Trichoplusia ni). We find that a large fraction of TE families (576/636 in Tnms42 cells and 503/612 in midgut) is lowly expressed or not expressed at all [≤ 4 transcripts per million (TPM)] in the uninfected condition (median TPM of 0.37 in Tnms42 and 0.46 in midgut cells). In the infected condition, a total of 62 and 187 TE families were differentially expressed (DE) in midgut and Tnms42 cells, respectively, with more up- (46) than downregulated (16) TE families in the former and as many up- (91) as downregulated (96) TE families in the latter. Expression log2 fold changes of DE TE families varied from −4.95 to 9.11 in Tnms42 cells and from −4.28 to 7.66 in midgut. Large variations in expression profiles of DE TEs were observed depending on the type of cells and on time after infection. Overall, the impact of AcMNPV on TE expression in T. ni is moderate but potentially sufficient to affect TE activity and genome architecture. Interestingly, one host-derived TE integrated into AcMNPV genomes is highly expressed in infected Tnms42 cells. This result shows that virus-borne TEs can be expressed, further suggesting that they may be able to transpose and that viruses may act as vectors of horizontal transfer of TEs in insects.Most studies of stress-induced transposable element (TE) expression have so far focused on abiotic sources of stress. Here, we analyzed the impact of an infection by the AcMNPV baculovirus on TE expression in a cell line (Tnms42) and midgut tissues of the cabbage looper moth ( TEs are selfish genetic elements able to move in the genome of their hosts and that account for a large fraction of eukaryotic genomes . Based oDrosophila have shown that depending on cases, TEs can be upregulated, downregulated, or transiently upregulated before being downregulated in response to a stress  was particularly overexpressed in infected Tnms42 cells compared to all other TE families, likely due to the expression of copies inserted into AcMNPV genomes. Overall, our study shows that infection by AcMNPV affects the expression of a moderate number of TE families in Tnms42 cells and T. ni midgut. It further reveals that TEs inserted in viral genomes can be transcribed, in agreement with the possible role viruses may play as vectors of horizontal transfer of TEs between insects.Here, we addressed these questions by reanalyzing two published time course RNA-seq data sets that were initially produced to measure variation in gene expression levels of the moth ulovirus . These eT. ni genomes used in this study [HighFive (Hi5) germ cell line and larva]. The TE landscape of the T. ni larva genome was not characterized in the original publication , including 11,511 Helitron copies, followed by LINEs  and LTRs . The most abundant superfamilies were the class II DNA/PIF-Harbinger , the class I LINE/L2 , and the class II DNA/mariner , which collectively accounted for half of all TE copies . We retained copies masked by 636 consensus sequences after filtering. The TE landscape was overall very similar to that of the larva genome, with 53.9% of DNA TEs, 37.1% of LINEs, and 9.0% of LTRs before filtering, versus 55.0% of DNA, 40% of LINE, and 5.0% of LTR after filtering.De novo TE annotation of the sly done . HoweverT. ni Hi5 genome and the differential expression was computed by TE consensus, which we consider here as each representing a separate family . Among the 636 TE families, 576 are considered as not or very lowly expressed in the mock condition [transcripts per million (TPM) < 4]. The median for TE expression in the mock is 0.37 TPM and the maximum is 65.6 TPM for Tni_Contig_13_Harbinger. Thus, few TE families are expressed in the mock condition in Tnms42 cells, with only two of them being highly expressed, that is, their average TPM is higher than 50.Reads produced by T. ni cells  to 94 (14.8%) depending on the time point during the course of the AcMNPV infection in ni cells . When coni cells . Among tT. ni genes continuously increases with time, with about 20% of T. ni unigenes being DE at 0 hpi and 40% at 48 hpi (T. ni genes being upregulated early after infection (0 and 6 hpi) and downregulated at later time points (The time course RNA-seq data produced by t 48 hpi . Moreovee points . The proT. ni (TN-368) cells (The proportion of DE TE families was relatively similar for both retrotransposons (113 out of 354 or 31.9%) and DNA transposons (70 out of 278 or 25.2%). Furthermore, among DE TE families, the proportion of upregulated ones differed only moderately between the two types of TEs  . Thus, o8) cells .Out of 94 TE families found inserted in AcMNPV genomes in previous studies , 2016, 4T. ni larva genome and the differential expression was computed by TE consensus, which we consider here as each representing a separate family (612 TE families included here). Among these 612 TE families, 148 are expressed in at least one time point in mocks (TPM ≥ 4). More precisely, 464 are considered as not or very lowly expressed in mocks , whereas 81 can be considered as always expressed with confidence . Considering all time points, the median for TE expression in mocks is 0.41 TPM (compared to 0.37 TPM in the Tnms42 cell line) and the maximum is 1,847 TPM. Thus, as for the cell line data set, most TE families are not expressed at one or more time points in mock conditions, although the strength of expression is overall slightly higher in the midgut data set.Reads produced by T. ni larvae midgut . Overall, these data show that as in the T. ni Tnms42 cell line, AcMNPV infection moderately affects the expression of several TE families, the majority of which are upregulated in the infected condition. The impact of AcMNPV infection on TE expression is lower than in the cell line as only 10.13% of TE families are affected (compared to 29% in the cell line) and both positive and negative maximum log2 fold changes (log2FCs) are slightly lower than in the cell line.The number of DE TE families varied from 0 to 59  depending on the time point during the course of the AcMNPV infection in e midgut . When coe midgut . Among tT. ni genes. Indeed, only very few DE genes were detected at early time points , followed by medium numbers at intermediate time points (82–475 genes) and a sharp increase at 72 hpi  (The time course RNA-seq data produced by 0 genes) . Thus, iT. ni larvae midgut, being 202-fold more expressed in the infected condition than in mock at 72 hpi   and DNA transposons (25/269 or 9.3%). However, among DE TE families, the proportion of upregulated ones is higher for retrotransposons (81%) than for DNA transposons (64%) . One of  = 7.66) . This TET. ni larva genome  . This correlation could be expected as it is difficult to see how increasing copy number could lead to a decrease in TE family expression level. Similarly, we found a very weak but significant positive correlation between TE family expression level and TE family age . This correlation may appear counterintuitive as one could expect that younger copies may be more likely to be functional and more strongly expressed. However, it may be partly explained by the fact that TE copy number is also weakly but significantly correlated to TE family age  . Overallmily age . TE famimily age , reinforT. ni larvae infected by AcMNPV  were at a frequency lower than 0.1% and the highest insertion frequency in this data set was 1.4%  accounted for the vast majority of the chimeric reads , with 5,580 and 5,953 reads aligning at its 5′ and 3′ extremity, respectively. Among the other chimeras, 64 aligned at the 5′ end of piggybac (2105_S.frugiperda), 22 reads aligned at the 3′ end of piggybac (22360_S.mediterranea), and insertions of Harbinger Hitchhiker TE were supported by 16 reads (7 at the 5′ extremity and 9 at the 3′ extremity). Among all 11,914 TE-virus chimeras, only 1.93% did not align at the TE tips but on their internal part, indicating that the vast majority of chimeras correspond to expression of TEs that were generated by bona fide transposition. Further supporting the biological nature of the chimeras detected in this analysis, we found target site duplications (TSDs) for TFP3 and Harbinger TEs. For example, for Harbinger, two chimeric reads were found to align on the viral genome 3 bp apart from each other, separated by a TTA motif , known tRegarding the dynamics of virus-borne TEs during infection, we observed a sharp increase in the number of chimeric reads from 12 hpi followed by relatively steady counts afterwards. Three chimeric reads were detected at 0 hpi, 107 at 6 hpi, 2,458 at 12 hpi, 2,077 at 18 hpi, 2,093 at 24 hpi, 2,078 at 36 hpi, and 2,868 at 48 hpi . The peaPH (polyhedrin), FP (few polyhedra), and Ac-Orf78  and FP  genes. In other words, the more PH and FP are expressed, the higher the expression of TPF3 copies inserted in those genes. Because only the TFP3–virus junction is considered for measuring TFP3 expression, it is likely that the true expression level of viral-borne TFP3 is much higher. Yet, it is noteworthy that even underestimated, the overall expression of the three viral-borne TFP3 copies at 12 hpi (935 RPKM) is higher than the maximum expression level reached by about 35% of AcMNPV genes during the entire duration of the experiment , with 30 shared expressed TE families. Taking all time points postinfection together, our analyses reveal that a moderate number of TE families are DE in AcMNPV-infected T. ni Tnms42 cells (187/636 TE families) and midgut (62/612 TE families), with widely overlapping ranges of fold changes in expression in the two data sets (from 30-fold decrease to 553-fold increase in cells and from 19-fold decrease to 202-fold increase in midgut). Of note, these fold changes overlap with those calculated for non-TE T. ni gene expression in Tnms42 cells , the response to AcMNPV also differs in terms of the proportion of up- versus downregulated TE families between the two data sets. While there are in total three times more upregulated than downregulated TEs in the midgut  and e midgut , there ae midgut . The impe midgut . By conte midgut . Altogetell line . Such moT. ni midgut tissues. These differences are perhaps best illustrated by the fact that only 26 shared TE families were DE in both data sets  in both data sets. Furthermore, the TE families with the highest or lowest log2FCs in one data set were not DE in the other data set. More globally, the differential impact of AcMNPV infection in the two data sets is also illustrated by the fact that the proportion of TE families that are DE among each TE type significantly differs between Tnms42 cells and T. ni midgut . For example, the proportion of DE DNA transposons is twice higher in T. ni midgut than in Tnms42 cells (9% of DNA TEs in midgut and 25% of DNA TEs in cells). Furthermore, while a relatively similar proportion of LINE and LTR families is DE in the cell line (35% of LINEs and 27% of LTR), there are 3.5 times more LTR than LINE families that are DE in the midgut (18% of LTR vs. 5% of LINE). These differences of regulation in both data sets are possibly due to differences in the regulatory landscapes of the two cell types. Another explanation can be the expression of copies specific to each genome  located in different genomic regions. The low number of DE TEs shared between both data sets is not unexpected given what is known about the impact of stress on TE expression in eukaryotes, as no unique, clear trend emerges  differ widely from ovary (the tissue from which the cell line is derived) and other T. ni tissues in their piRNA response. For example, only 71 piRNA clusters were annotated in Hi5 cells compared to 348 in T. ni ovaries and many piRNA clusters that are active in ovaries only produce few piRNA in Hi5 cells  bearing highly expressed TFP3 copies are known to be involved in the formation of occlusion bodies (OBs). Inactivation of FP or PH leads to a drop of AcMNPV OB formation , increasing our ability to detect TE-virus chimeras in this data set. Importantly, the longer read length (101 bp) produced by The three genes  of 10. After a 1-h incubation, the inoculum was removed and the cells were rinsed and further cultured with new medium. The time at which the inoculum was removed was designated 0 hpi. Total RNA was isolated from AcMNPV-infected cells, as well as from a set of parallel control cells (uninfected or mock infected), at 0, 6, 12, 18, 24, 36, and 48 hpi. Polyadenylated RNA isolated from 20 µg total RNA was used for sequencing. The sequencing library was constructed with the TruSeq protocol and sequenced on an Illumina platform. Single-end reads of 101 bp were produced for the infected condition and for the 0-hpi mock condition, whereas 51-bp reads were produced for the mock condition of the other time points and for one replicate at each time point of the infected condition. To avoid any bias potentially introduced by different read lengths, we only used replicates produced from 101-bp reads. Further information can be found in RNA-seq data were retrieved from train E2 . For infT. ni fourth-instar larvae (Cornell strain) that were ready to molt were held for 0–5 h without diet, and newly molted 5th instar larvae were used for oral infections. Larvae were orally inoculated with 5 µl of a 10% sucrose solution containing a total of 7 × 104 OBs of wild-type AcMNPV strain E2 (as in RNA-seq data were retrieved from E2 as in . Mock-inT. ni genome assemblies were retrieved from GenBank: 1) one derived from a single male T. ni larva  was run with default options on the in vivo T. ni genome, which allowed us to identify 567 TE consensus sequences. In addition, 458 TE consensus sequences of the T. ni Hi5 genome were retrieved on https://cabbagelooper.org/. We also added to our TE library 94 TEs previously found inserted in viral genomes (KM667940.1), which led us to remove 45 viral contigs. RepeatModeler version 1.0.11 was then run on the remaining contigs, which yielded 183 TE families. We also aligned the 45,049 nonviral contigs on a library of TE proteins (“RepeatPeps”) provided in the RepeatModeler package using diamond (T. ni genomes using RepeatMasker version 4.0.7 (http://www.repeatmasker.org). We then grouped RepeatMasker hits into more complete TE copies with the tool “One code to find them all” with the option –strict and –unknown (keeps only the copies greater than 80 bp in length and with more than 80% identity with the consensus)  .T. ni genomes with Bowtie2 v2.2.4 .Differential expression analysis was computed on the concatenated count tables with the R Bioconductor package DESeq2 . For thiBased on the concatenated gene and TE count tables, TE family counts were normalized to TPM. For each data set, we first calculated the number of reads per kilobase (RPK) by dividing the count of each gene or TE family in each replicate by the length of the gene or the length of the corresponding TE consensus in kilobases. RPK of all genes and TE families were then summed up by replicate and divided by one million. We finally used this million-factor for each replicate to divide all RPK values previously calculated. Since T. ni larvae mock condition and the following factors: TE copy number, TE age, and TE proximity with genes. For TE copy number, we counted the number of copies included in our study for each TE family . TE age was estimated by the percentage of divergence to the consensus for each copy. We used the average divergence of copies to estimate the age of a TE family. About TE proximity with genes, we indicated a distance of 0 for TE copies inside genes, otherwise, we counted the distance to the closest gene, in base pairs (genome annotation tni_gene_v1.gff3 at tnibase.org). The closest gene could be downstream or upstream; in any case, we calculated only positive values. Then, we calculated the average distance to nearest gene for each family. We investigated correlations between factors with the R package “corrplot,” using the Pearson method.We investigated possible correlations between the expression level of TE families in KM609482) and to a library of TEs including all TEs annotated in this study  genome were included. To identify chimeric reads, all reads were aligned to the AcMNPV WP10 genome (GenBank accession number is study . The pipTo confirm host TE insertions in viral genomes, we searched for TSD that are signatures of canonical transposition. We separated chimeric reads in 5′ of a TE sequence from those in 3′. To be sure reads in 5′ and 3′ corresponded to the same insertion, we used different criteria. The viral insertion coordinate had to be equal to more or less 5 bp between the 5′ and 3′ chimeric reads. The same TE had to be detected at this insertion point. The 5′ and 3′ chimeric reads had to have a concordant orientation.T. ni genomes. The data used in this article are available in the GenBank Sequence Read Archive [SRA] database under accession numbers SRA057390  and PRJNGenome Biology and Evolution online.C.G. acknowledges funding from ANR grants ANR-15-CE32-0011-01 TransVir and ANR-18-CE02-0021-01TranspHorizon.evab231_Supplementary_DataClick here for additional data file.


In the process of infecting the host, alphaherpesviruses have derived a series of adaptation and survival strategies, such as latent infection, autophagy and immune evasion, to survive in the host environment. Infected cell protein 22 (ICP22) or its homologue immediate early protein 63 (IE63) is a posttranslationally modified multifunctional viral regulatory protein encoded by all alphaherpesviruses. In addition to playing an important role in the efficient use of host cell RNA polymerase II, it also plays an important role in the defense process of the virus overcoming the host immune system. These two effects of ICP22/IE63 are important survival strategies for alphaherpesviruses. In this review, we summarize the complex mechanism by which the ICP22 protein regulates the transcription of alphaherpesviruses and their host genes and the mechanism by which ICP22/IE63 participates in immune escape. Reviewing these mechanisms will also help us understand the pathogenesis of alphaherpesvirus infections and provide new strategies to combat these viral infections. Alphaherpesvirinae, Betaherpesvirinae, and Gammaherpesvirinae  and resists the host’s immune response, finds and destroys the key targets of its molecular mechanism. Any drug that interferes with these steps may decrease viral survival, which will help develop new antiviral drugs and vaccines.Previously, research on ICP22 mainly focused on its structure and transcriptional regulation function. Studies have shown that ICP22 is a transcription inhibitor that can restrict the transcription and expression of host genes that are not conducive to virus replication through different mechanisms during the transcription process . In receAt present, ICP22 research mainly focuses on HSV-1, HSV-2 and VZV. The ICP22 gene is found in a different location in the α-HV genome Figure 1Bioinformatics analysis of the ICP22 protein showed that the α-HV ICP22 protein has a conserved Herpes_IE68 superfamily domain Figure 1In addition, the C-terminus of ICP22 has a large number of phosphorylation sites. Phosphorylation modification is essential for ICP22 to perform transcriptional regulation. After HSV-1 ICP22 is phosphorylated by the viral UL13 protein kinase, it participates in changing the phosphorylation status of Pol II, thereby promoting the transcriptional expression of late genes ; the traMost ICP22 homologs have one or more nuclear localization signals (NLSs) , 20–23, Viruses lack the basic mechanism of replication and must hijack the relevant functions of the host cell to complete the virus replication cycle, thereby producing progeny virus particles that can survive in the host. Similar to most nuclear-replicating DNA viruses, α-HV uses cellular Pol II to transcribe viral genes, thereby reproducing in host cells . ICP22 iThe Pol II-mediated eukaryotic transcription process includes pretranscription initiation, transcription initiation, transcription extension and transcription termination . The iniAfter Pol II starts transcription, it pauses approximately 30-50 nucleotides downstream of the transcription start site (TSS) , 35 Fi, 37. 1-βThe role of IE63 as a transcriptional regulator is not fully understood and is still controversial. At present, most studies claim that IE63 is a transcription inhibitor, but some studies have shown that IE63 can activate the transcription of certain genes. The current consensus is that IE63 has limited transcriptional effects on viral and cellular genes , 44–48. IE63 may regulate the expression of certain viral genes to promote viral survival. For example, IE63 clearly inhibits the transcription of the IE62 gene , 49. IE6HSV-1 significantly alters the phosphorylation modification of Pol II after infecting host cells, and ICP22 is a key protein involved in this effect , 54, 55.Pol II CTD Ser2 phosphorylation is mediated by P-TEFb. The CDK9 subunit of P-TEFb provides enzymatic activity, while cyclin has a regulatory role , 63. ManICP22 mediates the loss of Ser-2 phosphorylation on the Pol II CTD, which not only inhibits host cell gene transcription but also affects the expression of viral genes . The HSVSeveral studies have provided maps of Pol II localization on the virus and host genome after HSV-1 infection , 28. HSVin vitro using biochemical experiments, such as Facilitates chromatin transcription (FACT), Spt6, PAF complex and PARP  into the nuclear domain , 113. ReIt is generally believed that ICP22 not only promotes apoptosis but can also inhibit apoptosis. HSV-1 in the absence of ICP22 induced more apoptotic cells, indicating that ICP22 can block apoptosis , 124. HoIn addition, ICP22 was cleaved by caspases in cells infected with HSV-1 d120 (apoptosis inducer), revealing another product called Mr 37500 . This prIn addition, HSV-1 ICP22 can interact with p53 and antagonize p53 . p53 is On the other hand, the antiapoptotic effects of HSV-1 US1.5 and ICP22 during infection were the opposite. Overexpression of US1.5 with a baculovirus vector has been shown to trigger the activation of caspase 3 in rabbit skin cells . This reThe nuclear factor kappa-B (NF-κB) transcription factor family can be found in almost all animal cells, and they are involved in the response of cells to external stimuli. NF-κB transcription factors are activated in response to a variety of signals, including cytokines, pathogens, injury, and other stress conditions. The activation of this factor leads to the expression of several immune response genes, such as proinflammatory cytokines , chemokines and adhesion molecules. Therefore, NF-κB plays a key role in the inflammatory response and immune response of cells , 135. InStudies have reported that transiently expressed VZV IE63 can downregulate the activity of several cellular NF-κB-responsive gene promoters, such as IL-8 and IL-6 . SubsequAmbagala and Cohen reported that VZV IE63 is required to inhibit IFN-α-induced antiviral responses , and theThe deletion of IE63 makes the deletion virus sensitive to IFN-α(the replication of the deletion virus is significantly reduced), suggesting that IE63 may be involved in the regulation of JAK-STAT signaling . The latVZV IE63 can also block apoptosis , 148. rOin vitro cell assays cannot fully reveal all the functions of ICP22. ICP22 mutants should continue to be used in animal models to further reveal the regulation and mechanism of ICP22 on host and viral gene transcription in vivo, as well as the antiviral effect of ICP22. With the deepening of the understanding of viral proteins, it will inject new vitality into the treatment of herpesviruses and the development of new vaccines.In alphaherpesviruses, ICP22 is a transcriptional regulatory protein that promotes viral survival by participating in multiple transcriptional regulatory processes: VZV IE63 can interact with certain PIC components including Pol II, TFIIH, and TFIIE to limit the transcriptional start of cellular genes; HSV-1 ICP22 can inhibit its subunits by interacting with P-TEFB CDK9, which phosphorylates Pol II, thereby inhibiting transcription pause release; HSV-1 ICP22 can promote viral gene transcription extension by recruiting FACT to the viral genome in the viral replication compartment. Alphaherpesviruses have corresponding strategies to release the inhibitory effect of ICP22 on viral genes. For example, HSV-1 VP16 can release the inhibitory effect of ICP22 on the IE gene through interaction with P-TEFb. The final manifestation is that in the early stage of viral infection, ICP22 downregulates the expression of host genes and promotes high-level transcription of viral genes. As a result, the expression of host cell genes that are not conducive to virus replication is turned off, and the host’s antiviral immune response is destroyed. These complex mechanisms involved in ICP22 provide a foundation and challenge for us to understand these mechanisms and develop various potential treatment options. In addition, ICP22 destroys the host’s antiviral immune response in a variety of ways and promotes viral survival. In the future, the relationship between ICP22 and viruses and hosts can be further analyzed by using ICP22 genetically engineered mutants combined with deep sequencing, such as PRO-seq. Current QH and YW contributed to the design and writing of the article. MW, RJ, SC, QY, DZ, ML, XZ, SZ, JH, XO, SM, QG, DS, and BT all provided ideas contributing to the structure of this article. AC modified the article. All authors contributed to the article and approved the submitted version.This research was supported by the China Agriculture Research System of MOF and MARA and the Program Sichuan Veterinary Medicine and Drug Innovation Group of the China Agricultural Research System (SCCXTD-2021-18).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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The function of the transcription factor, cAMP response element‐binding protein (CREB), is activated through S133 phosphorylation by PKA and others. Regarding its inactivation, it is not well defined. cAMP response element‐binding protein plays an essential role in promoting cell proliferation, neuronal survival and the synaptic plasticity associated with long‐term memory. Our recent studies have shown that CREB is an important player in mediating stress response. Here, we have demonstrated that CREB regulates aging process through suppression of αB‐crystallin and activation of the p300‐p53‐Bak/Bax signaling axis. First, we determined that two specific protein phosphatases, PP‐1β and PP‐2Aα, can inactivate CREB through S133 dephosphorylation. Subsequently, we demonstrated that cells expressing the S133A‐CREB, a mutant mimicking constant dephosphorylation at S133, suppress CREB functions in aging control and stress response. Mechanistically, S133A‐CREB not only significantly suppresses CREB control of αB‐crystallin gene, but also represses CREB‐mediated activation of p53 acetylation and downstream Bak/Bax genes. cAMP response element‐binding protein suppression of αB‐crystallin and its activation of p53 acetylation are major molecular events observed in human cataractous lenses of different age groups. Together, our results demonstrate that PP‐1β and PP‐2Aα modulate CREB functions in aging control and stress response through de‐regulation of αB‐crystallin gene and p300‐p53‐Bax/Bak signaling axis, which regulates human cataractogenesis in the aging lens. This figure illustrates that the PP‐1β and PP‐2Aα modulate CREB functions in aging control and stress response through suppression of alphaB‐crystallin and activation of the p300‐p53‐Bax/Bak signaling axis in normal and cataractous lenses. CREBcAMP response element‐binding proteinDMEMDulbecco's modified eagle mediumGOglucose oxidaseJB6mouse skin epithelial cellsOAokadaic acidPAGEpolyacrylamide gel electrophoresisPBSphosphate‐buffered salinePKAprotein kinase ARBretina blastoma proteinSDSsodium dodecylsulfateTBStris‐buffered salineTBS‐Ttris‐buffered saline with tween‐20αBαB‐crystallinαTN4‐1mouse lens epithelial cells1Protein phosphorylation/dephosphorylation is one of the most important post‐translational modifications, modulating functions of more than one‐third of total eukaryote proteins, and thus participates in control of various physiological processes such as gene expression and regulation, DNA replication and damage response, cell proliferation, growth and differentiation, cell transformation, and apoptosis Cohen, .It is well established that protein phosphorylation/dephosphorylation is also implicated in control of cell senescence and organism aging. Through regulating functions of the various signaling transducers and transcription factors, protein phosphorylation/dephosphorylation plays essential roles in the control of aging Hart, . The tumcAMP response element‐binding protein mediates the regulation of the cAMP response genes by binding as a dimer to a conserved cAMP response element (CRE): TGACGTCA , αTN4‐1 with okadaic acid (OA), a potent inhibitor that has been shown to inhibit PP‐2A activity at low concentration (<20 nM) but both PP‐2A and PP‐1 at higher concentrations (>20 nM)  for 3–6 h Figure . During 2.5To further understand why CREB and S133A‐CREB expression cells displayed differential sensitivity to oxidative stress‐induced apoptosis, we conducted RNAseq analysis with WT‐CREB and mutant S133A‐CREB‐transfected cells. As shown in Figure 2.6To determine whether CREB‐mediated upregulation of Bak and Bax contributes to the hypersensitivity of the CREB expression cells to oxidative stress response, we have conducted CRISPR/Cas9‐mediated knockout of either Bak, Bax, or both of them in mouse lens epithelial cells. Bak, Bax, and Bak/Bax KO were verified by sequencing Figure . When th2.7To understand why CREB causes upregulation of the pro‐apoptotic regulators, Bak and Bax, we first used bioinformatics to determine whether CREB can directly control p53 to upregulate Bak and Bax and found that p53 promoter does not contain CREB binding sites within 10 kb upstream and downstream (data not shown). Next, we checked if CREB could regulate p53 stability and activity through post‐translational modifications. Since the co‐activator, p300 acts as an acetyltransferase and has previously been shown to acetylate p53  Treatment of both lens epithelial cells, αTN4‐1 and mouse skin epithelial cells, JB6 with different concentrations of OA or LB100 causes dose‐dependent hyperphosphorylation of CREB at S133; (2) Silence of PP‐1β and PP‐2Aα causes hyperphosphorylation of CREB at S133; (3) Overexpression of PP‐1β and PP‐2Acα through the Tet‐on system leads to complete dephosphorylation of CREB. Together, our results for the first time defined the specific phosphatase isoforms that dephosphorylate CREB at S133. (4) CREB suppression of αB‐crystallin to promote stress‐induced apoptosis of lens epithelial cells can be largely inhibited in cells expressing the mutant CREB, S133A‐CREB; (5) S133A‐CREB mice express much higher level of αB‐crystallin in the ocular lens, confirming the in vivo suppression of αB‐crystallin by CREB; (6) RNAseq analysis, QRT‐PCR, and Western blot analysis demonstrated that CREB but not S133A‐CREB activates the p300‐p53 signaling axis and the downstream target genes, Bax and Bak; 7) Knockdown of Bax, Bak, or both of them increases resistance against oxidative stress‐induced apoptosis in CREB expression cells; 8) Both PP‐1β and PP‐2Aα are significantly upregulated in normal human lenses from 30 to 60 years old, which correlates with aging‐dependent down‐regulation of CREB. From normal transparent lenses to cataractous lenses of the 60s age group, however, both PP‐1β and PP‐2Aα are significantly downregulated. Their down‐regulation could enhance CREB suppression of αB‐crystallin and activation of p53 acetylation as observed  , and premature aging . Informed written consent was obtained from each of the cataract patients. Detailed information is described in the Appendix 4.3The S133A‐CREB heterozygote mouse model was generated using CRISPR/Cas9 technology as described before . Detailed information is described in the Appendix 4.4Culture of mouse lens epithelial cells (αTN4‐1), and mouse skin epithelial cells (JB6) and their treatment by okadaic acid (OA) and LB100 were conducted as we described before  as we described  as described before  as previously described  except for RNAseq analysis in which each analyzed sample was a pool of two separated samples (N = 4). Significance was determined by two‐tailed Student's t‐test. The error bar in all figures represents standard deviation. The p value < 0.05 was considered statistically significant. *, **, and *** represent p < 0.05, 0.01, and 0.001, respectively.All experiments were repeated at least three times (None declared.LW, YZL, and DW‐CL designed research. LW, XDG, LZ, JLF, YWG, JWX, YX, YW, SYZ, and LY performed the experiments. QN, MH, and HMC coordinated collection of capsular epithelia samples from surgeons. LW, LZ, XDG, JLF, YWG and DW‐CL analyzed the data. LW and DW‐CL wrote the paper.Patient consent has been obtained for all patients.Supplementary MaterialClick here for additional data file.


Cellular fate and gene expression patterns are modulated by different epigenetic factors including non-coding RNAs (ncRNAs) and chromatin organization. Both factors are dynamic throughout male germ cell differentiation on the seminiferous tubule, despite the transcriptional inactivation in the last stages of spermatogenesis. Sperm maturation during the caput-to-cauda transit on the epididymis involves changes in chromatin organization and the soma-to-germ line transference of ncRNAs that are essential to obtain a functional sperm for fertilization and embryo development. Here, the male environment  is crucial to modulate these epigenetic factors throughout sperm maturation, affecting the corresponding offspring. Paternal transgenerational inheritance has been directly related to sperm epigenetic changes, most of them associated with variations in the ncRNA content and chromatin marks. Our aim is to give an overview about how epigenetics, focused on ncRNAs and chromatin, is pivotal to understand spermatogenesis and sperm maturation, and how the male environment impacts the sperm epigenome modulating the offspring gene expression pattern. Nuclear processes are highly regulated by macromolecular complexes composed mainly by proteins and nucleic acids. Every nucleus of human cells contains approximately two meters of DNA that is highly packaged in the form of chromatin in a compartment of 10–15 micrometers. The basic unit of chromatin, the nucleosome, allows this incredible level of compaction where a histone protein octamer  wraps around 146 DNA base pairs [Later, new experimental techniques allowed us to define RNAs as fundamental chromatin components. Through protein interactions or by directly interacting with DNA, RNA molecules act as modulators of the integrity of nuclear compartments, chromatin accessibility, chromatin remodeler activity, and gene expression –7. FurthBoth RNA and chromatin have been fully involved in physiological sperm production followed by their maturation through the male tract. Germ cell differentiation into sperm generates different cellular intermediates Fig. A, which Due to advances in the comprehension of these processes, paternal reproductive influence on offspring has gained attention in recent years. Studies focused on paternal transgenerational inheritance have shown the relevance of epigenetic changes on the paternal phenotype transference. This is mainly driven by the fact that the sperm epigenome escapes reprogramming after fertilization . Thus, eIn this review we want to give an overview of RNA and chromatin features and changes during spermatogenesis, and sperm passage throughout the epididymis for maturation, with a final focus on environmentally induced epigenetic transgenerational inheritance. Understanding that RNA molecules and chromatin, or both associated, are essential components that define specific genomic organizations in sperm, is key to explain their role in controlling gene expression and establishing specific phenotypes in the offspring.The seminiferous tubule is organized as a complex stratified epithelium where germ cells differentiate into spermatozoa in a process called spermatogenesis. For a more detailed explanation of this process please refer to . During Throughout the spermatogenic process, germ cell genetic material is packed by canonical and testis-specific histones until the transition from round to elongated spermatids . At thisAll these changes highlight some exceptional features of the testis, given specifically by the germ cells developing inside the seminiferous tubule. The histone epigenetic profiling of genes in mammalian germ cells showed that core poised genes  are transcriptionally dominant, controlling somatic gene expression patterns and embryonic development of diverse species spanning 300 million years of evolution . This suThe diversity of gene expression levels during spermatogenesis has been examined by single cell RNA-seq combined with bulk RNA-seq, showing a less complex transcriptome in the earlier steps of meiosis and the highest number of expressed genes at the prophase I level in diplotene spermatocytes. Thus, during early spermiogenesis, canonical histones are atypically expressed during round spermatid differentiation, while testis-specific histones and protamines are enriched in late spermatids followed by the lowest number of expressed genes . The morNuclear processes that modulate the chromatin compaction, transcriptional levels, and functional ncRNAs expression, are highly regulated at different stages of spermatogenesis. One class of ncRNAs described on spermatogenic cells are the endogenous small interfering RNAs (endo-siRNAs), which are produced from naturally-occurring double-strand RNA (dsRNA). The endo-siRNAs are one type of small non-coding RNAs (ncRNAs) involved in the RNA-interference (RNAi) mechanism to modulate gene expression at the post-transcriptional level . endo-siAnother class of small ncRNAs involved in RNAi, but derived from single stranded RNA, which are abundantly expressed in the germ lines, are the so called Piwi-interacting RNAs (piRNAs) . piRNAs Additionally, another class of small ncRNAs, the microRNAs (miRNAs) has been detected in spermatocytes nuclei . miRNAs In addition, with the functional expression of miRNAs in germ cells, the Argonaute proteins and the miRNA maturation machinery are highly expressed in testis and male germ cells, specifically the endonuclease Drosha and Ago4 . Ago4 anHence, the spermatogenic process ends up with an immature sperm cell that is transcriptionally inactive, but with several chromatin accessible regions corresponding with TSS and loaded with a considerable number of small RNA molecules Fig. B.Non-functional spermatozoa released from testes follow an essential caput-to-cauda transit through the epididymis, which takes 2–6 days in humans  and 10–1Similarly, the RNA payload is also fine-tuned by the differential transference of miRNAs throughout the epididymis . The seqSperm RNA content variations during caput-to-cauda transit have been functionally analyzed by sperm capacity for subsequent embryo development. Caput-derived sperm embryos showed alterations during preimplantation, most probably due to the overexpression of key regulatory (RNA- and chromatin-associated) factors. Strikingly, this preimplantation failure was reverted by microinjecting miRNAs, but nor tRFs, purified from cauda epididymosomes along with caput-derived sperm during the Intracytoplasmic Sperm Injection (ICSI) procedure . These fIn addition to RNA payload changes, the passage throughout the epididymis also modifies sperm chromatin architecture and accessibility. During this phase, intra- and inter-protamine disulphide bonds are promoted, increasing chromatin compaction levels to maintain and protect genetic material integrity , 73. Thivas deferens) fluids to degrade DNA [Sperm chromatin fragmentation is a natural phenomenon occurring throughout sperm transit in the epididymis tract. During this process, defective sperm are eliminated in an apoptotic-like process strongly influenced by the luminal epididymal  DNA methylated regions (DMRs), (2) Differential histone retention sites (DHRs), and (3) ncRNAs.DNA methylation at cytosines adjacent to guanine (CpG) sites was the first established epigenetic mark. High density CpG islands and low density CpG regions, termed CpG deserts have important roles in genome activity regulation . Sperm DIn the same line, DHRs position in the genome correlates with genes associated with cell signaling, metabolism and transcription, which may alter zygote and embryo development , 91, 99.On the other side, different long non-coding RNAs (lncRNAs) have been found to be enriched in sperm compared to round spermatids. Interestingly, those lncRNAs seem to target transcripts of genes related to nucleic acid metabolism, protein modification, chromatin and histone modification, heterocycle compound metabolic, sperm function and spermatogenesis . SimilarAn environmental factor that modifies offspring epigenomes, especially related to obesity, is paternal diet –107. UsiKdm6a. Here, the deletion of this tumor suppressor increased the incidence of tumors in their wild type offspring. Knockout mice sperm showed higher levels of methylation in both H3K27 and DNA at specific loci. Interestingly, some of these DNA hypermethylated regions in sperm were also observed in somatic cells of the wild type offspring, probably perturbing gene expression programs that resulted in elevated tumor incidence in the progeny [Another inheritable effect driven by epigenetic changes in sperm was shown in mice knockout for the histone demethylase  progeny . Another progeny . Sperm-s progeny . As epig progeny .Sfmbt2 gene in sperm, which led to the downregulation of miR466b-3p in the liver cells of the offspring. This miRNA targets the 3´UTR of the gluconeogenic enzyme phosphoenolpyruvate carboxykinase (PEPCK) mRNA. Therefore, the decreased expression of this miRNA increases PEPCK levels and induces hyperglycemia [Sfmbt2 promoter as a possible mechanism to mediate parental psychological stress reprogramming in offspring [Transgenerational inheritance has also been related to mental disease and cognitive function in offspring brains. Parental stress exposure influences the risk of stress reactivity and post-traumatic stress disorder (PTSD) risk in subsequent generations, contributing to the developmental programming of the hypothalamic-pituitary-adrenal (HPA) stress axis . A mouseglycemia . Consequffspring . Similarffspring . In contffspring . Anotherffspring , 122. UsSperm epigenetic variations are directly associated to embryo development and ARTs. Sperm-borne miRNAs and endo-siRNAs are important to control transcriptomic homeostasis in fertilized oocytes, zygotes, and two-cell embryos. sncRNA-deficient sperm displayed a significant reduction in embryo developmental potential, which could be rescued by injecting sperm-derived total or small RNAs into embryos during intracytoplasmic sperm injection (ICSI) , 123. AcBy contrast, ARTs can induce epigenetic variation that might be transmitted to the next generation. Specific and functional epigenetic changes in DNA methylation and H3K4me3 patterns from in vitro derived embryos demonstrate that the ICSI technique might interfere with processes associated with skeletal and immune systems in offspring . This coAPLF, CYB5R4, ERCC4 and TNRFSF21) and apoptosis-modulating genes , with an inverse correlation with age and DNA fragmentation [In recent years, conventional sperm quality analyses have tried to integrate new molecular biology techniques to increase human fertility. However, these new assays are not used routinely. Clinical sperm evaluations found that the epigenetic mark H3K4me2 is negatively correlated with sperm concentration, motility and mitochondrial activity in humans, and has therefore been considered a marker for sperm quality assessment . Similarentation . In thesentation . In a sientation .Altogether, these data demonstrate that sperm epigenetics is relevant for fertility, embryo development and transgenerational inheritance Fig. . UnderstThis literature review highlights the importance of regulatory ncRNAs, histone modifications and chromatin accessibility during spermatogenesis to obtain functional sperm and its implications on epigenetic paternal transgenerational inheritance.


TERT promoter mutations. Our work points to an intricate, still not fully characterized, regulatory network of TERT transcription in thyroid tumors. We caution against the assumption of mechanisms identified in other cancer lineages being identical in TERT-mutant thyroid specimens.Mutations in the promoter region of the telomerase reverse transcriptase (TERT) gene are enriched in patients with advanced thyroid tumors. Their consequence is the reactivation of TERT expression through mechanisms that involve specific transcription factors and other signaling inputs. Here, we show that, contrary to what it has been shown in other tumor types, multiple factors of the ETS family are able to control TERT transcription and they do so in both the presence and absence of promoter mutations. We also show that TERT expression is more dependent on the MAPK signaling pathway in thyroid cells without TERT (telomerase reverse transcriptase) gene are key determinants of thyroid cancer progression. TERT promoter mutations (TPM) create de novo consensus binding sites for the ETS (“E26 transformation specific”) family of transcription factors. In this study, we systematically knocked down each of the 20 ETS factors expressed in thyroid tumors and screened their effects on TERT expression in seven thyroid cancer cell lines with defined TPM status. We observed that, unlike in other TPM-carrying cancers such as glioblastomas, ETS factor GABPA does not unambiguously regulate transcription from the TERT mutant promoter in thyroid specimens. In fact, multiple members of the ETS family impact TERT expression, and they typically do so in a mutation-independent manner. In addition, we observe that partial inhibition of MAPK, a central pathway in thyroid cancer transformation, is more effective at suppressing TERT transcription in the absence of TPMs. Taken together, our results show a more complex scenario of TERT regulation in thyroid cancers compared with other lineages and suggest that compensatory mechanisms by ETS and other regulators likely exist and advocate for the need for a more comprehensive understanding of the mechanisms of TERT deregulation in thyroid tumors before eventually exploring TPM-specific therapeutic strategies.Hotspot mutations in the  TERT (telomerase reverse transcriptase) are the first genomic lesions in a gene regulatory region and display a high prevalence across multiple cancer types [TERT promoter mutations (TPMs) are observed with increasing frequency according to the severity of thyroid cancer [V600E driver mutation [Mutations in the proximal promoter of er types . They weer types ,3 and suer types , includier types ,6. TERT d cancer ,8. Thus,d cancer . In contmutation ,11. OverTERT transcription, which is typically silenced in adult tissues, is reactivated in cells carrying TPMs. The seminal papers reporting TPMs in melanoma pointed at an ETS-mediated role on TERT mutant promoter control [TERT in aggressive thyroid tumors is a necessary first step towards enabling new methods of blocking TERT expression and ultimately inhibiting cell growth in a cancer-specific manner.TPMs occur at either c.-124C>T or c.-146C>T in a mutually exclusive fashion. These single nucleotide substitutions generate an identical 11-nucleotide stretch creating de novo binding sites for the ETS (“E26 transformation specific”) family of transcription factors, which comprise 27 members with diverse functions and tissue-specific roles [ control , but theTERT-mutant glioblastomas demonstrated that GABPA, an ETS factor acting as a tetrameric protein along with its GABPB isoform, drives TERT-mutant transcription in this tumor lineage, opening the door to targeting the GABPA/GABPB axis to achieve TERT downregulation in that context [a priori attractive idea of GABPA also being the key player in TERT-mutant regulation across TPM-harboring thyroid cancers [TERT transcription in thyroid specimens [TERT wildtype promoter [Several studies in  context ,14,15. T cancers . Howeverpecimens ,17,18, specimens . In addipromoter ,21,22,23TERT mutant control have either focused on single ETS factors in several cell lines or screened multiple factors in a limited number of lines. Here, we adopted an agnostic approach, screening all ETS factors that are expressed in thyroid tumors in numerous, fully characterized, thyroid cancer cell lines. Our results point to a greater complexity of TPM-mediated regulation of TERT transcription from what was previously reported and caution against adopting what has been demonstrated in other cancer types carrying TPMs into thyroid tumors. Furthermore, we observed that the MAPK blockade was more efficient at suppressing TERT transcription in cells without TPMs, suggesting that a switch in TERT-mutant control might operate in thyroid cancers carrying TPMs. Overall, we believe that only observations that are generalizable to all thyroid cancers harboring TPMs will help in exploiting them as potential targets to implement tumor-specific epigenetic inhibition of this bona fide cancer gene.Thus far, most thyroid cancer studies aimed at identifying mechanistic underpinnings of http://firebrowse.org/?cohort=THCA&download_dialog=true, accessed on 1 January 2018) or retrieved from our published studies on PDTC, ATC, and thyroid cancer cell lines [Normalized transcriptomic data from The Cancer Genome Atlas (TCGA) evaluation of PTC  was eithll lines . Express2.The following authenticated thyroid cancer cell lines, which we recently characterized, were used in this study . Cell liTERT transcription via stable gene silencing. We individually silenced each of the 20 ETS factors that are expressed in thyroid cancers. To this end, we used the TRC collection of hairpins from the Genetic Perturbation Platform at the Broad Institute . Short hairpin RNA (shRNA) clones were obtained from the MSKCC Gene Editing and Screening core in either the pLKO.1 or pLKO_TRCN005 plasmid backbones. The specific shRNA clones and target sequences used in our study are listed in We evaluated the effect of ETS silencing on ® 480 II. SYBR™ Select Master Mix (Applied Biosystems) for measuring actin and ETS factors. TaqMan™ Gene Expression Master Mix (Applied Biosystems) and TERT TaqMan Assay  were used to measure TERT expression. Cells infected with pLKO_shScramble constructs were used as reference for each experiment. Specific forward and reverse primers used for these reactions are available in TERT were normalized to the beta-actin (ACTB) housekeeping gene using the delta-delta Ct method.Cells were lysed using TRIzol reagent, and RNA was isolated with chloroform and then precipitated from the aqueous phase using isopropanol. cDNA was synthesized using the High Capacity cDNA Reverse Transcription Kit  according to the manufacturer’s instructions. Quantitative PCR was performed on a Roche LightCycler50 values for each cell line to account for inter-specimen variability to MAPK inhibition and to make our comparisons accurate. For IC50 calculations, 50,000 cells were seeded in 6-well plates, six conditions per treatment in triplicates (trametinib: 0 nM (DMSO), 1 nM, 2 nM, 5 nM, 10 nM, and 30 nM; dabrafenib: 0 nM, 5 nM, 10 nM, 20 nM, 40 nM, and 80 nM). Cells were counted after incubation for 72 h, and IC50 values were calculated using linear regression. For the MAPK inhibition treatment experiments, cells were seeded using media with 1% FBS into 4 cm dishes at a density of 4 × 105 cells per plate. After 24 h, the cells were treated with trametinib only  or trametinib plus dabrafenib  at the IC50 dose determined for each cell line. After 6 h, the cells were harvested in total lysis buffer with protease and phosphatase inhibitors  for protein analysis and in TRIzol for RNA isolation.We ran MAPK inhibition experiments using the FDA-approved MEK inhibitor trametinib and RAF inhibitor dabrafenib . We calculated ICTotal protein concentrations were measured by Pierce BCA (ThermoFisher Scientific). Equal amounts of proteins were run on NuPAGE 4 to 12%, Bis-Tris protein gels (ThermoFisher Scientific) and subsequently transferred onto PVDF membranes (ThermoFisher Scientific) by wet electroblotting. Transfer efficiency was checked with Ponceau staining. MAPK inhibition was evaluated via a phospho-ERK antibody . Equal protein loading was controlled with the p85 antibody . Antibodies were diluted 1:1000 in 5% BSA in Tris-buffered saline with 0.1% Tween20, incubated overnight at 4 °C, and then probed for one hour at room temperature with a 1:3000 dilution of anti-rabbit  IgG HRP-linked antibody and developed using Pierce ECL Western Blotting Substrate (ThermoFisher Scientific).t-tests. Schematic figures were generated using BioRender software and images were exported under a paid subscription.All statistical analyses were performed using GraphPad Prism, version 9.2.0 . The expression data for the selected ETS factors are presented as the mean ± standard deviation from at least three independent experiments. Statistical differences between cell lines with ETS factor silencing against scrambled control lines and between the DMSO and drug-treated samples were analyzed by unpaired students TERT promoter in thyroid cancer specimens, we adopted an unbiased approach, evaluating their reported binding preferences and expression patterns in thyroid tumors and cell lines  at TERT-124 and-146). ETS factors from classes III and IV showed binding preferences  that likely render them less dependent on de novo sites created by TPMs  analysis of PTC  as well TERT c.-124C>T mutation, and Cal62, which was used as a control for a wild-type TERT promoter. In these cell lines, stable knocking down of specific ETS factors had a variable effect on TERT expression when compared with scrambled shRNA cells . To further study the effects of these factors in an extended panel of cell lines, we selected the aforementioned seven ETS proteins, along with EHF and ETS2, which showed marginally significant reductions in TERT expression, and GABPA, which had been reported in other cancer lineages. Interestingly, in our experiments, GABPA knockdown produced more variable results and did not consistently result in a reduction in TERT levels as previously described upon short-term disruption to GABPA expression.Taking the list of 20 ETS factors expressed in thyroid cell lines and tumors, we employed short-hairpin RNAs (shRNA) targeting each factor individually and generated knocked-down stable cell lines . InitialNA cells . We reasTERT expression in three additional cell lines: BHT101, BCPAP, and T238  and/or trametinib (MEK inhibitor), depending on their driver mutation (BRAFV600E or oncogenic RAS). To ensure accurate comparisons across cell lines with variable MAPK outputs, IC50 values for trametinib and dabrafenib were first determined, and each cell line was treated at its IC50 . The former prompted to the search for which ETS factors bind mutant TERT promoter as a first step towards exploring the idea of targeting TERT mutant transcription.The discovery of hotspot mutations in the TERT mutant promoter expression. Bell and colleagues sequentially knocked-down thirteen ETS transcription factors in two glioblastoma lines and showed that GABPA selectively reduces TERT transcription in the presence of the c.-124C > T mutation. They extended their observations to three other TPM-carrying tumor types: melanomas, hepatocellular, and urothelial carcinomas [TERT c.-146C>T) are bound by ETS factors ETS1/2, which cooperate with non-canonical NF-kB signaling via p52 to reactivate mutant TERT [TERT in glioblastoma and melanoma cells, but it does so, at least partially, via long-range chromatin interactions [TERT re-expression in glioblastoma, but its role in thyroid cancers remains uncertain. Several studies, typically using siRNA silencing, reporter assays, and ChIP approaches, on glioblastoma cells carrying TPMs demonstrated that the ETS factor GABPA controls rcinomas . This sarcinomas . Interesant TERT . They suTERT promoters in thyroid cancer was reported through ChIP assays on the K1 papillary thyroid carcinoma cell line [TERT mutant control. Our results show that GABPA stable silencing does not universally reduce TERT transcription in TERT-mutant thyroid cancer cells and that it also controls TERT wildtype promoter . In addition, GABP seems an unattractive target for inhibition in thyroid cancers due to its recently reported tumor suppressor role [In this regard, the capacity of GABPA to bind to mutant ell line . The autsor role . TERT mutant transcription, suggesting that no clear (GABPA-like) candidate exists in this lineage and that compensatory mechanisms across ETS proteins likely operate. Our work confirms some of the observations and further expands the findings reported by other thyroid cancer groups. Of note, Bullock and colleagues nicely showed that both ELK1 and ETV5 are able to bind TERT promoter in discrete thyroid cell lines and that they do so in cooperation with thyroid transcription factor FOXE1 [TERT in various thyroid cell lines carrying c.-124C>T mutation [TERT mutant control. We show that sustained knockdown of specific ETS over weeks, at most, moderately impacts TERT levels. This is a key difference from other studies, which assessed TERT knockdown transiently, not allowing for the likely compensatory mechanisms that other factors exert in our cells and probably in actual tumor specimens re-expressing telomerase. Our study shows that multiple ETS factors are able to control or FOXE1 ,18. A semutation . Taken tTERT promoter regulation that remains elusive is determining whether some of the reported non-canonical TPMs, which occur at very low frequencies (1–2% of cases) but also create de novo ETS sites, reactivate telomerase expression through the same mechanisms operating in TERT c.-124C>T or c.-146C>T specimens [TERT to a different degree, while others could be passenger alterations resulting from an overdetailed dissection of this particular genomic locus. In any case, once the mechanisms of hotspot TPM-mediated expression of TERT are identified, it would be advisable to study these other non-coding lesions.Another aspect of pecimens ,28. In tTERT transcription. We observed that, at low doses (low nanomolar range), MAPK inhibition was very effective at suppressing TERT mRNA levels in cells without TPMs but not in their TERT-mutant counterparts. Although we acknowledge the preliminary nature of this observation, our results point to a potential partial switch of TERT mutant regulation, which might have been missed by other works employing MAPK inhibitors in the micromolar range, which fully suppressed this pathway [TERT transcription is inherently difficult due to their roles in the absence of TPMs. This is because the TERT wildtype promoter has native ETS sites as well as binding motifs for Sp1 and c-Myc, both MAPK-activated factors that control TERT expression [TERT regulation. However, in the absence of unambiguous ETS proteins controlling TERT mutant expression, the TPM-specific role of MAPK input remains elusive.Our work also explored the role of a MAPK pathway blockade via pharmacological inhibition by dabrafenib and/or trametinib in  pathway ,18. Studpression ,21,22,23pression  or phosppression , which wTERT promoter has been shown to be subjected to other regulatory inputs, some of which might be modified by the presence of TPMs, whereas others likely operate as determinants of TERT baseline transcriptional repression. Although this is beyond the scope of this paper, the role of genomic insulator CTCF, which likely determines long-distance interactions [TERT transcription, which only becomes unchecked during cancer transformation. Incidentally, it is possible that some of the variability in ETS-binding is determined by specific co-factors and chromatin states that might respond to other signaling inputs. Other differences are likely attributable to the stable nature of the ETS silencing used here (vs. transient approaches in other studies), which likely allows cancer cells to enhance compensatory mechanisms. Overall, we believe that our observations, together with the remarkable efforts from other colleagues, have exhausted the possibilities of finding unequivocal, mutation-specific, ETS factors controlling TERT in thyroid cancers, and we caution against the generalization of discrete ETS findings from other tumor lineages. In the future, a less ETS-centric vision of TERT promoter control will be required to fully understand this process. In this regard, our ongoing research directions involve exploring ways of assessing the proteomic landscape of this genomic region in defined genetic states using isogenic models.Beyond the regulation by the ETS/MAPK axis, ractions  as well ractions ,32,33, aTERT mutant promoter in thyroid cancers likely differs from that reported in other tumors carrying TPMs in the same hotspots. Epigenetic targeting of mutant TERT transcription remains an attractive yet ambitious goal due to the high prevalence of TPMs in advanced tumors and the cancer-specific nature of this approach. However, we believe that the former will first require a detailed understanding of the transcriptional regulation of TERT mutant promoter specifically in thyroid specimens. To achieve this, a precise role of the mechanisms of compensation across different ETS factors, the integration with other inputs  and ultimately a factor-agnostic approach, ideally in cancer isogenic models, which assesses the epigenetic reconfiguration around TERT mutant promoter, will be required.In conclusion, our data suggest that the ETS-mediated regulation of


ZNF224 was originally identified as a transcriptional repressor of genes involved in energy metabolism, and it was demonstrated that ZNF224-mediated transcriptional repression needs the interaction of its KRAB repressor domain with the co-repressor KAP1 and its zinc finger domains 1–3 with the arginine methyltransferase PRMT5. Furthermore, the protein ZNF255 was identified as an alternative isoform of ZNF224 that possesses different domain compositions mediating distinctive functional interactions. Subsequent studies showed that ZNF224 is a multifunctional protein able to exert different transcriptional activities depending on the cell context and the variety of its molecular partners. Indeed, it has been shown that ZNF224 can act as a repressor, an activator and a cofactor for other DNA-binding transcription factors in different human cancers. Here, we provide a brief overview of the current knowledge on the multifaceted interactions of ZNF224 and the resulting different roles of this protein in various cellular contexts.The transcription factor ZNF224 is a Kruppel-like zinc finger protein that consists of 707 amino acids and contains 19 tandemly repeated C Genesn genome .2H2 zinc finger proteins possess other protein domains, such as BTB/POZ , SCAN  and KRAB (Kruppel-Associated Box) domains [During evolution, new species arose with differences in the amino acid sequences of the zinc finger motifs and in the spacing between them, as well as in the number of zinc finger domains and their structures. Consequently, these new members of the zinc finger family developed the ability to interact with DNA, RNA or proteins and in such a way defining new structures and functions ,5. Besid domains , which, 2-terminus of most C2H2 zinc finger proteins, shows very strong transcriptional inhibitory activity towards the target genes to which the KRAB-containing zinc finger proteins (KRAB-ZFPs) bind [Among these domains, the KRAB domain, located in the NHPs) bind ,8. The pPs) bind . CompariPs) bind ,8.By protein–protein interaction studies, the mechanism of transcriptional repression based on the interaction between the KRAB motif of KRAB-ZFP proteins and the KAP-1 corepressor was successively highlighted. This latter protein, indeed, was found to work as a hub capable of recruiting chromatin remodeling factors, stimulating heterochromatin formation and thus silencing the transcription of the target genes ,11 Figu.The KAP1/KRAB-ZFP interaction is also critical for the recruitment of KAP1 to transposable elements for their epigenetic silencing, thus preventing aberrant gene expression .The KAP1/KRAB interaction is an ancestral property of KRAB-ZFPs; however, the oldest members of this protein family show a weak ability to bind KAP1 due to the presence of an unusual and not well-conserved KRAB domain. Moreover, the heterogeneous affinity binding between KAP1 and the various KRAB-ZNPs and the presence of additional interacting proteins, responsible for post-translation modification, in the KAP1/KRAB-ZFPs complex contribute to affect KRAB-ZFPs’ subcellular distribution and their biological functions .Several KRAB-ZFPs display many physiological and pathological roles in the control of embryonic development, cell differentiation, cell proliferation, apoptosis, neoplastic transformation and cell cycle regulation . In addiDespite the enormous number of KRAB-ZFPs having been discovered so far, surprisingly, for a few of them, the corresponding gene targets have been revealed, the molecular mechanisms of their regulatory functions defined and, finally, the biological processes in which they are involved elucidated. Analysis of the gene expression of around 800 structurally different KRAB-ZFPs generated by 400 genes present in the human genome contributed to clarifying various aspects of the structure/function dichotomy concerning the KRAB-ZFP family, thus revealing, sometimes, a various and multifaceted landscape.During these years, a comparison of the KRAB-ZFP sequences revealed that they contain, on average, from 12 to 30 zinc finger domains that allow efficient binding to the canonical DNA-binding motif on the promoter region of their target genes ,18. It iMoreover, sequence analysis between homologous clusters from human chromosome 19 (HAS19q13.2) and mouse chromosome 7 (Mmu7) indicated that human KRAB-ZFPs displayed noticeable differences from their mouse counterparts in both the number of zinc finger domains and the sequences, thus allowing us to hypothesize that the divergence between the species might have resulted from a dramatic difference in DNA-binding properties . This fuIn this review, we focus on some properties of KRAB-ZFPs through the description of specific structural features and protein–protein interactions of one member of this protein family, ZNF224, and the relative resulting functional abilities of this multifaceted protein.ZNF224 is a ubiquitous and multifunctional human KRAB-ZFP involved in many different physiological and pathological pathways.In particular, the transcriptional repression exerted by ZNF224 on metabolic genes, such as aldolase A and mitochondrial citrate carrier (CIC), indicates its involvement in the regulation of metabolic pathways ,22. MoreDifferent molecular mechanisms are responsible for the oncogenic features of ZNF224. In bladder carcinogenesis, ZNF224, interacting with the transcriptional co-repressor DEPDC1, downregulates the expression of A20, a negative regulator of the NF-kB pathway , whereasIn chronic lymphocytic leukemia (CLL), ZNF224 acts as a direct transcriptional activator of the cyclin D3 gene, thus exerting an important role in cell growth and drug resistance .Finally, our recent findings highlighted the role of ZNF224 in melanoma cells through the enhancement of TGF-β pro-oncogenic function. ZNF224 stimulates the expression of TGF-β- regulated genes that are involved in epithelial–mesenchymal transition (EMT) and thus it promotes the proliferation and invasiveness of melanoma cells .ZNF224 protein is encoded by a gene mapped at locus 19q13.31, in one of the most extended gene clusters coding for KRAB-ZFPs, and no functional orthologue was revealed in the neighbor species, e.g., mice. Sequence comparison between the KRAB-ZFP human cluster contained in chromosome 19 and the homologous region included in the mouse chromosome 7 (Mmu 7) showed only partial similarity because 21 human genes exist that are strictly related to 10 mouse genes. This observation suggests that both clusters were generated from a common ancestral gene and that, through duplications and amplifications in the primate lineage and loss of the related members in the mouse lineage, new KRAB-ZFPs arose in humans while few survived in mice . In addiThe exon/intron organization of the ZNF224 gene derives from the comparison between the genomic sequences and the related mRNA sequence. The mRNA coding sequence originates by the fusion of exons IV, V and VI. The first three exons  define the 5′ UTR region of ZNF224 mRNA. Exon IV and exon V encode for the KRAB-A and KRAB-b box of the KRAB domain, respectively, while the remainder of the coding sequence of ZNF224 is encoded in the separate exon VI . This ex2 terminus, as it lacks the KRAB domain  and (+KTS) splicing variants of WT1 was carried out [On the contrary, ZNF224 interacts in the nucleus with the transcriptional (−KTS) isoform of WT1. Subsequently, employing chromatin immunoprecipitation experiments, luciferase reporter assays and siRNA knockdown of endogenous expression, we demonstrated that ZNF224 acts as a transcriptional co-regulator of WT1, cooperating in the fine-tuning of WT1 apoptotic target genes in chronic myelogenous leukemia (CML) cells and thus exerting a tumor-suppressive role in this hematological malignancy ,26.The specific isoform and subcellular compartment interaction between ZNF224 isoforms and (−KTS) and (+KTS) variants of WT1 emphasizes distinct functional roles for these protein complexes in the control of separate aspects of gene expression regulation.ZNF224 was originally described as a transcriptional repressor acting in combination with KAP1 (KRAB-associated protein 1 KAP1) , the uniMoreover, interesting published data, obtained through KAP1 genomic-wide analysis, identified, in addition to the transcription start sites of target genes, thousands of intragenic and 3′-noncoding regions of KRAB-ZFPs occupied by KAP1. It was demonstrated that the KRAB/KAP1 complex can silence promoters situated tens of kilobases from their DNA-binding site through the spread of silencing chromatin marks. These data support a model suggesting that KRAB/KAP1 interaction may be involved in mediating the long-range regulation of transcription through a highly dynamic distribution of epigenetic signaling on large regions of the genome ,53.Interestingly, KAP1 can interact with a variety of nucleosome remodeling complexes and other transcriptional modulators associated with the actively transcribed promoters .Bioinformatic analysis conducted to predict the genomic localization of the putative ZNF224 binding sites suggested that the distribution of the ZNF224 protein to the genomic region was very similar to that of KAP1. Therefore, we speculate that ZNF224 may be one of the KRAB-ZFPs responsible for the spatial distribution of KAP1 on DNA. Thus, ZNF224/KAP1 complex formation might result in local and/or long-range chromatin remodeling, establishing active or repressive chromatin marks.SUMO  and ubiquitin ligase activities that are associated with the ring domain [Besides the transcriptional control exerted through the assembly of the epigenetic machinery, KAP1 displays non-transcriptional functions that appear to be essential for the modulation of different biological processes. In particular, KAP1 shows E3 g domain  and diveg domain . For exag domain . In suchg domain ,59,60.Sequence-based prediction analysis of ubiquitination and SUMOylation sites using computational methods showed the presence of SUMO and ubiquitin consensus sequences in the ZNF224 protein, suggesting that ZNF224 might be a SUMO and/or ubiquitin target of KAP1 activity. Therefore, KAP1 could represent a pivotal cofactor able to modulate ZNF224 function through its SUMOylation and lead to ZNF224 detachment from target DNA following its ubiquitination and subsequent degradation.Furthermore, we previously demonstrated that the arginine methyltransferase PRMT5 is a component of the ZNF224 transcriptional repressor complex. Indeed, by immunoprecipitation assays using a series of ZNF224 3′-deletion mutants, we showed that ZNF224 directly interacts with PRMT5 through its ZNF domains 2 and 3. In addition, the ChIP experiment indicated that PRMT5 methylated the histone H4 (H4R3me2s) of nucleosomes surrounding the promoter region of ZNF224 target genes, thus acting as a key mediator of the ZNF224-mediated transcriptional repression . ProteinRecently, the involvement of ZNF224 in cell cycle progression and proliferation has been shown in CLL (31), where the expression of PRMT5 is upregulated . In breaFurthermore, the characterization of the structural and functional properties of the ZNF224 transcriptional complex allowed us to show that KAP1 is a novel target of PRMT5 enzymatic activity that is known to regulate protein–protein interaction. In detail, co-immunoprecipitation experiments demonstrated that KAP1 interacts with PRMT5. The subsequent in vitro and in vivo methylation assays showed that KAP1 is symmetrically dimethylated by PRMT5. Furthermore, we observed that the KAP1 methylation by PRMT5 triggers the impairment of the ZNF224/KAP1 interaction. This modification is probably involved in the ZNF224 switch from a transcriptional repressor to a transcriptional activator  Figure .ZNF224 in concert with KAP1 and PRMT5 could also participate in the imbalance between proliferation and apoptosis to stimulate uncontrolled cell growth, even through a transcription-independent molecular mechanism regulating the activity and stability of cell cycle control factors. Therefore, ZNF224, as already described for other KRAB-ZFPs , besidesCollectively, the above-described data lead us to speculate that ZNF224 activity and the consequent expression of its target genes, in different physiological and pathological contexts, could be primarily regulated via the complex interplay of interactions between ZNF224, KAP1 and PRMT5.Moreover, it would be useful to clarify the crosstalk between the various post-transcriptional modifications that may affect these proteins and the effect on the dynamics of the protein–protein interaction in the ZNF224 complex, to better understand the functional implication in different biological events.In recent years, several experimental data have highlighted the involvement of ZNF224 in multiple pathways associated with cell survival, cellular proliferation and tumorigenesis through the interaction with numerous and different protein partners. In particular, the DEPDC1/ZNF224 protein complex plays a critical role in bladder carcinogenesis, promoting cell proliferation and suppressing apoptosis . The DEPThe NF-κB pathway is aberrantly activated in several solid and hematological malignancies , and difThe oncogenic role of the DEPDC1/ZNF224 complex through the activation of the NF-κB signaling pathway was also demonstrated in the human hepatoma cell line HepG2 .Finally, ZNF224 has been shown to work in the DNA damage response by interacting with MED28, a component of the Mediator complex, a large protein complex involved in the regulation of transcription mediated by RNA polymerase II . This prRecently, in human melanoma cell lines, we demonstrated the involvement of ZNF224 in the TGF-β pathway, whose activation is a critical event in promoting tumor progression and invasion through the induction of the EMT process . ZNF224 The KRAB-ZFP protein family represents one of the largest groups of transcription factors that recently arose in vertebrates throughout evolution by gene duplications and amplifications. New KRAB-ZFPs originated in higher and more evolutionarily developed species, in which they unquestionably contributed to providing new functions. Structural and functional studies will allow the elucidation of many aspects that still remain to be explored. Comparative analysis of protein domains of different members of the KRAB-ZFP family will further shed light on the roles and mechanisms in which they are involved.ZNF224 is a protein model providing numerous and interesting pieces of evidence that could be useful to integrate data from other laboratories and to define the mechanisms and pathways implied in the control of proliferation, differentiation, cancer and metabolism. We have learned, in these last few years, a great deal about the function of ZNF224 and other KRAB-ZFPs in the transcriptional regulation of target genes, but we still have much more to understand about their role in regulating cellular processes in normal and tumor cells.ZNF224 has been firstly found to work as a transcription factor, displaying transcriptional repression ability towards genes encoding for metabolic enzymes, such as the human aldolase A and the mitochondrial citrate carrier, which allowed the analysis at a molecular level of the repressor complex in a physiological setting. Recruitment of chromatin-remodeling factors to stimulate heterochromatin formation and thus silence transcription of the target genes indeed requires a specific interaction with the KAP1 co-repressor. To strengthen the ability to repress transcription, in addition, the ZNF224/KAP1 complex takes advantage of the supplemental binding of the arginine methyltransferase PRMT5; the methylating arginine 3 of histone H4 on nucleosomes surrounding the promoter region of ZNF224 target genes induces chromatin modifications required for ZNF224 repression activity.miR-663 and cyclin D genes, respectively.ZNF224 also behaves as a transcriptional activator in different cellular contexts, such as breast cancer and CLL, where it induces cell growth and apoptosis resistance through the transcriptional activation of Recognizing and binding to WT1, ZNF224 displays the peculiar activity of a transcriptional co-regulator involved in the modulation of WT1 apoptotic target genes in CML cells. Finally, DEPDC1 and MED28 interact with ZNF224 in bladder and breast cancer cells, respectively, and elicit two different pathways involved in the promotion and progression of tumors in two distinctive cellular milieus. Such differential behavior appears to be dependent on the ZNF224 interactome. The interaction with different protein partners may govern the cell-type-specific activities of ZNF224.In this scenario, it is quite evident that the identification of novel protein partners of ZNF224 might lead to the complete knowledge of how ZNF224 can be regulated and to the discovery of new functions for this protein in proliferation, differentiation, cancer and metabolism. To this aim, we will use high-throughput approaches, such as Affinity Purification coupled to Mass Spectrometry (AP-MS), for the identification of protein–protein interactions involving ZNF224, and/or Chromatin-Interacting Protein Mass Spectrometry (ChIP-MS) to identify protein complexes recruited by ZNF224 on its different target genes. These studies, performed in the cancer cell lines where ZNF224 differently affects tumor progression, will allow us to characterize the various ZNF224 interaction networks, useful to fully define the multiple signaling pathways in which ZNF224 is involvedFuture findings will pave the way to the development of new therapeutic strategies based on molecules capable of selectively inhibiting these protein–protein interactions and consequently modulating ZNF224 transcriptional activity. Finally, the ultimate goal consists in identifying agents, able to modulate ZNF224 activity, with strong therapeutical potential to be used alone or in combination with conventional chemotherapy for the treatment of metabolic and degenerative pathologies.


This study shows that YY1 regulates hepatic lipid metabolism by directly or indirectly regulating the expression of several key upstream transcription factors and their coactivators. YY1 plays a pivotal role in many liver diseases. To obtain a detailed view of genes and pathways regulated by YY1 in the liver, we carried out RNA sequencing in HepG2 cells after YY1 knockdown. A rigid set of 2,081 differentially expressed genes was identified by comparing the YY1-knockdown samples (n = 8) with the control samples (n = 14). YY1 knockdown significantly decreased the expression of several key transcription factors and their coactivators in lipid metabolism. This is illustrated by YY1 regulating PPARA expression through binding to its promoter and enhancer regions. Our study further suggest that down-regulation of the key transcription factors together with YY1 knockdown significantly decreased the cooperation between YY1 and these transcription factors at various regulatory regions, which are important in regulating the expression of genes in hepatic lipid metabolism. This was supported by the finding that the expression of SCD and ELOVL6, encoding key enzymes in lipogenesis, were regulated by the cooperation between YY1 and PPARA/RXRA complex over their promoters.Recent studies suggested that dysregulated  Liver is one of the most important metabolic organs of the human body. Liver diseases arising from various etiologies account for ∼2 million deaths per year worldwide, mostly due to complications of cirrhosis, viral hepatitis, and hepatocellular carcinoma (HCC) . Over thYY1 is overexpressed in many forms of carcinomas including HCC, the expression of which was commonly correlated with advanced malignancy or poor clinical outcomes (YY1 in various liver diseases.Yin Yang 1 (YY1) is a ubiquitous and multifunctional zinc-finger transcription factor (TF) that can activate or repress gene expression, depending on the cellular context . A largeoutcomes . In addioutcomes . YY1 hasoutcomes . This maYY1 is involved in the pathogenesis of NAFLD  of these samples revealed a rigid set of genes and pathways regulated by YY1. The genes up-regulated by YY1 knockdown were tightly associated with perturbed promoter and enhancer interactions mediated by YY1, whereas the genes down-regulated by YY1 knockdown were significantly enriched in various biological processes in lipid metabolism  accumulation in the cytoplasm of hepatocytes that is caused by the imbalance between lipid acquisition and removal in the liver . As the of NAFLD . The expt stages . By utilt stages . These stabolism . Our stuYY1 expression in the liver cancer cell line HepG2 employing both lentiviral-mediated shRNA and artificial miRNA (amiRNA). The expression of YY1 was significantly down-regulated by YY1 knockdown determined by quantitative reverse transcription polymerase chain reaction (RT-qPCR) assay  and four batches of samples transduced with the control virus (n = 14) cultured under the same condition were subjected to RNA-seq. By targeted sequencing of the 3′ end of polyadenylated RNA, we obtained an average of 7.2 million reads per sample (range from 5.5 to 8.4). An average of 5.7% of the reads (range from 3.0 to 9.1%) were filtered out by quality trimming. The remaining reads which were properly paired were mapped to the reference human genome (UCSC version hg19). We obtained an average mapping rate of 88.5% (range from 85.0 to 90.7%) for paired reads that are uniquely mapped and an average mapping rate of 9.8% (range from 7.4 to 12.9%) for paired reads that are mapped concordantly more than once (Table S1). The uniquely mapped reads were further mapped to known genes with an average mapping rate of 77.9% (range from 76.0 to 79.8%) by featureCounts  assay . The effern blot . We nextreCounts .Summary statistics of RNA-seq data in this study.Table S1 2 fold change of 0.7 and P-value of < 0.001 (corresponding to Padj < 0.003) to identify a consensus of DEGs. A total of 2,273 DEGs composed of 1,348 up-regulated genes and 925 down-regulated genes were identified based on Ensembl gene annotations  and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis . The up-To validate the identified enrichment of GO terms and KEGG pathways in the DEGs, we further carried out gene set enrichment analysis (GSEA) with the C2 gene sets from the Molecular Signature Database (MSigDB) as input . Accordin = 8; independent from the samples used in RNA-seq) as templates to validate the identified DEGs in lipid metabolism. A total of 31 DEGs encoding important enzymes or proteins in abovementioned biological processes in lipid metabolism were selected for RT-qPCR validation. We observed that except for CPT1A, all the other 30 DEGs showed similar degree of down-regulation in RT-qPCR in comparison with the RNA-seq data , PGC1B, NR coactivator 1 (NCOA1), NCOA2, and NCOA3 were significantly down-regulated by YY1 knockdown , which encoding SREBP1. The expression changes of SREBF1 together with CHREBP and its heterodimeric partner MAX dimerization protein (MLX) were then verified by RT-qPCR which confirmed that only CHREBP was significantly down-regulated  HNF4A, forkhead box A1 (FOXA1), and forkhead box A2 (FOXA2) are important transcription regulators of both liver organ development and liver metabolism . FOXA1 w RNA-seq . RT-qPCRnockdown .The presence of YY1 binding nearby the DEGs can be indicative of a direct regulatory role of YY1 in regulating the DEGs expression. To achieve better understanding of the molecular mechanisms regulating the transcriptional alternations induced by YY1 knockdown, we obtained YY1 chromatin immunoprecipitation coupled with massively parallel sequencing (ChIP-seq) data in HepG2 cells and liver tissues from the ENCODE project . In accoTo find the causal TFs that are enriched over the DEGs with or without YY1 bound nearby, we further performed enrichment analysis against the ChIP-X enrichment analysis (ChEA) gene set library with the Enrichr webtool . The resPPARA and RXRA together with several of their coactivators including PGC1A, PGC1B, and NCOA1/2/3 were significantly down-regulated by YY1 knockdown  . The expnockdown . This sunockdown .PPARA was down-regulated by YY1 knockdown. In both HepG2 cells and liver tissues, we found multiple YY1 ChIP-seq peaks at the promoter (defined as P) and upstream enhancer regions (defined as E1–E4) of PPARA  and polyunsaturated FAs synthesis . First, except for ELOVL5, all the other six genes were significantly down-regulated by YY1 knockdown validated by both RT-qPCR and Western blot analysis  showed significant response to PPARA overexpression in luciferase assay  were significantly induced by the co-overexpression of YY1 and PPARA compared with overexpression of only YY1 or PPARA  to EZH1  in RNA-seq.In this study, the expression of ilencing . Interesilencing . YY1 hasilencing . The disilencing . This isilencing . As key ilencing . Even thYY1 has been reported to lead to dysregulated cellular metabolism including glycometabolism, lipid metabolism, and bile acid metabolism in the liver, which is believed to be one of the underlying mechanisms of how YY1 is involved in various liver diseases  were plated in 12-well plate 24-h before harvesting with TRIzol reagent . Total RNA was isolated from TRIzol reagent with the PureLink RNA Mini Kit  following the manufacturer’s instructions. The optional on-column PureLink DNase  treatment was carried out to get rid of trace amount of genomic DNA during RNA extraction. The quality of the extracted total RNA was evaluated using the Agilent 2200 TapeStation system. The library was constructed with QuantSeq 3′ mRNA-Seq Library Prep Kit REV for Illumina  following the protocol from the manufacture. The library was sequenced on an Illumina HiSeq 2500 sequencer (pair-end with 100 bp) in Macrogen. All the sequence data have been deposited in NCBI’s Gene Expression Omnibus (GEO) and accessible through GEO Series accession number GSE158884.Equal number of cells (∼8 × 10https://www.bioinformatics.babraham.ac.uk/projects/fastqc/), adapter sequences and poly(A) tail sequences were removed using Trim Galore . Reads were mapped to the human hg19 genome with HISAT2 version 2.1.0 using –score-min L,0,-0.8 –no-unal parameters  followed by total RNA extraction with the PureLink RNA Mini Kit  as described in RNA-seq library preparation. A total of 1 μg total RNA was reverse transcribed into cDNA with Maxima First Strand cDNA synthesis kit (Thermo Fisher Scientific). The qPCR reactions were performed with JumpStart Taq ReadyMix (Sigma-Aldrich) coupled with EvaGreen dye (Biotium). The expression was normalized to two control transcripts Primers used for gene quantification in RT-qPCR.Table S4 GSE96514), a 32-yr-old male (GEO: GSE96146) and HepG2 cells (GEO: GSM803381). The reads distribution of the ChIP-seq libraries over genes was visualized by deeptools version 3.1.3 (https://amp.pharm.mssm.edu/Enrichr/).YY1 ChIP-seq experiments performed in liver tissue or liver-originated HepG2 cells were collected from the ENCODE project . The daton 3.1.3 . The genon 3.1.3 . The binP-values for the neighboring and overlapping TF pairs were calculated using the hypergeometric distribution.We downloaded the full collection of TFs ChIP-seq and DNase-seq from ENCODE for HepG2 cells (Table S5). TFs represented by more than one experiment were combined by merging the overlapping TFs binding sites to avoid artifacts of overestimation of TFs co-occurrences. Next, we ran tfNet to detect a collection of putative regulatory regions and TF interactions in HepG2 cells . We clusSummary of NGS data in HepG2 cells from the ENCODE project that are used in tfNet analysis.Table S5 PPARA in human 293T cells as the positive control. Equal number of 293T cells (∼8 × 105) were plated in six-well plate and transfected with 2 µg of pCDNA3.1-PPARA 24 h after plating using polyethylenimine (Polysciences) following the manufacturer’s instructions. The cells were harvested 48 h posttransfection with RIPA buffer . The nontreated human 293T cells were also harvested and used as the control in the following Western blot analysis.To determine the in-vivo expression of PPARA, we overexpressed 5) were plated in 12-well plate 48-h before harvesting with RIPA buffer . The concentration of each protein extraction was quantified with Qubit protein assay kit . Western blotting analysis of protein extracts was performed as previously described , PPARA antibody SC-398394 (Santa Cruz Biotechnology), and RXRA antibody SC-553 (Santa Cruz Biotechnology) were used in this study. For each ChIP experiment, the same amount (8 µg) of normal rabbit IgG antibody  was also incubated with sonicated chromatin from the same number of cells to check the background of antibody nonspecific binding. Each experiment was replicated three times. The results are expressed as the relative enrichment of target DNA fragments immunoprecipitated by different TFs above fragment-specific background (IgG). The occupancy level of TFs normalized with IgG in the region GDCHR12 was used as the negative control as previous described . The resulting plasmids pCDNA3.1-YY1 and pCDNA3.1-PPARA were verified by Sanger sequencing.The coding sequence of human FADS1 which was constructed by T4 DNA ligation (New England Biolabs). Putative enhancer regions were inserted into pGL4.23 (Promega) digested with KpnI and EcoRV through In-fusion cloning system (Takara). A three fragments In-fusion cloning system with mutations introduced through primer sequences was used to introduce desired mutations into luciferase constructs. The detailed primer information and cloning method for each construct is listed in Table S8. All the resulting plasmids were verified by Sanger sequencing.To test the promoter activities, the putative promoter regions were inserted into pGL4.10 (Promega) digested with KpnI and EcoRV through In-fusion cloning system (Takara), except for the promoter region of Luciferase plasmids constructed in this study.Table S8 Luciferase plasmids were purified with GenElute Plasmid Miniprep Kit (Sigma-Aldrich) and quantified by NanoDrop 2000 (Thermo Fisher Scientific). HepG2 cells were plated 1 d before transfection in 96-well plates. The confluency was 70% on transfection. For normal luciferase assay, each well was transfected with 0.3 μl XtremeGENE HP DNA transfection reagent (Roche) and 100 ng of experimental firefly luciferase reporter plasmid, and 1 ng of pGL4.74 renilla luciferase reporter vector (Promega) as internal control for monitoring transfection and lysis efficiency. For luciferase assay overexpressing YY1, each well was transfected with 0.3 μl XtremeGENE HP DNA transfection reagent, 50 ng of firefly luciferase reporter plasmid, 50 ng pCDNA3.1-YY1, and 1 ng of pGL4.74. For luciferase assay overexpressing PPARA, each well was transfected with 0.3 μl XtremeGENE HP DNA transfection reagent, 40 ng of firefly luciferase reporter plasmid, 50 ng pCDNA3.1-PPARA, and 10 ng of pRL-MP described earlier . For expt tests.Cells were harvested 24 h after transfection and assayed with the Dual-Luciferase Reporter Assay System (Promega) on an Infinite M200 pro reader (Tecan). All the results are expressed directly as the ratio of firefly luciferase activity from experiment plasmids to renilla luciferase activity from control plasmids. All the luciferase experiments came from two independent transfections, that is, independent plasmid preparations and transfections each with three technical replicates. Luciferase values are expressed as averages with error bars representing SDs from all technical replicates and statistical analyses were performed by two-tailed GSE158884. The lentiviral plasmid pBMN-AS-YY1 used for YY1 knockdown in this study is deposited to Addgene (plasmid # 154943). The expression plasmids pCDNA3.1-YY1 and pCDNA3.1-PPARA have also been deposited to Addgene and assigned the identifier number 169018 and 169019, respectively.Transcriptome data from this study are available at GEO under accession number