Aging is a universal, intrinsic, and time-dependent biological decay that is linked to intricate cellular processes including cellular senescence, telomere shortening, stem cell exhaustion, mitochondrial dysfunction, and deregulated metabolism. Cellular senescence is accepted as one of the core processes of aging at the organism level. Understanding the molecular mechanism underlying senescence could facilitate the development of potential therapeutics for aging and age-related diseases. Recently, the discovery of long non-coding RNAs (lncRNA) provided insights into a novel regulatory layer that can intervene with cellular senescence. Increasing evidence indicates that targeting lncRNAs may impact on senescence pathways. In this review, we will focus on lncRNAs involved in mechanistic pathways governing cellular senescence. Aging is a time-dependent decline of physiological capabilities. This progressive decay is caused by multiple factors such as the accumulation of senescent cells, mitochondrial dysfunction, disruption of inter/intracellular signaling, and impairment of metabolic homeostasis. Physiological degeneration is the primary risk factor for the age-related diseases such as Alzheimer, cancer, and type-2 diabetes. World population over 60 is expected to double and reach 22% by 2050 while countries like Japan, UK, Germany, and Finland will reach that level in next 5 years, and these statistics are calling for further study of aging biology .INK4A positive cells) was shown to elongate lifespan in mouse models  –9. SASP Hayflick and Moorehead challenged the cellular immortality idea with their findings on the limit of cellular replication after extensive passaging , 11. LatINK4A, which represses the CDK4–6-mediated phosphorylation of pRB, thereby blocking cell cycle. This pathway may coordinate with the p53–p21 response, depending on stress signal and/or cell types , activation of survival genes to avoid apoptosis, and the production of the SASP  project and the functional annotation of the mammalian genome (FANTOM) consortium made their early release. They have challenged this concept by identifying a large number of novel transcripts, namely non-coding RNAs (ncRNAs), from the “junk” regions. Based on their transcript lengths, ncRNAs were further divided into small ncRNAs and long ncRNAs (lncRNAs). lncRNAs are a major class of heterogeneous ncRNAs with the lengths more than 200 nucleotides. They are now being recognized as novel regulators in multiple cellular processes, including development, differentiation, chromosome remodeling, imprinting, and cell cycle control –44. ReseLong non-coding RNAs often contain a small open reading frame similar to mRNAs, which was a challenge on their distinction . RibosomRegulatory role of lncRNAs in gene expression has been studied. According to these research, their molecular mechanism is quite versatile and there are multiple modes of action , 51. lncin cis to regulate the expression of nearby genes or in trans to regulate genes from distant genomic locations. Nuclear lncRNAs often bind to heterogeneous ribonucleoprotein complexes (hnRNPs) and polycomb repressor complex (PRC), consistent with their involvement in modulating epigenetic markers and interacting with transcription factors of target genes. One of the well-known nuclear lncRNAs, Xist, is transcribed from the inactive X chromosome, and it controls dosage compensation of chromosome X in human females  of lncRNAs. By analyzing a genome-wide survey on SCNAs of lncRNA in 2394 tumor specimens from 12 types of cancer, they identified a correlation between copy number of focally amplified lncRNA on chromosome 1 (FAL1) and progression of ovarian cancer. They found out that FAL1 interacts and stabilizes the epigenetic repressor BMI1 (the PRC1 core protein) so as to repress p21 expression. Silencing FAL1 with siRNAs significantly blocked tumor growth n of p21 , 81.BRAF-activated non-coding RNA (BANCR) is a lncRNA required for cell migration in different types of cancer –84. Shi LincRNA-p21 plays a role in regulating p21 levels. Upon DNA damage, p53 activates lincRNA-p21 that is located next to the p21 gene. In the nucleus, lincRNA-p21 activates transcription of p21 by recruiting hnRNP-K to the promoter region of p21 . Using cThe transcript of metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) gene was first identified in 1997 , and it In 1991, Sakamoto et al. cloned 7SL sequence partially . They obVery long intergenic non-coding RNA-vlincRNA antisense to DDAH1 (VAD) and ANRIL have been identified from senescent cells and found to have an impact on cellular senescence while MIR31HG and UCA1 have been identified through oncogenic pathways.in cis and activates gene expression in trans at the INK4 locus. Moreover, VAD blocks the recruitment of H2A.Z, repressive histone variant, into the proximity of INK4 gene in senescent cells and maintains transcription of it  are induced during senescence. They showed that VAD, one of the antisense vlincRNAs, was highly expressed during senescence and it is essential for maintaining senescence phenotype. VAD regulates chromatin structure on of it .INK4A and p15INK4B (p15 in mouse) are transcribed. SNPs in ANRIL gene are linked to various diseases in genome-wide association studies (GWAS). Additionally, silencing of this locus affects cellular proliferation, and it has been found that polycomb complex is recruited to this region by ANRIL via SUZ12 (a component of polycomb complex). Silencing of ANRIL produces senescent cells that are stained positive for beta-galactosidase. Current research suggests that ANRIL recruits PRC1 and PRC2 to INK4 region to initiate and maintain silenced chromatin signature: H3K27ME and H2AK119ub1  proteins and MIR31HG are necessary for PcG-mediated repression of the p16INK4A locus. Hence, their data suggested a new lncRNA-mediated inhibition of the p16INK4A  that has low expression in senescent cells. When they overexpressed the SALNR, cellular senescence was delayed.Furthermore, they found that SALNR physically interacts with NF90 , which is able to suppress biogenesis of senescence-associated miRNAs, such as miR-22 and miR-181a. Inhibiting NF90 resulted in premature senescence since NF90 is the suppressor of senescence miRNAs.Moreover, when cells were exposed to Ras-induced stress (activates senescence), NF90 gets translocated to nucleolus and NF90 can no longer suppress senescence-associated miRNA biogenesis, which can be rescued by SALNR overexpression. Thus, SALNR antagonizes NF90 translocation into nucleolus and rescues its inhibitory activity on senescence-associated miRNA expression. Their data suggest that lncRNA SALNR controls cellular senescence through modulating NF90 localization .First, telomeric repeat-containing RNA has been identified in yeast and it has a specific hotspot in the subject of senescence. It forms DNA–RNA pairing with telomere region at R-loop formation that contains G-quadruplex, TERRA, and TERRA-binding proteins. TERRA also increases upon DNA damage at telomere region to involve in recombination and DNA repair. Arnoult et al. showed that TERRA expression decreases upon telomere elongation in multiple cancer cell lines . ElongatIn parallel, increased levels of TERRA was also found in several primary human tumors containing short telomeres . In otheOn a different research, TERRA was shown to maintain the telomere length in the lack of telomerase enzyme as explained above. RNA–DNA complex formed between TERRA and telomeres postpones the senescence by activating homologous recombination at telomeres . These sVillegas et al. have first reported a mitochondrial transcript of 2374 nucleotides whose expression correlates with the cellular replication . Followitrans to hundreds of genomic sites by HOTAIR. Recently, Ozes et al demonstrated a novel function of HOTAIR in DDR, which is regulating the expression of genes to block proliferation. Their results showed that after induction of DNA damage, HOTAIR activates the cellular senescence through NF-κB pathway. Furthermore, they demonstrated the presence of a positive-feedback loop that induces HOTAIR. This activates DDR and sustains NF-κB expression (The human lncRNA HOX transcript antisense RNA (HOTAIR) is transcribed from the HOXC locus of homeobox genes as an approximately 2.2-kb RNA . It bindpression . Recentlpression . First, pression . Their rWith the help of super high-resolution tiling array analysis in CDKN1 region, Puvvula et al. identified P21-associated ncRNA DNA damage activated (PANDA) as a lncRNA, which is induced upon DNA damage.P21-associated ncRNA DNA damage activated plays a dual role in proliferating cells versus senescent cells. In proliferating cells, scaffold-attachment-factor A/hnRNPU (SAFA) interacts with lncRNA PANDA to block senescence genes by recruiting PRC1 and PRC2 to senescence activating genes loci including CDKN1. Silencing SAFA and PANDA induces cell cycle arrest, and it also causes senescence in proliferating cells by allowing transcription of senescence activating genes.In senescent cells, SAFA–PANDA–PRC interactions are blocked therefore, pro-senescence genes are transcribed. PANDA inhibits the expression of proliferative genes by sequestering the transcription factor NF-YA from occupying its target promoters in senescent cells. Depletion of PANDA in the senescent cells reactivates proliferative genes and allows cells to replicate .in vivo has yet to be established.As concluding remarks, with the recent advancement in technology, our understanding on the function of lncRNAs has expanded vastly. Here, we have summarized an emerging role of lncRNAs as regulators of cellular senescence and age-related diseases. Albeit of these progresses, lncRNAs in senescence field is still in its infancy so as lncRNAs in general. Most of these studies remain at the cellular level, but the evidence that lncRNAs can regulate aging process Understanding lncRNAs function may help us fill some knowledge gap in genetic causes for human phenotypes. Many SNPs are not associated with coding genes but with non-coding region where lncRNAs may be transcribed . For exaUD wrote the manuscript. SL reviewed and edited the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


LTRs) of specific mouse endogenous retroviruses (ERVs) drive the expression of many long non‐coding transcripts (lncRNA). This process occurs post‐mitotically predominantly in spermatocytes and round spermatids. We demonstrate that this transposon‐driven lncRNA expression is a conserved feature of vertebrate spermatogenesis. We propose that transposon promoters are a mechanism by which the genome can explore novel transcriptional substrates, increasing evolutionary plasticity and allowing for the genesis of novel coding and non‐coding genes. Accordingly, we show that a small fraction of these novel ERV‐driven transcripts encode short open reading frames that produce detectable peptides. Finally, we find that distinct ERV elements from the same subfamilies act as differentially activated promoters in a tissue‐specific context. In summary, we demonstrate that LTRs can act as tissue‐specific promoters and contribute to post‐mitotic spermatogenic transcriptome diversity.Spermatogenesis is associated with major and unique changes to chromosomes and chromatin. Here, we sought to understand the impact of these changes on spermatogenic transcriptomes. We show that long terminal repeats ( The production of high‐quality gametes is essential to the propagation of life and the long‐term health of a species. Thus, cells of the germline and the molecular processes occurring within them carry special importance to the evolution of life. Spermatogenesis Fig A is a degag, pro, pol and env) flanked by two long terminal repeats (LTRs) that are essential for their replication env protein is no longer required and may be lost, while the replicative components of ERVs retain the hardware required to copy‐paste themselves to novel locations Transposable elements (TEs) occupy a large fraction of mammalian genomes having colonized approximately 35–50% of human and mouse genomes Non‐LTR retrotransposons, such as LINEs and SINEs, are also prevalent env genes play an essential function in placental development and ERVs are enriched within enhancers, contributing transcription factor binding sites Due to the features associated with their LTRs, ERVs are increasingly seen as both drivers of genome architecture but also as active players in shaping transcriptomes in tissue‐specific manners. ERVs have been shown to act as enhancers lncRNAs have previously been postulated as a possible pool for deriving novel functionality and novel peptides de novo transcript genesis.Previous studies of the male germline reveal a highly complex and global RNA regulatory network of mRNAs, lncRNAs and piRNAs with TEs and pseudogenes acting as regulatory sequences in vitro‐cultured spermatogonial stem cell lines, meiotic spermatocytes and the haploid round spermatids , and more than 75% of the lncRNA transcripts are novel  tags, we explored the 5′ localization of ENCODE 10(FPKM) values, although in raw expression terms, lncRNAs are still expressed at a lower level. This is in stark contrast to erythroblast controls, where lncRNAs expression is significantly lower than coding genes, in agreement with previously published data We inspected exon conservation across the assembly. Protein‐coding transcripts exhibit higher sequence conservation across their exons and in particular at splice junctions Fig C, while We sought to determine the genomic origins of this class of upregulated spermatogenic lncRNAs. Spermatogenesis coincides with dramatic chromatin remodelling associated with derepression of certain TEs, although transposition is suppressed at the post‐transcriptional level P < 1 × 10−42). This relative increase in the proportion of non‐coding promoters associated with LTR elements is also reflected as a genomewide enrichment for the elements in the promoters and at the TSSs of lncRNAs expressed in round spermatids, particularly at higher expression thresholds  and zebrafish (D. rerio). Rat diverged from mouse approximately 30 Mya Having observed ERV families driving expression of lncRNAs in spermatocytes and spermatids, we sought to determine whether this is a conserved feature of vertebrate spermatogenesis. We obtained and analysed data from rat  would evolve that could be translated into peptides. These emerging nascent ORFs would be subject to positive selection as they test, acquire or refine novel functionality. To test this hypothesis, we identified the longest ORF in each assembled protein‐coding and non‐coding transcript cluster. Subsequently, for each ORF, we calculated the fraction of bases undergoing negative selection or rapidly accumulating changes in the ORF compared to its putative 3′UTR. As expected, ORFs of protein‐coding transcripts show a greater proportion of bases undergoing negative selection Fig A as compet alOur results indicate ERVs are drivers of major transcriptional plasticity in the male germline. Previously, Faulkner Having established that ERV elements are expressed across many tissues, we wished to expand this analysis further to explore whether ERV‐regulated lncRNA expression is phenomenon‐restricted to the germline. Using Ensembl annotation and mouse ENCODE RNA‐Seq data, we identified tissue‐specific lncRNAs in a panel of 13 tissues. For these genes, we assessed the absolute number and fraction of transcripts with a promoter or TSS‐associated ERV element . From thThese results indicate that although the germline is a significant source of ERV‐driven transcription, ERVs can drive transcription across many tissues in a highly regulated manner.We present one of the most comprehensive analyses to date of non‐coding transcription during spermatogenesis, complementing the work of previous studies Naip genes is an ORR1E element, in contrast to the human copy of the gene As previously described we note an increase in promiscuous transcription in spermatocytes and round spermatids The activity of transposable elements is regulated by a number of mechanisms, and the onset of LTR‐driven lncRNA expression coincides with genomewide loss of the euchromatic H3K9me2 repression et alde novo gene genesis and subsequent selection of ORFs within lncRNA transcripts. By connecting ERV promoters presented here to extensive annotation of associated lncRNAs, we were able to investigate whether these transcripts could be further selected for function. As a first step, we have begun to explore their potential for the evolution of protein‐coding loci. Genesis of functional protein‐coding loci from intergenic regions and lncRNA has been demonstrated de novo genesis of both lncRNAs and peptide‐encoding loci.The germline is conceptually an ideal location to select and evolve transcript function, as any broadly toxic gene product (RNA or protein) would be rapidly eliminated through deleterious effects on gametogenesis. This “out of the testis” hypothesis has been described previously by Kaessmann et alIntriguingly, our analysis of FANTOM5 CAGE data demonstrated that LTR‐driven transcription can be far more widespread than we were expecting. This is in agreement with the work of Faulkner Finally, we can show that retrotransposon‐driven expression is a conserved feature of vertebrate spermatogenesis and plays a particularly significant role in driving and regulating lncRNA expression in rodents. Understanding the extent to which ERVs rewire transcriptional networks will be an important future direction, but this work helps to transfer ERVs from their traditional status as parasitic and opportunistic DNA elements to promoter elements with a major influence on the regulation, diversification and evolution of vertebrate transcriptomes.For full detail of experimental methods in all cases, please refer to the in vitroin vitro as described previously Ex vivo germ cells were obtained from dissection of 8‐week‐old adult mice through enzymatic digestion and mechanical disaggregation in EKRB buffer as previously described ® strain purchased from Charles River. Mice were maintained at the EMBL Mouse Biology Unit, Monterotondo, in accordance with Italian legislation  under licence from the Italian health ministry. RNA was prepared via Qiazol lysis followed by DNase treatment in the presence of an RNase inhibitor. RNA was recovered via EtOH precipitation; 5 μg of RNA was ribodepleted using Ribo‐Zero (Illumina), and 50 ng of this RNA was used for strand‐specific cDNA library preparation . Libraries were purified and analysed on High‐Sensitivity DNA chip (Agilent) on BioAnalyzer, and each paired‐end library was sequenced on one lane of a HiSeq 2000 sequencer.Per each cell type and species, libraries were prepared from two biological replicates. Erythroblasts were differentiated from E12.5 mouse livers Two biological replicates from erythroblasts, spermatogonial stem cells, spermatocytes and round spermatids were processed. Adapter contamination was removed, replicates merged and sequences de‐duplicated such that each sequence is unique per sample using Kraken −10) versus Ensembl Transcripts were assigned as non‐coding if they had a PhyloCSF Repeat annotation was obtained using RepeatMasker, NCBI/RMBLAST and the RepeatMasker database of elements (v20130422) for mouse, rat and zebrafish. When non‐overlapping repeat analysis is performed, the lowest scoring repeat match at overlapping sites is trimmed until no overlaps remain. Promoter analysis was performed by searching for overlaps between repeats and sites 1 kb upstream of defined TSSs. Unless otherwise stated see , when noP‐values were adjusted according to the Hochberg method. For comparison of coding to non‐coding promoter proportions, briefly, repeats were divided according to family, subfamily or class. Overlapping repeats in each set were merged. Expression was determined as above, and for each cell type, a minimum threshold of 0.25 FPKM was used. Promoters with non‐strand‐specific overlaps were merged. These promoter regions representing solely coding or non‐coding genes were retained. Promoter regions overlapping the repeat sets were counted. Repeat sets with fewer than 50 representative promoter regions were discarded. A hypergeometric test was performed to find repeat sets with a non‐coding/coding promoter region enrichment. The mouse ENCODE tissue analysis was performed by mapping 13 paired‐end strand‐specific samples to the mouse genome followed by count quantitation, normalization and generation of FPKM values where necessary (see Zebrafish and rat annotation was downloaded from Ensembl (v81), filtered and assigned a coding potential see . Gene exsary see .P ≤ 0.05) for both the ORF and paired 3′UTR.Detection of conserved lncRNAs was performed via mapping the longest isoform from each lncRNA cluster against 15 genome sequences obtained from Ensembl using WU‐BLAST swan (Kraken), and reads that map to a repeat masked genome were discarded . Remaining CAGE tags were mapped to a database of sequences for individual, non‐redundant ERV elements . Read depth was split between multimapped reads. Both uniquely mapped and multimapped counts were used.Cap analysis gene expression tags were retrieved from FANTOM5 A database for LC‐MS/MS search was created from a set of ranked ORFs selected based on a series of criteria see . SpermatPRJEB15333) and the European Bioinformatics Institute (http://www.ebi.ac.uk/research/enright/testome).Primary sequencing data, assembled transcripts and ancillary data are available via the European Nucleotide Archive (Study: MPD led the analysis of the data and performed the core computational analyses. CC contributed to the design analysis and generation of the library/preparation of the samples. HKS contributed to the analysis and the generation of the assembly. SvD, TL, GB, JMM and AJE contributed to the analysis. TA performed the mass spectrometry under the guidance of RCA and JR. AS and AB contributed to the analysis and provided the zebrafish samples. AJE and DO conceived and supervised this study. MPD, AJE and DO wrote the final version of the manuscript.The authors declare that they have no conflict of interest.AppendixClick here for additional data file.Review Process FileClick here for additional data file.


Virus-encoded transcription factors have been pivotal in exploring the molecular mechanisms and regulation of gene expression in bacteria and eukaryotes since the birth of molecular biology, while our understanding of viral transcription in archaea is still in its infancy. Archaeal viruses do not encode their own RNA polymerases (RNAPs) and are consequently entirely dependent on their hosts for gene expression; this is fundamentally different from many bacteriophages and requires alternative regulatory strategies. Archaeal viruses wield a repertoire of proteins to expropriate the host transcription machinery to their own benefit. In this short review we summarise our current understanding of gene-specific and global mechanisms that viruses employ to chiefly downregulate host transcription and enable the efficient and temporal expression of the viral transcriptome. Most of the experimentally characterised archaeo-viral transcription regulators possess either ribbon–helix–helix or Zn-finger motifs that allow them to engage with the DNA in a sequence-specific manner, altering the expression of a specific subset of genes. Recently a novel type of regulator was reported that directly binds to the RNAP and shuts down transcription of both host and viral genes in a global fashion. Euryarchaeon and was originally mistakenly classified as a phage owing to its head–tail morphology and the fact that the archaea had not yet been recognised as a separate domain of life  residing in the two large subunits. The DPBB of the largest subunit (Rpo1 in archaea) harbours three aspartic acid residues located within the NADFDGD sequence motif that chelate the catalytic Magnesium ions A and B in the active centre of the enzyme  and AvtR (ATnnTnnTAnnACnTT) form imperfect inverted repeats whereas F55 interacts with sequences that contain two tandem repeat sequences with an ATAGATAGAGT consensus and C68 interacts recognises the TATG(C/GG)TTTTC motif.SvtR, AvtR, F55 and E73 possess a variation of the HTH motif known as the ribbon–helix–helix (RHH) fold Fig. . RHH proSulfolobus virus transcription regulator  is a small, 6.6 kDa protein encoded by Sulfolobus islandicus rod-shaped virus 1 (SIRV1). SvtR consists of a RHH fold and forms a homodimer  promoter where it acts as a repressor of transcription and thus downregulates its own expression. SvtR is known to bind to three other sites on the viral genome of which it has the highest apparent affinity for the promoter region of the gp30 gene that encodes a structural protein involved in the formation of tail fibres which are required for virion assembly  is a 11.9 kDa protein encoded by Acidianus filamentous virus 6 (AFV6) and is highly conserved in the Beta-lipothrixvirus genus. Unlike other RHH proteins which need to form dimers to interact with the DNA, AvtR interacts with DNA as a monomer. The AvtR monomer in turn is composed of two tandem RHH motifs that are connected by a linker , and in addition is able to both activate and repress transcription from the gp30 gene in a concentration-dependent manner. Intriguingly gp30 is predicted to encode a further RHH protein. This makes AvtR the only known archaeo-viral protein to act as both a repressor and an activator of transcription. DNaseI footprinting assays showed that AvtR protects a stretch of about 100 nucleotides between the gp29 and gp30 promoters which is in support of the hypothesis that several subunits are able to oligomerise along the DNA as also suggested for SvtR. It is proposed that AvtR first binds to high affinity operator sites and then binds with weaker affinity to more degenerate sites. The stimulatory effect of AvtR is only observed at low protein concentrations and diminishes as AvtR concentration increases and oligomerises along the DNA. Therefore, the expression levels of AvtR may serve as a tipping point between stimulation and repression of targeted genes  of the Fuselloviridae family and is probably the archaeo-viral transcription factor with the most well defined biological role. SSV1 is a lysogenic virus that is unique among Crenarchaeal viruses in its propensity to enter a replicative life cycle upon exposure to UV light  with orthologs identified in at least six other SSV genomes including E51, the product of the SSV1 early T5 transcript TTTTC consensus motif, a high affinity site that overlaps with the BRE motif of the orfc68 promoter and a lower affinity site located equidistant between the promoters of orf68 and orf60. The recognition motif of C68 is also present in the promoter of a predicted DNA-binding protein located in the CRISPR locus of S. islandicus, and thus it has been speculated that C68 could be involved in the regulation of the host immune response  and has homologues in the Crenarchaeal spindle-shaped viruses. Interestingly AFV1p06 is related to ORFs encoded by both Cren- and Euryarchaeaota, which are believed to be derivatives of the viral factor judging from their flanking viral att-like sites, hallmarks of site-specific recombination. AFV106 contains an atypical Zn-finger motif with two cysteines, one histidine and one glutamic acid residue that chelate the Zn ion . This 7 kDa protein is encoded by the ion Fig. .Acidianus two-tailed virus (ATV) that binds apical to, or even partially inserted into, the DNA-binding channel of the RNAP with nanomolar affinity. One of the key target sites is the RNAP clamp, a domain renowned for its flexibility that enables the widening (‘opening’) or narrowing (‘closing’) of the DNA-binding channel that is required for the productive progression of RNAP through the transcription cycle  but also a paralog in ATV itself, the major coat protein ATV131, suggesting that RIP may be a representative of a novel family of transcription regulators. This family of proteins can be phylogenetically divided into two main clades depending on their similarity to either RIP or ATV131. A high-confidence structural homology model reveals RIP as a 4-helix bundle structure followed by a flexible C-terminal tail that is essential for RNAP-binding and function  is a 16.8 kDa protein encoded by the 45 is a 1Sulfolobus spindle-shaped virus 1 (SSV1) system . In addition to regulators encoded by the virus, it is noteworthy that regulators encoded by the cellular genome such as Sta1 have been implicated in the regulation of viral transcription  transcription of phage genes (Sheppard et al. Hitherto only a single global regulator encoded by archaeal viruses has been described: RIP which efficiently inhibits RNAP transcription of all genes, host and virus alike (Sheppard et al.


Most importantly, HSV-1-induced DoTT, but not stress-induced DoG transcription, was accompanied by a strong increase in open chromatin downstream of the affected poly(A) sites. In its extent and kinetics, downstream open chromatin essentially matched the poly(A) read-through transcription. We show that this does not cause but rather requires DoTT as well as high levels of transcription into the genomic regions downstream of genes. This raises intriguing new questions regarding the role of histone repositioning in the wake of RNA Polymerase II passage downstream of impaired poly(A) site recognition.Lytic herpes simplex virus 1 (HSV-1) infection triggers disruption of transcription termination (DoTT) of most cellular genes, resulting in extensive intergenic transcription. Similarly, cellular stress responses lead to gene-specific transcription downstream of genes (DoG). In this study, we performed a detailed comparison of DoTT/DoG transcription between HSV-1 infection, salt and heat stress in primary human fibroblasts using 4sU-seq and ATAC-seq. Although DoTT at late times of HSV-1 infection was substantially more prominent than DoG transcription in salt and heat stress, poly(A) read-through due to DoTT/DoG transcription and affected genes were significantly correlated between all three conditions, in particular at earlier times of infection. We speculate that HSV-1 either directly usurps a cellular stress response or disrupts the transcription termination machinery in other ways but with similar consequences. In contrast to previous reports, we found that inhibition of Ca Recently, we reported that productive herpes simplex virus 1 (HSV-1) infection leads to disruption of transcription termination (DoTT) of most but not all cellular genes. This results in extensive transcription beyond poly(A) sites and into downstream genes. Subsequently, cellular stress responses were found to trigger transcription downstream of genes (DoG) for >10% of protein-coding genes. Here, we directly compared the two phenomena in HSV-1 infection, salt and heat stress and observed significant overlaps between the affected genes. We speculate that HSV-1 either directly usurps a cellular stress response or disrupts the transcription termination machinery in other ways with similar consequences. In addition, we show that inhibition of calcium signaling does not specifically inhibit stress-induced DoG transcription but globally impairs RNA polymerase I, II and III transcription. Finally, HSV-1-induced DoTT, but not stress-induced DoG transcription, was accompanied by a strong increase in chromatin accessibility downstream of affected poly(A) sites. In its kinetics and extent, this essentially matched poly(A) read-through transcription but does not cause but rather requires DoTT. We hypothesize that this results from impaired histone repositioning when RNA Polymerase II enters downstream intergenic regions of genes affected by DoTT. At 7-8h p.i., about 50% of all 4sU-seq sequencing reads mapping to the human genome originated from intergenic regions (compared to <10% in uninfected cells). Previously, we referred to transcription beyond poly(A) sites due to DoTT as ‘read-out’. As this term has led to confusion, we now use the term ‘read-through’ to refer to transcription that extends beyond poly(A) sites. Transcription into a downstream gene arising from read-through from an upstream gene is referred to as ‘read-in’. For more than half of expressed cellular genes, poly(A) read-through affected >35% of their transcription. Read-in transcription into downstream genes was responsible for the seeming induction of about 1,100 cellular protein-coding and non-coding genes late in infection. In addition, it resulted in chimeric transcripts spanning two or more genes as evidenced by intergenic splicing events that connect exons of neighboring cellular genes.Transcription termination is an essential process in gene expression that is coupled to all parts of RNA metabolism including transcription initiation, splicing, nuclear export and translation . It de novo protein synthesis but appeared to at least partially rely on inositol-1,4,5-trisphosphate receptor (IP3R) activation and calcium signaling [Subsequently, two other studies reported on the disruption of transcription termination in cellular stress responses and cancer , 12. Traignaling . In addiDoG transcription during osmotic stress was identified by Vilborg et al. upon exposure to 80mM KCl for 1h  in a human neuroblastoma cell line (SK-N-BE(2)C) by RNA-seq on nuclear, RiboMinus-treated RNA . This reAlthough DoTT was much more prominent at late times (7-8h p.i.) of HSV-1 infection than in salt or heat stress, we wondered whether the two phenomena might reflect the same cellular mechanism. We thus performed a detailed comparison and characterization of HSV-1-induced DoTT and DoG transcription triggered by salt and heat stress using 4sU-seq in the same cell type, namely HFF. This showed clear similarities in read-through between HSV-1 infection and the different stresses but also clear context- and condition-specific differences. Furthermore, we performed ATAC-seq (transposase-accessible chromatin using sequencing ) to compwww.bio.ifi.lmu.de/HSV-1). As previously reported for HSV-1 infection [To directly compare HSV-1-induced DoTT with DoG transcription during cellular stress responses, we performed 4sU-seq analysis (60min 4sU-tagging followed by RNA sequencing) of HFF exposed to either salt (80mM KCl) or heat stress (44°C) for 1 and 2h see . Two bionfection  Fig 1E)www.bio.infection , 11. As To compare the extent of DoTT/DoG transcription between the three conditions, we focused on the 9,404 protein-coding and lincRNA (long intergenic non-coding RNA) genes whose expression was well detectable (fragments per kilobase of exons per million mapped reads (FPKM) ≥1) in all uninfected/untreated 4sU-seq samples. We then applied our previous approach  of dividples see . Read-inples see . With thples see ; Rs≥0.85The induction of DoG transcription upon salt and heat stress was reflected in median read-through levels of 6 to 15% -signal upstream of the gene 3’end. Similarly, Vilborg et al. found several 6-mers to be depleted (including AAUAAA) or enriched downstream of genes with pan-stress DoG transcription. However, their analysis focused on the total frequency of the 6-mers downstream of all pan-stress DoG genes instead of the frequency for individual genes. We now aimed to identify 6-mers whose abundance in the 100nt up- or downstream of individual gene 3’ends was significantly correlated to read-through  for each condition . This idInterestingly, the only gene experiencing ≥75% read-through already after 2-3h p.i. HSV-1 infection and in all stress conditions was interferon regulatory factor 1 (IRF1) Fig H in . IRF1 isA striking characteristic of HSV-1-induced DoTT was the associated increase in aberrant splicing . In part2+ release from intracellular stores and downstream kinases [2+ signaling pathways and triggers Ca2+ release from intracellular stores [2+ at late times of infection indicating a bimodal role of Ca2+ signaling in HSV-1 infection [2+ signaling inhibitors on DoTT in HSV-1 infection of HFF, we first aimed to reproduce the results by Vilborg et al. in salt stress. HFF were exposed to 80mM KCl for 1h in presence of (i) an inhibitor of IP3R signaling (2-APB), (ii) the membrane permeable Ca2+ chelator BAPTA-AM, or (iii) inhibitors of the downstream kinases Ca2+/calmodulin-dependent protein kinase II (CaMKII) and protein kinase C/protein kinase D (PKC/D) . DoG transcription was first quantified by qRT-PCR on total RNA for DDX18, which shows strong read-through in HSV-1 infection as well as salt and heat stress. Consistent with the previous report, BAPTA-AM prevented DoG transcription while the other inhibitors resulted only in a moderate (25–65%) reduction C cells depends on IP3R activation, Ca kinases . HSV-1 er stores , 26. In nfection . Before eduction . We thusmoderate –65% redueduction .2+ by BAPTA-AM in HFF might globally impair Pol II activity rather than specifically interfere with DoTT/DoG transcription. We thus analyzed the effect of 1h of BAPTA-AM treatment of uninfected cells on transcriptional activity of three cellular genes . For this purpose, we labeled newly transcribed RNA by adding 500μM 4sU to the cell culture medium for 1h. Following isolation and purification of the 4sU-labeled newly transcribed RNA (4sU-RNA) from a fixed amount of biotinylated total RNA per condition (60μg), transcriptional activity of these genes was quantified using qRT-PCR on 4sU-RNA. BAPTA-AM indeed induced a drop in transcriptional activity that was at least as strong as observed upon inhibition of Pol II using actinomycin D , the observed effects did not result from the co-depletion of intracellular Mg2+ [2+ signaling do not result from direct effects on DoG transcription but from global inhibitory effects on cellular transcription in general. To our knowledge, this strong inhibitory effect of BAPTA-AM treatment on RNA polymerase activity has not been appreciated so far and should be considered when interpreting results obtained using BAPTA-AM to inhibit calcium signaling.Considering this strong reduction in viral gene expression, we hypothesized that depletion of intracellular CaD Act-D; . In addiD Act-D; . This inD Act-D; . In addilar Mg2+ . InteresdoSERBP1 (downstream of SERBP1), remained at the site of synthesis. However, they subsequently also observed DoGs in the nucleoplasma of cells when searching for them by confocal microscopy with increased sensitivity [Vilborg et al. initially reported that DoG transcripts (DoGs) were strongly enriched at the chromatin  and thatsitivity . To assesitivity , 30 and In uninfected cells, only chromatin-associated RNA showed notable levels of downstream transcription . For all ATAC-seq samples, open chromatin regions (OCRs) were enriched around promoters, thereby confirming the high quality of the data Fig L in . Both leFig M in . NotablyFig M in , were chFig M in . In summWe next analyzed the impact of HSV-1-induced DoTT on chromatin accessibility. To our surprise, we observed a substantial increase in open chromatin downstream of individual genes with HSV-1-induced DoTT . Here, drand see . Accordirand see . Finallyrand see .Given the striking increase in dOCR length for well-expressed genes affected by HSV-1 induced DoTT, we also expected to see an increase in chromatin accessibility for salt and heat stress. However, there was no general increase in the number of long OCRs during salt or heat stress and no increase in dOCR length for individual genes in contrast to HSV-1 infection Fig P in . AccordiIn addition to enhanced chromatin accessibility downstream of pan-stress DoGs, Vilborg et al. also found an enrichment of several histone marks typically found at actively transcribed genes  and at enhancers  based on ENCODE data from unstressed murine NIH-3T3 fibroblasts . ConsideIn collaboration with Wyler et al., we recently reported on the activation of antisense transcription in the human genome during lytic HSV-1 infection . To asse+ concentrations on the exposed cells. In this respect, the expression of viral proteins counteracting the consequences of detrimental stress responses such as translational arrest and apoptosis may enable the much more efficient disruption of transcription termination by HSV-1.HSV-1 infection, cellular stress responses and cancer result in extensive transcriptional activity downstream of a subset of cellular genes –12, but vhs) [de novo pervasive transcription initiation downstream of the respective genes. However, we disfavor these models. First, it is important to note that we analyzed newly transcribed rather than total RNA. Therefore, transcriptional activity downstream or upstream of genes is always directly compared to the transcriptional activity of the corresponding gene occurring during the same timeframe of infection. The global loss in Pol II activity should equally affect genomic regions within, downstream and upstream of genes. Furthermore, strong transcriptional down-regulation of hundreds of genes has been analyzed in a broad range of different conditions using 4sU-seq [vhs-null mutant, which does not trigger a notable decline in transcriptional activity until at least 12h of infection [The results presented here and in our previous manuscript  could havhs) . Alterna 4sU-seq –36, nonenfection , still rnfection .de novo transcription initiation downstream of genes is provided both by the intergenic splicing events between neighboring genes induced in HSV-1 infection and the strong strand-specificity of the downstream transcriptional activity. De novo transcription initiation would not be limited to the strand of the upstream gene but would be expected to occur on either strand. The strong strand-specificity also excludes that downstream transcriptional activity is an artifact of the reported activation of antisense transcription during infection [The data obtained in this study provide further strong evidence that downstream transcriptional activity arises from DoTT. First, the high correlations between the extent of read-through in HSV-1 infection, salt and heat stress indicate that all three conditions involve a common mechanism, namely poly(A) read-through. Second, RNA-seq analysis of subcellular RNA fractions revealed a striking dependence of nuclear retention of exonic regions during infection on the extent of read-through observed for the respective genes. The most likely scenario is that DoTT and extensive poly(A) read-through transcription result in large aberrant transcripts that cannot be efficiently exported to the cytoplasm. Third, the induction of extensive dOCRs for genes experiencing DoTT, which depends on the transcription level of these genes, provides strong evidence for an increase in absolute transcriptional activity downstream of these genes during infection. Additional evidence against pervasive nfection . MoreoveVilborg et al. reported that DoG transcription was associated with an open chromatin state downstream of genes prior to stress . This obThe most striking finding of our study is the extensive increase in genome accessibility downstream of well-expressed genes affected by DoTT during HSV-1 infection, which essentially matched the transcriptional read-through observed at the respective time of infection. Of note, the peak heights of extensive dOCRs were often similar to levels observed in gene promoters of the respective genes where histones are displaced by transcription factors binding to promoter elements. However, in DoTT-associated dOCRs, this was not restricted to a few hundred base pairs but extended for tens-of-thousands of nucleotides. Our data indicate that dOCRs are not the cause but rather the consequence of DoTT and their formation additionally requires high levels of transcriptional activity in the respective downstream genomic regions. Considering the high correlation between DoTT and DoG transcription, we were surprised not to observe any evidence of dOCRs for DoG transcription in salt or heat stress. As DoTT-associated dOCRs were already well detectable by 4h of infection when the overall extent of DoTT and DoG transcription was very similar, the lack of dOCRs in salt and heat stress is not merely due to quantitative differences between the three conditions.Progression of transcribing Pol II across a gene is accompanied by the displacement of nucleosomes, followed by their rapid co-transcriptional repositioning immediately behind Pol II (reviewed in ). We hypIn summary, our findings provide a much more detailed picture of the molecular processes involved in DoTT/DoG transcription and point the direction for further studies to elucidate the underlying molecular mechanisms.Human fetal foreskin fibroblasts (HFF) were purchased from ECACC and cultured in DMEM with 10% FBS Mycoplex and 1% penicillin/streptomycin. HFF were utilized from passage 11 to 17 for all high-throughput experiments. This study was performed using wild-type HSV-1 strain 17. Virus stocks were produced in baby hamster kidney (BHK) cells (obtained from ATCC) as described [T approach. Dot blot analysis was performed as described previously [Salt stress was initiated by adding 80mM KCl to the tissue culture medium. Heat stress was started by replacing the cell culture medium with pre-warmed 44°C medium and culturing the cells for 1 or 2h at 44°C. Newly transcribed RNA was labeled for 1h using 500μM 4-thiouridine (Carbosynth). Total RNA was isolated using Trizol and newly transcribed RNA was purified as described . The IP3eviously  with a fSubcellular RNA fractions  were prepared combining two previously published protocols , 30. ForSequencing libraries were prepared using the TruSeq Stranded Total RNA kit (Illumina). While rRNA depletion was performed for total RNA and all subcellular RNA fractions using Ribo-zero, no rRNA depletion was performed for the 4sU-RNA samples. Sequencing of 75bp paired-end reads was performed on a NextSeq 500 (Illumina) at the Cambridge Genomic Services and the Core Unit Systemmedizin (Würzburg).5 cells per condition [HFF were infected for 8h with wild-type HSV-1 at an MOI of 10 or exposed to 1h or 2h of 80mM KCl or 44°C as described above. ATAC-seq was performed according to the original protocol starting with 1x10ondition . ATAC-seSequencing adapters were trimmed from sequencing reads using cutadapt . Trimmedfragments per kilobase of exons per million mapped reads (FPKM) and averaged between replicates. Only reads mapped to the human genome were counted for the total number of mapped reads for FPKM calculation. Fold-changes in FPKM values were normalized by dividing by median fold-changes for housekeeping genes (as defined in [Number of read fragments per gene were determined from the mapped 4sU-seq reads in a strand-specific manner using featureCounts  and genefined in ) to accoThe percentage of transcription downstream or upstream of a gene (on the same strand) were calculated separately for each replicate as:%downstream transcription = 100 x (FPKM in 5kb downstream of gene)/(gene FPKM)%upstream transcription = 100 x (FPKM in 5kb upstream of gene)/(gene FPKM)As both transcription downstream or upstream of the gene (= FPKM in 5kb downstream or upstream of gene) and transcription within the gene (= gene FPKM) are quantified in the same timeframe of infection using 4sU-seq, both should be affected to the same degree by a general decrease in transcription. Thus, calculation of this ratio cancels out the effect of any general decrease in transcription.%downstream and upstream transcription were averaged between replicates and transcription read-through and read-in were then calculated as:read-through = %downstream transcription in infected or treated cells–%downstream transcription in uninfected or untreated cellsread-in = %upstream transcription in infected or treated cells–%upstream transcription in uninfected or untreated cells.If this resulted in negative values for a gene, read-through or read-in were set to 0. As calculation of %downstream transcription or %upstream transcription cancels out the effect of any overall decrease in transcription, calculation of read-through or read-in are independent of any such decrease.mock read-through = %downstream transcription in replicate Mock read-through values were calculated from the two replicates for each time-point for each condition. Here, cor.test function in R and adjusted for multiple testing for each sample using the method by Benjamini and Hochberg for controlling the false discovery rate (FDR) [Occurrence numbers of all possible 6-mer nucleotide sequences were determined within 100nt up- or downstream of gene 3’ends. Spearman correlations between these counts for each gene and read-through values in each sample as well as significance of correlations were calculated using the te (FDR) .Splice junctions and read counts for splice junctions were determined from spliced 4sU-seq/RNA-seq read mappings. All predicted junctions were considered that used at least one annotated exon boundary and ended within the annotated 3’ and 5’ ends of the corresponding gene. Only reads were counted that included at least 5bp on either side of the splice junction. Regulation (up- or downregulation) of splice junctions was evaluated in terms of the odds-ratio: Hochberg . SplicinAdapter trimming and mapping to human and HSV-1 genomes was performed as described for the 4sU-seq data. BAM files with mapped reads were converted to BED format using BEDTools  and OCRscor.test function in R and adjusted for multiple testing for each sample using the method by Benjamini and Hochberg [Narrow peaks for ChIP-seq data of histone modification marks  in HFF were downloaded from ENCODE (epigenome series ENCSR403RCR). Presence of histone modification marks downstream of each gene was evaluated by determining the number of nucleotides in the 5kb directly downstream of the gene 3’ end that overlap peaks for the corresponding histone marks (denoted as downstream histone mark length). Spearman correlations between read-through in all conditions and downstream histone mark length and significance of correlations were calculated using the Hochberg .The datasets generated and analyzed in the current study are available in the Gene Expression Omnibus (GEO) database under the following accession numbers:4sU-seq data of HSV-1 infection: GSE59717.4sU-seq data of salt and heat stress: GSE100469.RNA-seq of total, cytoplasmic, nucleoplasmic and chromatin-associated RNA: GSE100576.ATAC-seq data for HSV-1 infected cells: GSE100611.ATAC-seq data for salt and heat stress: GSE101731.S1 FileTable A provides read-through values obtained from 4sU-seq data for HSV-1 infection, salt and heat stress. Table B provides read-through values for total, cytoplasmic, nucleoplasmic and chromatin-associated RNA at 8h p.i. HSV-1 infection. Table C lists genes for which read-through transcripts at 8h p.i. HSV-1 infection appear to remain at the chromatin, i.e. genes with ≤5% read-through in nucleoplasmic and cytoplasmic RNA, but ≥25% in chromatin-associated RNA. Table D lists all qRT-PCR primers used in this study.(XLSX)Click here for additional data file.S2 FileProtocol for the separation of subcellular RNA fractions used in this study.(PDF)Click here for additional data file.S3 FileContains Supplementary Figures A-R and legends.(PDF)Click here for additional data file.


Bidirectional gene pairs are highly abundant and mostly co-regulated in eukaryotic genomes. The structural features of bidirectional promoters (BDPs) have been well studied in yeast, humans and plants. However, the underlying mechanisms responsible for the coexpression of BDPs remain understudied, especially in plants.Here, we characterized chromatin features associated with rice BDPs. Several unique chromatin features were present in rice BDPs but were missing from unidirectional promoters (UDPs), including overrepresented active histone marks, canonical nucleosomes and underrepresented H3K27me3. In particular, overrepresented active marks  were truly overrepresented in type I BDPs but not in the other two BDPs, based on a Kolmogorov-Smirnov test.Our analyses indicate that active marks  may coordinate with repressive marks (H3K27me3 and H3K9me1/3) to build a unique chromatin structure that favors the coregulation of bidirectional gene pairs. Thus, our findings help to enhance the understanding of unique epigenetic mechanisms that regulate bidirectional gene pairs and may improve the manipulation of gene pairs for crop bioengineering.The online version of this article (doi:10.1186/s12864-016-3125-0) contains supplementary material, which is available to authorized users. Drosophila [Bidirectional promoters (BDPs) regulate the bidirectional transcription of protein-coding gene pairs with head-to-head orientation, which means that the transcription of each gene occurs on a different DNA strand and in opposite directions. These promoters have been well characterized in the eukaryotic genomes of yeast , 2, Drososophila , humans osophila , 5 and sosophila , 7. Inveosophila , 5, 8. Tosophila –11. Composophila , 12. By osophila , 13–19. osophila –23, the Arabidopsis [Populus [Progress has been made in characterizing plant BDPs in bidopsis , 24, 25,bidopsis , maize [bidopsis  and Popu[Populus  due to t[Populus , 24, 26.[Populus –31. HoweIn this study, we continued to perform a comprehensive analysis of chromatin-based epigenetic features in rice BDPs. BDPs were classified into three types  as described previously . The BDPJaponica version 7.0) as described previously [To comprehensively characterize the DNA sequence profiles of the BDPs in rice, we first identified bidirectional gene pairs with head-to-head orientations using the updated version of the rice genome (The Institute for Genomic Research (TIGR), rice subsp.eviously , which ceviously .p < 0.01)than its counterpart  (data not shown). This result indicated that the GC or TATA content may affect the expression level of the corresponding genes.We then calculated the GC contents and observed approximately 54 %, 50 % and 45 % GC contents in types I, II and III BDPs, respectively  . When compared to control genes, 62 up-regulated gene pairs and 70 down-regulated gene pairs with fold change greater than 2 were identified under drought stress. We then identified 14 overrepresented motifs in the promoter regions of gene pairs that were both up-and down-regulated during drought stress  as described previously [Arabidopsis [Bidirectional gene pairs in animals and xpressed , 43. Howeviously . We obseeviously , here webidopsis . By contTaken together, the above analyses indicated that bidirectional gene pairs, especially in type I BDPs, are highly coexpressed in rice. However, the underlying mechanisms need to be further investigated.Histone modifications play fundamental roles in controlling the chromatin-based regulation of gene expression in eukaryotic genomes. To profile the histone marks around BDPs, we performed chromatin immunoprecipitation (ChIP) followed by high through-put sequencing (ChIP-seq) for six histone marks as described previously , which iTo confirm the accuracy of the ChIP-seq analysis, a qPCR assay was performed following a ChIP experiment using antibodies against H3K27ac and H4K12ac. In general, we found that ChIP-qPCR enrichment (% of input) for an individual BDP locus was consistent with the ChIP-seq result for that locus   and +/−1 nucleosome positioning between upstream non-coding sequences and downstream coding gene. However, elongation-related marks  were only present in downstream gene bodies rather than the upstream non-coding sequences, suggesting that transcription elongation is a key determinant of the final fate of transcriptional direction from divergent promoters –70.Nucleosome-free or low occupancy of nucleosomes have been reported in the plant unidirectional promoter regions. Majority of plant promoter regions are associated with DNase I hypersensitive sites (DHSs), which are sensitive to cleavage by DNase I or other nucleases , 71–73. Drosophila [A possible correlation between nucleosome occupancy and coexpression rates was observed in humans and yeast –78. Addiosophila , humans osophila , 80–82 aosophila , 84. HowCompared to UDPs, we observed that all active marks tested and nucleosome occupancy were overrepresented in BDPs  genomic sequence and annotation data sets from the Rice Genome Annotation Database at TIGR (http://www.tigr.org/tdb/e2k1/osa1) as described previously [We retrieved the rice (eviously . BidirecWe downloaded publicly available RNA-seq datasets (GSM655033) from seedlings , that we46 datasets obtained from seedlings for H3K4me3, H3K4me2, H3K36me3 and K4K12ac (GSE26734) [ChIP-seq datasets (GSE79033)  for H3K4SE26734)  were dowSE26734) .To confirm the ChIP-seq results, we conducted a ChIP-qPCR assay following ChIP experiments using two histone marks (H3K27ac and H4K12ac). Five of the BDPs were randomly selected to design primers  as described previously [To calculate the expression mode of gene pairs, we used eleven of the raw expression datasets deposited in NCBI from the Rice Genome Annotation Project ;σ, standard deviation of the mean value for 1000 by randomly selected sequences;n, count of inquiry sequences.p-value of less than 0.05 were considered significantly enriched in the inquiry sequences compared to gene promoters in the whole rice genome.A list of inquiry sequence lengths within 500 or 1000 bp was analyzed as for 250 bp sequences above. Ultimately, motifs with a To normalize the reads counts distributed in BDP/UDP regions for assessing nucleosome positioning (MNased reads) and histone marks, we first identified all uniquely mapped reads in the region 1000 bp downstream of the TSSs. This region was equally divided into 20 sliding windows. We then calculated the number of reads within a specific sliding window divided by the length of the sliding window (bp), followed by the number of reads within the mapped genome (Mb). The sum of each BDP/UDP per sliding window was divided into the number of BDPs/UDPs. For all mapped reads, their positions in the rice genome were used to determine the midpoint of the reads.p-value was less than 0.05.A two-sample test was performed to test for significant differences in gene expression and chromatin features (histone modifications and nucleosome occupancy) between BDPs and UDPs as described previously . Briefly


Abcb1 gene. In this study, the transcription start site of the pig Abcb1 gene was identified by 5′-RACE. A 1.9-kb fragment of the 5′-flanking region of the Abcb1 gene was cloned from pig genomic DNA and sequenced. The region critical for its promoter activity was investigated via progressive deletions. Further, using mutation assays, two proximal Sp1 binding sites within the 5′-flanking region of Abcb1 were proven to be important cis-regulatory elements involved in regulating the constitutive expression of porcine Abcb1. RNA interference experiments showed that Sp1 regulated the expression of the porcine P-gp at both mRNA and protein levels. Hence, the current work provides valuable information on the regulatory mechanisms of pig Abcb1.P-Glycoprotein  plays a crucial role in drug disposition and functions by hydrolyzing ATP. However, little is known about the regulatory elements governing the transcription of the porcine  ABC transporters are a large superfamily of transmembrane proteins and are able to transport a broad range of substrates with preference for hydrophobic or cationic compounds by hydrolyzing ATP . P-GlycoAbcb1 gene promoters have been identified from human, mouse, and hamster DNAs . Animal use and handling protocols were approved by the regional Animal Ethics Committee and Nanjing Agricultural University. Sixty-day-old healthy crossbred pigs  were purchased from Jiangsu Agricultural Academy  and reared under standard conditions of light  and temperature (20–22°C). Jejunum from adult pigs were collected, snap-frozen in liquid nitrogen, and stored at -80°C until use.TM RACE 5’/3’Kit  to identify the transcription start site (TSS) of pig Abcb1. Total RNA was extracted from the porcine jejunum tissue and reverse-transcribed using the reagent from the SMARTerTM RACE 5′/3′Kit . The Abcb1 gene-specific reverse primers (GSPs) were designed as shown in the diagram  and are listed in Table 1. Reaction products were analyzed by agarose gel electrophoresis, then cloned into the pMD18-T vector  and sequenced.5′-RACE was performed using the SMARTerAbcb1 gene, was extracted from adult porcine jejunum using the Universal Genomic DNA Extraction Kit Ver. 5.0 . Based on the porcine genomic sequence GL880643.1, we designed the following primers to amplify the 5′-flanking region of pig Abcb1, 5′-TGC TAG AAA CCT GTT AGA AAG TCT AAA TAG CAG TTG-3′ (sense primer) and 5′-TTA TCC CTT TTC AAG AAG TTC TTC TTC CCT-3′ (antisense primer), generating a product of 1,905 bp from -1,843 nt to +62 nt (relative to the ATG initiation codon). Each 50 μl of PCR reaction mixture contained 10 μl of 5× PrimeSTAR GXL Buffer, 4 μl of dNTP Mixture, 1 μl of forward primer (10 μM), 1 μl of reverse primer (10 μM), 32 μl of water, 200 ng of genomic DNA, and 1 μl of PrimeSTAR GXL DNA Polymerase. The reaction conditions were as follows: 94°C for 5 min, then 32 cycles of 94°C for 30 s, 66°C for 30 s, and 72°C for 2 min, and finally at 72°C for 15 min. Amplicons were cloned using PMD18-T vector  and sequenced in both directions.Genomic DNA, used for amplifying the 5′-flanking sequence of the pig 1 (2 (3 (The putative transcription factor binding sites were predicted using AliBaba2.11  and the 1 (2 . The CpG1 (2 (3 .Abcb1 gene were constructed in this study. All the primers used for the construction were tailed with Nhe I site (forward primers) or Hind III site (reverse primers) (Table 1). The amplified DNA fragments were digested with Nhe I and Hind III, and immediately inserted into the pGL3-basic vector  and sequenced. After sequencing verification, the plasmids  were extracted with an Endo-free Plasmid Mini Kit  and quantified.A series of plasmids containing fragments with various sizes of the 5′-flanking region of the porcine ® II Fast Mutagenesis kit  and Dpn? , following the manufacturer’s protocol. The -195-Luc vector containing the Sp1 binding sites was chosen as the template. The specific mutagenic primers are shown in Table 1. PCR products were amplified with the plasmids extracted from DMT competent cells  and confirmed by sequencing.The Sp1 mutated vectors were constructed by the PCR-based site-directed mutagenesis using the Mut Express2.IPEC-J2  and Caco-2 cells were obtained from Shanghai Institute of Cell Biology, the Chinese Academy of Sciences  and grown in Dulbecco’s modified Eagle’s medium /high glucose supplemented with 10% (v/v) fetal bovine serum , 100 unit/ml penicillin and 100 μg/ml streptomycin and maintained at 37°C in 5% COTM 2000 Reagent . The luciferase activity was determined 24 h after the transfection using a Dual-luciferase® Reporter Assay Kit  and a dual luciferase reporter assay system . A promoter-null plasmid, pGL3-Basic, was also included in the transfection assay as a negative control (NC). All transfections were carried out in triplicates and repeated at least in three independent experiments.The cells were seeded in 24-well culture plates and cultured overnight, and then co-transfected with 0.7 μg of the reporter constructs and 0.05 μg of the Renilla luciferase reporter plasmid pRL-TK  to normalize for transfection efficiency using LipofectamineTM 2000 reagent according to the manufacturer’s instructions. After transfection, the cells were collected to detect the expression of Sp1 by western blotting as described previously . The membranes were washed three times with PBS-T before incubated with the appropriate secondary antibody (HRP-anti-rabbit IgG or HRP-anti-mouse IgG) for 1 h. The immunoreactive bands were visualized by an ECL enhanced chemiluminescence system . After proving the Sp1 siRNA with a good interference efficiency, pGL3-D4 construct (0.7 μg), the Renilla luciferase reporter plasmid pRL-TK (0.05 μg) and 12 nM siRNAs were co-transfected into the cells with 60–70% confluence in 24-well culture plates for 36 h using LipofectamineTM 2000 reagent according to the manufacturer’s instructions. The luciferase activity was determined as described above.Silence efficiency of the small interfering RNAs (siRNAs) was detected first. Briefly, cells were seeded in 6-well culture plates and grown to 60–70% confluence. Then the cells were transiently transfected with 50 nM siRNA for 36 h using Lipofectamineeviously . At the g for 4 min at 4°C. Then the cells were lysed with 25°C SDS lysis buffer for 10 min on ice. After washing with cold PBS, the cells were harvested, and then sonicated to produce chromatin fragments about 200–750 bp in size. Fragmented chromatin was added into ChIP dilution buffer, and incubated overnight with anti-Sp1 . A Normal Rabbit IgG  was added as a NC. Immunoprecipitated products were collected after incubation with Protein A + G coated magnetic beads. The bound chromatin was eluted and digested with proteinase K, and the DNA was then purified for PCR analysis (the primers set A and B are listed in Table 1). Primers set B were designed toward 2 kb upstream of the promoter, which serves as a control for the specificity.The ChIP assay was conducted following the instruction of the ChIP assay Kit . The IPEC-J2 cells cultured in 100 mm dishes were fixed and neutralized. Briefly, proteins were cross-linked to DNA with 1% formaldehyde for 10 min at room temperature. Then, the reaction was quenched by adding glycine  to the media with shaking for 5 min and washed three times with PBS. The cells were scraped with PBS, and centrifuged at 2000 × t-test. Differences were considered significant at p < 0.05.All experiments were performed in triplicates and repeated at least in three independent experiments. Data were presented as mean ± standard deviation (SD) of three replications. Mean values between groups were compared using the two-tailed Student’s Abcb1 gene, we first determined the exact TSS of Abcb1 by 5′-RACE. Our previous study indicated that P-gp was highly expressed in the jejunum of pigs . After cloning and sequencing of 14 different clones, we identified the major Abcb1 TSS  located at 666 bp upstream of the ATG. Only two RACE clones showed a slightly different TSS , and this site was identified as an additional minor TSS, which often occurred in TATA-less promoter. The major TSS was defined as +1 for later illustration.To better understand the transcriptional regulation of porcine  of pigs , therefoAbcb1 gene was obtained from the pig genomic DNA. Several transcription factor binding sites, including AP1, C/EBP α, C/EBP β and Sp1 binding sites, were recognized in this region by analyzing the 5′-flanking sequences . A putative binding site was found in bases -249 to -238, which was usually recognized by AP1. The binding sites for C/EBP α and C/EBP β were found in bases -170 to -160 and -134 to -124, respectively . Two putative Sp1 binding sites were also found in the bases -61 to -51 and -43 to -31, respectively . In addition, two CpG islands were predicted in the pig Abcb1 promoter using MethPrimer , indicating that the methylation level of the CpG islands might influence the transcription of pig Abcb1.A total of 1, 905 bp 5′-flanking sequence of Abcb1 gene, we generated a series of deletion luciferase reporter constructs of the 5--region of the gene , which were transiently transfected into the pig-derived IPEC-J2 cells and human-derived Caco-2 cells, respectively. The luciferase activity derived from Abcb1 promoter with different sizes was determined using Dual-Luciferase® Reporter Assay System. As shown in Figure 3, transfection of (-1177∼+312)-Luc construct into IPEC-J2 cells resulted in an eightfold induction of luciferase activity compared with the pGL3-Basic vector (p < 0.05). Further deletions to bases -777, -345, and -195, respectively, did not cause significant difference of the luciferase activities compared with each other, indicating that there are no important regulatory elements within these regions . We noticed that the luciferase activity was not diminished by deleting DNA up to position -195 (pGL-195/+312). However, the removal of the region (-195 to +24) remarkably decreased the luciferase activity of the (+25 to +312)-luc construct to 4.2% of the (-195 to +312)-luc construct, strongly suggesting that there are cis-acting elements responsible for the constitutive expression of Abcb1 in the region from bases -195 to +24 .To investigate the core promoter of porcine Figure 2, two Sp1 binding sites were located in this region (-195 to +24). Therefore, to further functionally determine the contribution of Sp1 binding sites to the constitutive expression of porcine Abcb1, site-directed mutagenesis, which can disturb the recruitment of the transcription factors, was performed . The newly generated constructs (with -61/-51 and -43/-31 mutations) were transfected into IPEC-J2 and Caco-2 cells, respectively. Luciferase activities were measured with the pGL3-D4, Sp1-mut1, and Sp1-mut2 in both IPEC-J2 and Caco-2 cells , respectively. Their effects on promoter activities were examined by dual luciferase assay. As shown in Figure 4B, the mutation in -61/-51 region significantly reduced the relative luciferase activity in IPEC-J2 cells to about 8% of the wild-type control (pGL3-D4), whereas the mutation in -43/-31 region decreased the luciferase activity to 66% of the wild-type control (pGL3-D4), indicating that the promoter activity of Abcb1 is more significantly inhibited by the dysfunction of -61/-51 region than -43/-31 region. Similar results were observed in Caco-2 cells where the mutation in -61/-51 region had more significant effect on the relative luciferase activity than the mutation in -43/-31 region , but the mutation in -43/-31 region led to quantitative difference in the relative luciferase activity in the two cell lines.As shown in Figures 5A,B. Then, we co-transfected the reporter plasmid pGL3-D4 together with siRNA-Sp1 (siSp1) or NC into IPEC-J2 cells individually. As shown in Figure 5C, when Sp1 was silenced by specific siRNAs, porcine Abcb1 promoter activity decreased by about 50% compared to NC. Accordingly, the expression levels of Abcb1 were effectively reduced by siRNA-Sp1 in IPEC-J2 cells, as detected by qRT-PCR and western blot . Taken together, the data presented here confirmed that Sp1 acted as a positive regulator of Abcb1 transcription.To further verify the role of Sp1 in the regulation of porcine Abcb1 promoter activity, western blot was performed to detect the efficiency of siRNA-Sp1 (siSp1). The results are shown in Abcb1, ChIP analysis was performed in IPEC-J2 cells. For ChIP assay, the genomic DNA should be sheared uniformly and randomly, and the DNA fragment size after sonication should be 200–750 bp . With the particular set of primers set A (Table 1), bands were detected in the input lane . Besides, the bands with the expected size were also observed when anti-Sp1 antibody was added , indicating that Sp1 could interact with the Abcb1 promoter. Conversely, no DNA band was amplified from the normal rabbit IgG immunoprecipitated chromatin with the primers set A . With the primers set B, bands were detected in the input lane but not in the immunoprecipitated sample lane. These findings suggested that the proximal Sp1 binding sites of the Abcb1 promoter were able to bind to Sp1 protein.To determine whether Sp1 binds to the promoter region of porcine 0–750 bp . Thus, cAbcb1 genes are regulated by different mechanisms , suggesting that the core promoter is located in this region and the regulatory elements of this region may affect the promoter activity of porcine Abcb1. Notably, the promoter activity of the pGL3-D5 was even lower than that of the pGL3-basic vector. This might be due to the presence of a short open reading frame (sORF) in the pig Abcb1 promoter, which sometimes occurs in the promoter of other gene, like pig ADRB2 . However, when we transfected the mutant plasmids into Caco-2 cells, the mutations of Sp1 binding site at position from -61 to -51 and position from -43 to -31 significantly reduced the transcriptional activities of Abcb1 promoter by 88 and 75%, respectively . The results indicated that Sp1 binding sites were cis-regulating motif in the porcine Abcb1 promoter, which was the same in the human Abcb1 promoter proved in the Drosophila cells (Abcb1 transcription and thus affects the bioavailability or drug–drug interaction of substrate xenobiotics.By using JASPAR and AliBaba2.1, two potential binding sites for Sp1 were predicted in the core promoter regions of porcine b1b gene , and theb1b gene . Based ola cells . AdditioUnderstanding whether a drug is an inducer or inhibitor of pig Abcb1 is also important for predicting drug–drug interactions in veterinary medicine and may be a strategy for developing new drugs. The current Food and Drug Administration guidance on evaluating P-gp induction potential of a new chemical entity is not based on direct evaluation of whether a drug induces P-gp, but depends on whether it induces CYP3A . Based oIn summary, here we, for the first time, identified and characterized the TSSs and core promoter of the pig Abcb1 gene. Our results demonstrated that Sp1 could bind to the Abcb1 promoter directly to regulate the expression of the porcine P-gp at both mRNA and protein levels.TG, CH, and LW: participated in the research design. TG, JH, and CH: conducted the experiments. TG, FH, YZ, and ZB: performed the data analysis. TG and LW: wrote or contributed to the writing of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Mogat1) catalyzes the conversion of monoacylglycerols (MAG) to diacylglycerols (DAG), the precursor of several physiologically important lipids such as phosphatidylcholine, phosphatidylethanolamine and triacylglycerol (TAG). Expression of Mogat1 is tissue restricted and it is highly expressed in the kidney, stomach and adipose tissue but minimally in the normal adult liver. To understand the transcriptional regulation of Mogat1, we characterized the mouse and human Mogat1 promoters in human kidney proximal tubule-2 (HK-2) cells. In-silico analysis revealed several peroxisome proliferator response element (PPRE) binding sites in the promoters of both human and mouse Mogat1. These sites responded to all three peroxisome proliferator activated receptor (PPAR) isoforms such that their respective agonist or antagonist activated or inhibited the expression of Mogat1. PPRE site mutagenesis revealed that sites located at -592 and -2518 are very effective in decreasing luciferase reporter gene activity. Chromatin immunoprecipitation (ChIP) assay using PPARα antibody further confirmed the occupancy of these sites by PPARα. While these assays revealed the core promoter elements necessary for Mogat1 expression, there are additional elements required to regulate its tissue specific expression. Chromosome conformation capture (3C) assay revealed additional cis-elements located ~10–15 kb upstream which interact with the core promoter. These chromosomal regions are responsive to both PPARα agonist and antagonist.Monoacylglycerol acyltransferase 1 ( Mogat1 increased while phenotyping the 1-acylglycerol phosphate O-acyltransferase 2 (Agpat2-/-) null mouse [Agpat2-/- mice revealed all the metabolic complications associated with human CGL1. The most interesting finding was a robust increase in the expression of Mogat1 in the livers of Agpat2-/- mice, both at the mRNA (~25–50 fold increase) and protein (~6-fold increase) levels [Mogat1 in Agpat2-/- mice constitutes an alternate route by which the livers of these mice could synthesize TAG. Thus, Mogat1 became a potential molecular target to reduce liver TAG synthesis. A few studies using siRNA or antisense oligonucleotides (ASO) in an acute setting showed suppression of Mogat1 expression in mice livers [Mogat1 on the Agpat2-/- and ob/ob genetic backgrounds did not result in any decrease in liver TAG levels [Mogat1 is upregulated in the liver.Triacylglycerol (TAG) is synthesized by two major pathways in mammals: the glycerol 3-phosphate (G-3-P) pathway  and the ll mouse , a murin) levels . The ince livers , resultiG levels . HoweverMogat1 have been presented in the past [Mogat1 in an in-vitro system. We initiated the current study in detail to help understand how the expression of Mogat1 might be transcriptionally regulated in tissues like the stomach and kidney, in addition to the liver [Mogat1 is a highly conserved gene in mammals, it is highly expressed in tissues like the stomach and kidney [Mogat1 might have a few non-enzymatic functions yet to be discovered. In this study, we characterized the promoter region of Mogat1, showing that the transcriptional regulation of Mogat1 could be regulated by all three peroxisome proliferator-activated receptors . The chromosome conformation capture (3C) assay further revealed that another putative PPAR regulatory region is located ~10–15 kb further upstream of the transcriptional start site (TSS) which interacts with PPARα to regulate transcription of Mogat1.A limited number of studies related to the transcriptional regulation of the past , 10. In the past  and moushe liver . It is id kidney  which arDetailed experimental procedures used in this study are available upon request.Animals used in this study were approved by the Institutional Use and Care of Animals and BioSafety Committee (IACUC) at the UT Southwestern Medical Center.http://www.cbil.upenn.edu/tess/) and TRANSFAC (TRANScription FACtor database). “TRANSFAC® from BIOBASE Corporation” and [http://www.ebi.ac.uk/Tools/clustalw2.index.html) and NCBI BLAST-basic local alignment search tool (http://blast.ncbi.nlm.nih.gov/Blast.cgi). Conserved regions between mouse, human and rat were identified using the University of California, Santa Cruz genome browser program (genome.ucsc.edu). To predict the presence of CpG islands in mouse and human Mogat1 promoters a bioinformatics online tool called Sequence Manipulation Suite was used [MOGAT1 upstream region and ~100 bp of downstream region was browsed.Identification of transcription factor binding sites was performed using TESS-Transcription Element Search System (ion” and . Multiplwas used . For thiThe cell lines included in this study were human embryonic kidney 293 (HEK-293), human kidney proximal tubule (HK-2), human epithelial colorectal adenocarcinoma (Caco-2), human colorectal adenocarcinoma (HT-29), human hepatocarcinoma (Huh-7), human breast adenocarcinoma (MCF-7), mouse fibroblasts (3T3-L1), Chinese hamster ovary (CHO), rat hepatic tumor (HTC) and normal rat kidney (NRK). Most of the cells used were obtained from ATCC and a few were obtained from other investigators on the campus.2. All cell culture reagents were from Life Technologies .HEK-293, Caco-2, Huh-7, HTC and HT-29 were grown in high glucose DMEM supplemented with 10% FBS and 1% antibiotics. HK-2 cells were grown in low glucose DMEM. CHO cells were grown in F-12 media and HT-29 cells were grown in McCoy’s 5a media with 10% FBS maintained in a 37°C incubator with 5% COPrimers for mouse genes used in conventional and real time PCR reactions in this study are listed in 32P-labeled DNA probe (a 250 bp cDNA fragment of Mogat1). Membranes were washed with hybridization buffer at 50°C for 1 h, followed by 2xSSC/0.5% SDS at 50°C for 30 min. The blots were exposed to X-ray film.Northern blot analysis was performed as previously described . Twenty Mogat1 gene. The first round of PCR was performed using 5′-Outer and 5′ Outer Universal Primers followed by the second round of PCR using 5′-Inner and 5′ Inner Universal Primers (The 5′ region of the transcript was amplified using 5′-RNA ligase mediated RACE kit as suggested by the manufacturer (Ambion) to generate the 5′ cDNA sequences of the  Primers .Mogat1 upstream region was cloned into the pGL3-basic luciferase reporter vector and was used to generate serial deletion promoter constructs. The deletion clones were amplified and sequenced to determine PCR errors. Primers used are listed in The mouse 5 cells in a 6-well plate. The cells were transfected with a 1:3 ratio of plasmid DNA:fugene HD complex . 24 hr post-transfection cells were washed with 1X PBS. Luciferase reporter assay was performed using dual luciferase reporter assay system according to the manufacturer’s protocol . The ratio for firefly:renilla luciferase activity was calculated and the relative luciferase activity was normalized to protein and expressed as a fold change in relative luminiscence units (RLU).HK-2 or HTC cells were seeded at a density of 3 x 10The plasmid consisting of Mogat1 promoter region from -2832/+136 bp  was used as the parental clone for all mutagenesis experiments. Mutation in PPRE site 1 and site 2 located at -592 and -2518 bp of the promoter were generated using Quikchange XL site directed mutagenesis kit (Agilent) according to the manufacturer's protocol. All the deletion constructs were verified by Sanger sequencing. Primers used are listed in ChIP assays were performed as reported earlier . Briefly7 cells per 150 mm plate. Cells were crosslinked with 37% formaldehyde to crosslink  and incubated at room temperature for 10 min, then 1.25 M Glycine  was added to quench unreacted formaldehyde. Cells were scraped with ice-cold PBS containing protease inhibitors and pelleted. For pre-clearing, 100 μl of protein A/G agarose beads were added and incubated at 4°C for 1 hr with rotation. The beads were pelleted at 300xg for 5 min at 4°C. The supernatant was removed and protein A/G agarose beads along with 2 μg of PPARα antibody were added and incubated overnight at 4°C with rotation. Protein A agarose beads were pelleted. The immune complexes were eluted in elution buffer and digested with proteinase K. The DNA was recovered by phenol/chloroform extraction and ethanol precipitation. The purified DNA is used for PCR as above.HK-2 cells were seeded at a density of 1 x 106 per well in a 6-well plate and the cells were transfected with Mogat1_-2832/+136 construct. 24 hr post transfection cells were treated with DMSO or 25, 50 or 100 μM WY14643, GW6471, rosiglitazone, GW9662, GW0742 or GSK0660. In some experiments, to measure the competitive inhibition of PPARs by their respective antagonist, cells were incubated with an equimolar concentration of agonist and antagonist for respective PPARs. HTC cells were also transfected as above and treated with 100 μM of the PPAR agonists and antagonists. After 24 hr of treatment, cells were lysed in passive lysis buffer (Promega) and luciferase activity was measured using dual luciferase reporter assay kit from Promega according to the manufacturer’s protocol. The ratio for firefly:renilla luciferase activity was calculated and the relative luciferase activity was normalized to protein and expressed as a fold change in RLU.HK-2 cells were seeded at a density of 1x10Agpat2-/- female mice as described earlier [6 cells were seeded into a collagen coated 6-well plate and allowed to attach for 2 hr in low glucose DMEM containing 10% FBS and 1% antibiotics. A stock solution (5 mM) of the following fatty acids were prepared by conjugating these fatty acids to BSA as described earlier: palmitic, stearic, oleic and arachidonic acids [Primary mouse hepatocytes were isolated from 1 month-old non-fasted WT and  earlier . 1x106 cic acids . The solThe 3C assay was performed according to the method described earlier . BrieflyHindIII restriction sites in the ~20 kb Mogat1 promoter of rat, HindIII was chosen as an appropriate restriction enzyme for rat promoter 3C assay. Primers used for 3C assay in HTC cells are listed in The PCR products were resolved on a 2% agarose gel and the amplified DNA was gel purified using the QIAquick gel extraction kit (Qiagen) and then cloned into pDrive cloning vector (Qiagen). The clones were sequenced to confirm the ligation of the two distal fragments. RT-qPCR was performed to quantify crosslinking efficiency. To determine the role of PPARα, cells were also incubated with DMSO, WY16873 (100 μM) or GW6471 (100 μM) for 24 hr prior to the 3C assay. Primers are listed in Values are given as mean ± S.E.M. Statistical significance was calculated by two-tailed Student’s t-test using GraphPad Prism version 6.04 for Windows. A p-value ≤0.05 was considered statistically significant.Mogat1 expression is tissue restricted, being expressed in the kidney, stomach and at somewhat lower levels in the brown adipose tissue (BAT) and epididymal fat [Mogat1 in the human and mouse liver is minimally detectable [+ RNA but not using total RNA [Mogat1 has also been reported in the livers of diet induced obese mice [ob/ob mice [KKAy and db/db mice [Mogat1 expression in the livers is several fold less when compared to tissues like the stomach or kidney and it is only upregulated in pathological conditions like hepatic steatosis [Mogat1, a conventional PCR of various mouse tissues was performed and our observations were consistent with the findings published earlier  encoded from 6 exons   . We furt  G (A/T) (C/T) G/A/C (T)) usually located ~28–32 bp downstream of the ATG for initiation of transcription [To define the TSS of equenced . The ~14 the ATG . On insppromoter . Most TApromoter . The laccription . Althougcription . Using acription , for CpGMogat1 using mouse kidney . The CpG island for mouse Mogat1 was located -156 to +87 bp from the ATG.Similarly, we also defined the TSS in the mouse e kidney . The expe kidney . In the Mogat1 promoter region were generated from the ~5.5 kb sequence upstream from the ATG. Luciferase activity was measured in transiently transfected HK-2 cells. The strongest luciferase activity (~94-fold) was recovered with the construct containing the -2832/+136 region  in the luciferase activity suggesting the presence of a repressing element in this region . Thus, these observations suggests that the -2832 upstream region may be the most critical region in the Mogat1 promoter which might include the proximal promoter along with the primary regulatory elements.Usually, the proximal promoter of a gene consists of a core promoter of ~50 bp located around the TSS and another 1 to 2 kb sequence which drives the expression of the gene and most likely includes all the genetic information required for its transcriptional activation. Reporter constructs of serial deletions of the 6 region . The luc6 region . This sus region . Next, wMogat1 promoter sequences are sufficient to drive its transcription in non-permissive cells like HEK-293 and CHO cells, we also measured the luciferase-reporter activity in these cell types. We tested constructs consisting of -2000/+136 and -5630/+136 of the Mogat1 promoter. Both the constructs resulted in ~7 to ~11-fold increase in the luciferase-reporter activity . As shown in As described above , we notecis-acting elements in the ~5.6 kb region of the mouse Mogat1 promoter to generate a lead transcription factor(s) (TF) which might regulate the Mogat1 transcriptional activity. Employing bioinformatics tools like TRANSFAC (TRANScription FACtor database) and UCSC genome browser, we determined the conserved regions among various species and identified putative TF sites  in the presence of the PPAR agonists and antagonists. Remarkably, we observed that all three PPAR agonists activated the promoter to the same level. In the presence of 25, 50 and 100 μM of PPARα agonist WY14643, 3-, 11- and 22-fold increase in the luciferase reporter activity was observed. Similarly, a dose-dependent response was observed in the presence of PPARγ agonist rosiglitazone  and PPARβ/δ agonist GW0741 showed 10-12-fold increase at 50 and 100 μM doses, although at a lower dose of 25 μM it has no effect (PPARs are ligand activated TFs which belong to the superfamily of nuclear receptors. PPARs can function as homodimers or form heterodimers with retinoid X receptor (RXR). PPARs bind to PPRE composed of a direct repeat (DR) preferably spaced by one nucleotide (DR1) with a consensus sequence of AGGTCA-N-AGGTCA. PPARs also recognize DR2 motifs that are preferably spaced by two nucleotides , 28. We ectively . On the o effect . At the Mogat1 promoter luciferase-reporter construct (-2832/+136 bp) was activated by PPARα agonist WY14643. This activation was inhibited ~34-fold in the presence of PPAR antagonist GW6471  and stearic acid (C18:0), monounsaturated oleic acid (C18:1), and polyunsaturated arachidonic acid (C20:4) (Fatty acids and fatty acid derived molecules have been shown to activate PPARs . Fatty a (C20:4) .Mogat1 expression in the presence of PA species which have been shown to increase gluconeogenesis in primary hepatocytes of Agpat2-/- mice. Mogat1 expression in Agpat2-/- hepatocytes remained unchanged in the presence of C16:0/18:1 PA (~0.2 fold decrease). This suggests that PA did not have any role in the transcriptional regulation of Mogat1 expression.We have previously observed that PA induced the expression of gluconeogenic genes in primary mouse hepatocytes . We measMogat1 transcription. To further validate whether the mouse Mogat1 PPRE sites are occupied by PPARα, we performed chromatin immunoprecipitation (ChIP) assays. The mouse kidney homogenate was immunoprecipitated with anti-IgG and anti-PPARα antibodies and DNA was amplified. Although all PPRE sites were occupied by PPARα  to the chromatin DNA in the intact nuclei. The protein-DNA complexes are digested and ligated for capturing the intra- or inter-molecular interactions. The ligated DNA is reverse-crosslinked and amplified by PCR using specific primer sets to identify the interacting genomic region.The above study of the 3C assay . This meMOGAT1 promoter . Genomic region F interacts with two regions: A and D. Similarly, region A, which contains the PPARα sites, interacts with the three regions C, E and F. All the PCR products obtained were sequenced to verify the predicted sequence. How these interactions are brought about, or the sequence in which these interactions occur, is still unclear. These interactions suggest that the PPARα site present in the region A was most active and formed more loops with the distant upstream regions compared to other PPARα sites.We initially attempted the 3C assay in the mouse whole kidney and kidney primary cells. Despite our efforts, we could not get the 3C assay to work reliably and it will require further optimization for detecting the DNA-DNA interactions in the mouse kidney. However, we were successful in detecting the long range genomic interactions using HK-2 cells, which is our chosen cell culture model. Various combinations of primer sets were used to amplify the possible DNA interacting regions . The PCRpromoter . Similarpromoter . GenomicMogat1 transcriptional regulation.These DNA-DNA interactions are responsive to PPARα agonist and antagonist. Real time PCR data demonstrated a ~2.8-fold increase in DNA-DNA interaction between regions C and A in the presence of PPARα agonist WY14643 and a negligible decrease (~0.2-fold) in the interaction in the presence of PPARα antagonist GW6471 . SimilarMogat1 in HTC cells. Interestingly, though Mogat1 is minimally expressed in the adult liver, we could amplify exons 4–6 of Mogat1 in HTC cells  for PPARα (WY14643), PPARγ (rosiglitazone) and PPAR β/δ (GW0742) , none reached statistical significance (Mogat1 promoter luciferase-reporter construct (-2832/+136 bp) in the presence or absence of PPAR agonists and antagonists. Interestingly, we observed that only PPARα and PPARβ/δ agonists activated the promoter while PPARγ agonist had no effect. In the presence of PPARα agonist (WY14643) and PPARβ/δ agonist (GW0742) a ~9- and ~10-fold increase in the luciferase reporter gene was observed, respectively (Mogat1 (~7-fold decrease).The endogenous expression of PPARs were quantified by real-time PCR in the HTC cells. The expression pattern of PPARs in the HTC cells are different than those of HK-2 cells. The highest expressing isoform was PPARβ/δ followed by PPARα and PPARγ . The pre(GW0742) . On the ificance . To veriectively . On the Mogat1 promoter we found that HindIII restriction sites were evenly distributed and could reasonably cross-link DNA-DNA interactions. Primer pairs were designed across a ~20 kb region of rat Mogat1 promoter and amplified the possible DNA-DNA interacting regions (Mogat1 promoter (We then attempted the 3C assay in HTC cells as performed in HK-2 cells. In the rat  regions . All the regions  which wepromoter . Though MOGAT1 promoters lack TATA-box and initiator (Inr) sequences or a downstream core promoter element (DPE) [In this study we provide an extensive and detailed characterization of the mouse and human Mogat1 promoter in kidney and hepatic cell lines. We show that both mouse and human nt (DPE) , 32. Hownt (DPE) .Human kidney expresses a truncated MOGAT1 transcript (this study) but this is not the case in the mouse kidney. Evolutionary conservation of genes shows that only those genes, and by extension proteins, which are functionally required in animals’ physiology survive. It is unclear why it is expressed in the mouse kidney as a functionally active protein, while in the human kidney it is alternatively spliced to generate a catalytically inactive enzyme. It could be speculated that during evolution the expression of catalytically active Mogat1 protein interfered with human kidney physiology and was inactivated by an alternative splicing mechanism. Similar to the human kidney, the human liver also expresses the alternatively spliced MOGAT1 transcript . The impMogat1 to devise additional ways to suppress hepatic TAG synthesis, targeted genetic deletion of Mogat1 in Agpat2-/- and ob/ob genetic backgrounds did not attenuate the hepatic TAG [Mogat1 is highly expressed in tissues like the kidney and stomach which are not known to synthesize any significant levels of neutral lipids such as DAG or TAG. The function of Mogat1 in these tissues is still unclear. Mogat1 can synthesize DAG from MAG. DAG is a signaling molecule on its own and is also a precursor for phospholipid synthesis. Phospholipids are critical lipids both as signaling molecules and by providing a structural backbone for cellular membranes. From this perspective, the characterization of the Mogat1 promoter (the current study) will provide a lead to study its role in these tissues. Although we were unable to show a robust decrease in liver TAG or improved glucose tolerance in the Mogat1-/-;Agpat2-/- and Mogat1-/-;ob/ob mice [Mogat1 in other tissues like stomach and kidney.While our goal was to understand the transcriptional regulation of atic TAG . It shou/ob mice , it mighMogat1 promoter activity when expressed in HK-2 cells. This suggests that PPARα also modulates Mogat1 promoter activity (this study), in addition to PPARγ which also occupies the PPRE site [MOGAT1 promoter also contains PPRE sites which are occupied by PPARα as determined by ChIP assay. Two recent reports [Mogat1 proximal promoter and activates its expression. These experiments were conducted in 293T, HepG2 cells and primary human hepatocytes. From these studies it is also unclear whether PPARγ is the only receptor that could activate MOGAT1. Reduction in the levels of liver TAG and expression of liver Mogat1 have been achieved both by using antisense oligonucleotide (ASO) inhibition in obese mice and were also observed in a liver specific PPARγ knockout mouse on a high fat diet [Mogat1 is capable of responding to all three PPARs (using agonists and antagonists) and also that PPARα specifically occupies the putative PPRE site in-vivo (ChIP assay).We also show that PPARα agonist and antagonist also modulate the ~2.8 kb mouse PRE site . Similar reports , 10 alsofat diet . On the Mogat1 with PPARα. PPARα increases hepatic fatty acid oxidation and prevents hepatic steatosis [Pparα-/- mice display increased hepatic steatosis, oxidative stress, and inflammation when fed a high fat diet [In hepatic steatosis, expression of several genes is dysregulated, including PPARγ and PPARα. While PPARγ has been studied previously , 10, froteatosis . Pparα-/fat diet , 37 but cis-elements to regulate transcriptional activation of Mogat1. Our 3C assay shows at least five different DNA-DNA interactions where the DNA region A,  genome editing system could be employed to modulate gene expression. This would help identify the function of MOGAT1 in non-lipid synthesizing tissues. This study also shows that deleting the PPRE or upstream elements (responsive to PPARs) has reduced the Mogat1 promoter activity by several fold. Recently, Li., et al [In the current study we have identified upstream DNA regions which are responsive to PPARα agonist and antagonist adding new regulatory elements for the regulation of ., et al  developeS1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S4 Fig(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.