Cdk1/2/4 inhibitors. Following cell cycle exit, CEBPE unleashes the CEBPA-primed differentiation program to generate mature granulocytes. These findings highlight how tissue-specific transcription factors coordinate cell cycle exit with differentiation through the use of distinct gene regulatory elements.Differentiation of multipotent stem cells into mature cells is fundamental for development and homeostasis of mammalian tissues, and requires the coordinated induction of lineage-specific transcriptional programs and cell cycle withdrawal. To understand the underlying regulatory mechanisms of this fundamental process, we investigated how the tissue-specific transcription factors, CEBPA and CEBPE, coordinate cell cycle exit and lineage-specification in vivo during granulocytic differentiation. We demonstrate that CEBPA promotes lineage-specification by launching an enhancer-primed differentiation program and direct activation of CEBPE expression. Subsequently, CEBPE confers promoter-driven cell cycle exit by sequential repression of MYC target gene expression at the G1/S transition and E2F-meditated G2/M gene expression, as well as by the up-regulation of  Here the authors show that differentiation of haematopoietic stem cells into mature blood cells is primed by cell type-specific transcription factors at the enhancer level during early differentiation, before they confere promoter-driven growth arrest, and activate post-mitotic terminal differentiation. This temporal coupling of lineage-commitment, cell cycle exit, and terminal differentiation is fundamental for the lifelong maintenance of tissue homeostasis. Consistently, genetic aberrations of key regulators of differentiation programs can lead to disease, including cancer9. Hence in the context of disease, it is essential to understand how key transcriptional regulators coordinate proliferation and differentiation during normal organ and tissue development.The maintenance of mammalian tissues and organs is sustained by stem cells and their progeny which gradually change their transcriptional programs as they transit along their differentiation trajectory and restrict their lineage potential before entering a postmitotic state, and ultimately become fully mature tissue-specific cells12. Hence the backbone of the regulatory machinery controlling cell cycle progression is formed by CDK4/6–cyclin D driven de-repression of E2F target genes by mitogenic stimuli in the early G1 phase and subsequent E2F-mediated upregulation of CDK2–cyclin E and CDK1-cyclin A/B expression in G1/S and G2/M phases, respectively13. Cell cycle exit and persistent postmitotic growth arrest during the course of tissue and organ development are controlled by mechanisms inhibiting the activities of cell cycle master regulators. These include transcription factors (TFs), which concomitantly upregulate differentiation genes and inhibitors of CDKs, leading to CDK–cyclin inhibition and sustained RB repression of E2F-mediated cell cycle gene expression15. Moreover, direct inhibition of E2F and repression of cyclin expression by TFs have been reported as a regulatory mechanism blocking E2F-mediated gene expression and proliferation18. However, the exact temporal sequence and combination of regulatory mechanisms launched by TFs to coordinate cell cycle exit and differentiation are currently poorly understood3.In actively proliferating cells, cyclin-dependent kinases (CDK) and their cognate-activating cyclin partners are master regulators of the cell cycle machinery, which coordinate the transition from one cell cycle phase to the next. Mitogenic stimuli such as growth-promoting factors upregulate Cyclin D leading to activation of CDK4/6 during the early G1 phase which in turn phosphorylates RB in complex with E2F, conferring its release from E2F and transcription of E2F cell cycle target genes such as cyclin E/A/B, CDK2, CDK1, and MYC19. Simplified, this process can be categorized into two functionally distinct phases; (i) an early phase of lineage-specification that is characterized by cellular proliferation and differentiation of HSCs via multipotent progenitors (MPPs), bipotent pre-granulocyte macrophage, and granulocyte-macrophage progenitors (preGMs and GMPs) toward progenitors restricted to the granulocytic lineage (GPs), and (ii) a terminal phase of differentiation which is characterized by growth arrest and acquisition of a highly specific cell identity while cells differentiate via a series of intermediary stages into fully mature GRs24.Hematopoiesis represents a paradigm of mammalian differentiation and tissue homeostasis where multipotent tissue-specific hematopoietic stem cells (HSCs) either self-renew to maintain the stem cell pool or differentiate to sustain lifelong production of all mature blood cell lineages. Among these, polymorphonuclear neutrophilic granulocytes (in the following referred to as GR) are short-lived effector cells (1–2 days) of the innate immune system that are continuously replenished by HSCs in the bone marrow (BM) through a process referred to as granulocytic differentiation26. CEBPA has emerged as a key regulator of myeloid lineage-specification and granulocytic differentiation and is expressed in HSCs as well as in myeloid-committed hematopoietic progenitor cells (HPCs) such as preGMs, GMPs, and their lineage-restricted granulocytic progeny27. Mice with conditional disruption of Cebpa in the hematopoietic system, exhibit a block at the preGM to GMP transition. As a result, these mice accumulate preGMs in their BM and lack GMPs as well as their mature progeny, similar to what is observed in humans with acute myeloid leukemia (AML)28. In contrast, CEBPE is expressed during terminal granulocytic differentiation30. Consistently, mice with a targeted disruption of Cebpe as well as patients suffering from specific granule deficiency (SGD) due to mutations of the CEBPE gene fail to produce mature GRs but rather exhibit an expansion of progenitors restricted to the granulocytic lineage32.Recent mechanistic and genetic studies by our group and others have demonstrated that members of the CCAAT/enhancer-binding protein (CEBP) family of transcription factors, namely CEBPA and CEBPE, are indispensable for normal granulocytic differentiation35. Besides acting as a transcriptional activator, CEBPA has been demonstrated to bind to E2F in vitro and in vivo via its basic region, and repress E2F-mediated transcription of target genes such as Myc17. In alignment with CEBPA, CEBPE has also been shown to bind E2F during granulocytic differentiation of myeloid cell lines and repress E2F-mediated transcription in luciferase reporter assays36.Consistent with their expression during granulocytic differentiation, mechanistic studies have demonstrated that CEBPA and CEBPE can transactivate several myeloid- and GR-specific genes, including a number of early and late-appearing granule proteins and hematopoietic growth factor receptors critical for proliferation and specification of cell identity during granulocytic differentiationTaken together, these studies have identified CEBPA and CEBPE as key regulators of cellular proliferation and activators of lineage-specific gene transcription during hematopoietic differentiation along the granulocytic pathway. However, despite their substantial functional redundancy, little is known of how CEBPA and CEBPE actually coordinate their mutual activities in a temporal manner to promote granulocytic differentiation during steady-state hematopoiesis in vivo.In this work, we applied a systematic approach to uncover how designated key transcriptional regulators  orchestrate sequential lineage-specification, cell cycle exit, and terminal differentiation at the promoter and enhancer level during hematopoietic differentiation. For this, we implemented a hierarchy of fifteen immunophenotypically defined differentiation stages, which refined the granulocytic and monocytic (GM) differentiation hierarchies at a hitherto unprecedented resolution and subjected this hierarchy to global mRNA and chromatin immunoprecipitation sequencing (RNA-seq and ChIP-seq) analyses. Here, we demonstrate an almost exclusive sequential expression of CEBPA and CEBPE during early and late granulocytic differentiation, respectively. Strikingly, our study further demonstrates that CEBPA promotes lineage-specification by direct activation of CEBPE expression and transient priming of differentiation genes at enhancers. Subsequently, CEBPE takes over and coordinates promoter-driven repression of cell cycle activators with enhancer-driven activation of a plethora of differentiation genes defining the cell identity of fully mature GR.37. Through combinatorial flow cytometry-based immunophenotyping, assessment of cellular morphology by microscopy, and cell cycle analyses, we further developed a protocol for analysis and purification of murine BM populations representing successive stages of late granulocytic and monocytic differentiation , as well as bipotent myeloid preGMs and GMPs, were purified as reported previously Fig. 37. Throuion Fig. . With thion Fig. , which a38. As shown in Supplementary Fig. 24.In order to assess the gradual changes of gene expression as HSCs commit to bipotent GMPs and further differentiate into fully mature GRs and MOs, we conducted RNA-seq analyses on fifteen prospectively purified BM populations representing successive immunophenotypic stages of our branching granulocytic and monocytic differentiation hierarchy  including a narrow developmental window of co-expression in PMs during granulocytic differentiation .We next assessed the expression patterns of the designated key regulators of granulocytic differentiation, CEBPA and CEBPE, as well as G1/S and G2/M phase cell cycle genes and a series of primary, secondary, and tertiary granule proteins known to be expressed sequentially during granulocytic differentiation Fig. . Strikinion Fig.  ) before subsequent downregulation of G2/M genes at the MY2 to MM transition when cells exit the cell cycle (cluster B(MY)) Fig. . As expeCebpe KO mice revealed aberrant high expression of early granulocytic differentiation, cell cycle (cluster A (GMP) + B (MY)), and monocytic differentiation genes (cluster D (GR + MO) + E (MO)). In contrast, a large number of genes expressed during late granulocytic differentiation (cluster C (GR)) were markedly downregulated in Cebpe KO mice  was still 2.5- to 4.0-fold lower compared to the expression of CEBPE in Cebpe WT MY1s +MY2s and MMs . The latter suggests that cell cycle exit and granulocytic differentiation are partially regulated in a dose-dependent manner by CEBPs. Consistently, transduction of KIT + Cebpe WT and KO BM cells with retroviral vectors expressing CEBPA-WT-ERTM and CEBPE-WT-ERTM, demonstrated that 4-HT induction of CEBPA and CEBPE activity promoted terminal granulocytic differentiation at comparable levels . In contrast, only CEBPA induced monocytic differentiation of KIT + Cebpe WT and KO BM cells   toward lineage-restricted progenitors  and expression of early granulocytic differentiation genes . In contrast, Cebpe/CEBPE expression is indispensable for sequential downregulation of G1/S and G2/M phase genes  when cells exit the cell cycle, and for the upregulation of a substantial number of granulocytic differentiation genes as differentiation progresses and cells become fully mature GRs. Collectively, these findings suggest that CEBPE-dependent cell cycle exit is a prerequisite to complete terminal granulocytic differentiation in vivo.Overall, these findings demonstrate that Cebpe WT and Cebpe KO and measured CEBPE binding by ChIP-seq at proximal  and distal  cis-regulatory elements (CREs) of the genes from each of the five clusters in MY1s + MY2s. For simplicity, measurement of CEBPE ChIP-seq binding in MMs, BCs, and GRs were not included in this analysis since more than 90% of CEBPE binding sites in these populations were also bound by CEBPE in MY1s + MY2s (See below). Strikingly, CEBPE bound and regulated expression of genes  expressed during early differentiation at the promoter level (cluster A(GMP) and cluster B(MY), Fig. To explore how CEBPE coordinates the regulation of gene expression with other TFs during granulocytic differentiation, we assessed differentially expressed genes in Cebpe WT, but not in Cebpe KO mice, exhibited enrichment of E2F binding motifs at their promoters , Fig. CEBPE-ERTM cell line)41 confirmed that CEBPE directly bound to E2F complexes, repressed E2F-mediated gene expression in a dose-dependent manner and promoted growth arrest and granulocytic differentiation  and B(MY)) which were downregulated during cell cycle exit in ers Fig. . Strikiners Fig. . In lineCebpe KO mice  and D(GR + MO)) and downregulated in Overall, these findings demonstrate that regulation of differentiation is predominantly controlled at the enhancer level, while cell cycle exit is predominantly regulated at the promoter level, partially through repression of E2F-mediated transcription of key cell cycle regulators.Cebpe/CEBPE at the PM to MY1 transition were enriched for MYC binding at their promoters, pointing towards a direct or indirect regulation of MYC-dependent G1/S phase genes by CEBPE  at the PM to MY1 transition, which in absence of MYC, might lead to the formation of repressive MAD/MAX dimers (instead of activating MYC/MAX dimers) and direct repression of MYC target gene expression  and B(MY) gene clusters, of which the former is enriched for the G1/S phase genes and later for the G2/M phase genes Fig. . TF motiBPE Fig. . The latnd2 Fig. . Myc is Y2s Fig.  when MycMad expression at the PM to MY1 transition which ultimately initiates cell cycle exit by downregulation of MYC-regulated G1/S target genes.Taken together, these findings suggest that CEBPE represses E2F-mediated MYC expression and upregulates Cdkn2d (p19 INK4D) and Cdkn1b (p27 Kip1) at the PM to MY1 transition (cluster B(MY)) ) Fig. .Cebpe KO mice at the MM stage ) concomitant with the completion of cell cycle exit. CEBPE ChIP analyses of G2/M gene promoters demonstrated frequent CEBPE binding at E2F binding sites in the absence of CEBPE motifs Fig. , which page Fig.  and the age Fig. .43, and are upregulated in G2/M phase by activating E2F1-3 in combination with NFY11. Consistently, our TF motif analyses identified sites for E2F, NFYB, and LIN54 at bona fide G2/M gene promoters  based on all combinations of direct CEBPE binding and known E2F1, NFY, and LIN54 TF binding sites at their promoters. We next examined the impact of CEBPE on promoter class activity by assessment of gene expression changes in Cebpe KO vs. Cebpe WT  if their promoters exhibited binding/binding sites for all four TFs  sitesers Fig. . While bxit Fig. . CEBPE bxit Fig.  suggesti WT Fig. . Notablyice Fig. . These fice Fig. . Importaice Fig.  as compaice Fig. . Gene onice Fig. . These rnes Fig. .Fig. 5CEGadd45a at the MY2 to MM transition (cluster C (GR)) ) Fig. .Cebpa/CEBPA and Cebpe/CEBPE expression would dictate the CEBPA and CEBPE binding dynamics at their CREs. For this, we combined our previously generated CEBPA ChIP-seq analyses with the newly generated CEBPE ChIP-seq analyses of BM populations exhibiting expression of Cebpa/CEBPA and Cebpe/CEBPE , Fig. Genes exclusively upregulated during late monocytic differentiation concomitant with sustained Cebpe WT MY1s + MY2s and MMs revealed a clear loss of CEBPA binding at CREs concomitant with decreased Cebpa/CEBPA expression in these populations , Fig. ce Figs. c, 7a, anice Fig. .Fig. 7CECEBPE-ERTM cell line, which differentiates in response to 4-hydroxy-tamoxifen (4-HT) induced translocation of CEBPE-ERTM to the nucleus. We identified three putative promoter-regulated genes  and one promoter-/enhancer-regulated gene (Dhrs7) that were upregulated after 2 or 4 days of 4-HT induced CEBPE differentiation and whose expression were substantially reduced by CRISPR interference (CRISPRi) of their CEBPE-bound promoter  and enhancer (Dhrs7) sites , resulting in high levels of Cebpe/CEBPE expression  as compared to four, five, and six developmental stages reported for recent comprehensive sorting protocols and a recent scRNA-seq study  orchestrate cycle exit and specification of cell identity at the promoter and enhancer levels during differentiation in vivo.49. Consistently, studies of muscle development in Caenorhabditis elegans have demonstrated that muscle-specific TFs recruit SWI/SNF leading to chromatin remodeling and ultimately sequential cell cycle exit and activation of a muscle-specific differentiation program50. In this context, our findings support a model where TFs, indispensable for tissue-specific development, direct somatic stem/progenitor cells toward lineage-specific progenitors exhibiting a full enhancer-primed differentiation program predestined for postmitotic activation and completion of differentiation. Such a model is supported by embryonic stem cell studies, demonstrating that sequential binding of TFs to tissue-specific enhancers establishes an early tissue-specific chromatin state before they actually launch a full transcriptional differentiation program and differentiate into the various types of tissue-specific cells53.Intriguingly, CEBPA and CEBPE were expressed in an almost exclusive sequential manner and preferentially bound to enhancers of target genes exhibiting CEBP binding motifs during early and late differentiation, respectively. Notably, shared CEBPA and CEBPE target genes defined a core set of GR-specific genes  which were not expressed upon CEBPA binding during early differentiation, but almost exclusively upregulated by CEBPE during terminal postmitotic differentiation. Notably, enhancers of these GR-specific genes were primed  concomitant with CEBPA binding during early differentiation  and activated  concomitant with CEBPE binding during late granulocytic differentiation  Fig. . Given tCebpa/CEBPA expression and onset of Cebpe/CEBPE expression at the PM to MY1 transition, suggesting that this step is crucial for the initiation of terminal granulocytic differentiation. Consistent with previous in vitro studies demonstrating the binding of CEBPs to E2F36, our in vivo ChIP-seq analyses revealed significant overlapping of CEBPE binding at bona fide E2F promoter binding sites without the presence of CEBP binding motifs. Complementary functional analyses revealed upregulation of several identified CEBPE/E2F target genes in Cebpe KO mice, CEBPE binding to E2F, and CEBPE-driven repression of E2F-mediated transcription in reporter assays. Together, these findings strongly suggest that CEPBE regulates cell cycle exit at the promoter level during in vivo granulocytic differentiation through interaction with E2F and repression of E2F-mediated transcription.In contrast to differentiation genes, cell cycle genes were predominantly regulated at the promoter level during a narrow developmental window at the intersection of early vs. late granulocytic differentiation. The high resolution of our differentiation hierarchy demonstrated an abrupt termination of Cdk4/6), Cyclins (Ccnd1/d2), and Myc were markedly downregulated concomitantly with the switch of CEBPA and CEBPE expression at the intersection of early vs. late differentiation. In contrast, G2/M phase genes were downregulated after cessation of G1/S phase gene expression in parallel with completion of cell cycle exit. This sequential progression of cell cycle exit points to distinct regulatory mechanisms for lock-down of G1/S and G2/M phase genes during terminal differentiation. To decipher potential regulatory mechanisms, we conducted elaborate analyses on cell cycle gene promoters. Analyses of G1/S phase gene promoters suggest that the direct binding of CEBPE at E2F sites of the Myc promoter leads to repression of Myc expression concomitant with the downregulation of several designated MYC target genes critical for G1/S phase progression. Importantly, CEBPE also conferred direct activation of Mad expression which, in the absence of MYC, can dimerize with MAX and directly repress MYC target gene expression during cell cycle exit and terminal differentiation. Strikingly, these findings link a tissue-type-specific TF  to the MYC–MAD differentiation switch at the onset of cell cycle exit54.Notably, key G1/S phase genes including CDKs  E2Fs are dependent on adjacent NFY binding at promoters to activate G2/M gene transcription, our findings suggest a direct CEBPE repression of E2F-mediated G2/M gene expression11. Indeed, the latter was supported functionally by the marked upregulation of G2/M genes in Cebpe KO mice, concomitant with sustained proliferation and a block of differentiation at the MM stage. In addition to its role as a repressor of E2F target gene expression, CEBPE also regulated cell cycle exit by sustained direct activation of CDK4, CDK2, and CDK1 inhibitor expression  concomitant with cell cycle exit and terminal differentiation. This hitherto undescribed regulatory mechanism of CEBPE is in agreement with previous reports of cell type-specific TFs promoting growth arrest by upregulation of CDK inhibitor expression15. Previous studies have demonstrated that both CEBPA and CEBPE can repress E2F target gene expression and exhibit overlapping expression profiles in granulocytic differentiation models, suggesting that both TFs contribute to the regulation of cell cycle exit during granulocytic differentiation36. However, these findings are challenged by the high resolution of our in vivo differentiation model, which clearly demonstrates termination of Cebpa/CEBPA expression at the onset of Cebpe/CEBPE expression concomitant with initiation of cell cycle exit in vivo the PM to MY1 transition. These somewhat unexpected findings are supported by genetic studies demonstrating that CEBPA is indispensable for lineage-specification of HSCs toward GMPs, but is not required for GMPs to exit the cell cycle exit and complete terminal granulocytic differentiation25. Importantly, the ability of CEBPA to promote granulocytic differentiation of Cebpe KO cells in vitro while failing to do so in vivo might indeed reflect the 2.5- to 4-fold lower levels of CEBPA protein in Cebpe KO MY1s + MY2s as compared to CEBPE in Cebpe WT MY1s + MY2s. Intriguingly, ChIP-seq experiments demonstrated that CEBPE is bound to a distinct set of enhancers and promoters of granulocytic differentiation genes not bound by CEBPA, suggesting that CEBPE and CEBPA to some extent differ functionally. While these findings suggest that cell cycle exit and completion of granulocytic differentiation might partially be regulated in a dose-dependent manner by CEBPs, they do not provide any information on potential functional specificities.Complementary promoter analyses of G2/M phase genes demonstrated binding of CEBPE at their E2F binding sites in absence of any CEBPE binding motifs. These CEBPE-bound E2F sites were adjacent to NFYB sites at promoters of G2/M phase genes, such as Cebpa/CEBPA and Cebpe/CEBPE might rely on distinct sequential cis-regulatory events. Consistently, we identified sequential CEBPA and CEBPE binding to a reported functional 6 kb enhancer of Cebpe45. The latter suggests that CEBPA initiates Cebpe expression, which is subsequently enhanced through CEBPE autoregulation at the onset of cell cycle exit. As stated above, CEBPE promotes cell cycle exit, not only by repression of E2F-mediated Myc expression, but also by upregulation of Mad which, in absence of MYC can heterodimerize with MAX leading to inhibition of Myc target gene expression. Given that the Cebpa promoter harbors functional MYC/MAX—MAD/MAX binding sites .56. Briefly, murine BM cells were collected from tibiae, femur, and ilia of 8–10 weeks old mice. Subsequently, BM cells were KIT-enriched using anti-CD117-MoAb microbeads . Whole BM cells or KIT-enriched BM cells (planned for sorting) were subsequently stained with the following cocktail of fluorochrome-conjugated antibodies: CD150-APC , CD41-FITC , CD105-PE or CD105-PE-Cy7 , CD115-PE , Sca1-PerCP-Cy5 , FcgRII/III-A700 , Kit-A780  and a lineage cocktail consisting of the following PE-Cy5 conjugated antibodies: Ter119-PE-Cy5 , Gr1-PE-Cy5 , B220-PE-Cy5 , CD3e-PE-Cy5  and Mac1-PE-Cy5 .Flow cytometry-based analyses and cell sorting of LSKs, preGMPs, and GMPs were carried out as previously describedFor analyses and sorting of BM populations representing sequential developmental stages of late granulocytic  and late monocytic  differentiation hierarchies, BM cells were subjected to red blood cell lysis with PharmLyse . BM cells were then stained using the following fluorochrome-conjugated antibodies: CD34-FITC , CD115-PE , Ter119- PE-Cy5  B220-PE-Cy5 , CD3e-PE-Cy5 , NK1-PE-Cy5 , Sca1-PerCP-Cy5.5 , CD11b-PE-Cy7 , KIT-APC , FcgRII/III-A700 , and Ly6G-APC-Cy7 . Antibodies were provided by eBiosciences  unless otherwise stated.21.To assess the proliferation rates for individual BM populations, BM samples were surface-stained as described above and subjected to intracellular DNA staining with DAPI  as described previously by our laboratoryFlow cytometry analyses of cells were carried out on BD LSR II or BD ARIA III flow cytometers  according to the gating strategy depicted in Supplementary Fig. 21.The morphologies of sorted BM populations were assessed by microscopy of Wright-Giemsa stained cytospins as described previouslyTotal RNA was purified from sorted BM populations using the RNeasy Micro Kit  as described by the manufacturer. RNA was subjected to double-stranded cDNA synthesis using the Ovation RNA-Seq System V2 , and cDNA libraries were prepared from sheared cDNA fragments (150–550 bp) using the Ovation Ultralow System V2 (NuGEN). The indexed cDNA libraries were pooled in equimolar ratios and subjected to 75-cycles of sequencing at Exiqon (Exiqon now at Qiagen) on an Illumina NextSeq 500 Sequencing System .25. CEBPE, CEBPA, and H3K27ac ChIP-seq analyses of sorted BM populations  were conducted, essentially as described previously by our group58. In brief, we used 300,000–800,000 sorted MY1 + MY2s (pooled MY1s + MY2s), MMs, BCs, and GRs from Cebpe WT mice for indicated CEBPE and CEBPA ChIP-seq experiments, and 100,000 sorted cells for H3K27ac ChIP-seq experiments. 1,000,000 pooled MYs and MMs purified from Cebpe KO mice were used as a negative control for CEBPE ChIP-seq analyses. Chromatin was incubated with an antibody targeting CEBPE , CEBPA , and H3K27ac . Antibody-bound chromatin was captured with a mixture of Protein-A/G sepharose beads (1:25) or a mixture of DynabeadsTM Protein-A/G (1:100) (Invitrogen/Thermo Fisher Scientific), washed, de-crosslinked, and precipitated. If the amount of precipitated DNA was higher than 2 ng, DNA was directly amplified. If the amount of DNA was below 2 ng, it was mixed with fragmented E. Coli DNA to yield a tot of 2 ng before amplification using the NEBNext ChIP-seq Library Prep Kit for Illumina (discontinued) or NEBNext Ultra™ II DNA Library Prep Kit for Illumina  as described by the manufacturer. DNA libraries were sequenced on an Illumina HiSeq 2500 or NextSeq 500 Sequencing System.CEBPA, H3K4me1, and H3K27ac ChIP-seq analyses of sorted BM populations  have been described previously by our group2 in DMEM supplemented with 8% FBS and 2% chicken serum (InVitrogen/Thermo Fisher Scientific). Q2bn fibroblasts were transiently transfected by calcium-phosphate precipitation, grown for 24 h, and assayed for reporter gene expression as described previously16. The following plasmids were used for transient transfection experiments: pE2Fx6-TATA-LUC reporter, pCMV-E2F1, pCMV-DP1 expression vectors, and pCMVneoBam control vector . The pcDNA3-CEBPE and pcDNA3-CEBPE-BRM5 expression vectors were generated by insertion of full-length human CEBPE or CEBPE-BRM5 into the pcDNA3 vector . Empty pcDNA3 vector was used to adjust the total amount of DNA per dish and the beta-galactosidase reporter plasmid pRSV-βGAL, was used to normalize Luciferase activity.Q2bn fibroblasts  were cultured at 37 °C and 5% CO2. HEK293 were plated in 96-well tissue culture and transiently transfected with the following vectors: 0.2 ng of Renilla control vector , 20 ng of empty pGL4 vector or pGL4 vector containing a Cebpa promoter 57 base-pair fragment with or without its MYC-binding E-box , and 20 ng of either empty or MYC containing pcDNA3 vector . Vectors were transfected using a 3:1 μl/μg ratio of TransIT-2020 reagent as described by the manufacturer . After 2 days of incubation, dual-luciferase assays were performed according to the manufacturer’s instructions (Promega) using a standard luminometer.Human embryonic kidney (HEK) 293 cells  were cultured in DMEM supplemented with 10% FCS at 37 °C 5% COCebpa promoter sequence with its putative MYC-binding E-box (CGCGCA) or deletion thereof, were cloned between the NheI and HindIII restriction sites of the pGL4.23 vector (Promega). Cebpa promoter sequences for WT and mutated E-box: Cebpa_Myc_WT_s, CTAGGTGGGCGGCGGCGACAGCGGCGCCACGCGCAGGCTGGAGGCCGCCGAGGCTCGCCA;Annealed oligonucleotides containing a 57 basepair fragment of the Cebpa_Myc_WT_as, AGCTTGGCGAGCCTCGGCGGCCTCCAGCCTGCGCGTGGCGCCGCTGTCGCCGCCGCCCAC;Cebpa_Myc_MUT_s,CTAGGTGGGCGGCGGCGACAGCGGCGCCAGGCTGGAGGCCGCCGAGGCTCGCCACebpa_Myc_MUT_as, AGCTTGGCGAGCCTCGGCGGCCTCCAGCCTGGCGCCGCTGTCGCCGCCGCCCAC.CEBPE expression vectors by calcium-phosphate precipitation as indicated. After 24 h, nuclear extracts were prepared according to a protocol originally described by ref. 59. EMSAs were performed as described previously by our group16 using a CEBP probe derived from the FAVBP4 (AP2) promoter60, an E2F probe derived from the DHFR promoter61, and anti-CEBPE Ab .Q2bn fibroblast were transfected with pCMV-E2F1, pCMV-DP1, and pcDNA3-2 in Iscove´s modified medium  supplemented with 10% heat-inactivated calf serum, 1 ng/ml murine IL-3  and 100 units/ml penicillin/100 µg/ml streptomycin (InVitrogen/Thermo Fisher Scientific). Puromycin  was added to the medium of 32Dcl3 cell lines transduced with a pBabePuro retroviral vector.32Dcl3 cells  were maintained at 37 °C and 5% COCEBPE-ERTM cDNA construct was prepared by linking the full-length human CEBPE cDNA as a BamH1/AscI fragment in a frame to an AscI/EcoR1 fragment of the tamoxifen-responsive estrogen receptor hormone-binding domain 62. The one mutation in the non-DNA binding side of the CEBPE basic region (BRM5: Y208A) was generated using the QuickChange system  and confirmed by sequencing. The CEBPE-ERTM, CEBPE-BRM5-ERTM, and ERTM cDNAs were inserted as BamH1/EcoR1 fragments into the poly-linker of the pBabePuro retroviral vector (Nolan lab homepage: http://www.stanford.edu/group/nolan/index.html). The pBabePuro-CEBPE-ERTM, pBabePuro- CEBPE-BRM5-ERTM, and the pBabePuro-ERTM vectors were transfected into the ecotropic packaging cell line Phoenix-ECO , by calcium-phosphate precipitation. After 24 h, 32Dcl3 cells were co-cultured with transfected Phoenix cells for another 48 h in 32Dcl3 medium plus 4 μg/ml polybrene (Sigma-Aldrich). Subsequently, 32Dcl3 cells were selected in puromycin , and subclones were generated by the transfer of single cells into 96-well dishes using an automated Quickcell transfer device .The CEBPE-ERTM and 32Dcl3-CEBPE-BRM5-ERTM cell lines was induced by the addition of 200 nM of 4-hydroxy-tamoxifen  to the medium. 32Dcl3-ERTM cells induced by 4-HT served as control. To assess the ability of CEBPE to induce differentiation and cell cycle exit, 32Dcl3 cell lines were subjected to 4-HT induction and stained with fluorochrome-conjugated antibodies CD11b-PE (clone M1/70) or GR1-FITC (clone RB6-8C5) or propidium iodide (Sigma-Aldrich). Flow cytometry analysis was carried out on the BD LSR II flow cytometer (BD Biosciences). Subsequent analyses of flow cytometry data were conducted using FlowJo analysis software.Translocation of the fusion and control proteins from the cytosol to the nucleus in 32Dcl3-Cebpe WT and KO mice were MACS-enriched using CD117 Microbeads and LD columns according to the manufacturer’s recommendations (Miltenyi). KIT-enriched BM cells were maintained in in X-VIVO complete media at 37 °C, 5% CO2, 95% humidity, and retrovirally transduced with pBabePuro-CEBPE-ERTM, pBabePuro-CEBPA-ERTM generously provided by Gerhard Behre, Clinic for Internal Medicine I, Dessau Medical Centre, Dessau, DE) and empty pBabePuro vectors. For this, 24-well plates were RetroNectin–coated , blocked with 2% BSA-blocked (StemCell Technologies), and spinoculated with retrovirus . After spinoculation, the retroviral supernatant was discarded, and 500.000 KIT-enriched BM cells per well were plated in X-VIVO Complete media by centrifugation . cultured for 2 days, and subjected to puromycin selection  for 1 day. Subsequently, transduced KIT-enriched cells were treated with 4-HT for 3 days to assess differentiation after 4-HT induction of CEBPA and CEBPE activity by flow cytometry analyses as described above. Induced granulocytes (iGRs) and induced monocytes (iMOs) were defined as CD115-Ly6G+ and CD115 + CD11b + cells, respectively. X-VIVO complete medium: X-VIVO 15 with gentamicin , supplemented with 10% bovine serum albumin (BSA) (StemCell Technologies), 0.1 mM β-mercaptoethanol (Sigma-Aldrich), 1% l-glutamine (Gibco/Thermo Fisher Scientific), 1% Pen/Strep (Gibco/Thermo Fisher Scientific), and the following cytokines: hIL-6 (50 ng/ml), mSCF (50 ng/ml), mIL-3 (10 ng/ml), and GM-CSF (10 ng/ml) .KIT-positive BM cells from 64. 32Dcl3-CEBPE-ERTM cells were transduced with lentiviral dCas9-KRAB-MeCP2 (Addgene) and treated with blasticidin (40 μg/mL) to select for cells stably expressing the dCas9-KRAB-MeCP2 protein. Sequences for sgRNAs targeting putative promoters and enhancers bound by CEBPE were designed utilizing the Broad Institute website: Hlx promoter sgRNA, GAGCTTTCGAGTCAGACCCC; Dhrs7 enhancer sgRNA, TCAGAACTTTGAGGCCAACC; Dhrs7 promoter, GCCAAGCTGAGCCTTGACCA; Hp promotor sgRNA, TGCAAACACAGAAATGGAGG. To generate sgRNA constructs, sgRNA oligos were inserted into pL-CRISPR-SFFV-Puro-P2A-EGFP . sgRNAs expressing constructs were co-transfected with pAX8 and VSVG to HEK293FT cells using a standard calcium-phosphate protocol. Viral supernatants were collected 48 h after HEK293FT transfection and used for lentiviral transduction of 32Dcl3-CEBPE-ERTM cells with indicated sgRNAs or scramble sgRNA as control. Forty-eight hours after transduction, cells were cultured with 4-HT to induce CEBPE activity. On day 2 or 4 of 4-HT, 1 × 105 GFP-positive 32Dcl3-CEBPE-ERTM cells were sorted and subjected to real-time RT-PCR to assess gene expression levels as described previously65. The following primers were used: Hp forward primer, TTCTACAGACTACGGGCCGA, Hp reverse primer, CGACTGTGTTCACCCATTGC; Hlx forward primer, TGTCTGCGGAATTTGACCCA, Hlx reverse primer, AGATGCGAAGAACTGTCCCG; Dhrs7 forward primer, TGCAGCTCTTGCGCTTTTTG, Dhrs7 reverse primer, CAGCTCCCATTCTGGGCGT; B2m forward primer, ACGTAACACAGTTCCACCCG, B2m reverse primer, CAGTCTCAGTGGGGGTGAAT. Relative gene expression levels for Hp, Hlx, and Dhrs7 were calculated by normalization to the B2m housekeeping gene.Putative gene promoters and enhancers of genes bound by CEBPE and expressed during terminal granulocytic differentiation (at their promoters/enhancers) were selected for CRIPSRi experiments, which were done essentially as described previously66. Five hundred cells were sorted into wells containing 1 μl of lysis buffer (50 mM Triethylammonium bicarbonate (TEAB) pH 8.5, 20% 2,2,2-Trifluoroethanol (TFE), 10 mM tris(2-carboxyethyl) phosphine (TCEP), and 40 mM Chloroacetamide (CAA)). Directly after sorting, plates were briefly spun, snap-frozen on dry ice, boiled in a PCR device at 95 °C  for 5 min, and snap-frozen again on dry ice, and stored at −80 °C. Subsequently, 384-well plates with BM populations were thawed, and absolute quantified peptides  were dispensed into wells using the I.DOT One instrument . CEBPA peptide 1 = VGAPALRPLVIK, peptide 2 = VLELTSDNDR, CEBPE peptide 1 = GGQQPLEFSGGR, peptide 2 = VLEYMAENER. In addition, three to four dilution series for each synthetic peptide were dispensed to confirm the linear response of peak areas and to determine the limit of quantification (LOQ) for each peptide. These dilution curves were prepared in the same way as the absolute quantification experiments and thus contained the same background matrix.BM populations were sorted into a 384-well Eppendorf LoBind PCR plate  and prepared as previously describedDigestion was performed by adding 10 ng of Trypsin , dissolved in 1 μl of 100 mM TEAB pH 8.5 containing Benzonase  diluted 1:5000 (vol/vol) to digest any DNA that would interfere with downstream processing. Plates were kept at 37 °C overnight to complete the digestion. Digestion was stopped by adding 1 μl of 2% Trifluoroacetic acid  to each well. Samples were directly loaded onto conditioned EvoTips , by transferring the content of eight wells (4000 cells) into 40 μl of buffer A (0.1% Formic acid) that was placed on top of the EvoTips. Subsequently, EvoTips were prepared according to the manufacturer’s protocol. Samples on EvoTips were acquired using the 20 SPD Whisper method of the Evosep One System coupled to an Orbitrap Eclipse Tribrid Mass Spectrometer with FAIMS Pro Interface (Thermo Fisher Scientific) running Tune 3.4 and Xcalibur 4.3. FAIMS was set to −40 CV. A parallel reaction monitoring (PRM) method was run with the following parameters. Each cycle consisted of an MS1 scan with Orbitrap resolution of 60k, 400–1600 m/z scan range, 30% RF lens, 300% AGC, and 50 ms maximum injection time. Following the MS1 the eight targeted peptide ions  were measured in a retention time scheduled manner via MS2 with 1.2 m/z isolation window, 30% HCD collision energy, Orbitrap resolution of 500k or 240k, and 500% AGC target, maximum injection time set to auto, 300–2000 m/z scan range and 30% RF lens.https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/mas.21540)Raw files were analyzed with Skyline 21.1.0.146  for each peptide. For the absolute quantification of endogenous peptides in each sample, peak area ratios of an endogenous peptide to synthetic heavy-labeled spike-in of known amounts was used.as described previouslyCebpe WT mice  and BM populations of Cebpe KO mice  were mapped to the mouse genome assembly (mm9) using STAR (version 020201)68. Raw read counts mapping to Gencode-defined gene annotations (Ensembl 65) were determined using the featureCounts function of the Rsubread package (version 1.24.2)70. Complementary previously published mRNA-seq data of sorted WT LSKs, preGMs, and GMPs (GEO ID: GSE89767)25 were included in the final RNA-seq data set, which allowed for temporal gene expression profiling of 33,924 genes during the course of early and late granulocytic and monocytic differentiation. Batch effects of gene expression values were corrected using the removeBatchEffect function of the Limma package71. The PRCOMP function in R was used to generate the PCA plot based on the gene expression profile of all 33,924 genes expressed during granulocytic and monocytic differentiation. Genes  having at least 1 mapped read across at least two samples, and standard deviation across samples of more than 0 were selected for subsequent analyses.Paired-end reads derived from mRNA sequencing of sorted BM populations of 72. Genes differentially expressed in Cebpe KO vs. Cebpe WT GPs, PMs, MY1s, MY2s, and MMs were identified using the DESeq2 package 73. Subsets of the 15 gene clusters were merged into the following five major gene clusters represented in Fig. The optimal number of gene expression clusters was determined to be 15 by applying kmeans function in R and by minimizing the ‘sum of square’ distance among clusters. Heatmaps showing gene expression profiles of gene clusters during differentiation were generated using the complexHeatmap toolCebpe KO vs. Cebpe WT mice were defined as differentially expressed (DE) or neutral. Similarly, genes from cluster C(GR) that were downregulated in MY1s + MY2s and MMs in Cebpe KO vs. Cebpe WT mice were defined as differentially expressed (DE) or neutral.Genes from clusters A(GMP), B(MY), D(GR + MO), and E(MO) that are upregulated in MY1s + MY2s and MMs of 74 with a manually curated list of 34 genes. The MYC target gene list was previously reported by ref. 75.A list of 102 cell cycle genes was generated by combining 68 key cell cycle genes reported by ref. 76 to identify the top ten gene ontology terms of “biological processes” (FDR < 0.05) for the five gene clusters in Fig. Gene ontology analysis was performed using clusterProfilerCebpe enhancer was kindly provided by Dr. Pavithra Shyamsunder77. Changes of Cebpa and Cebpe expression following the loss of the +6KB Cebpe enhancer activity were determined using EdgeR78.A gene expression matrix containing the expression profiles of 32Dcl3 cells before and after CRISPR-mediated functional disruption of the +6KB 79. To annotate single cells with bulk RNA-seq profiles of sorted BM populations of the current study, and studies by Kwock et al., Evrard et al., and Xie et al., SingleR (v1.8.0) was used80. Single cells were annotated to different phases of cell cycle  using Seurat v4.0.1 (default parameters).Integrated analysis of single-cell data from whole bone marrow (The Tabula Muris Consortium—version 3) and Kwock et al. (GSE151630) was performed using Seurat v4.0.1 (default parameters)25 were mapped to mouse (mm9) genome assembly using Bowtie281. We used uniquely mapped and PCR duplicates (exact copies) collapsed as one read and extended to their fragment length by determining the read extension size using MACS2 (predicted parameter)82. Raw read counts were normalized to TPM using deeptools (bamCoverage)83.Raw reads derived from CEBPA , CEBPE, H3K27ac  ChIP-seq experiments and our previously published PU.1, CEBPA, H3K4me1, H3K27ac  ChIP-seq datasets82. To increase the specificity of the enriched regions, we used a control sample prepared with an IgG control antibody (PU.1 and CEBPA) or Cebpe KO cells (CEBPE). Irreproducible Discovery Rate (IDR)84 was used at a false discovery rate of 0.05 to filter out irreproducible regions between the two replicates. Genomic regions enriched for MYC, E2F1, and NFYB binding were inferred by using previously published ChIP-seq data derived from ESC 85. Since 99% of CEBPA peaks  were detected in GMPs  were defined as (i) regions distal to promoters (>1000 bp from TSS), bound by one or more of the following TFs: PU.1, CEBPA, CEBPE, MYC, or E2F1, and overlapping with open chromatin regions defined in a compendium of mouse immune cells39, or (ii) as regions previously identified as enhancer regions of myeloid BM populations25. Each enhancer region was set to a fixed width of 500 bp and was linked to the closest gene to define its potential cis-regulatory target.Potential enhancer regions  in R . Specifically, we identified DE genes and neutral genes from clusters A(GMP) and B(MY)  or 0 (not-bound) for each of the three TFs. Similarly, previously annotated MYC  and E2F1  bound regions in ESC were used to identify whether they overlapped with the promoters of genes from clusters A(GMP) and B(MY)40.To rank TFs  on the basis of their relative importance in regulating the expression of cell cycle genes that are differentially expressed in MY) Fig. , and mea86. For comparison across different cell populations, ChIP-seq signals of TFs were plotted to the same scale. Heatmaps showing the binding signal of CEBPE, NFYB, and E2F1 at promoters were plotted using the ngs.plot package87.To visualize the position of CEBPA, CEBPE, MYC, E2F1, NFYB, and LIN54 binding at the promoter of genes, we used Gviz to plot their ChIP-seq binding signalsN = 4071) that were bound by CEBPE  and measured the distance of CEBPE binding to the closest E2F1 binding site. Gene promoters for which the distance between the CEBPE and E2F1 binding sites was 0  were considered as promoters where CEBPE potentially interacts with E2F to regulate E2F-dependent gene expression.We identified gene promoters  or Hocomoco (E2F1 and MYC) and measured using findMotifsGenome.pl script in the Homer package90. Known TF-binding motifs were downloaded from MEME, Jaspar, Uniprobe, Hocomoco, and refs. 93. Motif enrichment was computed for promoters of genes differentially expressed from all five clusters in Cebpe KO vs. Cebpe WT mice and compared to their enrichment in neutral genes   genes (N > 30) were defined based on combinatorial binding sites of four TFs . CENL subclass: Binding of all four TFs. CE subclass: Binding of C and E with or without additional binding of either N or L. Rest: Binding of other TF combinations of C, E, N, L, or none thereof. Binding sites for each of the four TFs on gene promoters were defined based on ChIP-seq data  and binding motif analyses (NFYB and LIN54).Known E2F1 and NFYB binding sites (ChIP-seq) in ESCs were obtained from previous studies (GEO ID: GSE11431 and GSE56839)No statistical method was used to predetermine sample size. Median levels and standard error were calculated for replicates of each BM population analyzed by RNA-seq. ChIP-seq signals were normalized to tags per million (TPM) and the mean of the two replicates was used for subsequent analyses. The Wilcoxon test was used to test for statistical significance between groups unless otherwise specified in the figure legends. All the statistical analyses for RNA-seq and ChIP-seq experiments was performed in R version 3.4.4 and exact p-values were calculated and reported in the figures.Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Reporting Summary


More than half of human protein-coding genes have an alternative transcription start site (TSS). We aimed to investigate the contribution of alternative TSSs to the acute-stress-induced transcriptome response in human tissue  using the cap analysis of gene expression approach. TSSs were examined at baseline and during recovery after acute stress (a cycling exercise).We identified 44,680 CAGE TSS clusters (including 3764 first defined) belonging to 12,268 genes and annotated for the first time 290 TSSs belonging to 163 genes. The transcriptome dynamically changes during the first hours after acute stress; the change in the expression of 10% of genes was associated with the activation of alternative TSSs, indicating differential TSSs usage. The majority of the alternative TSSs do not increase proteome complexity suggesting that the function of thousands of alternative TSSs is associated with the fine regulation of mRNA isoform expression from a gene due to the transcription factor-specific activation of various alternative TSSs. We identified individual muscle promoter regions for each TSS using muscle open chromatin data (ATAC-seq and DNase-seq). Then, using the positional weight matrix approach we predicted time course activation of “classic” transcription factors involved in response of skeletal muscle to contractile activity, as well as diversity of less/un-investigated factors.Transcriptome response induced by acute stress related to activation of the alternative TSSs indicates that differential TSSs usage is an essential mechanism of fine regulation of gene response to stress stimulus. A comprehensive resource of accurate TSSs and individual promoter regions for each TSS in muscle was created. This resource together with the positional weight matrix approach can be used to accurate prediction of TFs in any gene(s) of interest involved in the response to various stimuli, interventions or pathological conditions in human skeletal muscle.The online version contains supplementary material available at 10.1186/s40246-022-00399-8. The human genome contains more than 20,000 protein-coding genes. One gene can encode several different protein isoforms, which can have both similar and slightly different functions. The variety of mRNA isoforms is generated and controlled by alternative splicing, alternative transcription start sites (TSSs), and polyadenylation sites. Analysis of RNA sequencing data from mouse nervous tissue at different stages of development  and in dDrosophila, zebrafish, and chicken  were involved in our study. An intermittent exercise induces greater molecular response compared to a continuous exercise with the same average power  + 2 min, 100% LT4] × 12) on a cycle ergometer  2 h after a standardized breakfast . The LT as well as V′O2max—markers of aerobic performance, were evaluated in a preliminary test session of the incremental cycling test till exhaustion using a Biosen C-line analyzer  and a medical gas mass-spectrometer AMIS 2000 with a mixing chamber . Subjects ate a standardized lunch  1 h 15 min after an intermittent exercise. Biopsy samples were taken under local anesthesia (2 mL 2% lidocaine) using a Bergstrom needle with aspiration from the m. vastus lateralis prior to, 2 min, 1 h, 3 h, and 6 h after an intermittent exercise   than that in skeletal muscle adapted to regular exercise . Therefoge power , 31. HenRNA was extracted from the frozen samples (~ 20 mg) using an RNeasy mini kit  with DNase I treatment ; the kit extract RNA with length > 200 bp. The RNA concentration and integrity were evaluated in a fluorometer  and by capillary electrophoresis , respectively; all samples were at least 7 in RIN. Libraries were constructed from 2.5 to 3 µg of RNA according to nAnT-iCAGE  protocol  using nAAverage effective size of the libraries  was ~ 11 million reads per sample. Raw sequencing data have been deposited to NCBI GEO: GSE164081.Adapter sequences and low-quality reads were trimmed using the Trimmomatic tool (v0.36) (options—illuminaclip:adapters.fa:2:30:10 leading:3 trailing:3 slidingwindow:4:15 minlen:35), then single 5′-guanine was clipped. Genome indexes for alignment were generated by STAR (v2.7.0a) for GRCh38.p13 primary assembly genome (with Gencode annotation v33), then reads were aligned with mismatch rate threshold 0.06. rRNA reads and reads aligned to mitochondrial genome excluded using split_bam.py script (RSEQC v.3.0.1) with combined annotation (RefSeq and Ensembl rRNA genes and mt genome). Only reads with MAPQ = 30 were used for further analysis.http://genome.gsc.riken.jp/plessy-20150516/PromoterPipeline_20150516.tar.gz) and were used for generation of the CAGE tag-defined TSS clusters (CAGE TSS clusters) by DPI algorithm (https://github.com/hkawaji/dpi1) for all (50) samples. TPM (tags per million reads) expression for the CAGE TSS clusters and counts of CAGE tags per CAGE TSS cluster were estimated by DPI.Files with CAGE tags positions (.bed files) were generated by level1.py script (https://github.com/Xinglab/SEASTAR). Then, the remaining CAGE TSS clusters were annotated to introns and intergenic regions  were annotated on the genome (Ensembl (GRCh38.101) and RefSeq (08/15/2020 release)) using R (rtracklayer package) and bedtools v2.26.0 . To avoid multiple features, an annotation priority of CAGE TSS clusters: TSS (with neighborhood ±50 bp) > 5′UTR > 3′UTR > CDS > exon of non-protein-coding transcripts > intron > intergenic region  were eliminated. Highly expressed CAGE TSSs were noted as major CAGE TSS clusters  data were used for the principal component analysis. Genes with differential TSSs usage were identified for each experimental time point using Dirichlet-multinomial-based algorithm [Padj < 0.05).Aggregated expression of CAGE TSS clusters per gene  we used as raw input data for differential expression analysis  with thresholds: |Fold Change|> 1.25 and lgorithm  from DRIPadj < 0.05  were regarded as significantly enriched.Functional enrichment of protein groups in relation to all detected  protein-coding genes was performed by the DAVID 6.8 using GOTERM_BP_Direct databases. GO terms with To localize genomic intervals with open chromatin around each CAGE TSS cluster (− 2000 to + 2000 bp) in human gastrocnemius medialis muscle (4 samples), we used ATAC-seq  and DNase-seq  data—MACS2 peaks and normalized signals . Open chromatin probability and average TFBS density were estimated for interval − 2000 to + 2000 bp around the mass center of most expressed TSS cluster in the interval  was estimated using 15,982 ChIP-seq experiments with human cells and tissues .The overlapped open chromatin intervals separated by < 71 bp  from each other were joined to an interval. Individual promoter was defined as regions in which open chromatin is located 200 bp or less from the CAGE TSS cluster Fig. A. Other http://wiki.biouml.org/index.php/Search_for_enriched_TFBSs_(tracks)_) using the PWM database TRANSFAC v2020.3 [adj, statistically corrected odds ratios with a confidence interval of 99%) was determined for each PWM (site frequency ≤ 1 per 2000 bp) relative to that in 5000 random individual promoters showing no differential expression in any of experimental time points . Adjusted fold enrichment (FEadj) > 1.5 for transcription factor binding site or promoter’s sequence number  and FDR < 0.05 were set as significance thresholds. If a TF has several PWM, the most enriched PWM was used.Differentially regulated individual promoters (as well as pseudo-promoter regions) were determined as described above for DEGs. Enrichment of predicted TFBSs (and corresponding TFs) in individual muscle promoter regions were performed by the geneXplain platform (the “Search for enriched TFBSs (tracks)” function  v2020.3 , 34. Thehttp://wiki.biouml.org/index.php/CRC_Analysis). The TFBSs (and corresponding TFs) were predicted using the individual promoter regions by the PWM method (as described above) for each cluster.To search for co-expressed individual promoter regions, ranked expression values were used. Namely, data of four time points  for each person were used for each promoter. The co-expressed promoters were identified by an unsupervised analysis: the Chinese restaurant process (Qin 2006) using the geneXplain platform  . Then, the corresponding transcripts and start codons were determined for each CAGE TSS cluster. Finally, genes having at least 2 alternative start codons were identified. The calculations were performed using the R environment, rtracklayer package, and bedtools v2.26.0 (closest).Additional file 1. Figure S1. Design of the study. A. Ten endurance-trained athletes carried out an intermittent exercise on a cycle ergometer. Intensity of exercise was selected based on an incremental cycling test till exhaustion. Biopsy samples were taken from the m. vastus lateralis prior to, 2 min, 1 h, 3 h, and 6 h after an intermittent exercise . B. An intermittent exercise induced metabolic shift indicated by markedly elevated blood lactate concentration. Figure S2. GO enrichment analysis for biological processes induced by acute exercise. The heat map shows the P-value adjusted (Padj). Dark red and blue denotes the most significant GO terms for up. The count indicates the number of genes enriched into a term. Figure S3.Distribution of nucleosome-depleted region markers around the CAGE TSS. The density of transcription factor binding sites (TFBSs) on the DNA , mean normalized DNase-seq and ATAC-seq signals (middle) and probability of open chromatin distribution (below) evaluated by normalized signals and MACS2 peaks for DNase-seq and ATAC-seq data, respectively .Additional file 2. Table S1. All and firstly annotated CAGE TSS clusters in the human vastus lateralis muscle. To eliminate low expressed CAGE TSS clusters 10 percent cutoff was applied to CAGE TSS clusters annotated to TSS, 5’UTR, CDS, 3’UTR, Non coding exon, or Verified by RNA sequencing and belonging to a gene. These CAGE TSS clusters were marked as Major or Minor; no cutoff was applied to CAGE TSS clusters belonging to Intron and Intergenic.Additional file 3. Table S2. DEGs induced in the vastus lateralis muscle by acute exercise and GO enrichment analysis for biological processes.Additional file 4. Table S3. Individual muscle promoters and pseudo promoters. Individual promoter was defined as regions in which open chromatin is located 200 bp or less from the CAGE TSS cluster Open – open chromatin near the CAGE TSS cluster. Other CAGE TSS clusters separated by 200 bp or less were grouped and defined as pseudo promoters and divided on promoters with removed (Closed200) and without (Closed2000) open chromatin. Closed200 – closed chromatin –200 bp to +200 bp and open chromatin –2,000 bp to –200 bp and/or +200 bp to +2,000 bp; Closed2000 – closed chromatin –2,000 bp to +2,000 bp). DEP and DEG – differentially expressed promoter and gene, respectively. Protein isoforms shows genes having at least 2 alternative start-codons.Additional file 5. Table S4. Clusters of co-expressed individual muscle promoters and TFs associated with the clusters. Clusters shows 21 clusters (C) of coexpressed individual promoters induced by exercise and identified by unsupervised analysis. Enriched transcription factors (TFs) show TFs with FDR <0.05  and adjusted fold enrichment >1.5 for both transcription factor binding site (Adj.site FE) or promoter’s sequence number (Adj.seq.FE).


The incidence of non-alcoholic fatty liver disease (NAFLD)-associated hepatocellular carcinoma (HCC) is increasing worldwide, but the steps in precancerous hepatocytes which lead to HCC driver mutations are not well understood. Here we provide evidence that metabolically driven histone hyperacetylation in steatotic hepatocytes can increase DNA damage to initiate carcinogenesis.Global epigenetic state was assessed in liver samples from high-fat diet or high-fructose diet rodent models, as well as in cultured immortalized human hepatocytes (IHH cells). The mechanisms linking steatosis, histone acetylation and DNA damage were investigated by computational metabolic modelling as well as through manipulation of IHH cells with metabolic and epigenetic inhibitors. Chromatin immunoprecipitation and next-generation sequencing (ChIP-seq) and transcriptome (RNA-seq) analyses were performed on IHH cells. Mutation locations and patterns were compared between the IHH cell model and genome sequence data from preneoplastic fatty liver samples from patients with alcohol-related liver disease and NAFLD.Genome-wide histone acetylation was increased in steatotic livers of rodents fed high-fructose or high-fat diet. In vitro, steatosis relaxed chromatin and increased DNA damage marker γH2AX, which was reversed by inhibiting acetyl-CoA production. Steatosis-associated acetylation and γH2AX were enriched at gene clusters in telomere-proximal regions which contained HCC tumour suppressors in hepatocytes and human fatty livers. Regions of metabolically driven epigenetic change also had increased levels of DNA mutation in non-cancerous tissue from NAFLD and alcohol-related liver disease patients. Finally, genome-scale network modelling indicated that redox balance could be a key contributor to this mechanism.Abnormal histone hyperacetylation facilitates DNA damage in steatotic hepatocytes and is a potential initiating event in hepatocellular carcinogenesis.The online version contains supplementary material available at 10.1186/s13073-022-01071-5. Telomerase (TERT) gene which is present in around 60% of cancers and is the earliest detectable of all the known mutations  an an22] anWe assessed whether the global chromatin changes are associated with DNA damage by performing immunofluorescence for ɣH2AX, a well-established marker of DNA damage , 36 whicTo investigate whether the DNA damage in vitro was dependent on histone acetylation, we inhibited the major biochemical pathways which produce acetyl-CoA, the substrate for histone acetylation. We found that the steatosis-associated ɣH2AX was reversed by a 4-h pharmacological inhibition of any of the major sources of acetyl-CoA  in the patients; similarly, 17 out of 21 genes at the chromosome 5 cluster had identified mutations . However, closer examination of the carcinoma risk factors in the TCGA patient history showed no statistically significant difference in the frequency of mutations within these 2 clusters between a group of alcoholic liver disease plus NAFLD cases  and a viral hepatitis group . Nonetheless, the combination of the cluster-wide epigenetic changes and the mutations in multiple genes within these clusters supports the possibility that large chromosomal regions have increased mutation risk from metabolism-associated epigenetic change in steatosis, which may overlap with mutagenic processes in viral hepatitis. Furthermore, the observation that the TERT gene, which is the most commonly mutated gene in HCC, had high histone acetylation and ɣH2AX levels in steatotic cells suggested that the mechanism could contribute to carcinogenesis.We next sought to identify which regions of the genome experience steatosis-associated increased ɣH2AX as that would identify which genes and biological processes could be disrupted by DNA damage. We performed chromatin immunoprecipitation with anti-H4K16ac and anti-ɣH2AX antibodies and next-generation sequencing on the enriched DNA from control and steatotic IHH cells. The ɣH2AX peak regions were compared between the control and steatotic cells. Seventy-seven of the 100 regions with biggest peak increases in steatosis compared to control cells were clustered on 7 chromosomes . These clusters displayed colocalization of H4K16 acetylation and ɣH2AX peaks  at oleic acid peak regions compared to control peaks, we re-examined the respective ChIP-seq peak regions in our sequenced whole genomes from human donors. While we did not observe any SVs at the control peak regions, we observed a deletion that affects tylation . It is ae in HCC . TherefoFinally, we examined the mutational signatures that are present in the human liver biopsy WGS datasets at the regions which correspond to the ɣH2AX peak regions. This indicated that the proportion of SNVs which are attributable to ROS-associated mutational processes are more pronounced in NAFLD clones in the steatotic ɣH2AX peak regions than control ɣH2AX peak regions , lipid storage (PLIN2), lipotoxicity (ATF4) and oxidative stress responses  , and the computationally predicted increase in aldehyde dehydrogenase (ALD5A1) and decrease in retinol dehydrogenase were also observed.Gene expression analysis identified 1769 upregulated and 2081 downregulated transcripts in oleic acid-supplemented IHH cells compared to those grown in control media  Fig. C. Genes JUN was the most significantly downregulated transcript which may indicate that garcinol reduces cell proliferation or increases apoptosis. Additionally, there was no indication that β-oxidation (CPT1A), lipotoxicity (ATF4), acetyl-CoA biogenesis  nor oxidative stress responses  were altered by garcinol although a slight decrease in a marker for lipid storage was seen (PLIN2) . There did not appear to be any overall cluster-specific transcriptional effect on protein-coding genes, with all clusters having a mix of significantly up- and downregulated genes. However, the RNA-seq also revealed that oleic acid-treated cells had a greater percentage of lincRNA or antisense transcripts with significantly increased expression , than were significantly decreased  which was a divergence from the relative percentage of all combined transcript types . Closer examination of the ChIP-seq enriched gene clusters also revealed that the highest upregulated transcript in each cluster was a non-coding RNA. The effects of garcinol treatment may mirror this, as the most significantly downregulated transcripts in 3 of the 5 clusters were non-coding RNAs .In this study, we provide evidence that energy metabolism can direct epigenetic change and DNA damage across the genome, including to the earliest mutated gene in HCC. While acetylation changes and HDAC expression changes are known in HCC  and NAFLTERT, may be predisposed for sensitivity [Overall, our data support the concept that increased acetyl-CoA flux in steatotic hepatocytes leads to increased histone acetylation at certain genomic regions thus increasing their sensitivity to the prevailing oxidative stress. We observed that many of the genomic regions which had the highest increases in ɣH2AX and H4K16ac in steatosis also had relatively high levels (compared to the rest of the genome) in cells grown in control media. This suggests that these regions, such as the telomere-proximal cluster which contains sitivity . There isitivity , but thesitivity . DespiteThe computational modelling of the metabolic changes induced by the different inhibitors of acetyl-CoA production suggests that reduced oxidative stress is responsible for the ɣH2AX decreases. This is supported by the presence of ROS-associated mutational signatures of the SNVs that are found at the genomic regions in fatty livers which correspond to the oleic acid-induced ɣH2AX peaks. NAD/NADP-consuming enzymes in folate and pyruvate metabolism were predicted to be altered, and dysregulation of either process has been shown to influence oxidative stress in liver , 49. TheTERT gene (Fig. The RNA-seq comparison of control media and oleic acid supplementation in IHH cells suggested that the increase in histone acetylation and ɣH2AX are linked to increased oxidative stress due to lipotoxicity and/or increased ROS generation from mitochondrial fat metabolism. These data also highlighted the possibility that oleic acid stimulated cell proliferation may contribute to increases in genome-wide acetylation. Garcinol treatment provided a variety of mechanistic insights as it reverses histone acetylation and ɣH2AX at the ene Fig. Aiii but ene Fig. B. The trThe RNA-seq data also revealed that an in vitro transcriptomic consequence of epigenome change in steatosis is increased transcription from lowly expressed non-coding genes. This fits with the transcriptionally permissive nature of histone hyperacetylation which may stimulate transcription from cryptic promoters. It will be important to identify whether these transcripts contribute to pathogenic changes in hepatocytes either by themselves, perhaps by promoting structural and base pair-level mutability, or by modulating the expression of protein-coding genes.The worldwide rates of HCC are increasing, and there is a switch from the incidence being driven by a relatively small population with viral hepatitis who have a high risk for HCC, to a large population with NAFLD who have a relatively low HCC risk . TherefoBesides HCC, future work will aim to determine whether regionally increased histone acetylation can progress the severity of NAFLD to NASH and cirrhosis through dysregulation of genes involved in inflammation and fibrosis. Finally, several drugs undergoing preclinical and clinical trials for reducing liver steatosis and fibrosis in NAFLD will likely impact acetyl-CoA metabolism  and/or hTERT gene is particularly affected indicates that this mechanism may be of particular importance for understanding the preneoplastic stages of HCC. To our knowledge, this is the first example of histone hyperacetylation being an initiating event in carcinogenesis. Future work can aim to manipulate this mechanism for reduction of HCC risk in patients with fatty liver disease.Our investigations reveal a new mechanism in which macronutrient-sourced metabolites induce transcriptional changes and promote mutations across the genome, including at oncogenes. The observation that the Additional file 1. Liver Cohort Baseline Clinical Data.Additional file 2. Supplementary Figures S1-S4.Additional file 3. ChIPseq significant histone peaks.Additional file 4. RNAseq DEG and GSEA.


SCD5 promoter and its polymorphisms in vitro, in silico and in a case-control study. The SCD5 promoter region was determined by a luciferase reporter system in HepG2, HEK293T and SK-N-FI cells and it was proved to be cell type-specific, but it was insensitive to different fatty acids. The effect of the SCD5 promoter polymorphisms rs6841081 and rs3811792 was tested in the transfected cells. The T allele of rs3811792 single nucleotide polymorphism (SNP) significantly reduced the activity of the SCD5 promoter in vitro and modified several transcription factor binding sites in silico. A statistically significant association of rs3811792 SNP with T1DM and T2DM was also found, thus supporting the medical relevance of this variation and the complexity of the molecular mechanisms in the development of metabolic disorders. In conclusion, the minor allele of rs3811792 polymorphism might contribute to the development of diabetes by influencing the SCD5 promoter activity.The combined prevalence of type 1 (T1DM) and type 2 (T2DM) diabetes mellitus is 10.5% worldwide and this is constantly increasing. The pathophysiology of the diseases include disturbances of the lipid metabolism, in which acyl-CoA desaturases play a central role as they synthesize unsaturated fatty acids, thereby providing protection against lipotoxicity. The stearoyl-CoA desaturase-5 (SCD5) isoform has received little scientific attention. We aimed to investigate the  About 537 million people worldwide have diabetes, the majority are living in high- and middle-income countries, and 1.5 million deaths are directly attributed to diabetes each year. Both the number of cases and the prevalence of diabetes have been steadily increasing over the past few decades . Diabetecis-Δ9 position of a saturated fatty acyl-CoA, which are mainly palmitoyl-CoA and stearoyl-CoA that produce palmitoleyl-CoA and oleyl-CoA, respectively [The balance of lipid metabolism in our body depends on a functionally appropriate combination of saturated (SFA), monounsaturated (MUFA) and polyunsaturated (PUFA) fatty acids (FAs) with different carbon chain lengths. Accordingly, changes in the FA distribution and composition have a significant impact on lipid metabolism and homeostasis, energy storage and many other lipid-related processes . In mammectively . Two isoectively ,13,14,15ectively ,19,20,21ectively ,23, and ectively  of SCD1.SCD5 gene is largely unidentified, several transcription factor (TF) binding sites in the putative 5′ regulatory region have been predicted in silico that have previously been proved to regulate SCD1 [SCD5 gene, to test the possible FA-sensitivity of its transcription, and to examine the SNPs in the region in silico, in vitro, and in an association analysis involving T1DM and T2DM patients.Unlike SCD1, the second human SCD isoform, stearoyl-CoA desaturase-5 (SCD5), has received considerably less attention. In contrast to SCD1, which is expressed in the tissues of major importance in lipid metabolism (such as liver and adipose tissue) , SCD5 isate SCD1 ,28. The ate SCD1 ,29, is sate SCD1 ,31. Despate SCD1 ,33,34,35ate SCD1 , its polSCD5 gene and examined the functional impact of rs6841081 and rs3811792 SCD5 promoter polymorphisms and their potential association with diabetes. The SCD5 gene expression was found to be insensitive to FAs, and it showed a pronounced tissue-specificity with a much higher promoter activity in the neural cells. The presence of the minor variant of rs3811792 SNP significantly reduced the activity of the SCD5 promoter in vitro and modified the binding probability of several TFs in silico. A statistically significant association of rs3811792 SNP with both T1DM and T2DM was also found, thus supporting the medical relevance of this polymorphism and the complexity of the molecular mechanisms in the development of metabolic disorders.In the present study, we identified the functional promoter region of the Culture medium and supplements were purchased from Thermo Fisher Scientific . Oleate, palmitate, stearate, linoleate, elaidate, vaccenate, bovine serum albumin, HepG2, HEK293T, and SK-N-FI cells were purchased from Sigma-Aldrich . All of the chemicals that were used in this study were of analytical grade. All of the experiments and measurements were carried out by using Millipore ultrapure water.http://jaspar.genereg.net/, accessed on 30 June 2022) [SCD5 promoter that was affected by rs6841081 or rs3811792 polymorphism. Two other online available prediction programs   open-accndex.php ), accessSCD5 upstream regulatory region were amplified using iProof™ High-Fidelity DNA Polymerase  from human genomic DNA template using primers that contain Kpn I and Hind III restriction endonuclease recognition sites. After purification and restriction endonuclease digestion , the amplicons were ligated  into pGL3B vector  that was upstream of the luciferase reporter gene. The studied natural variants were generated using Q5® Site-Directed Mutagenesis Kit  following the manufacturer’s instruction. Mutagenic primers were designed using the online NEB primer design software, NEBaseChanger™. After digesting the original nonmutated and methylated plasmid by KLD reaction, an aliquot of constructs was transformed into XL10-Gold® Ultracompetent Cells , which were then screened for positive colonies by single cell PCR. The cloning and mutagenic primers are listed in Different sized fragments of 5 cells per well) in Dulbecco’s modified Eagle medium (DMEM) which was supplemented with 10% fetal bovine serum and 1% penicillin/streptomycin solution at 37 °C in a humidified atmosphere containing 5% CO2. HEK293T cells were transfected with 0.5 μg pGL3B-SCD5_P1-P4 promoter constructs using 3 μL Lipofectamine 2000  in 1 mL DMEM. HepG2 and SK-N-FI cells were transfected with 1 μg pGL3B-SCD5_P1-P4 promoter constructs using 3 μL Lipofectamine 3000 that was supplemented with 2 µL P3000  in 1 mL DMEM. As a transfection control, 0.5 µg pCMV-β-gal plasmid was cotransfected into each sample. Cells were harvested and processed 24-30 h after transfection.Human embryonic kidney (HEK293T), hepatocellular carcinoma (HepG2) and neuroblastoma (SK-N-FI) cells were cultured in 12-well plates  to a final concentration of 50 mM and conjugated with 20% FA free BSA in 1:4 ratio at 50 °C for 1 h. The working solution for FA treatments was prepared freshly in FBS-free and antibiotic-free medium at 100 µM final concentration. The culture medium was replaced 5 h after transfection. The FA treatment was carried out for 24 h in 12-well plates.Cells were washed twice with PBS and harvested in 100 µL Reporter lysis buffer  was scraping and briefly vortexed. A single freeze–thaw cycle was followed by centrifuging in a benchtop centrifuge . Supernatants were used for enzyme activity determination.β-galactosidase activity of 20 µL cell lysates was measured by using o-nitrophenyl-β-D-galactopyranoside  cleavage rate. Luminescence was detected using a Varioskan multi-well plate reader . Values for luciferase activity were normalized to β-galactosidase activity (measured by standard protocol using the same Varioskan plate reader in photometry mode). Each experiment was repeated three times independently, and each sample was studied in triplicate.Luciferase activity was detected using the Luciferase Assay System kit  by adding 15 μL Luciferin reagent to 5 µL of all of the cell extracts. TM SYBRTM Green Master Mix, and 0.5 µM forward and reverse primers using QuantStudio 12K Flex Real-Time PCR System . SCD5 sequences were amplified by 5′ ATG GAA ACC GGC CCT ATG AC 3′ and 5′ CCC CAG CCA GCA CAT GAA AT 3′ primer pairs. GAPDH cDNA was also amplified as an endogenous control using 5′ GTC CAC TGG CGT CTT CAC CA 3′ and 5′ GTG GCA GTG ATG GCA TGG AC 3′ primers. The first step of the thermocycle was an initial denaturation and enzyme activation at 95 °C for 2 min. It was followed by 40 cycles of 95 °C for 15 s, 55 °C for 15 s, and 72 °C for 1 min; measurement of the fluorescent signal was carried out during annealing. Reactions were performed in triplicates, and a reaction mixture with RNase-free water instead of template cDNA was employed as non-template control. Relative expression levels were calculated as 2C−ΔT, where ΔCT values corresponded to the difference of the CT-values of the endogenous control and target genes.Total RNA was purified from HepG2, HEK293T and SK-N-FI cells by using RNeasy Plus Mini Kit  following the manufacturer’s instruction. Concentrations were measured using NanoDrop1000 spectrophotometer. To assess the integrity and purity of the isolated total mRNA samples, the ratios of their absorbance at 260/280 and 260/220 nm were determined, and they were also analyzed by agarose gel electrophoresis to visualize bands corresponding to 28S and 18S rRNAs, respectively. Human tissue RNAs were purchased from Thermo Fisher Scientific . cDNA samples were produced by reverse transcription of 0.5 µg DNA-free RNA using SuperScript III First-Strand Synthesis System for RT-PCR Kit . Quantitative qPCR assay was performed in 20 µL final volume containing 5 µL 20× diluted cDNA, 1× PowerUpβ for rs6841081: 0.0690, 1-β for rs3811792: 0.2866) and 253 patients that were diagnosed with type 2 diabetes mellitus  in the 2nd Department of Internal Medicine, Semmelweis University were recruited in the study. The control group consisted of 350 volunteers without medical history of any metabolic disease . The diagnosis of diabetes was made based on fasting blood sugar values, oral glucose tolerance test (OGTT), and HbA1C value according to WHO regulations. Individuals with autoimmune, infectious, or metabolic disorders other than type 1 or 2 diabetes were excluded from the study. Genetic analysis of the participants was approved by the Local Ethical Committee . Participants signed written informed consent documents before sample collection was performed for genetic analysis to take place. In order to avoid the risk of spurious association due to population stratification, only subjects of Hungarian origin were included to ensure the comparison of homogenous populations. Buccal epithelial cells were collected using swabs. The first step of the DNA isolation was the incubation of the buccal samples at 56 °C overnight in 0.2 mg/mL Proteinase K cell lysis buffer. Subsequently, proteins were denatured using saturated NaCl solution. DNA was then precipitated using isopropanol and 70% ethanol. DNA pellet was resuspended in 100 µL 0.5× TE buffer . Concentrations of the samples were measured using NanoDrop1000 spectrophotometer.One hundred and forty-five patients that were diagnosed with type 1 diabetes mellitus . qPCR assay was performed in 5 µL final volume containing approximately 4 ng genomic DNA, 1× TaqPath™ ProAmp™ Master Mix, and 1× TaqMan® SNP Genotyping Assay using QuantStudio 12K Flex Real-Time PCR System . Thermocycle was started by activating the hot start DNA-polymerase and denaturing genomic DNA at 95 °C for 10 min. This was followed by 40 cycles of denaturation at 95 °C for 15 sec, and combined annealing and extension at 60 °C for 1 min. Real-time detection was carried out during the latter step to verify the results of the subsequent post-PCR plate reads and automatic genotype calls.Rs6841081 and rs3811792 polymorphisms of the p < 0.05 value were considered to be statistically significant. Genotype–phenotype association was assessed by χ2-test comparing the genotype distribution of the patient and the control groups . Odds ratios were calculated by comparing the groups with and without the risk allele. The level of statistical significance was adjusted after Bonferroni correction. The statistical power for both patient groups and for both SNPs was calculated based on a likelihood ratio test framework using the additive model option [Relative luciferase activities and mRNA levels are presented in the diagrams as mean values ± S.D. and were compared by ANOVA with Tukey’s multiple comparison post hoc test using GraphPad Prism 6 software. Differences with a l option .SCD5. Four increasingly larger sizes of DNA segments of the 5′ regulatory region were cloned into the pGL3B luciferase reporter vector, the exact lengths and positions of these are shown in The first aim of our work was to identify the functional promoter of SCD5 promoter constructs and the pCMV-β-gal vector were transiently transfected into HepG2, HEK293T and SK-N-FI cells, and the luciferase activity of the cell lysates was measured and normalized to β-galactosidase 24-30 h after the transfection. All four of the promoter constructs presented significantly higher relative luciferase activity than the promoterless pGL3B did, but the 1040 bp construct SCD5_P3 showed the highest activity in each cell line  in the luciferase assay, but to ensure the reliability of the model, we first tested the possible effect of these FAs on the luciferase activity using HEK293T cells that were transfected with the control pGL3B vector. A mild FA sensitivity was observed, and a significantly higher luciferase activity was detected while it was in the presence of stearate in comparison to that of the untreated sample  are located in the promoter of SCD5 promoter activity when it was compared to that of rs6841081_G/rs3811792_T, but this was statistically significant only in the HEK293T cell line  of the two polymorphisms were created by a site-directed mutagenesis in the SCD5_P3 promoter construct, and their impact on the relative luciferase activity was examined in the HEK293T and SK-N-FI cells B,C. The ell line B. In sumSCD5 gene was analyzed in silico using the JASPAR transcription factor binding site prediction program. Specifically, we addressed the question of whether the exchange of the two nucleotides that were affected by the polymorphisms could cause a predictable change in the binding probability of any of the TFs in this region. During the analysis, two 41-nucleotide long DNA sections were compared for each SNP, in which either version of the polymorphic nucleotide was located at position 21.The possible impact of the two SNPs on the TF binding sites in the promoter of the In the first step, the matrix of all (949) of the TFs that were included in the JASPAR database was compared with the DNA sequences that are described above. In order to find all of the possible TF binding sites, the TF binding probability was set to the lowest value (1%) that was allowed by the software. More than 56,300 hits were obtained  for bothBy definition, the vast majority of these were very low probability hits. In the second step, the hit list was narrowed to identify the most relevant TFs. The TFs that were retained were those whose binding probability showed at least 15% difference between the two variations of the given polymorphism. Thus, the list of TFs was reduced to 438 for rs6841081 SNP and to 372 for rs3811792 SNP . HoweverThe binding probabilities of the SPI1, MEIS3, SOX18, and NFIA factors are increased by the presence of the minor polymorphic T allele  are predicted to bind more strongly to the minor alleles containing the T nucleotide, while in the case of five TFs , the same T allele reduces the likelihood of an interaction.SCD5 polymorphisms according to the in silico analyses are shown in The exact binding positions of the TFs that were affected by the two In the case of the rs6841081 SNP, TFAP2A was also confirmed to be present by the PROMO TF binding site search database, which is available online A. The NFχ2-test: p = 0.9769 for rs6841081, p = 0.9669 for rs3811792). The frequency of the minor rs6841081 SNP allele was 1.1% in the control population, which is in agreement with the European population average as per the NCBI database (0.9-2.8%). The 15.7% frequency of the minor rs3811792 SNP allele was slightly below the European population average (19%).The putative associations between the type 1 or type 2 diabetes mellitus and the rs6841081_G/T or rs3811792_C/T SNP were assessed by case–control setup. The observed genotype distributions of the control group for both of the polymorphisms were in accordance with the expected values that were calculated based on the Hardy–Weinberg equilibrium (χ2-test. Since this meant we had to conduct four different tests (two patient groups and two SNPs), the limit of the statistical significance was lowered from p < 0.05 to 0.0125 due to the Bonferroni correction. No association was found for the rs6841081 polymorphism either with T1DM or with T2DM  that provides a maximum amount of transcriptional activity and was identified as the functional promoter [SCD1 gene expression have been already identified [SCD1 gene [SCD5 are available. A number of TF binding sites at the 5′ regulatory region of human SCD5 indicate that C/EBP-α, AP1, SP1, NF-1, NF-Y, T3R, PPAR-a, and SREBP1 may bind to the promoter sequence of the gene [SCD1 [Despite the progress that has been made in the research on SCD5 in recent years, many aspects of the transcriptional, nutritional, and hormonal regulation of this desaturase are still to be elucidated. To understand the exact function of SCD5 and its role in lipid metabolism, it would be necessary to clarify the regulation of its gene expression. The long overdue step toward the identification of the valid regulatory molecules that are involved in it is the mapping of the functional  1000 bp . In addipromoter . Althougentified , and a lCD1 gene , only inthe gene . As the ne [SCD1 , and earSCD5 was not sensitive to the presence of different FAs in our experimental system. This observation is not without precedent, as the diets containing various unsaturated FAs, which have been shown to enhance the expression of SCD1 in cows, left the SCD5 mRNA level unchanged [SCD1, neither the change in the serum lipid level [SCD5 gene. The regulation of SCD1, but not SCD5, is affected significantly by the lipid-derived factors at different levels. It is known that the promoter activity of SCD1 is influenced positively by the SFAs, and it is negatively influenced by the MUFAs and PUFAs [SCD1 gene can stabilize the protein in an FA-dependent manner [However, them having a similar function seems less and less likely in light of the increasingly detailed mapping of the differences between the regulation of the two isoforms. The likelihood of the different transcriptional regulatory mechanisms of the two SCDs is also supported by the fact that the promoter activity of nchanged . A similid level  nor the id level  affectednd PUFAs ,20,21,24nd PUFAs ,43. Furtt manner . AlthougSCD5. It is well known that SCD1 is ubiquitously found in all tissues, but it is more predominantly present in adipose tissue, liver tissue, brain tissue, heart tissue, breast tissue, and lung tissue [SCD5 is primarily expressed in the fetal and adult brain, the pancreas, the gonads, and to a lesser amount, in the kidney tissue, lung tissue, and adipose tissue [The different regulation also raises the possibility of it having a different function, which might be further supported by the significantly different tissue expression of the two isoforms, as well as the cell line-specific promoter activity of g tissue , and whie tissue ,27. DetaSCD5, and it revealed that the T allele of rs3811792 reduces the SCD5 promoter activity in the kidney-derived and neuronal cell lines. Interestingly, not only the SCD5, but also the human SCD1 polymorphisms have been quite neglected, and only a few variants have been characterized so far, and there is no promoter SNP among them, instead there is only the stabilizing effect of a missense variant [Polymorphisms in the promoter region can modify gene expression. The present work is the first to functionally examine the two promoter SNPs of human  variant  and the  variant  have beeSCD5 promoter, was confirmed by several predictive programs, and this polymorphism was also shown to modify the promoter activity and to be associated with diabetes. NFATC2 is a member of the nuclear factor of the activated T-cells family which plays a central role in inducing gene transcription during the immune response. Obesity and obesity-related conditions are associated with changes in the immune system that significantly hinder its ability to mount efficient immune responses [SCD5 gene suggests the presence of several conserved regions for the microRNA families among vertebrates, including two sites for mammals [SCD5, which is a target for this microRNA [Just as certain polymorphisms can affect the microRNA binding sites (see above), other variations may largely modify the TF binding sites in the promoter. The in silico three-step analysis that we performed in the case of both polymorphisms identified that there are TFs whose binding probability is significantly affected by the exchange of the given nucleotide. Among these, NFATC2, which prefers the C allele of the rs3811792 polymorphic esponses . Moreove mammals . Importa mammals . The T-cmicroRNA , therebySCD5 polymorphism with diabetes before, although it would be plausible given the function of SCD1. Based on our result, the genotype frequency of rs3811792 SNP significantly differs from the healthy population both in T1DM, which is primarily caused by autoimmune processes, and in T2DM, which is obesity-related and also characterized by immune response abnormalities and chronic inflammation. It is proved that SCD5 may contribute to the development of T2DM, since SCD5 was identified as a master regulator of fat distribution, which plays a significant role in determining the visceral adipose tissue accumulation, which is a major risk factor for diabetes [p = 0.0029 vs. p = 0.0114). It is also worth noting that in T1DM, the frequency of the TT genotype containing the minor allele increases significantly, while in T2DM, the frequency of CT heterozygotes differs from that of the control group. This can be further evidence for the spectrum nature of diabetes according to the accelerator hypothesis since it is conceivable that while the CT genotype leads to the late onset of the condition in association with other environmental factors, while the TT genotype manifests itself phenotypically at a younger age. In any case, it is certain that the two types of diabetes are complex multifactorial conditions that develop on the basis of several genetic and environmental factors, and so the rs3811792 SNP of the SCD5 promoter may only be one factor in this complex system.The present work is pioneering regarding not only the functional characterization of these factors, but also the association analysis of them, since no one has investigated the association of a single diabetes . On the diabetes ,27,46, eSCD5 expression. Although these results strongly indicate that the TFs that are responsible for the tissue specific activation or repression of SCD5 bind to the upstream promoter, the contribution of possible downstream regulatory elements cannot be ruled out, and a thorough search for the relevant response elements should be extended accordingly. Since the study of the SCD5 promoter and its polymorphisms was performed in a cellular system in vitro, it would be necessary to prove the effect of these human variations on transcription in vivo, as well as to confirm the in silico predicted allele-dependent TF binding by direct methods either in vitro or in vivo. Our findings also showed that SCD5 expression is not sensitive to the different FAs, which is a remarkable difference in comparison to SCD1 expression, and it is likely related to the somewhat different roles of the two isoforms at the cellular and particularly at the organismal level. Although apparently SCD1 and SCD5 catalyze the same biochemical reactions, the formation of unsaturated fatty acyl chains might have significantly diverse metabolic functions in various cells and tissues. Nevertheless, our in vitro findings do not pinpoint the exact nature of these differences, so this intriguing area requires further research. Due to the rather low number of cases that we used and in order to increase the statistical power of the study, the extension of the association analysis to larger control and patient groups should also be considered. Nevertheless, the association that we found between a common SCD5 promoter polymorphism and diabetes mellitus not only extends the list of diabetes-related genes with another item because the cellular defense against lipotoxicity provides a reasonable, yet currently partly speculative functional relationship between FA desaturation and the development of diabetes. Experimental data support that a limited cellular capacity to convert SFAs to unsaturated ones may render β-cells sensitive to FA-induced damages and increase the risk of β-cell failure [β-cells are particularly sensitive to SFAs [The study that is presented here aimed to shed light on SCD5, the so far neglected isoform of human stearoyl-CoA desaturases of potential pathological importance. Outlining the functional upstream promoter region was a necessary first step to investigate the transcriptional control of the gene expression. The maximal degree of promoter activity that was ensured by an approximately 1 kb segment was highly dependent on the cell type, and the pattern closely resembled the tissue specificity of in vivo  failure ,48. This to SFAs ,50, and  to SFAs ,52. A geSCD5 promoter, as well as its tissue expression pattern that is different from that of SCD1, together imply that there is significantly different transcriptional regulation between the two human desaturase isoforms, thereby emphasizing their likely different role in lipid metabolism. In addition, the SCD5 promoter and its polymorphisms may represent a common denominator between T1DM and T2DM, which otherwise have mostly non-overlapping genetic backgrounds, but in a not yet fully elucidated manner. At the same time, these results raise several additional questions that may open new avenues in research to understand SCD5. The identification of protein and lipid components that regulate the tissue- and cell line-specific expression of SCD5 may also be a new research area. Although the role of SCD1 in the development of obesity-related conditions is a relatively clear and widely investigated topic, the potential relationship of SCD5 in diabetes is only now beginning to be noticed.In conclusion, the cell line-specific activity and FA insensitivity of the