CBFβ-MYH11 in primary inv(16) patient blasts, upon expression during hematopoietic differentiation in vitro and upon knockdown in cell lines by multi-omics profiling. Our results reveal that primary inv(16) AML cells share common transcriptomic signatures and epigenetic determiners with megakaryocytes and erythrocytes. Using in vitro differentiation systems, we reveal that CBFβ-MYH11 knockdown interferes with normal megakaryocyte maturation. Two pivotal regulators, GATA2 and KLF1, are identified to complementally occupy RUNX1-binding sites upon fusion protein knockdown, and overexpression of GATA2 partly induces a gene program involved in megakaryocyte-directed differentiation. Together, our findings suggest that in inv(16) leukemia, the CBFβ-MYH11 fusion inhibits primed megakaryopoiesis by attenuating expression of GATA2/KLF1 and interfering with a balanced transcriptional program involving these two factors.The inv(16) acute myeloid leukemia-associated CBFβ-MYH11 fusion is proposed to block normal myeloid differentiation, but whether this subtype of leukemia cells is poised for a unique cell lineage remains unclear. Here, we surveyed the functional consequences of  The CBFs are heterodimeric complexes composed of two distinct subunits, alpha and beta2. The CBF α-subunit is encoded by the RUNX family  and directly contacts the DNA sequence, whereas the non-DNA-binding CBF β-subunit is thought to facilitate stabilizing the DNA affinity of the CBF complex. CBFs are often mutated in acute myeloid leukemia (AML), for example, in t AMLs, characterized by expression of the AML1-ETO fusion gene, or inv(16) AMLs, delineated by the presence of the CBFβ-MYH11 (CM) event3. CBFβ-MYH11 encodes a fusion protein between CBFβ and smooth muscle myosin heavy chain (SMMHC/MYH11), and is associated with AML FAB subtype M4Eo accounting for around 6% of AML cases6. However, our understanding of its roles in leukemogenesis remains incomplete.Core-binding transcription factors (CBFs) have been proposed to shape both stem cell self-renewal and differentiation, and their dysfunction could potentially lead to cancer pathogenesis8. A recent study revealed that CBFβ-MYH11 maintains inv(16) leukemia by obstructing RUNX1-mediated repression of MYC expression, which is featured by the replacement of SWI/SNF for PRC1 at MYC distal enhancers9. However, at which differentiation stage CBFβ-MYH11 blocks myeloid differentiation is still unclear. Mutational analysis of FACS-purified hematopoietic stem cells (HSCs) as compared to leukemia cells confirmed the presence of CBFβ-MYH11 in HSCs, suggesting that the fusion event is involved in setting up a preleukemic cell state10. Further pursuing which differentiation pathway exactly is targeted by the oncoprotein would be needed.Expression of CBFβ-MYH11 is able to disrupt normal myeloid differentiation, predispose for AML initiation, and cause full leukemia transformation upon the acquisition of additional genetic changes12. Our previous findings have shown that a variety of cell surface markers increase in expression levels upon knockdown of CBFβ-MYH11 in the inv(16) cells, including those for the monocytic and megakaryocytic lineages11. In addition, mouse studies revealed that expression of the CBFβ-MYH11 protein causes abnormal erythropoiesis and gives rise to preleukemic pre-megakaryocyte/erythrocyte progenitors13. Overall, these results potentially implicate a role of the CBFβ-MYH11 fusion in skewing cell differentiation orientation.At the molecular level, CBFβ-MYH11 in a complex with RUNX1 acts as a transcriptional regulator, which can depending on local genomic context, activate and repress genes involved in self-renewal, differentiation, and ribosomal biogenesisCBFβ-MYH11 specifically blocks megakaryocyte/erythrocyte differentiation in the context of human hematopoiesis, and further probe its molecular mechanisms, we analyzed multiple transcriptomic and epigenomic profiles of inv(16) AMLs, several normal hematopoietic cell types and in vitro single-oncogene models. Our findings reveal a clustering of inv(16) AMLs towards megakaryocytes and erythrocytes based on DNA accessibility and H3K27ac-based super-enhancer (SE) profiles. Further molecular exploration indicates that CBFβ-MYH11 seems to be involved in interfering with normal differentiation through transcription deregulation and occupancy replacement of the transcription factors GATA2 and KLF1. Together, these results suggest that controlled expression of KLF1 and GATA2 expression is essential for inv(16) AML development.To investigate whether 11, and then subjected to high-throughput transcriptome and chromatin immunoprecipitation (ChIP) sequencing for histone marks, CBFβ-MYH11 fusion, RUNX1, and GATA2 as described in the Leukemic samples were either obtained from bone marrow or peripheral blood for subsequent processing. Patients cells and cell lines were processed through multiple steps as previously reportedCell culture, flow cytometry, cytospin, differentiation of iPSCs towards the granulocytic lineage, nuclear extraction preparation, pulldown, and mass spectrometry analysis were performed as detailed in the 14 and removal of PCR duplicates by Picard MarkDuplicates option (http://broadinstitute.github.io/picard/), peak calling of CBFβ-MYH11 fusion, RUNX1, and GATA2 ChIP-seq was conducted using MACS1.3.315 at a p-value cutoff of 10−6. For DNA accessibility and H3K27ac data in inv(16) patients, the detailed analyses procedure was described as before16.After read mapping to the hg19 reference genome using BWA17 to predict SEs.All H3K27ac peaks identified were filtered to exclude regions within ±2.0 kb around transcription start sites (TSSs), and then used as input for the ROSE algorithmhttp://genome.ucsc.edu).Read counts for each putative region were enumerated and then normalized to RPKM (reads per kilobase of gene length per million reads) for visualization in heat maps or boxplots. For each base pair in the genome, the number of overlapping sequence reads was determined, averaged over a 10 bp window, and visualized in the UCSC genome browser .Motif discovery was performed using GimmeMotifs19, and subsequently normalized to RPKM values for all RefSeq genes using tag counting scripts. Gene-level count matrix was used as input for DESeq2 package20 to distinguish differentially expressed genes between any two groups. Significant genes were determined by a fold change cutoff of 1.5 and adjusted p-value of 0.01.RNA-seq reads were uniquely mapped to the hg19 reference genome using STAR+ progenitor cells (CD34), megakaryocytes (Mega), erythrocytes (Ery), and monocytes (Mono). Unsupervised principal component analysis (PCA) revealed that inv(16) AMLs displayed different transcriptomic landscapes as compared to normal lineages  or mature cells such as megakaryocytes (PC2).To examine the transcriptional differences between inv16) AML patients expressing CBFβ-MYH11 and normal hematopoietic cell types, we used RNA-seq and compared global gene expression levels between AML blasts and normal CD346 AML pat+ progenitors, while the inv(16) genes expressed in C3 resembled more closely a Mono signature. Furthermore, the primary inv(16) blasts shared a subset of gene signatures with Mega/Ery as shown in the C5 and C7 cluster  were also differentially expressed in the comparison of normal cell types versus inv(16) AMLs  markers. Here, we identified 236 CD markers differentially expressed between inv(16) and normal cells. Our previous studies showed altered transcriptional activity of CD markers upon transient knockdown of CBFβ-MYH11 in ME-1 cellsMLs Fig. , suggestMLs Fig. . HoweverGFI1B, RUNX1, and GATA2  blasts expressed higher levels of GFI1B as compared to Mono, and similar to CD34 progenitors  AML cells and compared those to profiles created in Mega, Ery, and Mono. In addition, we downloaded public ATAC-seq data22, which showed high consistency with DNaseI-seq  and hierarchical clustering results based on DNA accessibility showed robust classification of cell types and differentiation trajectory , Mega, Ery, and Mono demonstrated high-quality H3K27ac-binding patterns and cell-type-specific SEs profiles, for example at the GATA2, PF4, and IRF8 loci  cell lines and primary inv(16) AML blasts is that they harbor many additional mutations. To exclude the disturbance of other genetic lesions, we utilized an in vitro iPSC-based hematopoietic differentiation system in which the expression of a single oncogene can be induced with doxycycline (dox), as successfully conducted in our previous studyH11 Fig.  and we eH11 Fig. , allowinH11 Fig. . In cont26)  cell line based on the inv(16) cell line ME-126) Fig. , and furved Fig. . The latved Fig. . To provved Fig. . Furtherved Fig. , again sved Fig. . Togethe29.Given that altered transcriptional levels are a reflection of epigenetic changes, we performed H3K27ac ChIP-seq (positively correlated with gene expression) on control and CBFβ-MYH11 knockdown cells, and inspected differential H3K27ac peaks (>100 tags and two-fold difference). A total of 2309 differential regions were identified, around 16.2% of them were covered by SEs from inv(16) AML patients. The genes associated with regions showing increased acetylation after knockdown were functionally related to megakaryocyte differentiation and platelet formation Fig. , while gGiven that we observed significant changes in transcription and H3K27ac occupancy after CBFβ-MYH11 knockdown, we set out to further excavate its regulatory mechanisms. As CBFβ-MYH11 binds the RUNX1 protein, it potentially interferes with the normal RUNX1-regulated gene program. To investigate the proteins which might be implicated in altering the transcriptional program, we performed DNA pull-down experiments using a specific nucleotide sequence bound by CBFβ-MYH11 that contains the RUNX1 core consensus motif TGTGGT (RUNX1 oligo), in control and CBFβ-MYH11-knockdown ME-1 cells Fig. . The priWe could show that the oligonucleotide with the RUNX1 motif efficiently pulled down CBFβ-MYH11 as well as RUNX1 and CBFβ from an ME-1 cell lysate Fig. , whereas30, using extracts derived from CBFβ-MYH11-knockdown ME-1 cells grown in light (L) or heavy (H)-labeled medium, incubated with oligonucleotides containing the RUNX1 motif (see Methods section). Of the >1300 identified proteins at a high confidence level, only a limited number displayed highly significant SILAC-ratios (>2) as CBFβ-MYH11 interactors. The CBFβ-MYH11 complex seems to facilitate the recruitment of MYH9 and MYL6 proteins to RUNX1 sites, as shown by their enrichment in the pull-down assay from ME-1 lysates  cells, and also examined the RUNX1-binding profile in parallel. The genome-wide screen indicated that GATA2 occupied similar genomic regions as RUNX1 at most locations. Quantifying GATA2 occupancy at RUNX1 loci revealed 2410 sites with increased GATA2 signal and only 25 reduced binding sites. The 2410 regions showed increased RUNX1 occupancy but reduced CBFβ-MYH11 binding Fig. , and ass31. Here, global transcriptional analysis identified a total of 367 genes increased and 171 genes decreased in transcriptional levels after GATA2 overexpression  based on relative expression ratio, and only showed the overlap of 20 genes (5.4%) increased in expression and 19 genes (11.1%) decreased. These results suggest that enforced GATA2 expression alone can partly reboot the gene program involved in megakaryocyte-directed differentiation, despite insufficiency to completely mimic CBFβ-MYH11 knockdown.To probe whether enforced GATA2 expression is sufficient to switch on this gene program, we transduced ME-1 cells with a GATA2 expression construct and performed global RNA-seq analysis. During hematopoiesis, overexpression of GATA2 shows a decrease in cell proliferation and induces differentiation toward the megakaryocyte lineageion Fig. . As expeTA1 Fig. , and werTogether, these findings suggest that activation of the GATA2-involved regulatory program after CBFβ-MYH11 knockdown is central but not sufficient in driving further differentiation, which is potentially orchestrated in collaboration with other factors like KLF1 and/or EGR1.CBFβ-MYH11 fusion arising from inv(16) rearrangement was reported to lead to differentiation blockage of normal myeloid cells and result in AML, but whether this fusion blocks specific cell commitment has not been discerned. Here, we compared the global landscapes of gene expression, DNA accessibility, and H3K27ac between primary inv(16) AML blasts and normal cell types, and further investigated the functional contributions of CBFβ-MYH11 and its involved regulatory program in vitro.The 32, but pinpointed towards unique gene expression programs underlying inv(16) AML cells. Further epigenomic analyses indicated more shared epigenetic determiners between inv(16) AML blasts and Mega/Ery cells, suggesting that primary inv(16) AML cells might be epigenetically primed for Mega/Ery differentiation with some key transcriptional pathways blocked. Therefore, in inv(16) leukemogenesis, the CBFβ-MYH11 fusion might skew leukemic blasts towards the Mega/Ery phenotype by epigenetic predisposition33 or be involved in setting up a specific Mega/Ery differentiation block by altering the cells gene program.Comprehensive transcriptomic exploration in vivo not only consolidated our previous findings11. Here, we used in vitro models with a single mutation (expression of CBFβ-MYH11) for surveying the role of CBFβ-MYH11. Using an iPSC system with dox-inducible CBFβ-MYH11 revealed that this fusion is able to specifically block in vitro Mega/Ery differentiation, but hardly has any effects on granulocyte and monocyte maturation. This finding suggests expression of CBFβ-MYH11 affects specific cell differentiation pathways.We have shown previously that CBFβ-MYH11 could activate transcription of self-renewal genes, and also repress expression of differentiation markers in the context of the cell line model ME-134. We found that GATA2 and KLF1 showed elevated expression levels11 and also acted as significant interactors of RUNX1 after CBFβ-MYH11 knockdown, suggesting that CBFβ-MYH11 alters normal transcriptional programs of the two regulators and competitively takes over their binding sites at RUNX1 occupancy loci. GATA2 and KLF1 exert key effects in the Mega/Ery lineage fate decision via interaction with other modulators37. Our RNA-seq analysis revealed attenuated expression levels of GATA2 and KLF1 in inv(16) blasts as compared to Mega/Ery, and that GATA2 overexpression could partly reboot a megakaryocyte-like gene program. As such, in line with previous reports38, weak expression of GATA2 might be essential for inv(16) leukemia, and responsible for partial myelomonocytic differentiation featured by occasional cells of “hybrid” nature (nuclear characteristics of monocytes and both basophilic and eosinophilic granules), but increased GATA2 levels are needed for further differentiation. Focusing on GATA2, ChIP-seq illuminated its transcriptional activation role at these RUNX1-dependent target genes by increased recruitment of histone acetyltransferase activity and putative other TFs like EGR1 (refs. 41). Consequently, the data suggest that the GATA2-involved binding/regulatory program might be obstructed by the CBFβ-MYH11 fusion, leading to block of differentiation towards Mega/Ery in inv(16) leukemogenesis.Previous studies have proposed that CBFβ-MYH11 impairs normal binding of other proteins due to the higher affinity with RUNX1, and alters expression of RUNX1-dependent target gene sets42. High transcription of GATA2 has been reported to solely promote megakaryocyte differentiation and suppress erythroid maturation43. In our study, GATA2 overexpression boosted expression levels of some typical marker genes driving Mega differentiation but did not display a strong correlation with results from CBFβ-MYH11 knockdown. This finding reveals that CBFβ-MYH11 interferes with coordinated orchestration of a precise balance of multiple factors in maturing Mega/Ery, but the enforced expression of GATA2 only recapitulates megakaryocyte differentiation during bifurcation of the two lineages. As a consequence, GATA2 alone is not sufficient to inhibit CBFβ-MYH11-caused leukemia, and it maybe has greater functional relevance only in context with overexpression of other regulators like KLF1.Megakaryocyte and erythrocyte share plenty of common molecular signatures, but the two cell types also exhibit distinct patterns in subtle regulatory networksGATA2 or other target genes.In summary, our study suggests that the CBFβ-MYH11 fusion maintains inv(16) AML cells by attenuating expression levels of GATA2 and blocks their further differentiation towards Mega/Ery lineages via interfering with a GATA2/KLF1-involved regulatory network. Collectively, these results corroborate our previous findings, facilitate a better molecular understanding of the role of CBFβ-MYH11 in the pathogenesis of leukemia, and might ultimately help to improve therapy decision of inv(16) AML by designing specific (epi)drugs to reprogram Supplementary Figure 1Supplementary Figure 2Supplementary Figure 3Supplementary Figure 4Supplementary Figure 5Supplementary Figure 6Supplementary InformationSupplementary Table 1Supplementary Table 2


Penicillium chrysogenum (renamed P. rubens) is the most studied member of a family of more than 350 Penicillium species that constitute the genus. Since the discovery of penicillin by Alexander Fleming, this filamentous fungus is used as a commercial β-lactam antibiotic producer. For several decades, P. chrysogenum was subjected to a classical strain improvement (CSI) program to increase penicillin titers. This resulted in a massive increase in the penicillin production capacity, paralleled by the silencing of several other biosynthetic gene clusters (BGCs), causing a reduction in the production of a broad range of BGC encoded natural products (NPs). Several approaches have been used to restore the ability of the penicillin production strains to synthetize the NPs lost during the CSI. Here, we summarize various re-activation mechanisms of BGCs, and how interference with regulation can be used as a strategy to activate or silence BGCs in filamentous fungi. To further emphasize the versatility of P. chrysogenum as a fungal production platform for NPs with potential commercial value, protein engineering of biosynthetic enzymes is discussed as a tool to develop de novo BGC pathways for new NPs. Penicillium notatum, the genus Penicillium has been deeply studied for its capacity to produce a wide range of natural products (NPs) (secondary metabolites), many of them with biotechnological and pharmaceutical applications. P. chrysogenum (recently renamed as P. rubens) is the most relevant member of more than 354 Penicillium species that constitute the genus   showed reduced levels of proteins related to secondary metabolism in the higher penicillin producer strains  in addition to the penicillin cluster, most of which have only be poorly studied and remain to be characterized  . The CSIompanies , and thiompanies . As conss region . Althoug strains . Genome Penicillium chrysogenum produces a broad range of secondary metabolites such as roquefortines, fungisporin (a cyclic hydrophobic tetrapeptide), siderophores, penitric acid, ω-hydroxyemodin, chrysogenin, chrysogine, sesquiterpene PR-toxin and sorbicillinoids, but likely also possesses the ability to produce other compounds not detected before. For most of the identified compounds, the responsible BGCs are unknown. The development of new bioinformatics tools   and NRPS (260)   and the tiSMASH) . RecentlPS (260) . In P. csynthase  . They have certain distinct properties in common, the most striking one being their structural division in domains and modules, which is manifested in their shared evolutionary history . Every eIn comparison to most ribosomally derived peptides, NRPs are low molecular weight products. The structural diversity of NRPs is tremendous, mostly due to their chemical complexity. Significantly contributing to this diversity is the fact that NRPS are not only reliant on proteinogenic amino acids, but up until now more than 500 substrates were identified, which serve as NRPS building blocks . These mStructurally, every NRPS module, initiation (1), elongation (n) or termination (1), requires a minimal set of domains Figure  Stachel. The twotype I NRPS when the modules are arranged on a single protein, while the type II NRPS are independent proteins in an transient manner during the NRP synthesis n-1-Te/C, where n represents the number of amino acids in the peptide. In this linear NRPS, the order and number of modules correlates with the amino acid sequence in the NRP and thus it is possible to predict the product that will be formed. Usually, in fungal NRPSs the cyclisation reaction is performed by a specialized C domain instead of Te domain. Since each module catalyzes one cycle during the chain elongation of the nascent NRP due to its specific activity, this system is considered analogous to type I PKS. In fungi, the most prominent examples of this type of NRPS are ACV synthetases (β-lactams), cyclosporin synthetases (Cyclosporin A) and peptaibol synthetases  , which is achieved through the repeated use of two modules. Other examples of type B NRPSs are the siderophore synthetases, which only contain three A domains that catalyze the biosynthesis of ferrichrome n-1 organization contained in linear NRPSs. Likewise, in these synthetases the module arrangement does not correspond to the amino acid sequence in the NRP. Unlike type A NRPS, in type C NRPSs the non-linear peptide is produced by a branch-point synthase and contains uncommon cyclization patterns. Another important difference is that non-linear NRPSs can incorporate small soluble structures, such as amines into the rising NRP through specialized C domains (Theses enzymatic machineries can be classified as ynthesis . A NRPS ynthesis  yieldingynthesis . To enabynthesis . To dateynthesis . The typic acid) . The typtructure . An examrichrome . In type domains . Capreom domains . In contAny NRPS module minimally consists of an A- and T-domain , enabling single module functionality and multi-modular functionality upon addition of C domains . They arC-domains are approximately 450 residue NRPS domains, representing a highly versatile class of NRPS domains. Any NRPS composed of more than one module must consequently contain at least one C-domain. However, also single modular NRPS may contain C-domains, especially if they cooperate with other NRPS. Essentially, the primary target of a C-domain is the condensation of the up- and downstream activated substrates through a nucleophilic attack, mainly leading to the formation of an n-peptide linked via a peptide bond. Nonetheless, several residues of the C-domain may have the intrinsic potential to fulfill multiple functions .The E-domains are among the most abundant modification domains intrinsic to NRPS. In contrast to the structurally similar C domains they are responsible for the site specific epimerization of a substrate, predominantly performing this function after peptide bond formation has occurred .The thiotemplate based enzymatic systems rely on a catalytic activity in order to remove a product or product-scaffold of the primary enzyme. Therefore, most NRPS contain a domain on their C-terminus responsible for precisely this purpose, the thioesterase domain (Te). Te-domains are a common commodity in single and multi-modular NRPS, although, in multi-NRPS systems only the terminal NRPS contains this domain . AdditioS-adenosylmethionine to N (N-MT), C (C-MT), O (O-MT) or for certain residues S (S-MT) atoms resolving around the amino acids Cα carbon , oxygenation (Oxy) as well as methyl-transferase (MT). These domains have been characterized to the extent of classifying their functions, although, especially Cy- and Oxy-domains may occur as a singular bi-functional unit or in a serial manner, respectively . Cy- andα carbon  and in cectively .P. chrysogenum 10 NRPS have been identified , antifungal (amphotericin B), immunosuppressant (rapamycin), antitumor (geldanmycin) and hypolipidemic (lovastatin)  was revived only as late as the 1950s by the work of Arthur Birch on the aromatic polyketide-6-methyl salicylic acid from astatin) . Their aastatin) .In addition to the NRPSs, PKSs are the main enzymes that build the structural scaffold of a wide range of secondary metabolites and NPs in plants, bacteria, insects and fungi . UsuallyType I PKSs are mainly found in bacteria and fungi. These multidomain proteins can be further subdivided in two categories: modular and iterative (Modular type I PKSs or non-iterative PKSs are unique for bacteria and are characterized by presenting a sequence (or set) of modules, each constituted with a set of specific catalytic domains. In consequence, the number of precursors fused in the PK is equivalent to the number of modules which are present  catalyzes around 35 reactions to produce dihydromonacolin L, an intermediate in the lovastatin biosynthesis (highly reducing (HR), non-reducing (NR) and partially reducing (PR) PKS  produce the linear or cyclic scaffold of some compounds such as fumonisins, T-toxins, solanapyrone E, squalestatin or/and lovastatin  typically, consist of six catalytic domains that are covalently associated and arranged in four components: loading (SAT), chain extension (KS-MAT-PT-ACP), cyclisation and processing components (TE-CLC) ((TE-CLC) .Type II PKSs are unique for bacteria and use a similar iterative mechanism as observed in iterative type I PKSs. However, the different catalytic domains are encoded by independent genes. In general, they often constitute a “minimal PKS,” which comprises of two KS units (KSα and KSβ) and an ACP protein that holds the growing PKS chain. The KSβ domain defines the length of the PK chain. The folding pattern of the poly-β-keto intermediates is determined by optional PKS units such as aromatases, ketoreductases, and cyclases. Other tailoring modifications are performed by oxygenases, methyl and glycosyl transferases. Known metabolites synthetized by type II PKSs are tetracyclines, anthracyclines and aureolic acids  before it is transferred to the ACP domain for the chain elongation cycle . This prholo-ACP (active) form is generated by the phosphopantetheinyl transferase enzyme (PPTase) through a post-translational modification of ACP whereby a 4′-phosphopantetheine (4′-PP) moiety from CoA is transferred to the conserved serine  using NADPH . Additiosyn or anti) at the β-hydroxy acyl chain position thereby producing trans double bonds  . This domain catalyzes water elimination (via oieties) .The ER domain is an optional tailoring unit involved in the final oxidation state of the growing PK. It reduces α,β-enoyl groups and thereby generates saturated α–β bonds. This reaction involves NAD(P)H as hydride donor in a Michael addition type of mechanism. In the enoyl reduction, the products formed during this reaction have a specific stereochemistry  or  due to the β-carbon attack performed by the pro-4R hydride of NADPH, contrasting the KR domain that utilizes the pro-4S hydride .Termination of PK biosynthesis involves the Te domain, which produces macrolactones via intramolecular cyclization or linear PKs by hydrolysis . In bothnon-reducing PKS, the ACP transacylase (SAT) domain acts as starter unit that loads the ACP whereupon chain extension is mediated for KS and AT domain. During this process, the malonyl-CoA:ACP transacylase (MAT) domain transfers the extension units from malonyl-CoA to the ACP, while the product template (PT) domain stabilizes the reactive poly-β-keto intermediates. The processing component acts after the initial assembly when the cyclized or PK intermediate is still attached to the ACP. Final cyclization and release is catalyzed by the Te/Claisen cyclase (CLC) domain (In ) domain .P. chrysogenum, 20 PKS genes have been identified  although less abundant as compared to Basidiomycota . Fungal Aspergillus, Penicillium, Claviceps, and Neosartorya, ABBA-type PTs are involved in the biosynthesis of a range of toxins  converts the product of a NR-PKS  as part of an earlier step in the dehydroaustinol/austinol biosynthesis pathway (In filamentous fungi such as f toxins . For thef toxins . In A. n pathway .prx1 to prx4 gene cluster involved in the biosynthesis of PR-toxin in P. roqueforti was cloned and sequenced. This cluster contains the gene prx2 (ari1) that encodes for a aristolochene synthase which forms a sesquiterpene aristolochene derivative (precursor of PR-toxin). Interestingly, an orthologous gene cluster was identified in P. chrysogenum (Pc12g06300 to Pc12g06330), as part of BGC of eleven genes, which is also involved in the biosynthesis of PR-toxin  or substrate protonation (class II) . A relevPR-toxin .Streptomyces. With respect to antibiotics, most of the chemical scaffolds used today were discovered during the golden age of antibiotics discovery (1940–1960s). This was followed by four decades during which hardly any new scaffolds from a natural source were developed  and it is estimated that the majority of these compounds are derived from filamentous fungal sources and from filamentous bacteria belonging to the genus eveloped . Howevereveloped . Furthereveloped  were useUnder natural conditions, fungi face a variety of biotic and abiotic conditions to survive. The cellular response to the environment involves complex regulatory networks that respond to stimuli such as light, pH, availability of carbon and nitrogen sources, reactive oxygen species, thermal stress, and interspecies-crosstalk .A. terreus  and global regulators up to epigenetic regulation involving the modification of the chromatin landscape . Additionally, global regulators also act on genes that do not belong to secondary metabolism . Global loss of aflR expression-A) was identified in 2004 as a global regulator in Aspergillus. Deletion of this gene results in the repression of many BGC, such as the one responsible for the production of penicillin, lovastatin, and sterigmatocystin. Overexpression of LaeA causes an opposite phenotype. Interestingly, LaeA is negatively regulated by AflR  in a feed loop mechanism (S-adenosyl methionine (SAM)-binding site with a novel S-methylmethionine auto-methylation activity, although this activity does not seem to be essential for its function. LaeA is not a DNA-binding protein, but it does affect chromatin modifications. In an A. nidulans ΔlaeA strain, high levels of the heterochromatin protein 1 (HepA) are detected and an increase in trimethylation of the H3K9 in the sterigmatocystin cluster. When LaeA is present, the levels of HepA, ClrD (H3K9 methyltransferase) and H3K9me3 decrease while the sterigmatocystin levels are raised. The heterochromatic marks stay until the sterigmatocystin cluster is activated, and apparently LaeA influences the offset of these marks in this particular cluster , which regulate the pathway. In A. fumigatus, veA regulates 12e BGCs  and these regulators have recently been associated with the production of secondary metabolites in filamentous fungi. In A. nidulans, overexpression of RsmA  has a compensatory effect on secondary metabolism in a strain in which LaeA and veA are missing. However, these transcription factors also display negative regulation. For instance, an increase in the biosynthesis of aflatoxin and chratoxin has been observed when yap1 is deleted in A. parasiticus and A. ochraceus (A. nidulans. Its function is associated in nitrogen regulation and has a negative effect on the biosynthesis of aflatoxin in A. flavus and bikaverin production in F. fujikuroi (Basic leucine zipper (bZIP) transcription factors are highly conserved in the eukaryotes. The dimeric bZIP transcriptional factors play an important role in the cellular responses to the environment. Regarding their structure, they contain a conserved leucine zipper domain and a basic region, which controls the dimerization of the protein and establishes sequence-specific DNA-binding, respectively. Once dimeric, bZIPs target palindromic DNA sequences by two mechanisms: redox and phosphorylation . In fungchraceus . MeaB isujikuroi .2His2 zinc finger DNA binding domains. Likewise, it is involved in the repression of nitrogen metabolism when ammonium or glutamine are present. Recently, this transcription factor and its orthologs have been shown to influence secondary metabolism. For instance, areA deletion strains of F. verticillioides are not able to produce fumonisins on mature maize kernels. In Acremonium chrysogenum, the deletion of areA resulted in the reduction of cephalosporin because of a reduced expression of the enzymes involved in cephalosporin biosynthesis. Additionally, AreA is a positive regulator of the production of gibberellins, trichothecene deoxynivalenol (DON), fusarielin H, beauvericin and zearalenone (2His2 zinc finger transcription factor that is involved in the repression of genes associated with the use of carbon sources other than glucose (Knox and P. chrysogenum CreA represses penicillin biosynthesis and causes a reduced expression of the pcbAB gene that encodes a NRPS involved in this pathway. Mutations in the putative CreA binding site in the pcbAB promoter result in enhanced enzyme expression when cells are grown in the presence of glucose (ipnA promoter (pcbC in other species) of A. nidulans revealed that in this organism repression of penicillin biosynthesis by glucose is independent of CreA  in Beauveria bassiana resulted in a loss of dipicolinic acid (insecticide compound) and oxalic acid production, compounds that reduce the pH of the medium. However, also production of a yellow pigment was noted. When A. nidulans is grown at alkaline pH, PacC modulates the expression of the acvA (pcbAB) and ipnA of the penicillin BGC, while it acts negatively on the expression of the sterigmatocystin BGC  genes  is deleted, cells show an altered hyphal morphology, reduction of growth, reduced pathogenesis and a deregulation of secondary metabolism  genes . Whereastabolism .2Cys6 binuclear cluster domain family (around 90%). With NRPS containing BGCs, the putative transcription factors are more diverse. The Zn2Cys6 family of transcription factors contain a DNA binding domain (DBD) that has two zinc atoms coordinated by six cysteines. There are three sub regions: a linker, a zinc finger and a dimerization domain. Additional to a DBD, these proteins contain two further functional domains, the acidic region and the regulatory domain. These transcription factors can act as monomers, hetero- and homodimers. They recognize single or multiple trinucleotide sequences, commonly CCG triples, in a symmetric or asymmetrical format. The affinity of the DBD for a given DNA stretch is also determined by the nucleotides surrounding this triplet. The transcriptional activity of these proteins is regulated by phosphorylation, exposing the activation and DNA binding domains for DNA binding GCA) that is found in most of the promoters of this BGC, albeit a second binding sequence has been reported that is associated with the autoregulation mechanism of the expression of AflR. The disruption of AlfR abolishes the production of aflatoxin/sterigmatocystin. Likewise, some BGCs encode multiple regulatory proteins. Next to the aflR gene in the aflatoxin cluster resides the aflS (formerly aflJ) gene. The corresponding transcription factor binds to AflR to enhance the transcription of early and mid-biosynthetic genes in the aflatoxin pathway  in A. nidulans, which controls the expression of two pathway associated NRPS genes (inpA and inpB). Surprisingly, two PKS genes (afoE and afoG) and one transcriptional activator (afoA) belonging to the asperfuranone BGC are also upregulated by ScpR, allowing the production of asperfuranone  for the inducible promoter of alcohol dehydrogenase AlcA induced the expression of a silent cluster that contained two NRPS genes (inpA and inpB) and scpR itself. Additionally, it also led to the expression of the asperfuranone BGC, which is normally silent  in a BGC by a strong constitutive or inducible promoter. For instance in y silent . Recentlstrength .promoter replacement approach. Using this strategy, i.e., overexpression of the transcription activator ApdR under control of the alcohol dehydrogenase promoter alcAp, it has been possible to induce the expression of a hybrid PKS-NRPS BGC in A. nidulans. This resulted in the production of aspyridones A and B  leading to the identification of the corresponding products  that binds an octamer of four different core histone proteins  in 1.75 turns. It has been shown that modifications of the chromatin structure  changes gene expression, amongst other genes involved in the biosynthesis of secondary metabolites. Structurally, chromatin represents an obstacle that complicates access of DNA-binding factors to their corresponding binding regions. According to the compaction level, chromatin can be in a dense (heterochromatin) or relaxed (euchromatin) state. These compaction levels are regulated by post-translational modification of the histone proteins by acetylation, methylation, ubiquitination, ethylation, propylation, butylation, and phosphorylation events. Regions that display low transcriptional activity have been associated with the heterochromatic conformation. In contrast, the euchromatic conformation is present in regions with abundant coding sequences and is usually highly active during transcription. Such regions are also linked with hyper-acetylated nucleosomal histones. Likewise, it has been reported that methylation of H3K9, H3K27, and H4K20 are typical markers of the heterochromatin, while in euchromatin methylation occurs at H3K4 .AlfR promoter, thereby affecting the expression of the sterigmatocystin pathway. The deletion of the methyltransferase encoding clrD and ezhB genes in Epichloe festucae, that act on H3K9 and H3K27, respectively (in axenic culture), results in the activation of the ergot alkaloids and lolitrem BGCs. These compounds are necessary to establish a symbiotic association with the plant Lolium perenne. Compass (complex of proteins associated with Set1) which methylates H3K4 in yeast, also impacts secondary metabolism in filamentous fungi. The deletion of one of its components (cclA) in A. nidulans allowed the activation of a cryptic BGC and the production of emodin  analysis revealed that GcnE and AdaB, the catalytic subunits of the complex Saga/Ada, are needed for acetylation of histone H3  in A. nidulans resulted in major changes in the metabolite profile  mediates the transcriptional crosstalk among sorbicillinoids biosynthesis and other BGCs, since a new compound as detected only under conditions of sorbicillinoids production , since this protein needs the di- and tri- methylation of H3K9 for binding to chromatin and to form heterochromatin. Deletion of LaeA allows the unobstructed binding of HepA to the f emodin . Likewisechanism . Other techanism . Usuallystone H3 . Indeed,tin BGCs . In cont profile . HdaA ise effect . In P. coduction .Cladosporium cladosporioides and A. niger underwent a significant change when these strains were exposed to suberoylanilide hydroxamic acid (SAHA), a HDAC inhibitor, allowing the detection of two new compounds, cladochrome and nygerone A, respectively  or at the level of transcriptional regulators  is deleted. This allowed for the overproduction of sorbicillinoids, the reduction of chrysogine related metabolites and the detection of a new compound whose origin still unknown  and ABC superfamily are most commonly encoded by BGCs . Since bat crops . Often, at crops . For exading BGC . Also, tproteins . Furtherproteins ,b.Several approaches have been used to activate the expression of cryptic BGCs in a targeted manner. Usually, this is achieved by manipulation of pathway-specific regulatory genes, or by replacing endogenous promoters for inducible systems or strong promoters . The varP. chrysogenum was based on the use of ku70/80 disrupted strains to improve the homologous recombination instead of the Non-Homologous End Joining (NHEJ) pathway , which catalyzes the last step in the penicillin biosynthesis was amplified from the P. chrysogenum penDE gene and expressed in Hansenula polymorpha , which eventually is integrated in the genome of this fungus proving the uncharacterized potential of P. chrysogenum as heterologous host . Its genome sequence revealed an unexplored potential of P. chrysogenum as a source of NPs , the use of organisms that have been genetically domesticated offers a promising target solution for NP discovery due to the availability of molecular tools for their genetic modification. Here, we have summarized the main approaches that have been applied for P. chrysogenum and other filamentous fungi to bioengineer secondary metabolite BGC pathways which have led to a greater understanding of the main obstacles to be overcome to use this fungus as a generic cell factory. We discussed the main characteristics of the building enzymes (PKS and NRPS) in filamentous fungi. Despite the apparent modular organization, the complexity of these mega enzymes and the inherent interactions between the various domains within their structures has not allowed a straight forward approach for the PKS/NRPS engineering genomes.Despite the progress in genetic engineering and bioinformatics tools to identify BGCs, the main bottleneck to identify potentially interesting compounds has not yet been solved. Bioinformatic tools perform poorly in the prediction of the structures formed, and therefore future discovery programs will mostly dependent on high throughput methods to express foreign pathways and then use advanced metabolomics to identify the novel products. Since such approaches depend on high throughput, further efforts are needed to implement high throughput cloning methods to FG-C and RZ wrote the manuscript. AD supervised, conceived, and designed the manuscript. RB co-supervised the manuscript.RB is an employee of DSM Biotechnology, Delft. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Increasing evidence demonstrates that dysfunctional TBX2 and TBX3 result in outflow tract malformations, implying that both of them are involved in CTD pathogenesis. We screened for TBX2 and TBX3 variants in a large cohort of CTD patients  contains supplementary material, which is available to authorized users. Conotruncal heart defects (CTDs) are a group of complex congenital heart malformations with an estimated prevalence of 0.1% of live births and roughly 10–25% in congenital heart defects (CHD) . In addiThe development of the OFT in the embryonic stage is an elaborate regulatory process, which includes the formation and development of the secondary heart field (SHF) and cardiac neural crest (CNC), during which any abnormal factor of inheritance or environment can lead to abnormal proliferation, differentiation, or migration of SHF and CNC cells, thereby causing CTDs –7. IncreIn genetics, many transcription factors are recognized as major contributors to normal cardiac morphogenesis, including the T-box family of transcription factors . TBX2 anCurrent studies for TBX2 and TBX3 have typically focused on gene knock-out animal models to observe phenotype and explore mechanism; however, they have not investigated whether genetic variants were involved in pathogenesis in populations of CTD patients. Only Pang et al. reported variants  located at the TBX2 gene promoter in a cohort of 324 patients with ventricular septal defects, and the variants reduced the transcriptional activities of the TBX2 gene promoter . TherefoHere, we show several rare heterozygous variants of TBX2 and TBX3 by target sequencing in a cohort of 588 CTD patients without 22q11.2 deletion, but none in population-matched healthy controls. Our data shows that these variants alter mRNA and protein expression of TBX2 and TBX3. We screen PEA3 and MEF2C as novel downstream target genes of TBX2 and TBX3, respectively. Function analyses reveal that the variants of TBX2 or TBX3 may regulate PEA3, MEF2C, and HAS2 (the known downstream gene of TBX2) promoting CTD incidence, first defining the connection between TBX2/TBX3 variants and CTDs and further elucidating the genetic pathogenesis of CTDs.We found variants of TBX2 and TBX3 through target sequencing in 588 CTD patients and identified three variants of TBX2 in seven patients and three variants of TBX3 in six patients, including TOF, TGA, SA, and SV Table . The varhttp://www.uniprot.org/).All variation sites in this study were highly conserved in vertebrates, as shown in multiple TBX2 and TBX3 protein alignments Fig. , b, indiP < 0.05). On Western blot, protein expression of R608W and R616Q variants , consistent with the mRNA expression of these two TBX2 variants; in contrast, protein expression of A192T and A562V variants , indicating that TBX3 variants might lead to protein degradation. Tbx3 is associated with SUMOylation  that may be a conserved mechanism controlling Tbx3 activity [To investigate whether the expression of the TBX2 and TBX3 variants were altered, we performed quantitative RT-PCR and Western blot. Quantitative RT-PCR analysis revealed that mRNA expression of R608W, T249I, and R616Q variants of TBX2 Fig.  and A192nts Fig. , c was dnts Fig. , f were activity , 22. TheTo detect the cellular distribution of TBX2 and TBX3 variant proteins, we carried out immunofluorescence assays that demonstrated that all the TBX2 and TBX3 variant proteins were expressed in the nucleus, as were wild-type TBX2 and TBX3 proteins Fig. , i. The P < 0.05), indicating that these were downstream genes of TBX2/TBX3 in CTD incidence.We selected several genes related to CTDs or OFT development from previous studies  and 2.6 times (P < 0.01), respectively  and 55% (P < 0.01), respectively ; their functions had never been studied before. All these variants were predicted as damaging as per SIFT, Mutation Taster or Polyphen-2. Moreover, TBX2R608W, TBX2R616Q, TBX3A192T, and TBX3A562V showed altered expression and function compared with wild-type TBX2/TBX3. Nevertheless, none of the six variants affected the subcellular expression of TBX2 and TBX3 in nucleus, and it is possible that these variants were not located in the critical region that influenced the nuclear distribution of TBX2 and TBX3 [Identifying rare variants of TBX2 and TBX3 in a large CTD cohort is required urgently; our study found six rare heterozygous variants of TBX2 and TBX3 in 13 patients from 588 sporadic patients with CTDs using target sequencing that included p.R608W, p.T249I, and p.R616Q variants of TBX2 and p.A192T, p.M65L, and p.A562V variants of TBX3, all of which were all highly conserved based on multiple sequence alignment, suggesting that these variants might have important biological functions. Among these variants, TBX3M65L was the novel variant first reported, and TBX2R608W had not been reported formerly in East Asians. The other four variants were reported in Ensemble , connexin 43 (Cx43), and natriuretic precursor peptide type A (Nppa) , 28. Lochttp://www.malacards.org/) as candidates for TBX2 or TBX3 downstream genes and found that mRNA expression of HAS2 and PEA3 in HEK293 cells were elevated substantially after TBX2 overexpression, while TBX3 transfection upregulated MEF2C abundance significantly. The activity of HAS2, MEF2C, and PEA3 luciferase reporter genes was dramatically increased by wild-type TBX2/TBX3 compared with that of blank vectors, providing further evidence that the expression of HAS2, PEA3, and MEF2C was regulated by TBX2 or TBX3. HAS2 has conserved T-box binding sites among promoter regions and encodes hyaluronan synthases 2, the major enzyme responsible for hyaluronan (HA) production in the heart [We screened 12 genes selected from previous studies and the MalaCards database , Mutation Taster (http://www.mutationtaster.org/), and Polyphen-2 (http://genetics.bwh.havard.edu/pph2/). Amino acid substitutions were predicted as damaging when the score was ≤ 0.05 in SIFT or ≥ 0.85 in Polyphen-2. In our study, variants with a minor allele frequency (MAF) < 0.5% were defined as rare [Target sequencing was performed using the Illumina HiSeq 2000 platform for variants in TBX2  and TBX3 . The candidate variants were validated by Sanger sequencing, and the primers were designed for PCR amplification of TBX2 and TBX3. To predict the effects of nonsynonymous variants, we used several bioinformatics criteria including SIFT ( as rare .Homo sapiens (human), Mus musculus (house mouse), Gallus gallus (chicken), Bos taurus (cattle), Canis lupus familiaris (dog), Pan troglodytes (chimpanzee), and Sus scrofa (pig) were downloaded from NCBI (https://www.ncbi.nlm.nih.gov/protein/) and were aligned with ClustalX software to confirm the conservation of TBX2 and TBX3 sequences.TBX2 and TBX3 protein sequences from The TBX2 and TBX3 cDNA plasmid was purchased from Genomeditech. Mutated primers were designed to amplify human TBX2 and TBX3 cDNA according to the protocol provided by the QuikChange SiteDirected Mutagenesis Kit , and then, variant TBX2 cDNAs were cloned into a pCDNA3.1-3xFlag vectors while variant TBX3 cDNAs were cloned into GV141-3xFlag vectors. For recombining luciferase reporter plasmid, a 5′-flanking region of downstream gene promoter was subcloned into Kpn I and Bgl II sites of the pGL3 luciferase reporter-basic vector .HEK 293T cells (Human embryonic kidney cells) were maintained in Dulbecco’s modified Eagle’s medium  with 10% fetal bovine serum  and 1% penicillin-streptomycin . pcDNA3.1-3xFlag-TBX2 and GV141-3xFlag-TBX3 including wild-type and variants were transfected into 293T cells with FuGene HD  according to the manufacturer’s protocol after seeding 24 h.Plasmids were transfected into HEK 293T cells that were seeded in 12-well plates. Cells were harvested 36 h after transfection. Total RNA was extracted with TRIzol reagent , and then, reverse transcription of cDNA was performed using Prime Script RT Master Mix  and was followed by quantitative RT-PCR using SYBR Premix Ex Taq  on an Applied Biosystems 7500 system . The relative quantification of expression was determined using the 2^-△△Ct method , and glyHEK 293T cells were transfected with 1 μg of wild-type and variant plasmid DNA. Cells were harvested 48 h after transfection. For protein degradation experiments, HEK 293T cells were cultured in the presence of 10 mM MG132 solution dissolved in DMSO for 8–10 h before harvest. Then, cells were lysed in RIPA lysis buffer  with PMSF (1:100). The proteins were subjected to 10% SDS-PAGE and were then transferred onto nitrocellulose membranes  and immunostained with rabbit anti-FLAG antibody  and mouse anti-β-actin antibody  at 4 °C overnight. The membranes were incubated with horseradish peroxidase-conjugated anti-rabbit secondary antibody (1:10000) and anti-mouse secondary antibody (1:10000). Immobilon Western Chemiluminescent HRP Substrate  was used for chemiluminescent immunodetection.HEK 293T cells were transfected with 200 ng of wild-type or variant plasmid DNA, 200 ng of luciferase reporter plasmid, and 8 ng of an internal control reporter plasmid (pRL-TK)  in a 48-well plate. The luciferase activity was measured on the Dual-Glo luciferase assay system  following the manufacturer’s protocol after 48 h.HEK 293T cells were seeded onto a 24-well plate covered with slips coated with poly-L-lysine (0.1 mg/mL) for 24 h and were then transfected with wild-type or variant plasmid DNA. Cells were harvested 24 h after transfection. Cells were incubated with rabbit anti-Flag antibody  diluted in PBS containing 5% BSA and 0.1% Triton X-100 at 4 °C overnight and followed by incubation with Cy3-conjugated goat anti-rabbit secondary antibody (1:250). Cell nuclei were stained by 4,6-diamidino-2-phenylindole (DAPI) . A Leica SP8 microscope was used for image analysis.Human embryos of Carnegie 13 stage were acquired after medical termination of pregnancy at Shanghai Xin Hua Hospital. The medical ethics committee of Xin Hua Hospital approved the study. Embryos were fixed overnight in 4% paraformaldehyde in PBS, embedded in paraffin, and sectioned at a thickness of 7 μm. For immunolocalization of TBX3, paraffin sections were incubated with a primary rabbit anti-TBX3 antibody , followed by horseradish peroxidase-conjugated secondary anti-rabbit antibody and DAB .t test. A P value < 0.05 was considered statistically significant.Each assay was performed for three independent biological replicates. The data are shown as the mean ± standard deviation (SD). Statistical differences were evaluated by one-way ANOVA and two-tailed unpaired Additional file 1:Table S1. Frequencies of alleles and genotypes of TBX2 and TBX3 variants in CTD patients and controls. (DOCX 19 kb)


N6-methyladenosine (m6A) can play important roles in regulating messenger RNA (mRNA) splicing, export, stability and translation. Defective mRNA modification through altered expression of the methyltransferase and/or demethylases results in developmental defects and cancer progression. Identifying modified mRNAs, annotating the distribution of modification sites across the mRNA, as well as characterizing and comparing other modification features are essential for studying the function and elucidating the mechanism of mRNA modifications. Several methods including methylated RNA immunoprecipitation and sequencing (MeRIP-seq) are available for the detection of mRNA modifications. However, a convenient and comprehensive tool to annotate diverse kinds of mRNA modifications in different species is lacking. Here, we developed RNAmod (https://bioinformatics.sc.cn/RNAmod), an interactive, one-stop, web-based platform for the automated analysis, annotation, and visualization of mRNA modifications in 21 species. RNAmod provides intuitive interfaces to show outputs including the distribution of RNA modifications, modification coverage for different gene features, functional annotation of modified mRNAs, and comparisons between different groups or specific gene sets. Furthermore, sites of known RNA modification, as well as binding site data for hundreds of RNA-binding proteins (RBPs) are integrated in RNAmod to help users compare their modification data with known modifications and to explore the relationship with the binding sites of known RBPs. RNAmod is freely available and meets the emerging need for a convenient and comprehensive analysis tool for the fast-developing RNA modification field.Dynamic and reversible RNA modifications such as  N6-methyladenosine (m6A), the most abundant modification on mRNA, has been linked to the control of mRNA splicing, export, stability, and translation  is highly enriched at the 5’ untranslated region (UTR) of mRNA (N4-acetylation (ac4C) (N7-methylguanosine (m7G)   and intene (m7G) .6A individual-nucleotide-resolution cross-linking and immunoprecipitation and sequencing) (7G by TRAC-seq (tRNA reduction and cleavage-sequencing)  based technologies has offered an unprecedented opportunity to discover and profile RNA modifications under various conditions, such as MeRIP-seq   and deteuencing)  and m7G- . We believe that it will meet the emerging need for a convenient and comprehensive analysis tool for the fast-developing RNA biology research field.Here, we developed RNAmod, a very convenient web-based platform, for the analysis and functional annotation of mRNA modifications in up to 21 species, including human, mouse, rat, zebrafish, fly, yeast and Arabidopsis, etc. RNAmod uses the commonly used BED format of chromosomal location of RNA modifications as input, which can be generated by almost all site/peak calling tools, such as MACS , exomePehttps://www.gencodegenes.org) for human (hg38 and hg19) and mouse (mm10), while for the other 19 species, the annotation files were retrieved from FTP site of Ensembl genome database (https://www.r-project.org). The reference genomes used for the sequences extraction were stored as BSgenome packages. For the species without an available BSgenome package in Bioconductor (https://www.bioconductor.org), we constructed them using in-house developed programs based on genome sequence download from Ensembl. We split the mRNA sequences into three different parts  and calculated their gene characteristics separately. The characteristics include sequence length, GC content, and minimum free energy, which are used in the comparative characteristics analysis of modified genes. RNAFold  (https://cutadapt.readthedocs.io/en/stable) and FASTX-toolkit (http://hannonlab.cshl.edu/fastx_toolkit). The clean data were then mapped to the reference genomes using hisat2  <0.05’. Based on the identified peaks, the exact m6A positions were predicted by searching consensus RRACH motifs   and mapped to the reference genomes using Tophat2 (v2.1.0)   and the us (GEO)  were firg hisat2  with defg hisat2  with the C or U) . By usinAG motif . The peafrom SRA  were cle(v2.1.0)  with defxomePeak  with defThe overall workflow of RNAmod is shown in Figure In the single case, RNAmod utilizes the commonly used BED format of chromosomal location of RNA modifications as input, which can be generated by almost all modification sites/peak calling tools based on MeRIP-seq, such as MACS , exomePeRNAmod provides users several parameters to flexibly re-define the mRNA features. The first is flank length interval (upstream and downstream), which can be used to define the transcription site/end site genomic regions, translation start/end site, and splicing site transcript regions. The second is the number of bins in which to divide the gene features for coverage plots and mRNA metagene analyses. The third is the parameter controlling the shape of metagene plot curve. The fourth is the length of the motif in the enriched motif identification. Meanwhile, RNAmod allows users to submit a group of genes to define the subset of modified genes used to conduct functional annotations. In the group case, an additional parameter is provided to control whether the intersection or union set in each group is used in the annotation. Notably, all input webpages are organized with examples to help users with correct inputs.http://homer.ucsd.edu/homer) to identify enriched motifs . Finally, based on the genes with modifications or the gene subset intersected from a user submitted list, RNAmod performs various functional annotations, including GO and KEGG pathway for all supported species, and Reactome pathway, Disease Ontology, Network of Cancer Gene, DisGeNET disease genes and MSigDB functional gene sets for human, mouse, rat, zebrafish, fly and C.elegans.RNAmod first extracts different gene features from the reference genome annotations, including (i) genomic regions of 5’UTR, CDS, 3’UTR, promoter regions, downstream regions, transcription start sites; (ii) transcript regions of translation start/end site and splicing sites; (iii) gene characteristics of GC content, length and minimum free energy. Next, based on extracted gene features, RNAmod performs various calculations based on the genomic locations of uploaded modification sites, including the intersection with different gene biotypes, intersection with gene features, modification distribution around specific site boundaries, and motif enrichment for the peaks/locations. For metagene analyses for each mRNA feature or the whole mRNA, after excluding the features with length shorter than the bins number, each gene feature is divided into equal size bins (100 bins by default) and the average number of sites is counted for each bin. For the coverage distribution near specific site boundaries, including transcription start/end sites, translation start/end site, and splicing site, RNAmod calculates the average coverage of peaks/sites for each nucleotide both upstream and downstream of the location. For motif analysis, sequences around modification sites and random genomic regions are extracted from constructed BSgenome package using getSeq function in Biostrings package. Then the extracted sequences are used as input for Homer software   The overall statistics of modifications across different RNA features, with the default priority of CDS, 3’ UTR, 5’ UTR, intron, promoter, and downstream if overlap annotations are found. (ii) The overall statistics of modifications across different RNA biotypes, such as mRNA, miRNA, tRNA, mt-tRNA, and lincRNA. (iii) Plot of modification site coverage at mRNA transcription start/end sites (with 1000 bp flank size as default). (iv) Plot of modification site coverage around translation start/end sites (with 100 bp flank size as default). (v) Plot of modification site coverage at the mRNA 5’ and 3’ exon/intron splicing junction sites (with 100 bp flank size as default). (vi) The coverage of modification sites among different gene features, including promoter, 5’ UTR, CDS, 3’UTR and downstream regions. (vii) The metagene plot of modification sites across whole mRNA. (viii) The top five enriched motifs for modification sites. (ix) The density heatmaps of modifications across transcription start/end site regions. (x) The density heatmaps of modifications across translation start/end site regions. (xi) The GO functional annotation barplots and detailed list of enriched GO terms. (xiii) The pathway functional annotation barplots and detailed list of enriched pathways. (xiii) Detailed lists of modified genes and modification sites. (xiv) JBrowse integration for the visualization of modification sites in comparison to known RNA modifications and RBP binding sites. In the coverage plots, 95% confidence interval (mean ± standard error of the mean × 1.96) is also shown. In the group-case study, besides the basic statistics and site annotation list for each group, the outputs also contain statistics for modification distribution comparison and the overlapping modification sites between groups. In the gene-case study, instead of the comparison between groups, the comparison between input genes and other background genes will be performed, with the output results shown in a similar format to that in the group case. All of the results are shown in interactive tables and figures on the web page, and these are all available for downloading as different formats . Several JavaScript libraries, such as JQuery, Bootstrap.js, DataTable.js, and Highchart.js libraries, were used for creating dynamic and interactive data visualization web browser interfaces, which provide users with a highly intuitive interface for manipulating the tool and viewing the analysis results.The web server is hosted within PHP/Apache environment under a Linux system and is equipped with two Octa-cores AMD processors (2.6 GHz each) and 64GB of RAM. The back-end pipeline is implemented in the Python/Perl language, and the plots are drawn by R , N1-methyladenosine (m1A), 5-methylcytosine (m5C), pseudouridine (φ) and N4-acetylcytidine (ac4C) modifications . Other modifications show similar distribution of sites with enrichment near the translation start sites (start codons), especially ac4C modification, which is in accordance with their reported roles in regulating translation. In contrast, a large proportion of pseudouridine modifications are located in 3’UTR regions, which may indicate specific functions in mRNA regulation.RNAmod was used to annotate five mRNA modifications, including N6-methyladenosine  have been identified as mom decay . RNAmod om decay  with a Gom decay . The covom decay . Differeom decay . The genion site .High-throughput sequencing greatly facilitates RNA epitranscriptomics studies and offers an effective method to comprehensively investigate mRNA modification in genome scale. Meanwhile, many software or web servers are developed to predict mRNA modification using machine-learning technologies. However, the convenient and integrated annotation of these mRNA modifications from large amounts of data still remains a challenge. Therefore, we developed an automated and easy-to-use web service, RNAmod, for research communities to analyze and annotate mRNA modifications. Currently, RNAmod supports 21 model reference genomes across vertebrates, insects, nematodes and plants. More species will be supported in the further. Besides, the data in RNAmod will be updated regularly to keep up with the source databases.Meanwhile, RNAmod can also be used for the annotation and visualization of CLIP-Seq data to study the binding features of RNA binding proteins (RBPs). We used RNAmod to annotate the known RNA modification sites and nearly 500 RBP binding sites for human, mouse, fly, yeast, zebrafish, Arabidopsis, etc., whose results are availed in the download page of RNAmod. In addition, RNAmod allows users to perform comparative analysis between groups or among specific gene contexts. Overall, RNAmod is a one stop online interactive platform for the annotation, analysis, and visualization of mRNA modifications. It will meet the emerging need for a convenient, and comprehensive analysis tool for the research field.gkz479_Supplemental_FilesClick here for additional data file.


USP16) has been reported to contribute to somatic stem-cell defects in Down syndrome. However, how this gene being regulated is largely unknown. To study the mechanism underlying USP16 gene expression, USP16 gene promoter was cloned and analyzed by luciferase assay. We identified that the 5′ flanking region (− 1856 bp ~ + 468 bp) of the human USP16 gene contained the functional promotor to control its transcription. Three bona fide NFκB binding sites were found in USP16 promoter. We showed that p65 overexpression enhanced endogenous USP16 mRNA level. Furthermore, LPS and TNFα, strong activators of the NFκB pathway, upregulated the USP16 transcription. Our data demonstrate that USP16 gene expression is tightly regulated at transcription level. NFκB signaling regulates the human USP16 gene expression through three cis-acting elements. The results provide novel insights into a potential role of dysregulation of USP16 expression in Alzheimer’s dementia in Down Syndrome.Ubiquitin Specific Peptidase 16 ( Down syndrome (DS) is a complex developmental disorder caused by genetic defects, leading to intellectual and developmental disabilities. It is a result of complete or partial trisomy of chromosome 21 , 4, and USP16 gene is mapped on chromosome 21 and triplicated in DS. USP16 gene contains 3 mRNA transcripts which share the same start codon, stop codon, and translation frame. USP16 has been reported to contribute to the somatic stem-cell defects in DS and reduce the self-renewal of multiple somatic stem cells [USP16. It was first identified as a histone H2A specific deubiquitinase that regulates cell cycle progression and gene expression in human cells [USP16, removes the ubiquitin protein from H2A-K119, and upregulates the transcription of the Ink4a locus [Ink4a and the p19Arf genes, which are important members participating in self-renewal and senescence pathways. It was reported that USP16 was upregulated in response to DNA damage, and the upregulation of its expression was HECT and RCC1-like domain-containing protein 2 (HERC2)- dependent [USP16 was shown to regulate embryonic stem cell gene expression and hematopoietic stem cell function [USP16 was involved in cancer, and its downregulation promoted hepatocellular carcinoma cells growth [USP16 ‘s functions, but the transcriptional regulation of USP16 gene is largely unknown.The human em cells , suggestan cells . This de4a locus . The Inkfunction , 21. A rs growth . The conNFκB signaling pathway plays an important role in the gene regulation –25 and iUSP16 gene expression is regulated and the role of NFκB in USP16 gene regulation. We cloned and functionally analyzed the human USP16 gene promoter region. We showed that the USP16 gene promoter contained functional cis-acting NFκB binding sites. By using EMSA, we identified three bona fide binding sites, through which NFκB signaling regulates USP16 gene transcription. p65 overexpression was shown to increase the endogenous USP16 mRNA level and the activators of the NFκB pathway, including LPS and TNFα, also upregulated the USP16 transcription. By knocking out p65 in mice embryonic fibroblasts, the effects of TNFα on upregulating USP16 transcription was abolished.Previous studies have shown that NFκB plays essential roles in cell cycle progression , senesceUSP16 gene was amplified by polymerase chain reaction (PCR) from human genomic DNA. The primers were designed with restriction enzymes sites compatible with multi-cloning sites of vector pGL4.10 (Promega). The pGL4.10 vector lacks eukaryotic promoter and enhancer sequences upstream of a reporter luciferase gene. We first cloned the longest 2324 bp (− 1856 bp ~ + 468 bp) promotor region into pGL4.10 at the XhoI and HindIII sites to generate pUSP16-A. Then, promotor deletion assays were conducted as previously described [USP16-A as the template and sub-cloned into pGL4.10 at proper restriction enzymes sites. All used primers were listed in Additional file The 5′ flanking region of the human escribed , 37. Bri2. For luciferase assays, pCMV-Rluc (Promega) was co-transfected with pUSP16-related promoter plasmids as a control to normalize the transfection efficiency. Specifically, 270 ng pUSP16-related promoter plasmids and 30 ng pCMV-Rluc were cotransfected into each well of a 48 well-plate by using 0.9 μl Lipofectamine-™2000 reagent (Invitrogen). Cells were harvested 24 h after transfection and lysed with 60 μl 1 × passive lysis buffer (Promega) per well. Activities of the Firefly and Renilla luciferases from the same sample were sequentially assayed by a luminometer (GloMax 20/20) following the protocol of the dual-luciferase reporter assay system . The Firefly luciferase activity was normalized by the Renilla luciferase activity and the results reflected the relative promoter activity. For RNA extraction analysis, 4 μg plasmid DNA was transfected by 12 μl Lipofectamine-™2000 reagent per well of a 6 well-plate.Human embryonic kidney 293 (HEK293) (RRID:CVCL_0045) and human neuroblastoma SH-SY5Y cell lines (RRID:CVCL_0019) were cultured in Dulbecco’s modified Eagle’s medium  containing 10% fetal bovine serum . Wildtype (WT) mouse embryonic fibroblasts (MEFs) and p65 knockout (KO) MEFs were maintained in DMEM supplemented with 15% FBS, β-mercaptoethanol, and ESGRO (LIF) . All celUSP16 3x NFκB contained three NFκB cis-acting elements, including NFκB2, NFκB3, and NFκB4. USP16-NFκB1, USP16-NFκB2, USP16-NFκB3, and USP16-NFκB4 oligonucleotide had a corresponding sequence. For competition experiments, 2 μl of nuclear extract was incubated with 0.01 pmol/μl of labeled probes and 100× (1 pmol/μl) unlabeled competition probes for 20 min at room temperature. For the supershift assay, monoclonal anti-NFκB p65 antibody  was added. The reaction mixtures were separated on a 4% Tris-glycine-EDTA gel for 70 min at 70 V in darkness. The gel was scanned using LI-COR Odyssey (LI-COR Biosciences) at a wavelength of 700 nm. The sequences of the oligonucleotides were listed in Additional file EMSA was performed as previously described . To obtaLPS  was reconstituted in DMEM and further diluted to a final concentration of 50 ng/ml, while TNFα  was reconstituted in sterile phosphate buffered saline (PBS) containing 0.1% endotoxin-free recombinant human serum albumin at a final concentration of 10 ng/ml. For qRT-PCR, HEK293 and SH-SY5Y cells were exposed to LPS and TNFα at the proper concentration for 24 h and then lysed for RNA extraction. For RT-PCR, MEF WT and p65 KO cells were treated with 5 ng/ml TNFα for 24 h.2 > 0.998). The relative expression of mRNA was calculated with the 2-ΔΔTmethod. Each sample was triplicated. qRT-PCR data were analyzed and converted to relative fold changes. Additionally, total RNA was extracted from MEF WT or p65 KO cells by TRIzol reagent (Invitrogen). Thermoscript™ SuperScript IV first-strand synthesis system (Invitrogen) was applied to amplify the first-strand cDNA by using 1.5 μg of total RNA as the template and then the newly synthesized cDNA was used as the template to perform PCR by Taq DNA polymerase. A pair of primers to amplify a 150 bp region of mice USP16 gene was as follows: forward, 5′- ctgccaagactgtaagactgac, and reverse, 5′- ggtgtcgtgtagtgcttcaag. Additionally, a pair of primers for amplifying a 205 bp fragment of mouse GAPDH gene coding sequence was as follows: forward, 5′- ggatttggtcgtattggg, and reverse, 5′- ggaagatggtgatgggatt. All samples were analyzed on 2.5% agarose gels.Total RNA was extracted from cells using TRI reagent , and quantified with Nanodrop 2000 . PrimeScript™ RT reagent Kit  was used to synthesize the first-strand cDNA from an equal amount of various RNA samples according to the manufacturer’s instructions. qRT-PCR was performed by using SYBR® Premix Ex Taq™ II  and the PCR program included one initial denaturation step at 95 °C for 3 min, 39 cycles of 95 °C for 10 s, 58 °C for 30s, and 72 °C for 30 s (Bio-Rad CFX96). Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was used as an endogenous control. Primers used in this assay were listed in Additional file t test was used to analyze the difference between two groups. One-way Analysis of variance (ANOVA) was applied to analyze the data in Fig. post-hoc Turkey’s method. Statistical analysis in Fig. post-hoc Turkey’s multiple comparisons test. p < 0.05 was considered as statistically significant.Three or more independent experiments were performed. All results were presented as mean ± the standard error of the mean (SEM) and 2-tailed Student’s USP16 gene is mapped on chromosome 21, at 21q21.3. It has three mRNA transcripts which share the same start codon, stop codon, and translation frame. Transcript 1 and 3 encode the same isoform a and transcript 2 encodes isoform b. Transcripts 3 is the longest one which contains all the 19 exons, while the other two lack Exon 2. The only difference between transcript 1 and transcript 2 is that the later is shorter and lacks the first codon “CAG” in Exon 7 , NFκB, hypoxia-inducible factor (HIF), nuclear factor of activated T-cells (NFAT), cAMP-responsive element binding proteins (CREB), and Ying Yang 1 (YY1)  plasmid. The luciferase activities of cells transfected with this plasmid largely rely on the presence of a functional promoter upstream of a luciferase gene. The plasmid pUSP16-A was transfected into HEK293 cells, and luciferase activity was measured by a GloMax 20/20 Luminometer to examine its promoter activity. Compared with cells transfected with an empty vector pGL4.10, pUSP16-A showed a significant increment of luciferase activity  , pUSP16-C , and pUSP16-D  have no significant changes of luciferase activities when compared with pUSP16-A . A series of 3’end deletion plasmids was constructed and transfected into HEK293 cells. Luciferase activities of these plasmids showed that a 41 bp deletion  from pUSP16-D  greatly increased promotor activity (p < 0.0001), indicating that there are negative regulatory elements located in this region. A further 42 bp deletion  significantly reduced promotor activity when compared to pUSP16-E  (p < 0.0001), while deletion plasmids pUSP16-G  and pUSP16-H  did not show significant changes to that of pUSP16-F . However, a further 20 bp deletion  from pUSP16-H (− 200 bp ~ + 150 bp) largely enhanced promotor activity (p < 0.0001), indicating that the 20 bp region contains negative regulatory elements.To identify the regulatory elements in the ted Fig. a. The luUSP16-I  to pUSP16-J  and a 12 bp deletion from pUSP16-J (− 200 bp~ + 110 bp) to pUSP16-N  substantially reduced promotor activity, while a 48 bp deletion from pUSP16-N (− 200 bp~ + 98 bp) to pUSP16-O  did not significantly change the promoter activity (p = 0.3357). However, a further 19 bp deletion from pUSP16-O (− 200 bp~ + 40 bp) to pUSP16-P  almost abolished promotor activity (p < 0.0001). These results showed that + 40 bp was the proper 3′ boundary of the USP16 promotor region. Since we found pUSP16-J  still had a high promotor activity compared with the empty vector pGL4.10 (p < 0.0001), pUSP16-J was chosen to investigate the effect of 5’end on promotor activity. A series of 5’end deletion plasmids was constructed and transfected into HEK293 cells. Luciferase activity showed that a 101 bp deletion  from pUSP16-J (− 200 bp~ + 110 bp) increased USP16 promotor activity (p < 0.0001), while a 47 bp deletion  from pUSP16-K (− 99 bp~ + 110 bp) decreased USP16 promotor activity (p < 0.0001) and a further 52 bp deletion  from pUSP16-L (− 52 bp~ + 110 bp) reduced USP16 promotor activity (p < 0.0001). Taken together, our data illustrate that the promoter region from + 1 bp to + 40 bp has the minimal promoter activity required for basal transcription and various cis-acting regulatory elements are located in the 5′ flanking region of USP16 gene.Further deletion analysis found that a 20 bp deletion from pcis-acting elements in the 1793 bp (− 1325 bp ~ + 468 bp) promoter region of the human USP16 gene  or empty vector (pMTF). Compared with empty vector pMTF, NFκB p65 expression plasmid co-transfecting with pUSP16-N1, pUSP16-N2, pUSP16-N3, and pUSP16-N4 resulted in enhanced luciferase activities to about 2.69, 2.51, 2.24, and 2.04 folds, respectively (p < 0.0001) , pUSP16-N1 vs. pUSP16-N4 (p < 0.0001) and pUSP16-N2 vs. pUSP16-N4 (p = 0.0004). These suggested that deletion of binding site 2 and 3 had substantial impact on NFκB p65’s role in upregulating USP16 gene promoter. In SH-SY5Y cells, similar results were observed for NFκB p65’s effects on increasing the activities of USP16 gene promoter (p < 0.0001)  and to 1.85 folds in SH-SY5Y cells (p = 0.0005) by p65 overexpression compared with the empty vector transfection. A further deletion fragment, pUSP16-N6, was completely abolished the effect of p65 overexpression on affecting its promoter activity  containing each NFκB cis-acting element as competitors. Labelled NFκB consensus probes were visualized as a heavy band on the bottom of the gel  end-labeled with IR700 dye as probes. Each probe contained a single putative NFκB cis-acting site. A shifted protein-DNA complex band was detected after incubating USP16 NFκB2 probe with NFκB-enriched nuclear extract  containing three NFκB cis-acting elements and gained similar results   or TNFα (10 ng/ml) for 24 h. Similar to the effect of NFκB overexpression on endogenous USP16 mRNA levels     and USP16 mRNA levels were examined. As shown in Fig. USP16 mRNA levels was significantly decreased to 0.65 folds by knocking out p65 in MEF cells (p = 0.0397), suggesting p65 is a strong activator for endogenous USP16 gene expression. Furthermore, TNFα treatment significantly increased USP16 mRNA levels by 1.12 folds compared with control (p < 0.0001), whereas such increasement was abolished in MEF p65 KO cells. These data suggest that activation of NFκB signaling pathway by p65, LPS and TNFα upregulates USP16 gene transcription. Taken together, endogenous USP16 gene transcription was enhanced by activators of the NFκB pathway, including LPS and TNFα, and p65 knockout abolished the effects of TNFα on upregulating USP16 gene transcription.To examine whether NFκB affects the endogenous gene transcription, qRT-PCR was conducted to measure the endogenous USP16 protein is a histone H2A-specific deubiquitinase with the coding gene located on human chromosome 21. Several previous studies suggest that it plays many roles in gene expression, cell cycle progression, cell self-renewal, and senescence pathways [USP16 affects hematopoiesis and hematopoietic stem cell function [USP16 was associated with a reduction of mature and progenitor cell populations, while HSC number did not change. USP16 was reported to be involved in hepatocellular carcinoma and decreased expression of USP16 by carboxyl-terminal truncated HBx (Ct-HBx) in live tumor cells promoted stem-like properties [USP16 contributed to neuronal progenitor defects and abnormal development of mammary epithelium. Overexpression of USP16 in human fibroblast cultures manifested growth impairment and senescence, reminiscent of DS’s cells [USP16 was shown to interact with HERC2 to regulate ubiquitin signaling during DNA repair during DNA damage response. This could be essentially important to DS, since cellular response to DNA damage was altered in DS patient cells [pathways , 18. USPfunction . In mousoperties . By usin’s cells . Additiont cells .USP16 gene transcription. We first identified that the 5′ flanking region of USP16 gene, from -1856 bp to + 468 bp, showed promotor activity. Then we found several functional regulatory elements by a series of promotor deletion analysis. By using a computer-based analysis, we determined four putative NFκB binding sites in the promotor region. After conducting EMSA, we provided solid evidence to support that three binding sites  physically interacts with p65. In this article, we first proved that p65 overexpression could enhance endogenous USP16 mRNA levels through three cis-acting elements. It was unexpected that the promoter activity of the pUSP16-N5 plasmid without any putative p65 binding site was still increased by p65 overexpression. It has been suggested that DNA-binding specificities are different among various NFκB dimers, which is linked to dimer-specific roles in gene regulation [USP16-N5, which was regulated by other NFκB family members except p65. As LPS and TNFα are strong activators of NFκB pathway, we tried stimulate USP16 gene by adding LPS and TNFα to cell culture medium and confirmed that both LPS and TNFα stimuli enhanced USP16 transcription. By knocking out p65 in MEF cells, the effects of TNFα treatement on upregulatingUSP16 gene expression was abolished.In this study, we demonstrated that NFκB enhanced human gulation . It was gulation . TherefoUSP16, in this case, may play a role in AD-related pathogenesis in DS. A number of genes on the chromosome 21 plays an important role in the AD pathogenesis. Duplication of amyloid β precursor protein (APP) gene was reported to cause autosomal dominant early-onset Alzheimer disease in five families [) gene, a gene on Chromosome 21, has been implicated in pathogenesis of DS and AD [USP16 gene transcription in this study, we attempt to explore the role of USP16 in AD pathogenesis in future studies.DS has been associated with early onset and higher incidence of aging-related diseases such as AD , 42, 43.families , and varfamilies . Our labfamilies . NFκB sifamilies . We alsofamilies , 24. RegS and AD . We showS and AD , 8. We dS and AD . As we hUSP16 gene transcription was positively affected by NFκB, we also found three negatively regulatory elements in the USP16 promotor region . These three negatively regulatory regions contain a common transcription factor binding site for YY1 (data not shown). The ubiquitous transcription factor YY1 is known to be a multifunctional protein that can either activate or repress gene expression depending upon the cellular context. Ying Yang 1 has been reported to play fundamental roles in embryogenesis, differentiation, replication, and cellular proliferation [USP16 gene transcription and the potential impacts of USP16 on DS pathogenesis may be warranted.Although we have identified that feration –54. Yingferation . FurtherUSP16 gene expression is tightly regulated at transcription level. NFκB signaling regulates the human USP16 gene expression through three cis-acting elements. The results provide novel insights into a potential role of dysregulation of USP16 expression in Alzheimer’s dementia in Down Syndrome.In conclusion, our study demonstrates that that Additional file 1. Supplementary Information.