially expressed genes (>2 or <-2 log 2 fold change) with p-value <0.05 were subjected to EnrichR analysis, and top-ranking gene sets were subjected to networked gene analysis using NetworkAnalyst web server (https://www.networkanalyst.ca/) 65 to find the top ranking transcription factors. The analysis was performed using the SIGNOR 2.0 database of Signaling Network as described previously 66 . Briefly, the top network node was organized into a circular/bi/tripartite layout before exporting the image. The gene names were relabeled in Adobe Photoshop CS5 to have legibility. Node tables were exported and the degree and betweenness scores were fed into the ggplot2 package in R to generate ranked dotplots to see the top-networked genes (Transcription factors were chosen). R code: > library(ggplot2) > ggplot(#DataFrameName, aes(x = Xgroup, y = YGene)) + geom_point(aes(size = Betweenness, color = Degree)) + scale_color_gradientn(colours = c("black", "blue", "magenta", "red"), limits = c(0, 50)) #DataFrameName: file name. The gene names in dotplots were relabeled in Adobe Photoshop CS5 to have legibility and color match. Microscopy C19MC miR-519D overexpressed stable MCF-7 cells were live stained with Hoechst-33342 (10 nM for 20 minutes; Cayman Chemicals, # 15547) for DNA and the sickle nuclear patterns of meiosis-III daughter cells were imaged using Zeiss Observer.Z1 microscope equipped with Axiocam 503 mono (Zeiss) camera, and composited in Adobe Photoshop CS5 as described previously 29 . Quantitative real-time PCR (qRT-PCR) quantification of C19MC miRNA expression Quantitative real-time PCRs (qRT-PCRs) for C19MC miRNAs were performed as described previously 29 . Briefly, RNAs were isolated from CEBPB-LAP overexpressed and their control stable cells (treated with or without 1 nM of IFN-γ for 24 hours) using miRNeasy Mini Kit, quantified using nanodrop. 250 ng RNAs were used for cDNA synthesis [using Multiscribe reverse transcriptase, RNAse inhibitor, 10X buffer, dNTPs, (TaqMan MicroRNA Reverse Transcription Kit: ABI, Cat # 4366596) and RT TaqMan Primers hsa-miR-519d-3p (ThermoFisher: Assay ID: 002403 ; Cat# 4427975), hsa-miR-520g-3p (ThermoFisher: Assay ID: 001121 ; Cat# 4427975), hsa-miR-526b-3p (ThermoFisher: Assay ID: 002383 ; Cat# 4427975), and RNU6B Control (ThermoFisher: Assay ID: 001093 ; Cat# 4427975)]. The cDNAs were further subjected to quantitative PCR reactions using corresponding PCR primers with probes and TaqMan Universal PCR Master Mix (Life Technologies Cat# 4324018). Comparative Ct (DDCt) was used to calculate the relative expression of C19MC miRNAs to the control cells, after normalizing the values based on RNU6B. The RNU6B values were set as 1 and the relative fold changes in C19MC miRNA expression were plotted using GraphPad Prism software as bar graphs with SEM as error bars (v7.04; La Jolla, CA, USA). The plot was composited and labelled in Adobe Photoshop CS5. Statistical analyses For EnrichR analysis, only statistically significant differentially expressed genes were included in the feed gene set, and the top signatures thus obtained with adjusted p-value below 0.05 were considered significant. For qRT-PCR bar-plots and other box-plots t-test statistical analysis was done using GraphPad Prism software (v7.04; La Jolla, CA, USA). The box-whisker plot is of 10-90 percentile type with 50% transparency for whisker data points. For GPS+C19MC positive and negative CCLE cell line groups, n=12 cell lines for GPS+C19MC-RNA Positive and GPS+C19MC-RNA Negative groups each was set based on C19MC miRNA expression set, and an equal number of negative cell lines were included to have equal statistical power. For ChIP-seq data the fold change over control data set was used if available or included the control with same track height settings. Throughout the study the Student’s T-test p-value of 0.05 was considered significant and are indicated with an asterisk (*) or with the p-value. Declarations Acknowledgements The data presented in this manuscript in part utilizes ChIP-seq datasets from ENCODE database 62 and datasets from CCLE database 63 . We sincerely thank Dr. Michael Snyder (Stanford University), Dr. Richard Myers (Hudson Alpha Institute for Biotechnology), Dr. J. Michael Cherry (Stanford University), and their team members who contributed ChIP-seq data to ENCODE database. We also sincerely thank the members who contributed to CCLE cell line miRNA-Seq and RNA-Seq data. We sincerely thank Dr. Xiaobo Li (who provided MCF-7 cell line), Dr. Hayley D. Ackerman, and Dr. Kimberly T. Nguyen for help in cell line authentication. We sincerely thank Ms. Nicole Hackel, Ms. Payal Raulji, and Ms. Bethanie Gore for various help in reagent acquiring and lab management. The authors sincerely thank the National Institutes of Health for funding under the award number K08CA255933 Funding declaration: Research reported in this publication was supported in part by the National Institutes of Health under award number K08CA255933. Author contribution: G.G.J. discovered GPS gene family, conceived the scientific concept, designed the study, performed experiments, performed data analysis, Visualized data, interpretated data, composited figures, and wrote the manuscript. M.N. performed regular quality control of all cell lines. A.S.B. conceived the viral response target C19MC, and contributed to funds. A.S.B. and E.R.F. supervised the study and offered lab space. G.G.J. and I.G. worked with genomic coordinate annotation of GPS genes. All authors read and agree to the entire contents of the manuscript. Competing interest statement A.S.B. has advisory board relationships with Deciphera. The remaining authors have no other conflicts of interests to declare. All authors agree to take individual responsibility and accountability in the event of any undeclared conflicts of interest(s) that existed before or at the time of manuscript submission. References Wang, J. et al. Inhibition of activated pericentromeric SINE/Alu repeat transcription in senescent human adult stem cells reinstates self-renewal. Cell Cycle 10, 3016–3030, doi: 10.4161/cc.10.17.17543 (2011). Younger, S. T. & Rinn, J. L. Silent pericentromeric repeats speak out. 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Nature 569, 503–508, doi: 10.1038/s41586-019-1186-3 (2019). Consortium, E. P. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74, doi: 10.1038/nature11247 (2012). Zhou, G. et al. NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis. Nucleic Acids Research 47, W234-W241, doi: 10.1093/nar/gkz240 (2019). Jinesh, G. G. & Godwin, I. Filaggrin(High) melanomas exhibit active FGFR and allergic signatures with impaired GNA14 and Th1 signatures. Front Genet 16, 1569403, doi: 10.3389/fgene.2025.1569403 (2025). Additional Declarations Yes there is potential conflict of interest. Competing interest statement A.S.B. has advisory board relationships with Deciphera. The remaining authors have no other conflicts of interests to declare. All authors agree to take individual responsibility and accountability in the event of any undeclared conflicts of interest(s) that existed before or at the time of manuscript submission. Supplementary Files SupplementaryText10192025Highlightamended.docx SUPPLEMENTAL Text TableS2.xlsx SUPPLEMENTAL Table-S2 TableS1.xlsx SUPPLEMENTAL Table-S1 FigureS1.jpg Figure-S1 FigureS2.jpg Figure-S2 Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: revise 17 Mar, 2026 Review # 3 received at journal 07 Mar, 2026 Review # 1 received at journal 24 Feb, 2026 Reviewer # 3 agreed at journal 10 Feb, 2026 Reviewer # 2 agreed at journal 10 Feb, 2026 Reviewer # 1 agreed at journal 02 Feb, 2026 Reviewers invited by journal 02 Feb, 2026 Submission checks completed at journal 16 Jan, 2026 First submitted to journal 16 Jan, 2026 Editor assigned by journal 16 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8621807","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":584178702,"identity":"d0549e1e-0ae1-4004-995d-8ba688443702","order_by":0,"name":"Goodwin Jinesh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYJACCQYDBmY2IIOZoQJEMjeQouUMiGQkRgsUMDO2gSgCWuTdmw/e5im4w84n3Xz4c+G82mj+dqCWHxXbcGoxPHMs2ZrH4Bkzm8yxNOmZ247nzjjM2MDYc+Y2bi0zcsykcwwOM7NJ5Jgx8247ltsA1AJ0IVFa8j9/5p1zLHc+IS3yEghbGKR5G2pyNxDSYsAD9MsfsJY0M2meYwdyNwK1HMTnF/n25oM3Z/w5nCw/I/nxZ56autx55w8ffPCjAo8tByB0MpR/GEwewKkeZEsDhLaD8uvwKR4Fo2AUjIIRCgCIAVWVGOFrGQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-2170-3245","institution":"Moffitt Cancer Center","correspondingAuthor":true,"prefix":"","firstName":"Goodwin","middleName":"","lastName":"Jinesh","suffix":""},{"id":584178703,"identity":"4152acf6-7f1f-4acd-9da2-e76431afd9a0","order_by":1,"name":"Isha Godwin","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Isha","middleName":"","lastName":"Godwin","suffix":""},{"id":584178704,"identity":"802524b7-8f06-4128-9fb8-42db30b3849a","order_by":2,"name":"Marco Napoli","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Marco","middleName":"","lastName":"Napoli","suffix":""},{"id":584178705,"identity":"2c35ec8a-0ea1-49fc-9f50-183e8e1fb3b5","order_by":3,"name":"Elsa Flores","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Elsa","middleName":"","lastName":"Flores","suffix":""},{"id":584178706,"identity":"ca454a2d-49cc-4a35-82b7-8853dc465ce1","order_by":4,"name":"Andrew Brohl","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Andrew","middleName":"","lastName":"Brohl","suffix":""}],"badges":[],"createdAt":"2026-01-16 19:30:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8621807/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8621807/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101847798,"identity":"45db7f4d-93c8-474a-9785-32aaff8b220d","added_by":"auto","created_at":"2026-02-04 09:38:05","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1262304,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDiscovery and characterization of pericentromeric intronless C6GPS gene\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA,\u003c/strong\u003e Identification of a H3K27Ac region (would-be C6GPS locus) within pericentromeric repeats of human chromosome-6 unique to human genome among 100 vertebrates list of UCSC Genome Browser. Red bar: centromeric region. \u003cstrong\u003eB, \u003c/strong\u003eChIP-seq data showing pericentromeric H3K27me3 mark and p300 binding along with the H3K27Ac mark at the would-be C6GPS region of chromosome-6. \u003cstrong\u003eC,\u003c/strong\u003e ChIP-seq data showing c-Jun binding at the would-be C6GPS region of chromosome-6. \u003cstrong\u003eD,\u003c/strong\u003e Identification of an open reading frame (ORF) within the H3K27Ac plus H3K27me3 mark on chromosome-6 pericentromeric region. \u003cstrong\u003eE,\u003c/strong\u003e Annotated protein sequence, characteristics and protein sequence similarity to proteins from \u003cem\u003ePlasmodium \u003c/em\u003eand \u003cem\u003eStaphylococcus hominis\u003c/em\u003e. \u003cstrong\u003eF,\u003c/strong\u003e RT-PCR amplification of C6GPS mRNA and its Sanger sequencing to identify that the C6GPS mRNA is an intronless transcript.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8621807/v1/10d61d83df42015aa0475abe.jpg"},{"id":101847803,"identity":"fa8673dd-23eb-4d47-b786-2f1daa3c21ac","added_by":"auto","created_at":"2026-02-04 09:38:05","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1291407,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDiscovery and characterization of pericentromeric intronless C17GPS gene\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA,\u003c/strong\u003eIdentification of a H3K27Ac region (would-be C17GPS locus) within pericentromeric repeats of human chromosome-17 unique to human genome among 100 vertebrates list of UCSC Genome Browser. Red bar: centromeric region. \u003cstrong\u003eB-C, \u003c/strong\u003eChIP-seq data showing p300 binding at the would-be C17GPS region of chromosome-17 in MCF-7 cells (panel-B), and the presence of pericentromeric H3K27me3 mark along with the H3K27Ac mark of the corresponding C17GPS region of chromosome-17 in K562 cells (panel-C). \u003cstrong\u003eD,\u003c/strong\u003eChIP-seq data showing c-Jun binding at the would-be C17GPS region of chromosome-17. \u003cstrong\u003eE,\u003c/strong\u003e ChIP-seq data showing E2F-1 binding at the C6GPS and would-be C17GPS loci of chromosome-6 and 17 respectively. The start codons are marked by gene symbols with 20 kb up and downstream regions marked. \u003cstrong\u003eF,\u003c/strong\u003e Identification of an open reading frame (ORF) within the H3K27Ac plus H3K27me3 mark on chromosome-17 pericentromeric region. \u003cstrong\u003eG,\u003c/strong\u003e Annotated protein sequence, characteristics of \u003cem\u003eC17GPS\u003c/em\u003e gene. \u003cstrong\u003eH,\u003c/strong\u003e C17GPS protein sequence similarity to proteins from \u003cem\u003ePlasmodium ovale, Streptococcus pneumoniae, Mycobacterium tuberculosis, Streptomyces, \u003c/em\u003eand \u003cem\u003eStaphylococcus hominis\u003c/em\u003e. \u003cstrong\u003eI,\u003c/strong\u003e ClustalOmega: Protein sequence similarity between C6GPS and C17GPS. \u003cstrong\u003eJ,\u003c/strong\u003eRT-PCR amplification of C17GPS mRNA and its Sanger sequencing to identify that the C17GPS mRNA is an intronless transcript.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8621807/v1/bc9a402a63020f561bd6c76a.jpg"},{"id":101847801,"identity":"e5abff56-b0c6-496c-b23c-bdb2dd69a455","added_by":"auto","created_at":"2026-02-04 09:38:05","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1715213,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDiscovery of GPS gene family, conserved FPFP-motif and its truncation by mutations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA,\u003c/strong\u003e Circos plot showing the genomic distribution of the GPS family genes across human genome. Note the predominant localization of these genes close to centromeres (red). \u003cstrong\u003eB, \u003c/strong\u003eNucleotide level (Top) and protein level (Bottom) homology among the GPS gene/protein family members. The radial distance from center (C6GPS) represents the identity level from C6GPS (Boxed). \u003cstrong\u003eC,\u003c/strong\u003e The GPS family proteins have conserved FPFP motif with flanking region homology to various microbial and a mammalian vertebrate (Miniopterus: bat) and is shown in radial cladogram. The bottom right inset represents the FPFP motif homology to RefSeq proteins from human proteome. The top right inset represents the known ERK-1/2 inhibitory function of FPFP motif from \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e Mce-1 protein. \u003cstrong\u003eD,\u003c/strong\u003e Sanger sequence-based mutations identified in MCF-7 C17GPS mRNA compared to the reference genome. Individual codons were shown with arrows indicating the ORF reading direction. A summary of mutations is indicated in the inset table on right. \u003cstrong\u003eE,\u003c/strong\u003e For additional confirmation C17GPS mRNA from Hep3B cell line was sequenced and a summary of similar and unique mutations were included in the table on right. The ~300 bp RT-PCR product was also sequenced and confirmed as the nested product of C17GPS. Note that the truncation mutation by stop codon introduction was similar in both MCF-7 cells (Panel-D) and Hep3B cells (Panel-E).\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8621807/v1/7fb8f41a6e5aef8f650e5f69.jpg"},{"id":101847799,"identity":"b5c838b0-b651-4459-82a4-5a53f9b01733","added_by":"auto","created_at":"2026-02-04 09:38:05","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1169631,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePericentromeric transcription of GPS gene family matches with C19MC expression and interferon signaling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA,\u003c/strong\u003e Examination of GPS gene family mRNAs in 100 CCLE cell lines from multiple cancer types. \u003cstrong\u003eB, \u003c/strong\u003eCombined mRNA expression score representation of GPS genes.\u003cstrong\u003e \u003c/strong\u003eNote that the C6GPS and C17GPS are the widely and strongly expressed mRNAs among all GPS genes. C9GPS1 and C9GPS2 despite express good levels of mRNAs (Top panel), these are not pericentromeric but located as part of non-coding RNA genes as host genes [Bottom panels: MCF-7 H3K27Ac ChIP-seq data of fold change over control (*FCoC)]. \u003cstrong\u003eC,\u003c/strong\u003e CCLE 100 cell line RNA-seq and miRNA-seq integrated data set analysis for co-expression of GPS gene family mRNAs with antiviral C19MC miRNAs. Sorted based on C19MC miRNA expression. \u003cstrong\u003eD,\u003c/strong\u003e Selection of cell line groups (n=12 each) that express both GPS genes and C19MC miRNAs or lack expression of both classes of RNAs: based on panel-C. The C19MC expression (Green peaks) is visualized in IGV. \u003cstrong\u003eE, \u003c/strong\u003eEnrichR analysis of differentially upregulated genes in C19MC+GPS RNA expressing cells showing interferon-γ pathway involvement. \u003cstrong\u003eF,\u003c/strong\u003eNetworkAnalyst analysis of highly networked interferon pathway genes from differentially upregulated genes in C19MC+GPS RNA expressing cells (Network) showing STAT-1 and IRF-1 as most networked transcription factors (Dot plot on right).\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8621807/v1/f887bceaabe1d542207d0a10.jpg"},{"id":101847800,"identity":"89a772f8-02ef-4d84-92ce-8884459938cc","added_by":"auto","created_at":"2026-02-04 09:38:05","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":560525,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eInterferons, C19MC miRNAs, all-trans retinoic acid (ATRA), and NMD regulate pericentromeric transcription of GPS family genes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA,\u003c/strong\u003e Differential expression of IFN-β response and target genes in GPS+C19MC\u003csup\u003ePositive\u003c/sup\u003e versus GPS+C19MC\u003csup\u003eNegative\u003c/sup\u003e cell lines. *Significant (p-value \u0026lt;0.05). \u003cstrong\u003eB,\u003c/strong\u003e ChIP-seq data showing STAT-1 and IRF-1 binding at the C6GPS region of chromosome-6 in K562 cells. \u003cstrong\u003eC,\u003c/strong\u003e Reverse transcriptase PCR showing interferons (IFN-γ + IFN-β) co-operate to promote pericentromeric transcription of \u003cem\u003eC6GPS\u003c/em\u003e and \u003cem\u003eC17GPS\u003c/em\u003e genes. \u003cstrong\u003eD,\u003c/strong\u003e Reverse transcriptase PCR showing C19MC miRNA-519D promotes pericentromeric transcription of \u003cem\u003eC6GPS\u003c/em\u003e and \u003cem\u003eC17GPS\u003c/em\u003e genes (Left panel) which correlates with meiotic sickle nuclear phenotype shown after live staining the DNA with Hoechst-33342 (Right panel). \u003cstrong\u003eE,\u003c/strong\u003e ChIP-seq data showing RARA binding at the C6GPS region of chromosome-6 in HepG2 cells. \u003cstrong\u003eF,\u003c/strong\u003e Nonsense-mediated decay (NMD) of C6GPS and C17GPS pericentromeric transcript RNAs were overcome by meiosis- inducer all-trans retinoic acid (ATRA) by transcription (Actinomycin-D inhibits it). Caffeine, a NMD inhibitor further augments the mRNA levels.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8621807/v1/b00e2912e27e4184048b2fe5.jpg"},{"id":101847804,"identity":"a34efa54-681b-4b71-b0aa-9b5fbed49e78","added_by":"auto","created_at":"2026-02-04 09:38:05","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":630240,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIFN-γ, CEBPB-LAP, and C19MC miRNAs cooperate to regulate pericentromeric GPS gene transcription\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA,\u003c/strong\u003e ChIP-seq data (histogram peaks) showing the inducible CEBPB binding at the C6GPS region as the strongest binding locus of chromosome-6 in HepG2 cells. C6GPS zoom in locus was shows as heatmap. \u003cstrong\u003eB, \u003c/strong\u003eRT-PCR in CEBPB-LAP stablyoverexpressed Hep3B cells showing the baseline transcription of C6GPS and C17GPS mRNAs. \u003cstrong\u003eC,\u003c/strong\u003e RT-PCR in CEBPB-LAP stably overexpressed and control Hep3B cells showing the IFN-γ-induced augmented transcription of C6GPS and to a lesser extent C17GPS mRNAs. \u003cstrong\u003eD,\u003c/strong\u003e RT-PCR in antiviral C19MC miRNA stablyoverexpressed Hep3B cells (miR-519D, miR-520G, miR-526B) showing the baseline transcription of C6GPS and C17GPS mRNAs. \u003cstrong\u003eE,\u003c/strong\u003e qRT-PCR in CEBPB-LAP stably overexpressed and control Hep3B cells showing the IFN-γ-induced ~100-fold augmented transcription of endogenous antiviral C19MC miR-526B. Controls are set to the value of 1.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8621807/v1/0ac42e99a26878b3a85a0b51.jpg"},{"id":101881619,"identity":"5f3a7457-597f-4cb1-aa72-68b4a4bbf5bd","added_by":"auto","created_at":"2026-02-04 15:14:09","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":962329,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRegulation of pericentromeric transcription of GPS family genes, and their FPFP-motif microbial context\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA,\u003c/strong\u003eSchematic showing the pericentromeric transcription of C6GPS and C17GPS genes from the chromosomes-6 and 17 respectively. The pericentromeric marker H3K27me3 is shown in green shade. \u003cstrong\u003eB, \u003c/strong\u003eProtein-level FPFP-motif homology of 29 GPS gene family members to various proteins of multiple pathogenic microbes and viral reservoir bats (\u003cem\u003eMiniopterus natalensis\u003c/em\u003e). The microbes were illustrated and their associated disease conditions are mentioned in red font. \u003cstrong\u003eC,\u003c/strong\u003e Schematic showing the regulation of GPS family gene mRNAs by interferons, transcription factors like STAT-1, IRF-1, CEBPB-LAP, RARA, and how mutations trigger nonsense-mediated decay (NMD) of these mRNAs. The proposed function of GPS family protein FPFP-motifs in the inhibition of ERK-1/2 is also shown which is hampered by NMD. A circuit of antiviral C19MC miRNAs fitting this context is also indicated.\u003c/p\u003e","description":"","filename":"Figure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8621807/v1/dd2348d4222996190bc356b3.jpg"},{"id":101943054,"identity":"007747ce-7b94-4033-bcce-3bdac2df24b8","added_by":"auto","created_at":"2026-02-05 09:40:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9216491,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8621807/v1/e10baaf3-6262-45bb-b9ec-69c15ca1d867.pdf"},{"id":101847797,"identity":"6d084cb0-48ba-49be-b3d7-4446e556876d","added_by":"auto","created_at":"2026-02-04 09:38:05","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":38520,"visible":true,"origin":"","legend":"SUPPLEMENTAL Text","description":"","filename":"SupplementaryText10192025Highlightamended.docx","url":"https://assets-eu.researchsquare.com/files/rs-8621807/v1/3d3792bda30a86dbb8938145.docx"},{"id":101847805,"identity":"3f81afb1-9f74-4636-ba9f-a1574f8afcab","added_by":"auto","created_at":"2026-02-04 09:38:05","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":12870,"visible":true,"origin":"","legend":"SUPPLEMENTAL Table-S2","description":"","filename":"TableS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8621807/v1/cc5f51c17f22f001868135f9.xlsx"},{"id":101881738,"identity":"e75809f8-55dd-4e44-9ee0-496b4c66b61b","added_by":"auto","created_at":"2026-02-04 15:15:43","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":14131,"visible":true,"origin":"","legend":"SUPPLEMENTAL Table-S1","description":"","filename":"TableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8621807/v1/f353988757b3424c1b301db3.xlsx"},{"id":101847807,"identity":"4850a8de-d789-4462-b7ef-ca088aa71e15","added_by":"auto","created_at":"2026-02-04 09:38:05","extension":"jpg","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":2104232,"visible":true,"origin":"","legend":"Figure-S1","description":"","filename":"FigureS1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8621807/v1/60d5a38f2e284267e3bfc645.jpg"},{"id":101847802,"identity":"a96d3b91-6ef3-498c-952a-1fb1a72d44fc","added_by":"auto","created_at":"2026-02-04 09:38:05","extension":"jpg","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":2215314,"visible":true,"origin":"","legend":"Figure-S2","description":"","filename":"FigureS2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8621807/v1/d3267ea09bf4677725048aa2.jpg"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential conflict of interest.\nCompeting interest statement\r\nA.S.B. has advisory board relationships with Deciphera. The remaining authors have no other conflicts of interests to declare. All authors agree to take individual responsibility and accountability in the event of any undeclared conflicts of interest(s) that existed before or at the time of manuscript submission.","formattedTitle":"Pericentromeric Transcription of Novel Pathogen-Related Human GPS Genes in Cancers is Regulated by C19MC miRNAs, CEBPB, IFN-γ, and IFN-β","fulltext":[{"header":"Summary","content":"\u003cp\u003ePericentromeric transcription is unique to testis, and oocytes among the normal tissues. However, its regulation in cancer is not well-understood. Here, we discover a novel human, intron-less, coding, pericentromeric GPS gene family in cancer cells, with protein-level homology to microbial proteins from , , and . GPS proteins harbor a conserved FPFP-motif, characteristic of a protein that hijacks the host ERK-1/2 phosphorylation. We examined the two most expressed GPS family genes (, and ) in cancer cells and discovered that the pericentromeric transcription is regulated by interferon-γ and interferon-β, CEBPB-LAP, and antiviral C19MC-miRNAs. Furthermore, GPS mRNAs are suppressed by truncation mutations, and nonsense-mediated decay (NMD). Thus, we discovered a novel pathogen-related GPS gene family in the human genome, and its pericentromeric transcription-regulatory network. This discovery will help to understand the role of GPS pericentromeric transcription in the biology, immunotherapy, and host-pathogen relationships of cancers in the future.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eHuman centromeres, and pericentromeres are highly enriched with repetitive sequences\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, and the presence of coding genes within these regions is rare. Although centromeres, and pericentromeres constitute a large portion of the non-coding region within the human genome, transcription of non-coding RNA genes and a few coding genes does happen within centromeric, and pericentromeric regions\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e resulting in clearly defined functions such as meiosis\u003csup\u003e\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, mitosis\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, self-renewal in senescent cells\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, centromeric cohesion\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, CENP-A targeting to the centromere\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, and drug resistance\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Therefore, centromeric and pericentromeric transcription is important for the chromosome dynamics during cell division\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, and can serve as a basic mechanism related to chromosomal instability or stability\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. However, regulation of the human pericentromeric transcription is not well-understood except that it is repressed in most normal human tissues, excluding testis\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, and mature oocytes\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, indicating a developmental role, which was demonstrated in mice\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e in addition to gametogenesis.\u003c/p\u003e \u003cp\u003ePericentromeric chromatin differs from centromeric chromatin by having predominant H3K27me3 methylation mark through transcript-directed recruitment of methylation factors to the pericentromeric region\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. H3K27me3 mark is also associated with PRC-1 and PRC-2-dependant chromatin compaction and heterochromatinization to repress genes\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Hypomethylation of pericentromeric chromatin leads to interferon (IFN) response\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Interestingly, the IFN-β promoter tends to associate with pericentromeric heterochromatin, and which dissociates from pericentromeric chromatin upon viral infection to promote IFN expression\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. IFN signaling is tightly associated with the viral response of the host\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, and viruses stimulate an antiviral response miRNA cluster from chromosome-19 (Chromosome-19 miRNA cluster: C19MC)\u003csup\u003e\u003cspan additionalcitationids=\"CR24 CR25 CR26 CR27\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, which is widely expressed in human cancers with critical functions\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan additionalcitationids=\"CR30 CR31\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Importantly, we uncovered the role of C19MC in nuclear division without nuclear envelope breakdown (NEBD) during a novel meiosis-III that happens in multiple human cancers\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Of note, meiosis is also related to pericentromeric transcription\u003csup\u003e\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, testis, and oocyte development\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. The biological context and regulation of pericentromeric transcription during C19MC viral response, and interferon immune responses are not understood to date.\u003c/p\u003e \u003cp\u003eHuman pathogens (such as multiple viruses\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, \u003cem\u003ePlasmodium\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, \u003cem\u003eStaphylococcus\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e\u003csup\u003e\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e, and \u003cem\u003eSalmonella\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e) are capable of eliciting interferon response in hosts. IFN signals through STATs, and extracellular signal-regulated kinases-1 and 2 (popularly referred to as ERK-1/2) to activate CCAAAT/Enhancer-binding Protein-β (CEBPB)-dependent transcription\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. CEBPB is often co-expressed with antiviral C19MC in human cancers\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e and modulates transcription in response to C19MC miRNA/IFN-γ\u003csup\u003e25\u003c/sup\u003e and has cooperative functions with C19MC miRNAs\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. In the context of chronic/persistent infections pathogens disable IFN signaling at multiple level\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, including the inhibition of ERK signaling. For example, the FPFP motif of the Mce3E protein of \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e binds to and inhibits host/human ERK signaling in the context of persistent \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e infection\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. However, the relationship between human pathogens, interferon signaling, CEBPB, and C19MC miRNAs in the pericentromeric transcription context remains unknown.\u003c/p\u003e \u003cp\u003eNonsense-mediated decay (NMD) is a mechanism of RNA catabolism where the unwanted transcripts such as mutated/translation truncated mRNAs are degraded using exonucleases, and endonucleases. Viruses\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e and other pathogens influence the host NMD mechanism, or have their own NMD mechanism to remodel the transcriptome\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. A widespread absence of pericentromeric transcripts in normal tissues\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e suggests that either a strong transcriptional repression at the pericentromeric region such as heterochromatinization, or an RNA decay mechanism such as NMD, might suppress the pericentromeric transcripts, but this is not understood to date.\u003c/p\u003e \u003cp\u003eHere, we discovered and characterized a novel intron-less, coding, pericentromeric GPS (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eG\u003c/span\u003eenes at \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eP\u003c/span\u003eericentromeric-repeat \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eS\u003c/span\u003eequences) human gene family with protein-level homology to proteins from \u003cem\u003ePlasmodium ovale/walkeri\u003c/em\u003e, \u003cem\u003eStaphylococcus hominis, Streptococcus pneumoniae, Streptomyces kurssanovii, Mycobacterium tuberculosis\u003c/em\u003e, \u003cem\u003eSalmonella enterica\u003c/em\u003e, and other pathogens, expressed in human cancer cells. We identify a highly conserved FPFP motif within the entire GPS gene family member proteins along with multiple proteins from various human pathogens, and a bat genus that often serves as a reservoir for viruses (\u003cem\u003eMiniopterus\u003c/em\u003e). We further found that the pericentromeric transcription is regulated by IFN-γ, IFN-β, CEBPB-LAP, miR-519D, miR-520G, and miR-526B (C19MC-miRNAs). Finally, we uncovered that the pericentromeric GPS mRNA transcripts are suppressed by nonsense-mediated decay (NMD). Thus, our study sheds light on the role of GPS pericentromeric transcription in the biology of cancers, especially in the contexts of immune (interferons), antiviral response (C19MC miRNAs), transcription (CEBPB), mutation and NMD, and paves the way to better understand antiviral, pathogen-induced, and pericentromeric transcription-directed signaling in human host cells in future.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDiscovery and characterization of C6GPS, a pericentromeric intron-less gene\u003c/h2\u003e \u003cp\u003eTo understand pericentromeric transcription, we scanned the pericentromeric regions of the human genome for the H3K27ac mark using the UCSC genome browser. We identified a strong H3K27ac mark that falls within the repetitive DNA region but closely outside the centromere of the chromosome-6 at the p-arm side (Figure-1A). Notably, this region is not conserved and is specific to humans among the 100 vertebrate genomes of the PhyloP set (Figure-1A). We refer to this locus as the \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003ec\u003c/span\u003e\u003cem\u003ehromosome-\u003c/em\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003e6\u003c/span\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eg\u003c/span\u003e\u003cem\u003eene at the\u003c/em\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003ep\u003c/span\u003e\u003cem\u003eericentromeric\u003c/em\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003es\u003c/span\u003e\u003cem\u003eequence\u003c/em\u003e (\u003cem\u003eC6GPS\u003c/em\u003e) based on the findings below. To confirm the pericentromeric nature and transcription competent potential, we examined the MCF-7 ChIP-seq data of H3K27ac (transcription potential), p300 (transcription potential), and H3K27me3 (pericentromeric mark) and found that the \u003cem\u003eC6GPS\u003c/em\u003e locus is indeed at the pericentromeric transcriptional region (Figure-1B). We chose the MCF-7 cell line for its known phenotypic features in meiosis-III\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. We also found that c-Jun transcription factor can bind to the \u003cem\u003eC6GPS\u003c/em\u003e locus in MCF-7 cells (Figure-1C). Considering multiple transcription factors (c-Jun and p300) can bind to the \u003cem\u003eC6GPS\u003c/em\u003e locus, we examined this region for any potential open reading frames (ORF) and found an ORF of 624 nucleotides in length with start, and stop codons (Figure-1D). The annotated protein sequence of this ORF indicated that C6GPS is a 207 amino acid long protein with a predicted molecular weight of 22.77 kDa and an isoelectric pH of 9.63, enriched in tyrosine, serine, and threonine residues, suggesting that C6GPS could be regulated by both receptor tyrosine kinases (RTKs), and serine/threonine kinases (STKs) (Figure-1E). Sequence homology search using BLASTp has shown that C6GPS has strong similarities to pathogen proteins such as 9APIC of \u003cem\u003ePlasmodium falciparum\u003c/em\u003e, and STAHO of \u003cem\u003eStaphylococcus hominis\u003c/em\u003e, among many others (see below) (Figure-1E).\u003c/p\u003e \u003cp\u003eTo determine if C6GPS is transcribed into mRNA, we performed RT-PCR in MCF-7 cells and found a feeble product of the expected size (~\u0026thinsp;813 base pairs). To confirm its identity and to understand if it has undergone splicing, we reamplified this product and subjected it to Sanger sequencing (Figure-1F). The sequencing data revealed that \u003cem\u003eC6GPS\u003c/em\u003e is an intronless gene and its mRNA is not subjected to splicing (Figure-1F and Figure-S1). Taken these data together, C6GPS is an intronless pericentromeric gene with protein-level homology to proteins from human pathogens, and is transcribed in MCF-7 cells without splicing.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDiscovery and characterization of C17GPS, a pericentromeric intron-less gene\u003c/h3\u003e\n\u003cp\u003eTo further investigate the pericentromeric transcription we undertook a nucleotide sequence-based search of C6GPS within the human genome and found no strong homologous genes. However, when we further examined the pericentromeric regions of the human genome for the H3K27ac mark, we identified another strong H3K27ac mark that falls within the repetitive DNA region but closely outside the centromere (pericentromeric region) of the chromosome-17 at the p-arm side (Figure-2A). Notably, this region is not conserved and is specific to humans among the 100 vertebrate genomes of the PhyloP set (Figure-2A). We refer to this locus as the \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003ec\u003c/span\u003e\u003cem\u003ehromosome-\u003c/em\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003e17\u003c/span\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eg\u003c/span\u003e\u003cem\u003eene at the\u003c/em\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003ep\u003c/span\u003e\u003cem\u003eericentromeric\u003c/em\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003es\u003c/span\u003e\u003cem\u003eequence\u003c/em\u003e (\u003cem\u003eC17GPS\u003c/em\u003e) based on the findings below. To confirm the pericentromeric nature and transcription competent potential, we examined the MCF-7 ChIP-seq data of H3K27ac (transcription potential), p300 (transcription potential), and H3K27me3 (pericentromeric mark) and found that the \u003cem\u003eC17GPS\u003c/em\u003e locus is indeed bound by p300 but had feeble H3K27ac and H3K27me3 marks in MCF-7 cells (Figure-1B). However, the K562 cell line exhibited strong H3K27ac and H3K27me3 marks, indicating that the \u003cem\u003eC17GPS\u003c/em\u003e locus is in a potentially transcription-competent pericentromeric region (Figure-1C). We also found that c-Jun transcription factor can bind to the \u003cem\u003eC17GPS\u003c/em\u003e locus in MCF-7 cells (Figure-1D). We examined both \u003cem\u003eC6GPS\u003c/em\u003e and \u003cem\u003eC17GPS\u003c/em\u003e loci for E2F1 binding (a meiosis-promoting transcription factor) and found that E2F1 can bind to both genes (Figure-1E). We examined the \u003cem\u003eC17GPS\u003c/em\u003e locus for any potential open reading frames (ORF) and found an ORF of 792 nucleotides length with start, and stop codons (Figure-1F). The annotated protein sequence from this ORF indicated that C17GPS is a 263 amino acid long protein with a predicted molecular weight of 28.93 kDa and an isoelectric pH of 10.1, enriched in tyrosine, serine, and threonine residues suggesting that C17GPS could be regulated by both receptor tyrosine kinases (RTKs), and serine/threonine kinases (STKs) (Figure-1G). Sequence homology search using BLASTp has shown that the N-terminal half of C17GPS has strong similarities to pathogen proteins of \u003cem\u003ePlasmodium ovale\u003c/em\u003e, \u003cem\u003eStaphylococcus hominis, Mycobacterium tuberculosis, Streptococcus pneumoniae, and Streptomyces\u003c/em\u003e, among many others (see below) (Figure-1H). Though our C6GPS nucleotide-based search did not identify C17GPS, their proteins had strong conserved motifs indicating the existence of a protein-level homology despite having a low homology at the nucleotide-level (Figure-2I).\u003c/p\u003e \u003cp\u003eTo determine if \u003cem\u003eC17GPS\u003c/em\u003e is transcribed into mRNA, we performed RT-PCR in MCF-7 cells and obtained a feeble product of the expected size (~\u0026thinsp;969 base pairs). To confirm its identity and to understand if it has undergone splicing, we reamplified this product and subjected it to Sanger sequencing (Figure-1J). The sequencing data revealed that \u003cem\u003eC17GPS\u003c/em\u003e is also an intronless gene and its mRNA is not subjected to splicing (Figure-1J and Figure-S2). Taken these data together, C17GPS is an intronless pericentromeric gene with protein-level homology to proteins from human pathogens, and is transcribed in MCF-7 cells without splicing.\u003c/p\u003e \u003cp\u003e \u003cb\u003eDiscovery and characterization of pathogen-related GPS family of pericentromeric intron-less genes: the conserved FPFP motif and its truncation in cancer cells\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIdentification of C6GPS and C17GPS at the pericentromeric region of different chromosomes prompted us to search for additional similar genes within the human genome. A nucleotide sequence-based search of C17GPS within the human genome resulted in the identification of 27 other homologous intronless genes, all located at the pericentromeric region of human chromosomes, with the exception of two genes that are located at the non-pericentromeric regions of chromosome-9 (Figure-3A). Notably, we did not identify pericentromeric genes at chromosomes-4, 13, and 22 based on \u003cem\u003eC17GPS\u003c/em\u003e sequence similarity search (Figure-3A). We named these genes based on the chromosomes in which they are located, for example if the gene is localized to chromosome-1, then we named it as \u003cem\u003eC1GPS\u003c/em\u003e, and so on. At this point, we called these genes collectively as the \u0026ldquo;GPS gene family\u0026rdquo;. Chromosome-Y harbors 5 \u003cem\u003eGPS\u003c/em\u003e genes (\u003cem\u003eCYGPS1-5\u003c/em\u003e) which are identical in sequence and located close to each other suggesting that this could be due to the result of repetitive DNA expansion (Figure-3B). On the other hand, \u003cem\u003eC9GPS1\u003c/em\u003e and \u003cem\u003eC9GPS2\u003c/em\u003e were also identical but not located at the pericentromeric repeats (Figure-3B). At the nucleotide level, all GPS gene family genes showed considerable homology except C6GPS (Figure-3B). All wild-type nucleotide sequences of the ORFs of the GPS gene family members are provided in Supplementary table-1. At the protein level, about half of the GPS gene family members shown close homology to C17GPS (Figure-3B). All wild-type protein sequences of the GPS gene family members are provided in Supplementary table-2. Again, C6GPS stood out as different among all the GPS family members (Figure-3B) despite having conserved motifs with C17GPS (Figure-2I).\u003c/p\u003e \u003cp\u003eConserved peptide motif analysis among all GPS gene family members revealed the presence of a conserved 12\u0026ndash;13 amino acid sequence. Homology search of this sequence using BLASTp revealed that this motif is also conserved with the proteins from multiple human pathogens including \u003cem\u003ePlasmodium ovale, Mycobacterium tuberculosis, Staphylococcus hominis, Escherichia coli, Vibrio sp., Salmonella sp., Acinetobacter sp., Cronobacter sp., Lactobacillus crispatus\u003c/em\u003e, and others (Figure-3C). While this stretch of 12\u0026ndash;13 amino acid sequence is well conserved, an FPFP motif within this sequence is notable as its function is known in the case of \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e FPFP motif of Mce3E protein, which binds to and inhibits host/human ERK phosphorylation-based signaling in the context of persistent infection\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e (Figure-3C). Among the human proteins, the FPFP motif is also present in a handful of proteins (Figure-3C), notably in human chorionic gonadotrophin (hCG), a known meiosis stimulator\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWe next investigated the potential role of the FPFP motif of GPS genes in cancer. Sanger sequencing of C17GPS mRNA from MCF-7 cells revealed multiple mutations compared to the UCSC human reference genome, ranging from silent, substitution, to truncation mutations (Figure-3D). The truncation mutation identified was at codon G132Stop, which could potentially result in the loss of FPFP motif from the translation product (Figure-3D). To check if these mutations are specific to MCF-7 cells or also present in other cancer cells, we examined C17GPS mRNA in Hep3B cells. C17GPS mRNA of Hep3B cells harbored identical (codons F42V, K97R, P129P silent, V131A, N153K, R163T, N180K, I222V, S249S silent, A252P, and L253P) as well as unique (F13V, N133K, and R215R silent) mutations compared to the MCF-7 cell line (Figure-3E). Of note, these alterations could be due to \u003cem\u003ede novo\u003c/em\u003e mutations or polymorphisms and understanding of which requires population-based studies. Importantly, the truncation mutation was identical to the MCF-7 C17GPS mRNA (G132Stop) (Figure-3E). Thus, the truncation mutation resulting in the loss of FPFP motif of GPS genes in cancer could be a common mechanism.\u003c/p\u003e \u003cp\u003eTaken together, these data demonstrate that GPS genes are a family of pericentromeric intronless genes located in most human chromosomes with a homologous FPFP ERK-1/2 inhibitory motif at their protein sequences, which are lost due to truncation mutations in MCF-7 and Hep3B cell lines.\u003c/p\u003e\n\u003ch3\u003eAntiviral C19MC miRNAs are expressed with pericentromeric GPS genes in the Interferon context\u003c/h3\u003e\n\u003cp\u003eConsidering the role of the FPFP motif in ERK-1/2 signaling and the role of ERK-1/2 in IFN-γ production, an essential role of interferons in the GPS gene family expression is conceivable. ERK-1/2 regulate the transcription of IFN-γ through the transcription factor CCAAAT/Enhancer-binding Protein-β (hereafter referred to as CEBPB)\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e in addition to its other targets, and IFN-γ is involved in the antiviral immunity\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Furthermore, multiple human pathogenic viruses are capable of eliciting C19MC miRNA response\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e as well as interferon response in hosts\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Therefore, we evaluated whether GPS mRNAs co-express with C19MC miRNAs. For this purpose, we first evaluated the expression of GPS gene mRNAs in 100 human cancer cell lines and found that GPS gene mRNAs are widely expressed in human cancer cell lines (Figure-4A). C6GPS and C17GPS mRNAs were the most expressed GPS family genes, followed by C9GPS1 and C9GPS2 mRNAs, which are not in fact pericentromeric genes but driven by non-coding RNA (ncRNA) host genes (Figure-4B). We matched the 100 cell line GPS gene expression data with C19MC miRNA data (miRNA-seq) and found that C19MC expression is tightly associated with GPS mRNA expression (Figure-4C). However, GPS gene mRNAs were also expressed in a small subset of cell lines without C19MC miRNA expression suggesting that the GPS gene family mRNAs could also be regulated independent of C19MC miRNA expression context.\u003c/p\u003e \u003cp\u003eTo understand the signaling context between the co-expression of C19MC miRNAs and GPS gene family mRNAs, we performed differential gene expression profiling of RNA-seq data of cell lines that co-express both GPS mRNAs plus C19MC miRNAs versus cells that do not express both RNAs (Figure-4C-D). While the results are enriched with interferon-related genes, we identify that the IFN-γ response geneset, and STAT-1/IRF1 as the most significantly enriched as well as most networked transcription factors (Figure-4E-F).\u003c/p\u003e \u003cp\u003e \u003cb\u003eInterferons, C19MC miRNAs, all-trans retinoic acid (ATRA), and NMD regulate pericentromeric transcription and mRNA levels of the GPS family genes\u003c/b\u003e \u003c/p\u003e \u003cp\u003eMany of the IFN-γ pathway genes are also related to the IFN-β pathway, which is also involved in antiviral response, and were upregulated in C19MC plus \u003cem\u003eGPS\u003c/em\u003e gene expression positive cell lines (Figure-5A). Some of the top downregulated genes were also a direct target of IFN-β regulated genes: for example, Ankyrin repeat gene \u003cem\u003eANK1\u003c/em\u003e product is a target for IKBKE kinase, which usually targets ankyrin repeats (Figure-5A). We examined two transcription factors, STAT-1 and IRF-1 binding to make sure interferon-regulated transcription factors can bind to the \u003cem\u003eC6GPS\u003c/em\u003e locus using MCF-7 ChIP-seq data. Both STAT-1 and IRF-1 can bind to the \u003cem\u003eC6GPS\u003c/em\u003e locus (Figure-5B). Therefore, we examined if IFN-γ and IFN-β could modulate the pericentromeric transcription of \u003cem\u003eC6GPS\u003c/em\u003e and \u003cem\u003eC17GPS\u003c/em\u003e in MCF-7 cells. The results revealed that both IFN-γ and IFN-β at 1 nM final concentrations can induce the pericentromeric transcription of both \u003cem\u003eC6GPS\u003c/em\u003e and \u003cem\u003eC17GPS\u003c/em\u003e genes at 24 hours, and their combination had an additive effect on \u003cem\u003eC6GPS\u003c/em\u003e gene transcript compared to \u003cem\u003eC17GPS\u003c/em\u003e (Figure-5C). This result suggested that both IFN-γ and IFN-β could use independent as well as overlapping pathways to regulate pericentromeric transcription to achieve the additive effect.\u003c/p\u003e \u003cp\u003eNext, we examined the effect of stable overexpression of antiviral C19MC miRNAs in MCF-7 cells. While we attempted three individual C19MC miRNAs (miR-519D, miR-520G, and miR-526B), we could generate stable cells only for miR-519D, and miR-526B. The C19MC miR-519D strongly induced the pericentromeric transcription of \u003cem\u003eC17GPS\u003c/em\u003e compared to the \u003cem\u003eC6GPS\u003c/em\u003e gene, whereas miR-526B did not have any effect (Figure-5D). This correlated with the sickle nuclear meiosis-III phenotype (Figure-5D), which we identified previously in response to miR-519D in MCF-7 cells\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAs all-trans retinoic acid, a stimulator of meiosis-III in cancer cells\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, which signals through one of its many receptors RAR-α (RARA), we examined the available RARA-ChIP-seq data to find whether RAR-α can bind to the \u003cem\u003eC6GPS\u003c/em\u003e locus and found that RAR-α binds to the \u003cem\u003eC6GPS\u003c/em\u003e locus in HepG2 cells (Figure-5E). Usage of all-trans retinoic acid (ATRA) in MCF-7 cells induced the pericentromeric transcription of both \u003cem\u003eC6GPS\u003c/em\u003e and \u003cem\u003eC17GPS\u003c/em\u003e mRNAs, and the usage of nonsense-mediated decay (NMD) inhibitor caffeine with ATRA further increased the levels of \u003cem\u003eC6GPS\u003c/em\u003e and \u003cem\u003eC17GPS\u003c/em\u003e mRNAs, indicating that the pericentromeric mRNAs are also subjected to NMD (Figure-5F). The inability of ATRA to induce pericentromeric \u003cem\u003eC6GPS\u003c/em\u003e and \u003cem\u003eC17GPS\u003c/em\u003e mRNAs in the presence of transcription inhibitor actinomycin-D indicated that fresh transcription is involved in the induction of pericentromeric transcripts by ATRA as a single agent (Figure-5F).\u003c/p\u003e \u003cp\u003eTaken together, these results demonstrate that the pericentromeric transcription is regulated by IFN-γ, IFN-β, antiviral C19MC miRNAs, and ATRA in the meiosis-III context, and that these transcripts are subjected to nonsense-mediated decay.\u003c/p\u003e\n\u003ch3\u003eIFN-γ, CEBPB-LAP, and C19MC miRNAs cooperate to regulate pericentromeric GPS gene transcription\u003c/h3\u003e\n\u003cp\u003eCEBPB liver-enriched activator protein (CEBPB-LAP isoform) modulates the transcriptional outcome of \u003cem\u003eMYO18B\u003c/em\u003e gene by IFN-γ in the context of C19MC miRNAs in the liver context\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Therefore, we examined if CEBPB can bind to the \u003cem\u003eC6GPS\u003c/em\u003e locus in HepG2 ChIP-seq data. CEBPB binding to the \u003cem\u003eC6GPS\u003c/em\u003e locus is induced by CEBPB activating stimulus (Forskolin) and is the strongest among all CEBPB binding sites in the entire chromosome-6 (Figure-6A). Stable overexpression of CEBPB-LAP isoform in Hep3B cells (Hep3B cells express basal C19MC miRNAs, and GPS gene expression: Figure-4C-D, and lack basal IFN-γ expression\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e) by itself induced the pericentromeric transcription of \u003cem\u003eC6GPS\u003c/em\u003e and \u003cem\u003eC17GPS\u003c/em\u003e mRNAs (Figure-6B). As Hep3B cells lack basal expression of IFN-γ but not its receptors\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, we examined the effect of exogenous IFN-γ in pericentromeric transcription. 1 nM IFN-γ in CEBPB-LAP stably overexpressed cells boosted the pericentromeric transcription of \u003cem\u003eC6GPS\u003c/em\u003e and to a lesser extent of \u003cem\u003eC17GPS\u003c/em\u003e genes (Figure-6C). Furthermore, stable overexpression of individual C19MC miRNAs miR-519D, miR-520G, and miR-526B induced the pericentromeric transcription of \u003cem\u003eC17GPS\u003c/em\u003e and to a lesser extent \u003cem\u003eC6GPS\u003c/em\u003e genes (Figure-6D).\u003c/p\u003e \u003cp\u003eFinally, we asked the question whether the IFN-γ induced hyper-pericentromeric transcription of C6GPS in CEBPB-LAP overexpressed cells involve C19MC miRNAs. Quantitative real-time PCR analysis of C19MC miRNAs in this context revealed that an approximately 100-fold induction of endogenous miR-526B (and possibly more miRNAs from the C19MC) over the basal expression is accompanied with the hyper-pericentromeric transcription of \u003cem\u003eC6GPS\u003c/em\u003e in CEBPB-LAP overexpressed cells in IFN-γ treated condition (Figure-6E). Therefore, we conclude that the CEBPB-LAP transcription factor cooperates with IFN-γ, and C19MC miRNAs to induce pericentromeric transcription.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eCancers are known for rapid proliferation, which is mediated by mitotic cell division. Meiosis is confined to gametogenic tissues such as testis and ovary. However, non-germ line cancer cells from multiple cancer types exhibit spermatogenesis gene expression signature and exhibit a novel meiosis-III in the context of antiviral C19MC miRNA expression\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Pericentromeric transcription is restricted to testis\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, and matured oocytes\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e and is repressed in other normal tissues. Pericentromeric transcription is associated with IFN signaling\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e and the IFN-β promoter tends to associate with pericentromeric heterochromatin, which dissociates from pericentromeric chromatin upon viral infection to promote IFN expression\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Here, we discovered a pericentromeric intron-less GPS gene family (Figure-7A-B) and identified that the pericentromeric transcription of these genes is regulated by cooperative interactions of IFN-γ, IFN-β, CEBPB-LAP, and C19MC miRNAs (Figure-7C).\u003c/p\u003e \u003cp\u003eHomology of GPS family protein FPFP motifs to various proteins from microbes, including \u003cem\u003ePlasmodium\u003c/em\u003e, and \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e, sheds more insight on the functions of GPS family genes (Figure-7B). For example, \u003cem\u003ePlasmodium\u003c/em\u003e-driven malaria is resisted by sickle cell disease and bacterial coinfections\u003csup\u003e\u003cspan additionalcitationids=\"CR54\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e, and the sickling pattern is strikingly similar to meiotic sickle cell-like morphological features upon miR-519D overexpression in MCF-7 cells\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e (Figure-5D). Induction of pericentromeric transcription by meiotic inducer ATRA further supports this result (Figure-5E-F). Mycobacterium tuberculosis Mce3E protein FPFP motif is implicated in the ERK-1/2 phosphorylation\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e (Figure-7C). The truncation mutation in the \u003cem\u003eC6GPS\u003c/em\u003e, and \u003cem\u003eC17GPS\u003c/em\u003e genes in cell lines can potentially remove the FPFP motif in these gene products. However, any other GPS gene products could still contribute to the FPFP motif-mediated influence of ERK-1/2 signaling. The level of FPFP motif and its flanking sequence homology to various human pathogenic microbial proteins to GPS family proteins (Figure-7B) indicates the importance of pericentromeric transcription of GPS genes. Although the GPS genes are not conserved among 100 vertebrate genomes at the nucleotide level (Figures-\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), their FPFP motif homology to proteins from the bat \u003cem\u003eMiniopterus\u003c/em\u003e suggests a protein level conservation could exist among vertebrates. FPFP motif homology in \u003cem\u003eMiniopterus\u003c/em\u003e is consistent with the fact that this bat is a reservoir for human pathogenic viruses\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e (Figures-\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). \u003cem\u003eMiniopterus natalensis\u003c/em\u003e bats are found in South Africa\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e, a place prone to HIV-1 epidemics\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eMiniopterus natalensis\u003c/em\u003e bats have a mysterious chimera of CCR5 and CCR2 chemokine genes responsible for HIV-1 infection/entry\u003csup\u003e59\u003c/sup\u003e. This scenario is further complicated by increased maternal death associated with recent pregnancy (C19MC miRNAs express during pregnancy) by \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e in South Africa\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. To add more spice, C19MC antiviral miRNA expression is strongly associated with HIV-infection signature in human cancers\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Therefore, the human GPS gene family and its homologous proteins of \u003cem\u003eMiniopterus natalensis, Mycobacterium tuberculosis\u003c/em\u003e might play an important role in HIV-infection, and cancer biology in the context of C19MC miRNAs and interferons.\u003c/p\u003e \u003cp\u003eWhile the truncation mutation precluding the translation of FPFP motifs from C6GPS and C17GPS, unusual stop codons are also capable of triggering nonsense-mediated decay (NMD) of target RNAs. As expected, we found that the pericentromeric mRNAs of \u003cem\u003eC6GPS\u003c/em\u003e, and \u003cem\u003eC17GPS\u003c/em\u003e are undergoing NMD (Figure-5F). Therefore, this could be a mechanism to keep these mRNAs in check, or a mechanism to prevent the inhibition of ERK-1/2, as cancers heavily depend on ERK-1/2 for oncogene-driven tumorigenesis\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn summary, our study uncovers a novel family of pericentromeric GPS genes that are related to various human pathogenic microbes, and their regulation by a cooperative network involving IFN-γ, IFN-β, CEBPB-LAP, and C19MC miRNAs. Further studies will help to understand the role of GPS pericentromeric transcription in the biology, immunotherapy, and host-pathogen relationships of cancers in the future.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eCell lines: culture and authentication by DNA fingerprinting.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHuman Hep3B hepatocellular carcinoma cells (ATCC # HB-8064), and MCF-7 (HTB22) human breast cancer cells were cultured in MEM containing L-Glutamine and Sodium bi-carbonate (Sigma #M4655), with 10% FBS (Sigma#F0926), vitamins (Gibco Life Technologies #11120052), sodium pyruvate (Gibco Life Technologies #11360070), non-essential amino acids (Gibco Life Technologies #11140050), and penicillin-streptomycin (Gibco Life Technologies #15140122). The cells were identity confirmed by STR fingerprinting as per institutional/lab standards. Fresh revived cells were used after every 6 months or after ~25 passages. The cells in culture were periodically tested for mycoplasma using MycoAlert Kit (Lonza).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePlasmids: C19MC miRNAs, CEBPB-LAP, and their controls\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Glycerol stocks of mammalian expression vectors such as pMIR-CMV (Control), pMIR-CMV-519D (CR215546), pMIR-CMV-520G (CR215781), and pMIR-CMV-526B (CR215142) were purchased from Vigene Biosciences (Rockville, MD USA) and described previously\u003csup\u003e24\u003c/sup\u003e. The control pLenti-GIII-CMV-RFP-2A-Puro (Cat# LV084) and the LAP isoform-CEBPB pLenti-GIII-CMV-human-CEBPB-RFP-2A-Puro (Cat# LV796074) vectors were purchased from Applied Biological Materials Inc., Richmond, BC, Canada and described previously\u003csup\u003e25\u003c/sup\u003e. All plasmids were isolated using Qiagen MIDI prep kit (#12143) as per manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStable cell line generation and authentication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHep3B stable cells with C19MC miRNA overexpression (miR-519D, miR-520G, and miR-526B) is described previously\u003csup\u003e24\u003c/sup\u003e. Briefly, the transfections were done using plasmids (not viruses) and Lipofectamine 2000 (Life Technologies # 11668019) and selected using 4\u0026nbsp;mg/ml puromycin (Invitrogen # A1113803) for 2 months while GFP/RFP positive clones were picked, expanded and frozen. MCF-7 stable cells with C19MC miRNA overexpression (miR-519D, and miR-526B) is generated as described above but with gradual increase in puromycin, where the miR-520G failed to grow as cell line after transfection, and the cells were sorted for GFP positivity instead of clone picking. The FACS sorted cells were further subjected to STR fingerprinting to make sure the identity of MCF-7 cells and to rule out cross contamination of cells.\u003c/p\u003e\n\u003cp\u003eHep3B stable cells with CEBPB-LAP and its control plasmid overexpression is described previously\u003csup\u003e25\u003c/sup\u003e. Briefly, the cells were transfected using plasmids (not viruses) and Lipofectamine 2000 (Life Technologies # 11668019) as per manufacturer\u0026rsquo;s protocol, and selected using 4\u0026nbsp;mg/ml puromycin (Invitrogen # A1113803) for 2 months before colony picking by RFP positivity. The overexpression of CEBPB-LAP was confirmed by LAP-specific RT-PCR (See below for primer details).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReagents and treatment doses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKits:\u003c/p\u003e\n\u003cp\u003eHigh-Capacity cDNA Reverse Transcription kit (ABI, Cat.# 4368814), Plasmid isolation MIDI-prep kit (Qiagen, Cat.# 12143), and Illustra GFX PCR DNA and Gel Band Purification Kit (GE Healthcare, Cat.# 28903470), Trizol RNA isolation reagent (ThermoFisher Scientific, Cat.# 15596018), miRNeasy Mini Kit (50) (Qiagen, Cat.# 217004).\u003c/p\u003e\n\u003cp\u003eCytokines and treatment conditions:\u003c/p\u003e\n\u003cp\u003eIFN-\u0026gamma;\u0026nbsp;(R\u0026amp;D Systems, Cat.# 285-IF-100, 1nM / 17 ng/ml for 24 h.), IFN-\u0026beta;\u0026nbsp;(R\u0026amp;D Systems, Cat.# 8499-IF-010, 1nM / 20 ng/ml for 24 h.).\u003c/p\u003e\n\u003cp\u003eChemical reagents and treatment conditions:\u003c/p\u003e\n\u003cp\u003eAll-trans retinoic acid (ATRA) (Cayman Chemicals, Cat.# 11017, 1mM for 24 h.), betaine (5M stock: Sigma # B0300-1VL, St. Louis, MO, USA), and Caffeine (Cayman Chemicals, Cat.# 14118, 10mM for 24 h.).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRT-PCR and sequencing primers\u003c/strong\u003e\u003c/p\u003e\n\u003ctable style=\"border-collapse: collapse;border: none;width: 631px;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117.9pt;border: 1pt solid windowtext;background: black;padding: 0cm 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:13px;font-family:\"Arial\",sans-serif;color:white;'\u003eTarget mRNA\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 292.5pt;border-top: 1pt solid windowtext;border-right: 1pt solid windowtext;border-bottom: 1pt solid windowtext;border-image: 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\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117.9pt;border-right: 1pt solid windowtext;border-bottom: 1pt solid windowtext;border-left: 1pt solid windowtext;border-image: initial;border-top: none;padding: 0cm 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:13px;font-family:\"Arial\",sans-serif;'\u003eCEBPB-LAP-Forward\u003cspan style=\"color:#EE0000;\"\u003e**\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 292.5pt;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0cm 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='font-size:13px;font-family: \"Arial\",sans-serif;'\u003e5\u0026apos;\u003c/span\u003e\u003cspan style='font-size:13px;font-family:\"Cambria Math\",serif;'\u003e‐\u003c/span\u003e\u003cspan style='font-size:13px;font-family:\"Arial\",sans-serif;color:#EE0000;'\u003eAACGCCTGGTGGCCTGGGACCC\u003c/span\u003e\u003cspan style='font-size:13px;font-family:\"Cambria Math\",serif;'\u003e‐\u003c/span\u003e\u003cspan style='font-size:13px;font-family:\"Arial\",sans-serif;'\u003e3\u0026apos;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63pt;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0cm 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='font-size:13px;font-family: \"Arial\",sans-serif;'\u003e60\u003c/span\u003e\u003cspan style='font-size:13px;font-family:\"Cambria\",serif;'\u003e˚\u003c/span\u003e\u003cspan style='font-size:13px;font-family:\"Arial\",sans-serif;'\u003eC\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117.9pt;border-right: 1pt solid windowtext;border-bottom: 1pt solid windowtext;border-left: 1pt solid windowtext;border-image: initial;border-top: none;padding: 0cm 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:13px;font-family:\"Arial\",sans-serif;'\u003eCEBPB-LAP-Reverse\u003cspan style=\"color:#EE0000;\"\u003e**\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 292.5pt;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0cm 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='font-size:13px;font-family: \"Arial\",sans-serif;'\u003e5\u0026apos;\u003c/span\u003e\u003cspan style='font-size:13px;font-family:\"Cambria Math\",serif;'\u003e‐\u003c/span\u003e\u003cspan style='font-size:13px;font-family:\"Arial\",sans-serif;color:#E36C0A;'\u003eAAGAGGTCGGAGAGGAAGTCGTGG\u003c/span\u003e\u003cspan style='font-size:13px;font-family:\"Cambria Math\",serif;'\u003e‐\u003c/span\u003e\u003cspan style='font-size:13px;font-family:\"Arial\",sans-serif;'\u003e3\u0026apos;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63pt;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0cm 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:0cm;margin-left:0cm;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style='font-size:13px;font-family: \"Arial\",sans-serif;'\u003e60\u003c/span\u003e\u003cspan style='font-size:13px;font-family:\"Cambria\",serif;'\u003e˚\u003c/span\u003e\u003cspan style='font-size:13px;font-family:\"Arial\",sans-serif;'\u003eC\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp style='margin-top:0cm;margin-right:0cm;margin-bottom:10.0pt;margin-left:0cm;line-height:200%;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:13px;line-height:200%;font-family:\"Arial\",sans-serif;color:#0070C0;'\u003e*\u003c/span\u003e\u003cspan style='font-size:13px;line-height:200%;font-family:\"Arial\",sans-serif;'\u003eSequencing \u0026amp; RT-PCR primers used in this study\u003cspan style=\"color:black;\"\u003e;\u003c/span\u003e\u003cspan style=\"color:#EE0000;\"\u003e **\u003c/span\u003ePublished previously\u003csup\u003e25\u003c/sup\u003e;\u0026nbsp;\u003c/span\u003e\u003cspan style=\"font-size:13px;line-height:200%;font-family:Calibri;color:#EE0000;\"\u003e\u0026dagger;\u003c/span\u003e\u003cspan style='font-size:13px;line-height:200%;font-family:\"Arial\",sans-serif;'\u003eG.G.J personal order.\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA isolation and Reverse transcriptase PCRs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNAs were isolated from cells were isolated from cells using either Trizol reagent, or using miRNeasy kit with RNAse-free DNAse digestion step as per manufacturer\u0026rsquo;s instructions. 20 ml complementary DNA (cDNA) synthesis reactions were performed using 1000 ng RNA and High-Capacity cDNA Reverse Transcription Kit with 1.5M final concentration of betaine (from 5M stock). The temperature steps for cDNA synthesis were, 25\u0026deg;C for 10m, 37\u0026deg;C for 120m and 85\u0026deg;C for 5m. The cDNAs were further diluted with 30 ml of nuclease free water and then 2.5 ml was used for each PCR reaction. For PCR reactions 1M betaine (final conc.) was used along with regular PCR reaction components (\u003cstrong\u003ePer reaction:\u003c/strong\u003e 10X PCR buffer without MgCl\u003csub\u003e2\u003c/sub\u003e: 2.5\u0026nbsp;ml; 25 mM MgCl\u003csub\u003e2\u003c/sub\u003e: 1ml; 5M Betaine: 5 ml; dNTP mix [2.5 mM each]: 1 ml; Taq polymerase: 1.25 U; DEPC water: 12.5 ml). The primer sequences were indicated above and each primer (forward and reverse) are used at 1 ml per reaction from a 10 mM stock. All PCR reactions were subjected to an initial denaturation of 3 minutes, and cycling denaturation (95\u0026deg;C) time of 1-minute, annealing temperature of 60\u0026deg;C (30 seconds) and 1 minute of extension time (72\u0026deg;C), with 34 cycles. A final extension time of \u0026nbsp;5 minutes was given for complete product synthesis. The PCR reactions were run on 2% agarose gels with GeneRuler 100 bp DNA Ladder (ThermoFisher Scientific #SM0243). The gels were imaged using LI-COR Odyssey Fc imager (Lincoln, NE, USA). The expected product sizes were indicated in the figures.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSanger sequencing of C6GPS and C17GPS: mutation, and splicing analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInitial RT-PCR amplificons of C6GPS, and C17GPS were reamplified for Sanger sequencing purposes. The reamplified products were GFX-column purified as per manufacturer\u0026rsquo;s instructions, and 5-10ng of purified products were submitted to paired-end Sanger sequencing PCR reaction with 1M betaine and single primer (forward or reverse) at Azenta (Genewiz/Azenta, USA). The sequences were analyzed using FinchTV chromatogram reader for mutations and splicing by comparing the corresponding UCSC human genome hg19 build as reference (The coordinates are indicated in the figures). The following mutant sequences (compared to the reference genome sequence of the ORF) were submitted to GenBank: C6GPS of MCF-7 cells (Accession: PX444937), C17GPS of MCF-7 cells (Accession: PX444936), C17GPS of Hep3B cells (Accession: PX444938).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBioinformatic ORF identification of \u003cem\u003eC6GPS\u003c/em\u003e and \u003cem\u003eC17GPS\u003c/em\u003e genes, protein annotation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePericentromeric human chromosome-6 and 17 regions were examined for H3K27Ac and H3K27me3 marks by enabling corresponding ChIP-seq layers in addition to repetitive DNA and centromeric DNA layers in UCSC genome browser (Hg19 build). DNA sequences that harbor H3K27Ac and H3K27me3 marks at the pericentromeric repetitive regions were subjected to 6-frame open reading frame analysis (ORF) in NCBI-ORF finder (https://www.ncbi.nlm.nih.gov/orffinder/) with ATG and alternative initiation codon, maximum ORF length, and standard genetic code options on. The ORFs were annotated to protein sequence using single letter amino acid code, to obtain calculated molecular weight using 110 Daltons weight for average amino acid.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGPS gene epigenetic and transcription factor binding analysis: ChIP-seq\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTranscription factor binding to GPS gene family loci (CEBPB, RARA, Jun, Fos, E2F1, EP300/p300, STAT-1 and IRF-1) and epigenetic histone regulatory marks (H3K27Ac, and H3K27me3) were examined using cell line ChIP-seq data. All ChIP-seq data were accessed from Encyclopedia of DNA Elements (ENCODE)\u003csup\u003e64\u003c/sup\u003e or from UCSC Genome Browser (if indicated). CEBPB ChIP-seq data sets with or without forskolin induction in HepG2 cells [ENCODE: ENCSR000EEX file: ENCFF000XPP (fold change over control hg19) and ENCSR000BQI file: ENCFF321NDM (fold change over control hg19)] were examined for CEBPB binding at whole chromosome-6 as well as at the C6GPS locus and visualized using Integrative Genomics Viewer (IGV: BROAD institute, version 2.4.10) as peaks or as heatmap. The data range was kept constant (500) for both uninduced and forskolin induced peak tracks whereas the data range was represented as scale for heatmap. Other ChIP-seq data used were: RARA HepG2 (ENCSR500WXT: fold change over control; data range FC: 0-15), Jun MCF-7 (ENCFF513YRC: Signal p-Value; data range FC: 0-10, 0-30, 0-60), Fos MCF-7 (ENCFF950XOS: Signal p-Value; data range FC: 0-10, 0-30, 0-60), E2F1 MCF-7 (ENCFF000ZLB: signal; data range FC: 0-800), EP300 MCF-7 (ENCSR000BTR: fold change over control; data range FC: 0-5), H3K27Ac MCF-7 (ENCSR752UOD: fold change over control; data range FC: 0-5), H3K27me3 MCF-7 (ENCSR000EWP: fold change over control; data range FC: 0-5), STAT-1 K562: IFN-\u0026gamma; treated for 6 hours (ENCSR000EHJ: Signal p-Value; data range FC: 0-20), IRF-1 K562: IFN-\u0026gamma; treated for 6 hours (ENCSR000EGT: Signal p-Value; data range FC: 0-20), H3K27Ac K562 [from UCSC Genome Browser], and H3K27me3 K562 [from UCSC Genome Browser]. These ChIP-seq data sets were examined for binding at whole chromosome or C6GPS or C17GPS loci and visualized using Integrative Genomics Viewer (IGV: BROAD institute, version 2.4.10) as peaks or as heatmap.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBLASTn and BLASTp homology search and nomenclature of GPS gene family members\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe C6GPS ORF was subjected to human genome contig and RefSeq transcriptome BLASTn searches in NCBI site (https://blast.ncbi.nlm.nih.gov/Blast.cgi) and no considerable matches were found. A similar search for C17GPS ORF yielded multiple ORFs with significant homology to C17GPS and predominantly localized to human pericentromeric regions. These genes are named based on the chromosome number in which it is located (For example, C3 if it is located on chromosome-3), and numbered if more than one such genes are located at same chromosomes (For example, six genes located on chromosome-Y: CYGPS1-6).\u003c/p\u003e\n\u003cp\u003eAnnotated protein sequences of GPS family members were subjected to non-redundant protein search across all proteins from multiple organisms including humans using BLASTp (https://blast.ncbi.nlm.nih.gov/Blast.cgi) and the matching reference protein sequences (RefSeq) were collected for further phylogenetic analysis (See below). A similar search and reference sequence collection was also done for nucleotide sequences of GPS family genes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGPS family gene mapping to human genome (Circos)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGenomic visualization of GPS family genes was done using Circa software (http://omgenomics.com/circa) as described previously\u003csup\u003e28\u003c/sup\u003e. Genomic coordinates of GPS genes were collected based on the ATG start position of each gene (Hg19) from UCSC genome browser and layered along with the coordinates for centromeres, and Giemsa positivity of DNA. The circos plot was then composited and labelled in Adobe Photoshop CS5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGPS family nucleotide and protein similarity distance analysis (iTOL)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBoth nucleotide and protein BLAST matching sequences were subjected to sequence homology analysis using EMBL-EBI Clustal Omega (protein/nucleotide options) (https://www.ebi.ac.uk/jdispatcher/msa/clustalo?stype=protein). iTOL (https://itol.embl.de/). The cladograms were composited, and labelled in Adobe Photoshop CS5. The cladogram homology/identity scale is read based on the circular but not radial lines. A similar analysis, and compositing were done for FPFP motif matching proteins.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGPS gene family mRNA and C19MC miRNA expression and differential gene expression analysis in CCLE cell lines:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e100 cell lines that have miRNA-seq and RNA-seq datasets from Cancer Cell Line Encyclopedia (CCLE: https://sites.broadinstitute.org/ccle/) database were integrated by matching the cell lines, and examined for all GPS mRNA expressions in RNA-seq BAM files. Maximum reads at single point (MRSP) within the GPS gene ORF was considered as expression level. To get the expression level of an individual GPS gene, the reads of that gene across all 100 cell lines were added up to get a combined score. To get an expression level of overall GPS gene family, all reads of GPS family per cell line were added up to get a GPS score. The GPS score is then integrated with the cumulative C19MC miRNA expression and sorted based on C19MC expression before generating heatmap.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFrom these 100 CCLE cell lines, high C19MC+GPS RNA expressing 12 cell lines, and an equal number of cell lines that lack C19MC+GPS RNAs were grouped (of GPS+C19MC-RNA\u003csup\u003ePositive\u003c/sup\u003e and GPS+C19MC-RNA\u003csup\u003eNegative\u003c/sup\u003e groups) for differential gene expression analysis. The differentially expressed genes (\u0026gt;2 or \u0026lt;-2 log\u003csub\u003e2\u003c/sub\u003e fold change) with p-value \u0026lt;0.05 were subjected to EnrichR analysis, and top-ranking gene sets were subjected to networked gene analysis using NetworkAnalyst web server (https://www.networkanalyst.ca/)\u003csup\u003e65\u003c/sup\u003e to find the top ranking transcription factors. The analysis was performed using the SIGNOR 2.0 database of Signaling Network as described previously\u003csup\u003e66\u003c/sup\u003e. Briefly, the top network node was organized into a circular/bi/tripartite layout before exporting the image. The gene names were relabeled in Adobe Photoshop CS5 to have legibility.\u003c/p\u003e\n\u003cp\u003eNode tables were exported and the degree and betweenness scores were fed into the ggplot2 package in R to generate ranked dotplots to see the top-networked genes (Transcription factors were chosen).\u003c/p\u003e\n\u003cp\u003eR code:\u003c/p\u003e\n\u003cp\u003e\u0026gt; library(ggplot2)\u003c/p\u003e\n\u003cp\u003e\u0026gt; ggplot(#DataFrameName, aes(x = Xgroup, y = YGene)) +\u003c/p\u003e\n\u003cp\u003egeom_point(aes(size = Betweenness, color = Degree)) +\u003c/p\u003e\n\u003cp\u003escale_color_gradientn(colours = c(\u0026quot;black\u0026quot;, \u0026quot;blue\u0026quot;, \u0026quot;magenta\u0026quot;, \u0026quot;red\u0026quot;),\u003c/p\u003e\n\u003cp\u003elimits = c(0, 50))\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e#DataFrameName: file name.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe gene names in dotplots were relabeled in Adobe Photoshop CS5 to have legibility and color match.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMicroscopy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eC19MC miR-519D overexpressed stable MCF-7 cells were live stained with Hoechst-33342 (10 nM for 20 minutes; Cayman Chemicals, #\u0026nbsp;15547) for DNA and the sickle nuclear patterns of meiosis-III daughter cells were imaged using Zeiss Observer.Z1 microscope equipped with Axiocam 503 mono (Zeiss) camera, and composited in Adobe Photoshop CS5 as described previously\u003csup\u003e29\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantitative real-time PCR (qRT-PCR) quantification of C19MC miRNA expression\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQuantitative real-time PCRs (qRT-PCRs) for C19MC miRNAs were performed as described previously\u003csup\u003e29\u003c/sup\u003e. Briefly, RNAs were isolated from CEBPB-LAP overexpressed and their control stable cells (treated with or without 1 nM of IFN-\u0026gamma;\u0026nbsp;for 24 hours) using miRNeasy Mini Kit, quantified using nanodrop. 250 ng RNAs were used for cDNA synthesis [using Multiscribe reverse transcriptase, RNAse inhibitor, 10X buffer, dNTPs, (TaqMan MicroRNA Reverse Transcription Kit: ABI, Cat # 4366596) and RT TaqMan Primers hsa-miR-519d-3p (ThermoFisher: Assay ID: 002403 ; Cat# 4427975), hsa-miR-520g-3p (ThermoFisher: Assay ID: 001121 ; Cat# 4427975), hsa-miR-526b-3p (ThermoFisher: Assay ID: 002383 ; Cat# 4427975), and RNU6B Control (ThermoFisher: Assay ID: 001093 ; Cat# 4427975)]. The cDNAs were further subjected to quantitative PCR reactions using corresponding PCR primers with probes and TaqMan Universal PCR Master Mix (Life Technologies Cat# 4324018).\u003c/p\u003e\n\u003cp\u003eComparative Ct (DDCt) was used to calculate the relative expression of C19MC miRNAs to the control cells, after normalizing the values based on RNU6B. The RNU6B values were set as 1 and the relative fold changes in C19MC miRNA expression were plotted using GraphPad Prism software as bar graphs with SEM as error bars (v7.04; La Jolla, CA, USA). The plot was composited and labelled in Adobe Photoshop CS5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor EnrichR analysis, only statistically significant differentially expressed genes were included in the feed gene set, and the top signatures thus obtained with adjusted p-value below 0.05 were considered significant. For qRT-PCR bar-plots and other box-plots t-test statistical analysis was done using GraphPad Prism software (v7.04; La Jolla, CA, USA). The box-whisker plot is of 10-90 percentile type with 50% transparency for whisker data points. For GPS+C19MC positive and negative CCLE cell line groups, n=12 cell lines for GPS+C19MC-RNA\u003csup\u003ePositive\u003c/sup\u003e and GPS+C19MC-RNA\u003csup\u003eNegative\u003c/sup\u003e groups each was set based on C19MC miRNA expression set, and an equal number of negative cell lines were included to have equal statistical power. For ChIP-seq data the fold change over control data set was used if available or included the control with same track height settings. Throughout the study the Student\u0026rsquo;s T-test p-value of 0.05 was considered significant and are indicated with an asterisk (*) or with the p-value.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data presented in this manuscript in part utilizes ChIP-seq datasets from ENCODE database\u003csup\u003e62\u003c/sup\u003e and datasets from CCLE database\u003csup\u003e63\u003c/sup\u003e. We sincerely thank Dr. Michael Snyder (Stanford University), Dr. Richard Myers (Hudson Alpha Institute for Biotechnology), Dr. J. Michael Cherry (Stanford University), and their team members who contributed ChIP-seq data to ENCODE database. We also sincerely thank the members who contributed to CCLE cell line miRNA-Seq and RNA-Seq data. We sincerely thank Dr. Xiaobo Li (who provided MCF-7 cell line), Dr. Hayley D. Ackerman, and Dr. Kimberly T. Nguyen for help in cell line authentication. We sincerely thank Ms. Nicole Hackel, Ms. Payal Raulji, and Ms. Bethanie Gore for various help in reagent acquiring and lab management. The authors sincerely thank the National Institutes of Health for funding under the award number K08CA255933\u003c/p\u003e\n\u003cp\u003eFunding declaration: Research reported in this publication was supported in part by the National Institutes of Health under award number K08CA255933.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution:\u0026nbsp;\u003c/strong\u003eG.G.J. discovered GPS gene family, conceived the scientific concept, designed the study, performed experiments, performed data analysis, Visualized data, interpretated data, composited figures, and wrote the manuscript. M.N. performed regular quality control of all cell lines. A.S.B. conceived the viral response target C19MC, and contributed to funds. A.S.B. and E.R.F. supervised the study and offered lab space. G.G.J. and I.G. worked with genomic coordinate annotation of GPS genes. All authors read and agree to the entire contents of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA.S.B. has advisory board relationships with Deciphera. The remaining authors have no other conflicts of interests to declare. 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Filaggrin(High) melanomas exhibit active FGFR and allergic signatures with impaired GNA14 and Th1 signatures. \u003cem\u003eFront Genet\u003c/em\u003e 16, 1569403, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fgene.2025.1569403\u003c/span\u003e\u003cspan address=\"10.3389/fgene.2025.1569403\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"genes-and-immunity","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"genes","sideBox":"Learn more about [Genes \u0026 Immunity](http://www.nature.com/gene/)","snPcode":"41435","submissionUrl":"https://mts-gene.nature.com/cgi-bin/main.plex","title":"Genes \u0026 Immunity","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"GPS: Genes at Pericentromeric-repeat Sequences, Pericentromeric transcription, C6GPS, C17GPS, CEBPB-LAP, Nonsense-mediated decay (NMD), IFN-γ, IFN-β, Plasmodium ovale wallikeri, Staphylococcus hominis, Streptococcus pneumoniae, Streptomyces sp., Miniopterus natalensis, Vibrio vulnificus, Salmonella enterica, C19MC, miR-519D, miR-520G, miR-526B","lastPublishedDoi":"10.21203/rs.3.rs-8621807/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8621807/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePericentromeric transcription is unique to testis, and oocytes among the normal tissues. However, its regulation in cancer is not well-understood. Here, we discover a novel human, intron-less, coding, pericentromeric GPS gene family in cancer cells, with protein-level homology to microbial proteins from \u003cem\u003ePlasmodium\u003c/em\u003e, \u003cem\u003eStaphylococcus, Streptococcus\u003c/em\u003e, and \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e. GPS proteins harbor a conserved FPFP-motif, characteristic of a \u003cem\u003eMycobacterial\u003c/em\u003e protein that hijacks the host ERK-1/2 phosphorylation. We examined the two most expressed GPS family genes (\u003cem\u003eC6GPS\u003c/em\u003e, and \u003cem\u003eC17GPS\u003c/em\u003e) in cancer cells and discovered that the pericentromeric transcription is regulated by interferon-γ and interferon-β, CEBPB-LAP, and antiviral C19MC-miRNAs. Furthermore, GPS mRNAs are suppressed by truncation mutations, and nonsense-mediated decay (NMD). Thus, we discovered a novel pathogen-related GPS gene family in the human genome, and its pericentromeric transcription-regulatory network. This discovery will help to understand the role of GPS pericentromeric transcription in the biology, immunotherapy, and host-pathogen relationships of cancers in the future.\u003c/p\u003e","manuscriptTitle":"Pericentromeric Transcription of Novel Pathogen-Related Human GPS Genes in Cancers is Regulated by C19MC miRNAs, CEBPB, IFN-γ, and IFN-β","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-04 09:37:56","doi":"10.21203/rs.3.rs-8621807/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2026-03-17T12:25:19+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-03-07T23:52:20+00:00","index":3,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-02-24T06:48:49+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-02-10T14:51:31+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-02-10T09:29:32+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-02-02T09:41:26+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2026-02-02T09:14:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-16T22:48:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"Genes \u0026 Immunity","date":"2026-01-16T19:26:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-16T19:26:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"genes-and-immunity","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"genes","sideBox":"Learn more about [Genes \u0026 Immunity](http://www.nature.com/gene/)","snPcode":"41435","submissionUrl":"https://mts-gene.nature.com/cgi-bin/main.plex","title":"Genes \u0026 Immunity","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"0782b1aa-f8e0-4f1c-975f-a7afeadc3b1b","owner":[],"postedDate":"February 4th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":62143387,"name":"Biological sciences/Genetics/Genome/Open reading frames"},{"id":62143388,"name":"Biological sciences/Genetics/Genotype"},{"id":62143389,"name":"Biological sciences/Immunology/Antimicrobial responses"},{"id":62143390,"name":"Biological sciences/Immunology/Cytokines/Interferons"},{"id":62143391,"name":"Biological sciences/Immunology/Tumour immunology"}],"tags":[],"updatedAt":"2026-03-17T12:54:36+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-04 09:37:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8621807","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8621807","identity":"rs-8621807","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}