The process of neurogenesis in the brain, including cell proliferation, differentiation, survival, and maturation, results in the formation of new functional neurons. During embryonic development, neurogenesis is crucial to produce neurons to establish the nervous system, but the process persists in certain brain regions during adulthood. In adult neurogenesis, the production of new neurons in the hippocampus is accomplished via the division of neural stem cells. Neurogenesis is regulated by multiple factors, including gene expression at a temporal scale and post-transcriptional modifications. RNA-binding Proteins (RBPs) are known as proteins that bind to either double- or single-stranded RNA in cells and form ribonucleoprotein complexes. The involvement of RBPs in neurogenesis is crucial for modulating gene expression changes and posttranscriptional processes. Since neurogenesis affects learning and memory, RBPs are closely associated with cognitive functions and emotions. However, the pathways of each RBP in adult neurogenesis remain elusive and not clear. In this review, we specifically summarize the involvement of several RBPs in adult neurogenesis, including CPEB3, FXR2, FMRP, HuR, HuD, Lin28, Msi1, Sam68, Stau1, Smaug2, and SOX2. To understand the role of these RBPs in neurogenesis, including cell proliferation, differentiation, survival, and maturation as well as posttranscriptional gene expression, we discussed the protein family, structure, expression, functional domain, and region of action. Therefore, this narrative review aims to provide a comprehensive overview of the RBPs, their function, and their role in the process of adult neurogenesis as well as to identify possible research directions on RBPs and neurogenesis. Neurogenesis is the formation process of new neurons derived from neural progenitor cells (NPCs), occurring in several regions of the brain including the olfactory epithelium, hippocampus, and subventricular zone (SVZ) . It consMore than 500 RNA-binding proteins (RBPs) have been identified in the human genome . RBPs arApart from RBPs, micro RNAs (miRNAs) are another common type of gene expression mediators. The regulation of gene expression by RBPs and miRNAs can take place in an antagonistic fashion in which RBPs and miRNAs can act on the same targets or nearby regulatory elements . For exavia RBPs (The translation of numerous mRNAs in the brain are controlled by their interaction with ribonucleoprotein (RNP) granules, which are made up of translational machinery, core RBPs, and miRNAs . RBPs revia RBPs . A comprThe RNA-binding protein known as the Cytoplasmic Polyadenylation Element-Binding Protein (CPEB) family is essential for synaptic plasticity . The CPEA recent discovery of three later members in this family (CPEB2-4) revealed the additional regulatory potential and biological functions of cytoplasmic polyadenylation . By contIn the process of establishing and maintaining neuronal development and synaptosomes, CPEB3 regulates translation by guiding necessary protein modifications . TherefoThe family Fragile X-Related Proteins (FXRs) includes the Fragile X Mental Retardation Protein (FMRP), involved in a condition known as fragile X syndrome, and FMPR’s autosomal paralogs, the RBPs Fragile X-related protein 1 and 2 . FXRs arStructurally, FXR1 and FXR2 are very similar as they have two RNA-binding domains that are highly conserved, namely the polyribosome binding domain and the nuclear localization sequence (NLS) domain . These pThe members of this family can bind to RNA and associate with polyribosomes , and theFXR2 targets Noggin mRNA to regulate neurogenesis in the dentate gyrus of the adult brain . FXR2 invia FXR2 only takes place in this neurogenic region , also known as HuA or embryonic lethal, abnormal vision-like 1 (ELAVL1), is an RBP member of the protein family embryonic lethal abnormal vision, or ELAV/Hu . The ELAvia the third RRM (The members of the ELAV family have three RNA binding domains which are known as RNA recognition motifs (RRMs) . The RRMhird RRM . HuD stahird RRM . For HuRhird RRM .In the adult brain, HuD is involved in the regulation of neuronal plasticity, nerve injury, learning and memory, and neuronal diseases . HuD funHuD participates in different stages of neuronal differentiation and maturation processes, including neurogenesis, axonal and dendritic outgrowth, and cell remodeling . RecentlIn the dentate gyrus of the hippocampus, HuD and its target mRNAs increase following neuro-toxin-induced injury . HuD hasHuD major effector is miR-375 which plays a role in neurite growth and dendritic maintenance . Other HHuR plays a role in adult neurogenesis  as it isLin28 is a highly conserved RNA-binding protein encoded by the Lin28 gene . The LinLin28 contains a unique combination of two coupled and highly conserved functional domains, the N-terminal cold-shock-domain and two retroviral type CCHC-zinc knuckles (CCHCx2) . Both doLin28 participates in several processes such as the generation of induced pluripotent cells from fibroblasts, glucose metabolism regulation, regeneration mechanisms in tissues, body size regulation, progression of cancer, and neurogenesis . Lin28 aLin28-mediated suppression activity of the let7 family promotes cell reprogramming to stimulate pluripotency . FurtherLin28 selectively and strongly binds the conserved terminal loop site of pre-let7 through its specific RNA-binding activity . The intA challenge in the understanding of the players involved in Lin28-let7 mediated mechanisms is the identification of mRNAs targeted by let7 . During Msi1 is a regulator that mediates the balance between self-renewal and cell differentiation . Msi1 isnELAV modulates actions of Msi1 at transcript and protein levels, which could alternate the cell cycle by shifting the stem/progenitor cells from cell proliferation to the cell differentiation phase in both neurogenic regions . . The co-Msi1 expression during neurogenesis goes in the opposite direction to the expression levels of miR-137 . In the Msi1 acts on the Notch-mediated proliferation pathway in NSC where it binds and prevents the translation of Numb resulting in inhibition of Notch activation . Msi1 paAnother mediator of Msi1 activity is HuD which participates in the stabilization of Msi1 mRNA to promote Msi1-mediated cell proliferation of NPCs . This meSam68, the Src-associated substrate during mitosis of 68 kDa, also known as the human KH domain containing RNA binding signal transduction associated 1 (KHDRBS1), is a member of the Signal Transduction Activator of RNA (STAR) family of RBPs . The proSam68 plays a role in RNA metabolism including polysomal recruitment of mRNAs and alternative splicing . Sam68 rSam68 participates in the alternative splicing of mRNAs involved in neurogenesis . In neurStau1 and Stau2 are involved in RNA transport as well as mRNA stability and translation . The Stavia nuclear import and export in NPCs. Stau2 plays a critical role in the determination of cell fate during neurogenesis  gene was found as an initial member of the SOX gene family capable of determining the male phenotype  and the amplifying progenitors (type 2a) . ThroughSOX2 is a well-known regulator of cell proliferation and neurogenesis, and it participates in the upstreaming events of the Lin28-let7 axis . In adulvia a specific regulatory partnership. However, it can also be observed that the same RBP-mRNA partners  also have the ability to act on different neurogenesis phases through the same mRNA targets. This phenomenon invites to ask whether other regulatory mechanisms are involved and whether there is a cross-talk among RBPs contributing to the regulation at each stage of the neurogenesis process. A clear case of an RBP-RBP cross-talk mechanism was shown in SOX2 in which this RBP interacts with the Lin28-let7 axis. Some RBPs such as HuD, Sam68, Msi1, and Stau1 act on multiple mRNA targets to regulate a specific stage of the neurogenesis process which raises the question whether there could be more target mRNAs that have not yet been identified for the other RBPs. At times, the process to activate or deactivate RBP mediated function has been clearly identified such as in Lin28 case, but often times the activation-deactivation process is not well understood. What is clear from the analysis presented in this review is that there is an intricate RBP-mediated regulatory network taking place in neurogenesis. Tracing the regulatory network mediated by RBPs in neurogenesis will potentially contribute to understanding the impact and clinical implications on cognition and mood. Therefore, efforts should be made to clarify the RBP-mediated regulatory mechanisms and to identify relevant mRNAs involved in neurogenesis.In this review, RBPs involved in the different stages of the adult neurogenesis process were discussed. RBPs such as Sam68 and Msi1 are involved at all stages of neurogenesis . The regvia RBPs, are backbone mechanisms that shape the architecture of the CNS. Several RBPs are involved in the intricate regulation of neurogenesis at all stages from, cell proliferation, migration, and differentiation, to integration into the existing circuit in both the SVZ and the dentate gyrus of the hippocampus  the bidirectional regulation of neurogenesis , 2) self-amplification effect , 3) overlapping RBPs targets and effectors , and 4) complementary actions among RBPs  as discussed in the review. Furthermore, the degree of understanding of the RBP mechanism, their molecular regulatory partners, and neurogenic region of action has been slowly emerging being HuD, HuR, FXR2, Lin28, Msi1, and Sam68 the most characterized RBPs to date. Despite the advances to understand the complex RBP-mediated regulation of neurogenesis, more research is needed to trace a clear map of the molecular regulatory mechanisms and the critical players to identify potential therapeutic neurogenic promoting targets.


Chromatin remodeling is essential for epigenome reprogramming after fertilization. However, the underlying mechanisms of chromatin remodeling remain to be explored. Here, we investigated the dynamic changes in nucleosome occupancy and positioning in pronucleus-stage zygotes using ultra low-input MNase-seq. We observed distinct features of inheritance and reconstruction of nucleosome positioning in both paternal and maternal genomes. Genome-wide de novo nucleosome occupancy in the paternal genome was observed as early as 1 h after the injection of sperm into ooplasm. The nucleosome positioning pattern was continually rebuilt to form nucleosome-depleted regions (NDRs) at promoters and transcription factor (TF) binding sites with differential dynamics in paternal and maternal genomes. NDRs formed more quickly on the promoters of genes involved in zygotic genome activation (ZGA), and this formation is closely linked to histone acetylation, but not transcription elongation or DNA replication. Importantly, we found that NDR establishment on the binding motifs of specific TFs might be associated with their potential pioneer functions in ZGA. Further investigations suggested that the predicted factors MLX and RFX1 played important roles in regulating minor and major ZGA, respectively. Our data not only elucidate the nucleosome positioning dynamics in both male and female pronuclei following fertilization, but also provide an efficient method for identifying key transcription regulators during development. However, the detailed process of protamine-to-histone transition in the paternal genome as well as the dynamics of chromatin state in the maternal genome shortly after fertilization remains to be elucidated.After the sperm penetrates into the oocyte, the chromatin of highly specialized male and female pronuclei (PN) undergoes remarkable reprogramming, which supports the transition from meiosis to mitosis and the reactivation of transcription in embryos.10 In the eukaryotic genome, nucleosome-depleted regions (NDRs) are observed at regulatory elements, including many promoters, enhancers, and terminator regions.12 RNA Pol II passaging results in upstream trafficking of histone proteins and the formation of a typical NDR at the transcription start site (TSS),13 and the nucleosome unit downstream or upstream of the NDR is referred to as the +1 nucleosome or –1 nucleosome, respectively. Meanwhile, nucleosomes also serve as barriers for RNA Pol II elongation and impact the gene activation logic and expression noise.14 In recent years, different regulatory models of zygotic genome activation (ZGA) after fertilization were proposed, in which tight temporal coupling between chromatin reorganization and minor/major waves of ZGA was widely discussed but still under debate.7 The recently published landscapes of RNA Pol II binding in mouse embryos reveal that Pol II is preferentially loaded to CG-rich promoters and accessible distal regions in one-cell embryo, and the loading of Poll II to future gene targets occurs earlier before genome activation.8 However, the detailed patterns of chromatin remodeling especially on the view of nucleosome positioning shortly after fertilization remain unclear. Moreover, whether Poll II or certain pioneer TFs coordinate with other chromatin remodelers to participate in NDR formation and how this process affects downstream gene expression as well as ZGA at the early stages remain a long-standing question.Nucleosomes are the basic units of chromatin structure and serve multiple cellular functions; they have a compact structure which inhibits the access of sequence-specific proteins. The genome-wide pattern of nucleosome positioning is determined by the combination of DNA sequence, ATP-dependent chromatin remodeling enzymes, and transcription factors (TFs).Here, we optimized micrococcal nuclease digestion-based high-throughput sequencing (MNase-seq) to elucidate the nucleosome organization dynamics during the first 12 h after fertilization. We investigated the dynamics of nucleosome establishment and re-positioning in the male and female pronuclei, respectively. Importantly, through integrative analyses of the NDR formation pattern on TF motifs, we identified novel regulators of ZGA for mouse early embryos.15 and subsequent library construction , which could analyze ULI-MNase-seq data systematically  method using a single tube for micrococcal nuclease digestion18 The pronuclei further developed to the PN3 stage at 6 hpf and reached each other at 12 hpf. Based on these observations, we collected parental pronuclei using micromanipulation at different time points (from 0.5 to 12 hpf) and performed ULI-MNase-seq to detect the chromatin state of the pronuclei from formation to fusion  and long (120–180 bp) fragments were distinct from each other  to approximately establish the same starting time point for 5–8 embryos per group Fig. . We obseion Fig. . Meanwhi22 only 10%–20% of the genome was occupied by nucleosomes in sperm and 0.5-hpf male PN, but this proportion dramatically increased to nearly 80% in 1-hpf male PN, indicating that nucleosomes were globally deposited into the paternal genome quickly at ~1 hpf . Genome-wide nucleosome occupancy in oocytes and sperm was quite different from that of the PN samples, even in 0.5-hpf male PN and female PN  around TSSs for each sample  in the eukaryote genome, and they are typically located at regulatory regions including promoters, enhancers, and origins of DNA replication.ple Fig. . To our ple Fig. . We obseple Fig. . For theple Fig. . These o25 No significant NDRs were observed on late 2-cell-defined enhancers in either male or female PN  and imprinted genes. The nucleosome profiles and NDRs are generally comparable between paternal and maternal genomes on ICRs . The NDR pattern was more obvious on promoters of both minor and major ZGA genes compared to all genes at 6 hpf when the minor ZGA begins  began during the S and G2 phases at the 1-cell stage, and the second wave of ZGA (designated the major ZGA) occurred during the G1 phase at the mid-to-late 2-cell stage.ins Fig. . Strikinins Fig.  when theins Fig. . These r27 We first analyzed the sequence features of newly established nucleosomes at each stage and found that nucleosomes established earlier tended to have higher GC content  on acetylated TSSs. Therefore, JQ1 might cause a weaker effect on the chromatin state compared to the genome-wide loss of histone acetylation. We further generated the nucleosome profiles on promoters showing de novo NDR establishment in male PN after fertilization (C3), and compared them with profiles of promoters with weak NDRs throughout the PN stages (C7). Reassuringly, the signal of +1 nucleosomes on C3 promoters was significantly decreased in male PN upon Hdac overexpression, but C7 promoters did not share this change, and the nucleosome signal remained relatively stable on both C3 and C7 promoters in female PN  embryos at 8 hpf  and late 2-cell (40 hpf) stages for RNA-seq. We first confirmed that the expression level of these factors was significantly reduced and the replicates were highly consistent ; further, the profiles of promoter NDRs were equalized in the parental genomes after 6 hpf. Interestingly, this discrepancy in the creation of promoter NDRs was very similar to the differential H4 hyperacetylation dynamics and transcription activities in the parental pronuclei revealed by immunofluorescent staining.18 Meanwhile, our analyses suggest that histone acetylation, but not DNA replication or RNA Pol II elongation, might be crucial for the re-establishment of promoter NDRs and +1 nucleosomes upon fertilization. Reducing the histone acetylation level by Hdac overexpression attenuated the formation of promoter NDRs only in male PN, which might be caused by the cascade effect on chromatin state alterations and reduced binding of pioneer TFs, as the male genome is opened earlier than the female genome. Blocking the recognition of histone acetylation by JQ1 showed a weaker and unstable influence on NDR formation and +1 nucleosomes, which also suggested that the Pol II recruitment or transcription initiation might not be required for creating NDRs at the PN stages. On the other hand, generation of promoter NDRs might be crucial for initiating the ZGA process, and further investigations are required to clarify factors responsible for the subsequent remodeling on promoter NDRs in both paternal and maternal genomes, which possibly relies on the function of ATP-dependent chromatin remodelers such as the SWI–SNF complex.Multiple epigenetic landscapes have been linked to transcription activation and subsequent regulations in mammalian embryos, including histone modifications, DNA modifications, chromatin accessibility, and high-dimensional structures.43 Interestingly, in the somatic cell reprogramming induced by TFs, pioneer factors also have the ability to access partial motifs on nucleosomal DNA and gradually induce the change from silent chromatin to open chromatin.44 In our study, we provided a new strategy, NEPTUNE, which includes functions for predicting pioneer factors during the developmental process in vivo. NEPTUNE first identified the dynamics of nucleosome positioning on TF binding motifs and screened the closed-to-open transition to predict pioneer factors that might bind the nucleosome-occupied chromatin and gradually open the genome with the help of other chromatin remodelers. Based on our data from PN-stage samples, NEPTUNE identified dozens of TFs whose motif regions showed obvious changes in the chromatin state, including the previously reported factor NFYA, as well as the novel regulators MLX and RFX1. Blocking the function of MLX and RFX1 leads to attenuation of NDR formation and failure of activation of certain ZGA-associated genes through either direct or indirect mechanisms. MLX was found to activate myokines by increasing the histone acetylation level,36 and this glucose-sensing factor could balance metabolism to suppress apoptosis and promote cell survival.36 RFX1 could also retain the cell viability under stress through activating cellular communication network factors.40 The ZGA process also induces many metabolism-associated genes, providing the possibility that MLX and/or RFX1 contribute to these transcriptional activation events. Although MLX and RFX1 both regulate metabolic genes, their motifs and target genes are highly different  mice were housed in the animal facility at Tongji University, Shanghai, China, and they were fed a standard diet. The temperature and light were strictly controlled . All animal experiments were performed in accordance with the University of Health Guide for the Care and Use of Laboratory Animals and were approved by the Biological Research Ethics Committee of Tongji University.B6D2F1 female mice (8–10 weeks old) were superovulated by injection with 7 IU of pregnant mare serum gonadotropin (PMSG), followed by injection with 5 IU of human chorionic gonadotropin (hCG)  48 h later. MII oocytes were collected from the oviducts of the superovulated female mice.Both cauda epididymides were collected from each C57BL/6 male mouse and then were punctured by needles. The semen was then squeezed out and placed into a 1.5 mL Eppendorf tube containing 500 μL of warm HEPES-buffered CZB (HCZB) medium; the sample was then incubated at 37 °C for 10–15 min to allow sperm to swim out. ICSI was then performed on the stage of an Olympus inverted microscope equipped with a Narishige micromanipulator. MII oocytes were placed in a drop of HCZB medium, and a single sperm head was injected into each MII oocyte with the aid of a piezo-driven micromanipulator. Embryos were then cultured in G-1 PLUS medium (Vitrolife) after fertilization before harvesting.H2B cDNA fused with the sequence of RFP was cloned into a T7-driven vector, and H2B-RFP mRNA was synthesized with the mMESSAGE mMACHINE T7 Transcription kit  following the manufacturer’s instructions. The concentration of the injected mRNA was found to be optimal at 100 ng/μL. MII oocytes were injected with ~10 pL of the diluted mRNA using a piezo-driven micromanipulator. After the injection, the oocytes were cultured for 2 h to allow recovery and H2B-RFP expression before fertilization.At specific time points after ICSI, fertilized embryos were fixed with 4% paraformaldehyde in PBS for 1 h at room temperature (RT). The fixed embryos were then washed in 0.5% BSA in PBS and treated with 0.2% Triton X-100 for 20 min at RT for permeabilization. The nuclei were stained with DAPI for 10 min at RT before the embryos were mounted on a glass slide in anti-bleaching solution. Fluorescence was detected under a laser-scanning confocal microscope .At 0.5 hpf, 1 hpf, 1.5 hpf, 2 hpf, 3 hpf and 4 hpf, the embryos were placed into HCZB medium containing Hoechst 33342 dye to make the pronuclei visible. At time points later than 4 hpf, the pronuclei became visible without staining. Zona pellucidae were punctured with a piezo-drill micromanipulator, and the pronuclei were isolated from the embryos. The parental pronuclei were distinguished by their sizes and distances from the second polar bodies. Isolated pronuclei were washed with 0.5% BSA in PBS before they were placed into the lysis buffer for low-input MNase-seq.2, 0.6% NP-40) for individual reactions. Then, 2.5 μL of MNase master mix , 2 mM DTT, and 5% PEG 6000) was added into each tube, and the reaction was incubated at 25 °C for 10 min for chromatin fragmentation. The reaction was stopped by the addition of 0.32 μL of 100 mM EDTA, and then 0.32 μL of 2% Triton X-100 was added to the reaction to release the fragmented chromatin. Then, 0.2 μL of 20 mg/mL protease (Qiagen) was added, and the reaction was incubated at 50 °C for 90 min for protein digestion followed by incubation at 75 °C for 30 min for protease inactivation.10–15 pronuclei per replicate were isolated and washed before they were placed into 0.7 μL of lysis buffer  following the manufacturer’s instructions. After standard procedures including end repair and A-tailing, adapter ligation, post-ligation cleanup, and library amplification, the resulting products were subjected to a second round of PCR amplification with the same provided primers to generate sufficient DNA materials for high-throughput sequencing. Paired-end sequencing with 150-bp read length was performed on the HiSeq X Ten (Illumina) platform at Cloudhealth Medical Group Ltd.Hdac overexpression, the mRNAs of Hdac1 and Hdac2 were synthesized as described above and mixed at a concentration of 500 ng/μL each, and the Hdac mRNA mixture was injected into MII oocytes before ICSI. Embryos injected with water served as the control group for Hdac overexpression. At 6 hpf or 12 hpf, the parental PN were collected for low-input MNase-seq.For drug-treated groups, embryos were placed to G-1 PLUS medium supplemented with 0.05% DMSO, 100 μM α-amanitin , 3 μg/mL aphidicolin  or 1 μM JQ1 , respectively, after ICSI-induced fertilization. For To verify that the transcription or DNA replication activities were successfully inhibited in each group, we transferred embryos into G-1 PLUS medium supplemented with corresponding drugs as well as 1 mM EU or 10 μM EdU at 8 hpf, and cultured these embryos for another 4 h. At 12 hpf, we fixed the embryos with 4% paraformaldehyde in PBS and performed EU  or EdU staining  following the manufacturer’s instructions, respectively.Two or three siRNAs were designed for each gene, and the sequences were listed as follows: control siRNA , siEtv5-1 (UACAUGAGAGGCGGGUAUUUC), siEtv5-2 (AGCUUGCCCUUUGAGUAUUAU), siEtv5-3 (GCGACCUUUGAUUGACAGAAA), siMlx-1 (CGGUGUCCUUCAUCAGUUGAA), siMlx-2 (GAAAGUGAACUAUGAGCAAAU), siRfx1-1 (AGAACACUGCACAGAUCAA), siRfx1-2 (ACUGUGACAAUGUGCUGUA), and siRfx1-3 (UCAUGGUAAACCUGCAGUU). The siRNAs against each gene were mixed together and diluted at a total concentration of 20 μM. Ovaries were obtained from B6D2F1 female mice (8–10 weeks old) 48 h after PMSG injection and were then transferred to M2 medium  supplemented with 0.2 mM 3-isobutyl-1-methylxanthine . The ovarian follicles were punctured with a syringe needle, and GV-stage oocytes were collected using a narrow-bore glass pipette. The GV-stage oocytes were then injected with ~10 pL of siRNAs using a piezo-driven micromanipulator.For IVM, the injected GV oocytes were washed thoroughly in IBMX-free αMEM  and were then incubated for 16 h in the maturation medium (5% FBS and 1.5 IU/mL hCG in αMEM). Oocytes presenting with a polar body were classified as MII, and ICSI was then performed to fertilize oocytes at the designated time. At 22 hpf and 26 hpf, the percentage of 2-cell embryos in each group was calculated as the early 2-cell rate. At 48 hpf, the percentage of embryos at 2-cell or 4-cell stages in each group was calculated as the overall 2-cell rate. At 16 hpf and 40 hpf, late 1-cell and late 2-cell embryos were harvested for RNA-seq, respectively.45 Briefly, harvested blastomeres were placed in lysis buffer containing 0.5% Triton X-100, free dNTPs and tailed oligo-dT oligonucleotides. Reverse transcription was performed with Superscript II , and cDNA amplification was performed as described. The amplified cDNA was fragmented using a Covaris sonicator  with conditions as follows: peak power 50, duty factor 20, cycles/burst 200, 2 min. The KAPA Hyper Prep kit (kk8504) was applied to generate sequencing libraries following the manufacturer’s instructions.RNA-seq libraries were prepared as previously described.https://github.com/chenfeiwang/NEPTUNE.We developed a computational pipeline NEPTUNE for integrated analysis of ULI-MNase-seq datasets. NEPTUNE consists of four major steps described as follows  mem command.NEPTUNE randomly sampled 1 M paired-end reads of each sample, and calculated the distance between paired ends as the read length to generate the length distribution plot. NEPTUNE also calculated the genome-wide nucleosome coverage by enumerating the 200 bp bins which were covered by the nucleosome signal. To examine the reproducibility of the MNase-seq libraries, we generated nucleosome profiles for all replicates and calculated the correlation of normalized nucleosome occupancy between biological replicates using promoter regions (defined as 2 kb upstream and downstream of TSSs) of Refseq genes. As the replicates were highly correlated with each other , we pooled the biological replicates together for each stage. Finally, NEPTUNE generated the averaged nucleosome profiles around unique regions such as TSSs, enhancers and the top 10,000 CTCF binding regions.O was defined as:N represents the number of normalized nucleosome fragments in this 1 kb region, s represents the normalized sequence depth (500 million reads), g represents the mouse genome size (2.7E9), and gr represents the fraction of genome occupied by nucleosomes, which is variable for different samples. The O(i) thus represents the number of observed nucleosome fragments versus the number of expected nucleosome fragments at the designated region. We calculated the relative occupancy, O, for each bin from ESC MNase-seq samples using different amounts of starting materials and estimated that bins with O(i) > 0.3 could represent nucleosome-occupied regions. We then used the same cut-off for parental PN samples to determine the nucleosome-occupied bins. Sperm-retained nucleosomes were defined as regions with O(i) > 3 in sperm samples. Newly established nucleosome regions in each stage were defined as regions containing no nucleosome (O(i) ≤ 0.3) in any of the previous stages, but containing nucleosomes (O(i) > 0.3) at the present stage.To calculate the genome-wide nucleosome occupancy for mESCs and parental pronuclei, we first separated the genome into 1 kb consecutive bins. Although we normalized the total sequence depth to 500 million reads per sample, in some samples such as sperm, 0.5-hpf male PN as well as single-cell ESC samples, only 5%–30% of the genomes were occupied by nucleosomes, leading to a higher background noise. To normalize the background noise, we took the genome-coverage fraction into consideration, and the relative nucleosome occupancy 48 TSS regions were profiled 2 kb upstream and downstream of the TSSs. TF binding regions were profiled 1 kb upstream and downstream of the motif centers, and only the top 10,000 regions with significant motif scores were included in the profiles. Enhancer regions were defined using ATAC-seq peaks at the corresponding stages, excluding the peaks from promoter regions.25We generated the averaged nucleosome profiles around TSS regions and TF binding motifs using the SitePro function from CEAS.To evaluate the nucleosome depletion and phasing status of TSS regions as well as TF binding motifs, we defined the NDR score and POS score.center represents the center region, which is defined as the mean of the normalized nucleosome profile from –50 bp to 50 bp; all represents all of the profiles, which represents –2 kb to +2 kb of the TSS or –1 kb to +1 kb of the motif center. The depletion score DS thus represents the depth of NDRs versus all profiles, which should range from –1 to 1. If the NDR score is > 0, then there is a canonical NDR at the center; if the NDR score is < 0, then the center region is assuredly occupied by nucleosomes.The NDR score was defined as:i represents a bin from the TSS or the center of a motif to 1 kb downstream, with a 50 bp resolution; bin j represents a bin from the TSS or the center of a motif +10 bp to 1 kb downstream, with a 50 bp resolution. The correlation between these two bins, ranging from –1 to +1, represents the periodicity of the profile.The phasing score is defined as:NEPTUNE generated the averaged nucleosome profiles around TSSs of all genes or ZGA-associated genes as described in Step 2. Users could also use a custom-defined gene list to generate the nucleosome profiles around TSSs. To normalize the influence of sequencing depth on nucleosome profiles and to compare profiles of different groups with each other, we divided the nucleosome signal at specific sites  by the averaged signal intensity in the corresponding sample. For nucleosome profiles of TF KD groups which were generated using a small set of genes, we smoothed the nucleosome profiles using smooth.spline function in R for better visualization. Difference in NDR scores was quantified. NEPTUNE calculated the NDR scores of TSSs for differentially treated groups using the formula in Step 2. Significance between different groups was evaluated using the one-sided Wilcoxon rank-sum test.35 We only focused on the TFs expressed at the oocyte, zygote, early 2-cell, and late 2-cell stages, and 122 TFs were left after setting the cut-off for fragments per kilobase million (FPKM) as 1. For each TF, the corresponding binding sites were defined using the top 10,000 sites with highest motif scores across the genome. We then calculated the NDR scores on these sites for all the parental PN stages and performed k-means clustering setting k = 3, which identified TFs with binding sites that (1) were always occupied by nucleosomes at the PN stages; (2) always had NDRs at the PN stages; (3) had a transition from nucleosome-occupied regions to NDRs, which might result from the binding of corresponding TFs during embryogenesis.To classify the functions of different TFs during the chromatin remodeling in mouse early embryogenesis, NEPTUNE calculated the nucleosome depletion scores for the TF motifs from the Cistrome database, including 335 curated motifs revealed by ChIP-seq data.23 ChIP-seq and ATAC-seq reads were aligned to the mouse genome build mm9 using the bwa (v 0.7.12) mem command.46 Signal tracks for each sample were generated using the MACS2 (v2.0.10.20131216) pile-up function and were normalized to reads per million mapped reads (RPM).49 The RNA-seq reads from the KD experiments were mapped to the mm9 reference genome using STAR (v2.5.2b).50 Expression levels for all Refseq genes were quantified to FPKM using stringtie (v1.3.6),51 and FPKM values of replicates were averaged.Public sperm histone modification data from ChIP-seq and ATAC-seq experiments were used in the analysis.The enrichment of nucleosome regions on genomic elements including promoters, high CpG density promoters (HCPs), intermediate CpG density promoters (ICPs), low CpG density promoters (LCPs), exons, introns, LINEs, SINEs, and long terminal repeats (LTRs) was calculated using observed probability versus expected probability. The observed probability was calculated using the lengths of nucleosome regions that covered the designated genomic elements versus the lengths of total nucleosome regions, and the expected probability was calculated using the total lengths of designated genomic regions versus the length of the whole genome.52 We only selected the GO terms from biological processes to calculate the enrichment. P-values were calculated similar to the online tool of DAVID, which is based on a modified Fisher’s exact test.Functional annotation analysis was performed using the MAGeCK-Flute package.http://www.geneimprint.com) and previous publications.54 All transcripts were separated into maternally imprinted and paternally imprinted based on the literatures. The 32 ICRs were downloaded from the published work.55We obtained 179 known imprinted genes (267 transcripts) from the geneimprint website , and to correct the potential effect caused by nucleosome occupancy in previous stages, we performed partial correlation analysis on nucleosome occupancy for each stage. Briefly, we performed linear regression of the newly gained nucleosome occupancy at the current stage with the nucleosome occupancy at the previous stage using the lm function implemented in R. We also similarly performed linear regression of GC content or other features with the nucleosome occupancy at the previous stage. Then, we calculated the Pearson correlation coefficients of the residuals from the two regression models as the partial correlation between nucleosome occupancy and the input feature, such as GC content. The relationship of newly established promoter NDRs with other genomic features was similarly determined.k = 7. Heatmap was generated using pheatmap function in R. We then performed ANOVA analysis on 7 NDR clusters with histone modifications defined at sperm, zygote, and 2-cell stages, respectively, as well as the GC content using aov functions in R, and the F-value of each histone modification was used to evaluate its association with NDR scores.To investigate the features correlated with promoter NDR scores, we first clustered the genes based on promoter NDR scores at 10 male PN stages using k-means clustering, setting We calculated the enrichment of minor and major ZGA gene promoters on binding regions of different TFs as the odds ratio between the observed and expected counts. The observed count is calculated as the number of ZGA gene promoters containing the specific TF motif divided by the total number of promoters containing this motif. The expected count is calculated as the number of ZGA genes divided by the total number of genes. GC content on binding sites of a designated TF was calculated as the averaged GC content of top 10,000 sites with highest motif scores across the genome.56 The counts in different replicates were fed into edgeR to perform differential expression analysis.57 Genes with a P-value (Benjamini and Hochberg-adjusted) < 0.05 and a fold change > 2 were defined as DEGs. Minor ZGA-associated genes were defined as genes upregulated at the zygote stage compared to MII oocytes (1640 genes), and major ZGA-associated genes were defined as genes upregulated at the 2-cell stage compared to zygotes (1012 genes) using our previously published RNA-seq data.59To identify differentially expressed genes (DEGs), we calculated the read counts of each RNA-seq sample using HTSeq (v0.6.0).60 and P < 0.05 was considered statistically significant. MNase-seq and RNA-seq experiments were performed 2–5 times for each group, and the precise numbers of replicates and the data qualities were summarized in Supplementary information, Table SError bars in the graphical data represent the standard deviation (SD). For all the presented boxplots, the center represents the median value, and the lower and upper lines represent the 5% and 95% quantiles, respectively. Significant difference between different groups was determined using the one-sided Wilcoxon rank-sum test adjusted by the Benjamini and Hochberg method,Supplementary information, Figure S1Supplementary information, Figure S2Supplementary information, Figure S3Supplementary information, Figure S4Supplementary information, Figure S5Supplementary information, Figure S6Supplementary information, Figure S7Supplementary information, Figure S8Supplementary information, Figure S9Supplementary information, Figure S10Supplementary information, Table S1Supplementary information, Table S2


The multi-level spatial chromatin organization in the nucleus is closely related to chromatin activity. The mechanism of chromatin organization and remodeling attract much attention. Phase separation describes the biomolecular condensation which is the basis for membraneless compartments in cells. Recent research shows that phase separation is a key aspect to drive high-order chromatin structure and remodeling. In addition, chromatin functional compartmentalization in the nucleus which is formed by phase separation also plays an important role in overall chromatin structure. In this review, we summarized the latest work about the role of phase separation in spatial chromatin organization, focusing on direct and indirect effects of phase separation on 3D chromatin organization and its impact on transcription regulation. The site for storing genetic information in eukaryotes is the nucleus, and chromatin is accommodated in its limited space through multi-level organization and compaction. Three-dimensional chromatin structure is highly correlated with multiple processes, including correct gene expression, DNA replication and so on. In order to gain deep insights into 3D chromatin organization, two kinds of methods have emerged. One is based on the microscope approach, and the other is based on high-throughput sequencing. These methods deepened our understanding of the 3D genome, and proved that chromatin organization is highly degree ordered and unevenly distributed in space ,2. The gThe mechanism of high-order chromatin organization received much attention in recent years. A few models were proposed and validated to contribute to chromatin architecture, such as self-organization and loop extrusion . More anThe continuous development of new technologies has provided us with unprecedented insight into the role of LLPS in 3D genome organization. This review first concisely introduces the emergence and development of LLPS, then briefly recounts 3D chromatin organization research. We emphatically summarize the role of LLPS in the formation of 3D chromatin organization at different scales, and discuss the contribution of several important nuclear bodies in the nucleus to the formation of chromatin structure. This can help us better understand the contribution of phase separation to chromatin remodeling and gene transcription regulation, and provide guidance for future studies.As early as 2009, Tony Hyman put forward the concept of LLPS. By studying the nuclear pore complexes (NPCs) and discovering the liquid-like properties of P granules in the reproductive cells of Caenorhabditis elegans, they found that P granules were membrane-free agglomerates formed by phase separation of protein and RNA . SimilarBiomolecular condensation formed by LLPS has some specific liquid-like characteristics. Typically, it is spherical and can separate or fuse under the shear force to form a smaller or bigger spherical droplet. Fluorescence recovery after photobleaching analysis demonstrated that the molecular exchange between phased droplets and the surrounding environment is fast and frequent. In addition, LLPS is highly dynamic. LLPS can be affected not only by the characteristics of its components, such as electronic characteristics, quantity, reactivity and spatial arrangement, but also by environmental factors, such as temperature, PH and ion concentration . LLPS haThe basic structural unit of eukaryotic chromatin is the nucleosome, which is composed of 147 bp of DNA wrapped around a histone octamer and forms a beads-on-a-string structure. Nucleosomes need to be further folded within a micro size nucleus and form higher order chromatin organization . At presHigh-order chromatin organization is closely related to all chromatin-based activity in the nucleus, including transcription, DNA replication and so on. Many studies focus on the mechanism of chromatin organization and remodeling. Although there is evidence that the formation of TAD and loops mainly depends on the loop extrusion model ,34, the In physiologic salt concentrations, 10 nm nucleosomes have the intrinsic ability to condensate chromatin into globules through LLPS A 38]. B. B38]. BHistone tails emanate from nucleosome core particles and can be modified by different kinds of post-translational modifications, including methylation, phosphorylation, acetylation and so on. These modifications combined with its related proteins, such as reader, writer and eraser, can influence chromatin phase separation and regulate the dynamic of chromatin organization A. AcetylChromatin loops bring together distal elements on DNA and have important functions, such as regulation of gene transcription through enhancer–promoter loops. Loops in mammalians are thought to be formed by loop extrusion in which loop-extruding factors, likely SMC complexes, slide along DNA until counter-border elements, such as CTCF . N-termiFurther studies showed that the C-terminal domain (CTD) of RNA polymerase II can undergo phase separation itself, and the number of CTD consensus heptads influence its localization to active transcription foci . In addiRecent studies showed that silencers, which are defined by enrichment of H3K27me3 or anchors of PRC2-mediated loops, can also function effectively across long distances through chromatin looping to perform their repressive functions ,60,61. RTADs are also thought to be assembled by loop extrusion and each TAD emerges from multiple loops dynamically formed through extrusion ,62. LoopTheoretical approaches such as polymer physics have been employed to investigate chromatin architecture and unveil the underlying shaping mechanisms . ModelinOne recent study illustrates the role of LLPS in TAD reorganization C. Jia etA and B compartments of chromatin roughly correspond to the transcribed euchromatin and silenced heterochromatin, respectively. More and more evidence shows that compartmentalization seems to be driven, at least in part, by the phase separation ,73,74. ALLPS has been validated to contribute to the formation of both constitutive and facultative heterochromatin D. The siFor the facultative heterochromatin marked by H3K27me, recent studies have shown that it is mediated by the phase separation of Chromobox homolog 2 (CBX2) protein . PolycomIn addition to the direct participation in formation of various layers of high-order chromatin organization, phase separation can affect overall chromatin structure within the nucleus by influencing interactions between chromatin and nuclear compartmentalization elements, such as nuclear speckles and nucleus. These micron-sized nuclear elements are driven by LLPS and can serve as physical anchors in nucleus. They will restrict chromatin location and mobility in 3D space, and strongly affect overall genome organization. Studies have shown that inactive chromatin accumulates near the nucleolus and nuclear lamina, while nuclear speckles are active chromatin centers . In the The nuclear speckles (NSs) are defined as bodies located in the interchromatic region of cell nucleoplasm, which is the region of pre-mRNA splicing and enriched in splicing factors . NSs areChromatin regions related to NSs tend to be transcriptionally activated  91]. Re. Re91]. The most prominent nuclear sub-structure is the nucleolus, which is a typical membraneless organelle. The nucleolus is the initial site of ribosome biogenesis and involves hundreds of proteins guiding the chemical modification of rRNA and the folding of pre-rRNA. The nucleolus of mammalian cells has three sub-compartments, namely, the fibril center (FC), dense fibrillar component (DFC) and granular component (GC) from inside to outside . IncreasThe chromatin regions around the nucleolus tend to be repressive heterochromatin  104]. P. P104]. The nuclear lamina (NL) is an important nuclear landmark lying in the inner surface of the nuclear membrane and can interact with the chromatin . It is aChromatin related to NL tends to be condensed heterochromatin . SeveralPhase separation may contribute to NL-chromatin interaction ,121. HP1Other nuclear bodies formed through liquid–liquid phase separation may also contribute to chromatin structure. Cajal bodies and Promyelocytic Leukemia Nuclear (PML) bodies act as foci to recruit different genes. Cajal bodies associated regions are enriched with transcriptionally active histone genes and U small nuclear or nucleolar RNA (sn/snoRNA) loci . In the In recent years, study on the function of phase separation within the nucleus is one of the most rapidly developing fields. Phase condensates can attract or repel certain molecules to activate or inhibit various biochemical reaction processes, which is an effective mechanism making the biological process in the crowded nucleus orderly. Current studies showed that LLPS is a key factor in spatial chromatin organization and gene expression regulation. Destroying specific liquid condensate may lead to changes in chromatin organization and the occurrence of various diseases, including cancer. Our review summarizes the latest work on the role of phase separation in 3D chromatin organization from both direct and indirect views. LLPS directly drives 3D chromatin organization from different levels, such as compartments, TADs, loops and nucleosomes condensation. LLPS also indirectly influences 3D chromatin organization by regulating the interaction of chromatin to important nuclear bodies. It is expected to provide certain support for the future study of the underlying mechanism for 3D chromatin organization. In this review, we focus on talking about LLPS. It is worth noting that other kinds of phase separation, such as polymer–polymer phase separation (PPPS) and liquid–gel phase separation (LGPS) may also play roles in chromatin organization ,70. In aInnovation of experimental techniques will accelerate the study of relevant fields. For example, Shin et al. developed a CRISPR—Cas9-based optogenetic approach (named ‘CasDrop’) which forms phase-separated condensates by artificial induction. Taking advantage of protein binding upon blue light activation, fusion proteins containing IDR were recruited to genomic loci targeted by dCas9, and led to formation of IDR oligomers at the target genomic loci, which would in turn drive localized LLPS. This system gave us a tool to specifically regulate the local biochemical microenvironment of chromatin and is beneficial for the study of the relationship between LLPS and 3D genome . MingleiIn particular, the disease mutations which cause changes in liquid condensation propensity of proteins and in chromatin organizations provide a new direction for the study of the pathogenesis of diseases. Rett syndrome (RTT) is a typical example, which is caused by the mutation of methyl-CpG-binding protein 2 on the X chromosome. These mutants inhibit phase separation at the specific chromatin focus in neurons . Studies


HvCslF6 is the main gene contributing to -β-glucan biosynthesis in the grain. Here, the transcriptional regulation of HvCslF6 was investigated using an in-silico analysis of transcription factor binding sites (TFBS) in its putative promoter, and functional characterization in a barley protoplast transient expression system. Based on TFBS predictions, TF classes AP2/ERF, MYB, and basic helix-loop-helix (bHLH) were over-represented within a 1,000 bp proximal HvCslF6 promoter region. Dual luciferase assays based on multiple HvCslF6 deletion constructs revealed the promoter fragment driving HvCslF6 expression. Highest HvCslF6 promoter activity was narrowed down to a 51 bp region located −331 bp to −382 bp upstream of the start codon. We combined this with TFBS predictions to identify two MYB TFs: HvMYB61 and HvMYB46/83 as putative activators of HvCslF6 expression. Gene network analyses assigned HvMYB61 to the same co-expression module as HvCslF6 and other primary cellulose synthases , whereas HvMYB46/83 was assigned to a different module. Based on RNA-seq expression during grain development, HvMYB61 was cloned and tested in the protoplast system. The transient over-expression of HvMYB61 in barley protoplasts suggested a positive regulatory effect on HvCslF6 expression.-β-Glucan is a non-cellulosic polysaccharide required for correct barley grain fill and plant development, with industrial relevance in the brewing and the functional food sector. Barley grains contain higher levels of -β-glucan compared to other small grain cereals and this influences their end use, having undesirable effects on brewing and distilling and beneficial effects linked to human health.  The primary cell walls of certain members of the Poaceae, including barley, are enriched with -β-glucan, a distinctive non-cellulosic polysaccharide that predominantly accumulates during cell expansion . In contCellulose synthase-like (Csl) genes required for -β-glucan biosynthesis, including members of the CslF, H and J families -β-glucan biosynthesis -β-glucan solubility -β-glucan levels observed in barley  was validated as a positive regulator of BdCslF6 binding to a GT-rich cis-element in the second intron of this gene -β-glucan in developing barley grain. In a co-expression analysis of transcribed genes during the cellularization of developing barley endosperm, his gene . In riceposition .Arabidopsis thaliana, particularly in the context of secondary cell walls. This led to the identification of key transcription factors    that actAC; SWN) . These MAC; SWN)  and netwr plants .HvCslF6 by identifying putative cis-elements in the 5′ promoter region of HvCslF6 and the transcription factor(s) binding to them. Such data would provide another avenue to investigate the regulation of HvCslF6 gene expression and how this affects -β-glucan abundance.Here, our work aimed to explore the transcriptional regulation of HvCslF6 upstream region to drive expression was tested by GFP tagging in transgenic barley lines. To identify regulatory motifs in the HvCslF6 promoter, a series of 5′ deletion constructs generated from the 3,000 bp HvCslF6 upstream region were fused to the dual luciferase reporter system. A barley protoplast-based transient expression system was adapted , gene network and co-expression analyses, and previous findings from other cereal species, which suggested several candidate transcription factors that may regulate HvCslF6 expression.First, the ability of a 3,000 bp  adapted  and usedHvCslF6 is expressed across a range of tissues including grain and young/developing tissues such as the coleoptile, root and leaves  driven by a 3,000 bp 5′ sequence upstream of HvCslF6 (pHvCslF6) were generated and screened in grain and vegetative tissues. Transverse sections of transgenic mature grain showed strong mGFP-ER expression in the starchy endosperm  were compared to identify which produced the most detailed motif predictions with the least number of redundant results. TFBS prediction outputs were compared across the three programs, revealing differences in frequency  and annotation (profile summary of each motif comprising TF class and origin species) of predicted TFBSs . These were: MYB/SANT , DNA-binding with one zinc finger DOF (13.3% and 8.9%), APETALA2/Ethylene response factors AP2/ERF (9.3% and 8.4%), basic leucine zipper bZIP (4.7% and 6.5%), WRKY (5.4% and 3.2%), auxin response factors ARF , and NAC (4.6% and 3.6%). Notably, 52% of PlantPAN predicted motifs could not be classified because no information/description was available regarding their hit sequence.As the 3,000 bp 5′ promotor region was sufficient to drive the temporal and spatial expression of ed TFBSs . It shoued TFBSs . Therefoin silico analyses of the proximal promoter region of HvCslF6  and 355 non-redundant motifs were identified. JASPAR TFBS scores are based on position frequency matrices (PFMs), defined as occurrences of each nucleotide at each position in a set of observed TF-DNA interactions  when compared to the total of 107 non-redundant motifs identified. JASPAR prediction scores for the three most abundant TF classes were similar to each other  to minimize the detection of false positives/redundant motifs in identical promoter locations , Brachypodium distachyon and rice (Oryza sativa), and compared the TFBS to those identified in barley . This revealed 59 common motifs across all species , and other less abundant bHLH and DOF-related motifs. The rice CslF6 upstream sequence contained the highest number of unique TFBS predictions (84) compared to other cereals . The frequency, location, and description of predicted TFBS across all species is shown in To understand if there was conservation of binding site motifs across grass species, we carried out  species  correspoCellulose synthase gene superfamily, namely HvCesA1, HvCesA2 and HvCesA6, which are involved in cellulose biosynthesis in the primary cell wall , and MADS box factors. The largest set of common motifs was found across HvCesA2 and HvCesA6 putative promoters (77), followed by HvCesA2 HvCesA6, and HvCslF6 (60)  which are not co-expressed with HvCslF6 were also analyzed for TFBSs. This analysis identified one common predicted TFBS, a SQUAMOSA promoter-binding protein-like (SPL) motif across all putative promoters  containing MYBs, AP2/ERFs HD-ZIP among other TF classes.  . As a coclasses. .HvCslF6 promoter region necessary for transcriptional activation, seven progressively deleted promoter constructs were generated from the 3,000 bp region upstream of the HvCslF6 start codon  and tested in a barley leaf-derived protoplast system  that showed a relative increase in luciferase activity and could be responsible for upregulation of HvCslF6 expression. HvCslF6 promoter activity was comparatively low from −607 to −3,000 bp upstream of the HvCslF6 CDS, indicating that repressors of HvCslF6 expression could be binding to this −382 to −607 bp region. Furthermore, no significant differences in promoter activity were observed across constructs carrying the longest HvCslF6 promoter fragments  from cv. Morex and cv. Golden Promise and carried out a pairwise sequence alignment. Both promoters were identical based on the barley pangenome sequences available at GrainGenes1 therefore subsequent in silico prediction of TF binding sites could also be extended to cv. Golden Promise.We retrieved HvCslF6 promoter, were tested alongside three previously tested deletion constructs  to normalize dual luciferase measurements and compare promoter activity across deletion constructs  was detected in the −357 bp deletion construct. In-silico prediction of this promoter fragment indicates that it includes a putative TATA box element (5′–TATAAA–3′). This likely explains the increase in HvCslF6 promoter activity with the inclusion of this region of the promoter, and the low/zero levels of promoter activity in the first three constructs which based on our in-silico prediction lack a TATA box. Highest HvCslF6 promoter activity was narrowed down to a 51 bp region located −331 bp to −382 bp upstream of the start codon, although no significant differences  were determined between the −357 bp and −382 bp deletion constructs. Moreover, PlantPAN and JASPAR in-silico motif analysis of the additional 25 bp included in the −382 bp fragment compared to the −357 bp fragment predicted a single MYB-related motif, AC-I, enriched in AC bases. Results also indicated low HvCslF6 promoter activity from −199 bp to −331 bp based on three deletion constructs analyzed . This region contained two (three in the case of −331 bp construct) predicted calmodulin-binding NAC elements and a MYB-related motif, described as a secondary wall MYB-responsive element (SMRE) based on JASPAR analysis  onto HvCslF6 promoter regions that conveyed increased promoter activity  corresponds to another MYB consensus motif, also described as a secondary wall MYB-responsive element (SMRE) or a MYB46-responsive cis-regulatory element, M46RE (cis-element was detected in reverse orientation (3′–5′) and in Arabidopsis the same motif can be bound by AtMYB46 and AtMYB83  and a weighted gene correlation network analysis (WGCNA) performed  were assigned to the yellow module (HvMYB61 (one of the candidate HvCslF6 regulators) and HvTHX1, the barley ortholog of BdTHX1, which binds to the intronic region of BdCslF6 and acts as a positive regulator of expression of this gene   located on chromosome 5H was shown to be co-expressed with HvCesA1, HvCesA2, and HvCesA6  . All areynthesis . Additioynthesis . COBRA-l HvCesA6 . The othHvMYB61, a selection of genes from the network analysis and others known to be co-expressed with HvCslF6 . The second subset was comprised of secondary cell wall genes not co-expressed with HvCslF6 , and included other members of the HvCslF/H/J gene family, and HvTHX1, the barley ortholog of BdTHX1, a positive regulator of BdCslF6 , which show no correlation with HvCslF6, it might suggest that our candidate gene is unlikely to be involved in the broader regulation HvCslF6 expression.Then we carried out a correlation analysis using transcript expression data from the eoRNA database , which c BdCslF6 . We hypoCesA genes and HvCslF6, we observed Pearson correlation coefficients of between r = 0.9 to −0.1, while the secondary cell wall CesA genes had r = 0.4 to −0.2 (HvMYB61 and HvCslF6 (Person correlation coefficient r = 0.7 to 0.1) and HvTHX1 and HvCslF6 (Person correlation coefficient r = 0.6 to −0.1). Therefore, this analysis from an extensive range of samples and conditions provides additional evidence supporting the similar expression dynamics of HvMYB61 and HvCslF6.For the transcripts of genes considered to be primary cell wall related  to −0.2 . The ranHvMYB61 is expressed abundantly across the entire barley plant , tiller (3rd internode), rachis, developing grain at 5 days post anthesis (DPA) and embryo; these are tissues where -β-glucan is present. Similarly, HvTHX1 is also expressed in multiple tissues including developing grain (5 and 15 DPA). Expanding the RNA-seq expression data across barley grain development, an independent expression dataset based on six different spring barley cultivars  Pearson correlation coefficients with HvCslF6 were: 0.95 for HvMYB61 and 0.98 for HvTHX1 , are consistent with a regulatory effect of HvMYB61.To further investigate the expression profile of candidate MYB transcription factors we surveyed several smaller transcript datasets from barley that are independent of those described above. An RNA-seq dataset from cv. Morex across 16 barley tissues showed that ey plant . HvMYB61HvMYB61 transcription factor, since evidence suggested this gene may influence HvCslF6 expression. The candidate regulator HvMYB46/83 was ruled out based on low levels of expression from gene co-expression analyses. The candidate transcription factor HvMYB61 was cloned and transfected into barley protoplasts plus an empty vector control, respectively. After 24 h, protoplasts were harvested and HvCslF6 relative transcript abundance was measured. We observed a significant increase in HvCslF6 expression in the presence of HvMYB61, representing a fold change of 2.63 ± 0.64 in HvCslF6 expression compared to protoplasts transfected with an equal amount of empty vector -β-glucan content ultimately arises from the beneficial health effects associated with -β-glucan-rich diets -β-glucan biosynthesis, which is present across grasses including many economically important crop species, remains largely unresolved. The interest in the identification of regulators able to fine-tune ch diets  and its ch diets . Severalbidopsis .HvCslF6 which contained a binding site motif for MYB61. We observed that when this gene was overexpressed in the presence of HvCslF6 it led to an increase in HvCslF6 expression relative to control samples which lacked HvMYB61. This reflects the results of OsCslF6 and other cell wall related genes were upregulated in rice protoplasts overexpressing OsMYB61. The authors also reported a 31% decrease in leaf -β-glucan content was observed in OsMYB61a knockout mutants compared to WT. Barley and rice have distinct patterns of -β-glucan distribution throughout the plant, with barley having relatively high levels of this polysaccharide in the grain compared to vegetative tissue -β-glucan are typically 5-fold lower in rice than barley, and hence the expression or function of regulatory genes might be different between these two species.We delimited a region of the functional promoter of e tissue ; the oppe tissue . PhenotyAi lines , confirmr traits . At presHvMYB61 was only present as a single gene on barley chromosome 1H at 47.8 cM. Notably, this co-located with an association peak for grain -β-glucan content (48.4 cM) which was identified in a previous genome wide association scan using elite barley germplasm -β-glucan synthase based on sequence similarity to other Csl genes, and HvGlbI, a -β-glucan endohydrolase. HvGlbI has been shown to hydrolyse both malt -β-glucan and -β-glucan from germinating grains -β-glucan content to wild-type barley grain, it seems likely that this gene plays a minor role, if any, in determining mature grain -β-glucan content -β-glucan content is at least already partially understood,HvMYB61 appears to be an enticing candidate for further investigations of variation in HvCslF6 expression during grain development.Unlike rice, which contains two MYB61 genes -β-glucan content. In contrast, HvMYB61 expression was detected across several tissues where -β-glucan is present, (and HvCslF6 is expressed) including early stages of grain development when -β-glucan biosynthesis is occurring. No significant differences in promoter activity were observed for constructs carrying the longer HvCslF6 promoter fragments  which We also identified another R2R3-MYB binding site located from −299 to −292 bp in the ynthesis . This SMt, M46RE . HoweverHvMYB61 and HvCslF6 from a comprehensive gene network analysis of HvCslF6 using 807 gene expression sets from different developmental stages and treatments. This analysis assigned HvMYB61 to the same co-expression module as HvCslF6, the primary cellulose synthases , and HvTHX1, the ortholog of a known enhancer of BdCslF6 expression -β-glucan content and ultimately provide diagnostics to enable selection for variation in this trait. Based on our findings, we speculate that selected MYB transcription factors may act as positive regulators of -β-glucan accumulation in barley primary cell walls. This relationship relates predominantly to HvMYB61 and the proximal promoter region of HvCslF6 and is supported by co-expression in a range of tissues including the young endosperm. However, we anticipate that the regulation of HvCslF6 expression could be tissue- and genotype-specific. We previously demonstrated that HvCslF6 expression is genotype-dependent in a relatively genetically narrow selection of barley cultivars  construct were generated via Agrobacterium-mediated transformation at The University of Adelaide following the protocol outlined in 2) were screened using a Zeiss Axioskop 2 Plus microscope  equipped with an external UV light source (HBO 100). mGFP was excited at 488 nm and emission collected at 500–530 nm. For coleoptile screening, lines were grown in a petri dish with filter paper for 3–4 days in the dark and screened 5 days after gemination. Transverse section images were captured with an AxioCam 512. Subsequent to collection, images were processed with Zen Software v6.0, utilizing global adjustment tools only.Barley transgenic lines (cv. Golden Promise) carrying a 3,000 bp upstream region from HvCslF6 start codon (cv. Morex) was retrieved from the barley genome explorer (® v2014 (HvCslF6 TFBS predictions from JASPAR and filtered based on ≥ 10.0 prediction score (maximum score = 15) to minimize false positive motif predictions. Upstream CslF6 sequences from wheat (Triticum aestivum), Brachypodium distachyon and rice (Oryza sativa) were retrieved from Ensembl Plants2. TFBS comparisons across species were carried out within a 1,000 bp CslF6 putative promoter region using JASPAR . Venn diagrams were created using InteractiVenn  were grown in a growth chamber with a 16-h light/8-h dark photoperiod at the Functional Genomics (FUNGEN) facility, at The James Hutton Institute, United Kingdom. After 3 weeks, 0.25 g of primary leaves were harvested for protoplast assays. Leaves were cut lengthwise and crosswise (∼20 mm × 10 mm) and peeled  in sterile conditions using a sharp razor, scalpel and tweezers under a Leica MZ6 stereo microscope.Arabidopsis mesophyll protoplasts , pH 5.7], filtered through a 70 μM gauze , washed with 2.5 mL of W5 solution and centrifuged for 3 min at 70 × g, RT . Protoplasts were gently re-suspended in 5 mL W5 solution and kept on ice for 30 min to allow cell sedimentation by gravity. Protoplasts were re-suspended to a final concentration of approximately 2 × 105 protoplasts/mL in MMG solution . Fluorescein diacetate (FDA) was used to determine cell viability under a using a UV-light Zeiss Axioskop 2 Plus microscope and Canon EOS D100 digital camera.The barley protoplast isolation protocol was mainly based on the protocol for preparation of toplasts  with mod2 , pH 5.7]. After a 10 min incubation in the dark, protoplasts were washed twice with 1.5 mL of W5 solution and centrifuged at 200 × g for 5 min . Protoplasts were re-suspended in 80 μL of W5 solution and incubated in the dark for 24 h, at room temperature. Three independent transfection assays were performed per construct and averaged as biological replicates.For each transfection assay, 100 μL of protoplasts were mixed with 7 μg of construct DNA and 110 μL of freshly prepared 40% PEG-solution [0.4 M mannitol, 40% w/v PEG-4000 , 0.1 M CaClHvCslF6 (HORVU.MOREX.r3.7HG0698110) promoter deletion constructs were generated by PCR amplification of a 3,000 bp region upstream HvCslF6 start codon as follows: 1 μL cv. Golden Promise gDNA, 1.25 μL each primer , 72°C for 5 min and 4°C hold. Promoter fragments were ligated by NotI restriction enzyme cloning into pGreenII 0800-LUC vector which contains luciferase and renilla reporter genes, enabled to be used in Dual Luciferase Reporter Assays . A total of seven PCR amplicons corresponding to HvCslF6 promoter fragments were NotI digested and purified with the QIAquick Gel Extraction Kit . pGreenII-0800 vector was linearized in a similar digestion reaction using NotI with the addition of 1 μL TSAP  and purified as described for the pHvCslF6 fragments. Following this, T4 DNA ligations  were set up for each construct and 1 μL of the ligation reaction was used for E. coli transformation. Plasmids were purified with QIAprep Spin Miniprep Kit  and confirmed by Sanger sequencing using M13F primer at the Genome Technology facility, The James Hutton Institute.The ® Reporter Assay System  was used to determine the promoter activity of HvCslF6 deletion constructs in barley protoplasts, 24 h after transfection. Luminescence results were obtained using a Varioskan LUX Multimode Microplate Reader  following the dual luciferase kit instructions. Protoplasts were lysed with 80 μL of a 1X passive lysis buffer and incubated for 15 min at room temperature. In parallel, 100 μL of LAR II (Luciferase Assay Reagent II) were pre-dispensed in a Corning® 96-well opaque flat bottom microplate . For all assays, 20 μL of lysed protoplasts were transferred to the 96-well plate and incubated for 1 min, room temperature. After Firefly luciferase (Fluc) activity was measured (3 s per sample with a 1.5 s delay between wells), 100 μL of Stop and Glo Reagent were added enabling Renilla luciferase (Rluc) detection (1.5 s with a 0.5 s delay between wells). For each construct tested, three technical replicates were performed per transfection assay. A negative control, which included protoplasts transformed with empty vector and dual luciferase reagents, was used in each batch of transfections. Differences in dual luciferase reporter assays across HvCslF6 promoter deletion constructs were determined by one-way ANOVA followed by Tukey’s test using GraphPad Prism 8.4.2 Software . Pairwise comparisons were determined by two-tailed Student’s t-tests.The Dual-Luciferase3 were used to identify R2R3 MYB family members. The sequences were uploaded to a webserver4 for automatic identification of MYB gene family members  were added and the sequences aligned using ClustalW in MEGA (5 resulting in LG model plus gamma distribution with invariant sites (LG+G+I) as the best choice. The unrooted phylogenetic tree was build using Maximum Likelihood with 100 bootstrap replications to estimate bootstrap support. Only bootstrap values above 0.5 are displayed.The protein sequences of cv. Morex v3 genome members  using de in MEGA . Unrelia in MEGA  v2.0. Mo6 and mapped against BaRTv1 . Edge coloring was based on weight. The subnetwork was extracted by filtering for nodes connected to HvCslF6 (BART1_0-p53331). For this we applied an edge weight which is a threshold, whereby connections between gene represent by values greater or equal to 0.188 are correlated.Gene expression values from 808 individual samples  were obtt BaRTv1  using Sat BaRTv1 . Expresst BaRTv1  was usedt BaRTv1 , with a HvMYB61 (HORVU.MOREX.r3.1HG0018590) containing: 1 μL of cv. Golden Promise protoplast cDNA (1:10 diluted in sdH2O), 1.25 μL of each primer , 1 μL of linearized pDONR207™ (50 ng/μL), 2 μL 5X BP Clonase™ Reaction Buffer  and 4 μL of TE buffer, pH 8.0 in a total volume of 10 μL. The BP reaction was incubated at RT overnight and stopped by adding 2 μL of Proteinase K and incubated for 10 min at 37°C. 1 μL of the BP reaction was used for E. coli transformation. Positive colonies were transferred to 4 mL of LB medium with gentamycin (100 μg/μL) and incubated overnight, 37°C and shaking at 230 rpm. Plasmids were purified using the QIAprep Spin Miniprep Kit  and confirmed by Sanger sequencing. HvMYB61 was transferred to pBract214m-HSPT plant expression vector by LR reaction containing: 2 μL of EcoRI linearized pDONR207™-HvMYB61 (40 ng/μL), 5 μL of pBract214m-HSPT (30 ng/μL), 1 μL TE Buffer, pH 8.0 and 2 μL LR Clonase™ II enzyme mix  in a total volume of 10 μL. The reaction was incubated at 25°C for 3 h and stopped by adding 1 μL of the Proteinase K (37°C for 10 min). After E. coli transformation, positive colonies were grown on LB medium with kanamycin (100 μg/μL) for plasmid purification. pBract214m-HSPT-HvMYB61 construct sequence was confirmed as described above using the ZmUbi forward primer (A nested PCR was used to amplify d primer .5 protoplasts (100 μL) using TRIzol® Reagent  according to the manufacturer’s instructions. RNA concentration and purity were measured using NanoDrop 2000 . Total mRNA to cDNA conversion was performed using cDNA EcoDry™ Premix . For each reaction, 100 ng of total mRNA was added to the lyophilized master mix following the manufacturer’s instructions. Quantitative real-time PCR (qRT-PCR) was performed in a StepOne Real-Time PCR machine  using PowerUp SYBR Green Master Mix  to determine HvCslF6 relative transcript abundance. Three independent experiments were performed, each of them included: HvMYB61 PEG-mediated transfection, RNA extraction, cDNA synthesis and qPCRs, respectively. Three replicate qRT-PCR reactions were performed for each cDNA sample  including a negative control (sdH2O as template). Each qRT-PCR reaction contained: 2 μL protoplast cDNA (1:2 dilution), 5 μL SYBR Green, 1 μL each forward and reverse primer at 4 mM and 1 μL of sdH2O in a total volume of 10 μL. Primer sequences for HvCslF6 and qRT-PCR conditions were used as in HvCslF6 gene expression was normalized to α-Tubulin, Gapdh and Hsp70 housekeeping genes and calculated using the 2CT–ΔΔ method (HvCslF6 expression were determined by Student’s t-test compared to WT protoplasts (empty vector) using GraphPad Prism 9.1 Software .Total mRNA was extracted from ∼2 × 10T method  for multThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.HvCslF6 promoter deletion series. GG-G performed the laboratory work, TFBS, and data analyses. KH carried out co-expression analyses. MS performed the gene network construction. RS carried out the barley transformations. GG-G, MS, KH, and MT drafted the manuscript. GD, GF, RB, and RW reviewed the manuscript. All authors have read and approved the manuscript.GG-G, GD, KH, MT, RB, and RW conceived the work. GD initiated the cloning of


The integrated stress response can output two contradicting outcomes in cells; pro-survival or apoptosis. The mechanism for choice between these outcomes is unknown, however combinations of ATF4 heterodimerisation partners and post-translational modifications have been linked to this regulation. This semi-systematic review article covers ATF4 target genes, heterodimerisation partners and post-translational modifications. Together, this review aims to be a useful resource to elucidate the mechanisms controlling the effects of the integrated stress response. Additional putative roles of the ATF4 protein in cell division and synaptic plasticity are outlined.ATF4 is a cellular stress induced bZIP transcription factor that is a hallmark effector of the integrated stress response. The integrated stress response is triggered by phosphorylation of the alpha subunit of the eukaryotic initiation factor 2 complex that can be carried out by the cellular stress responsive kinases; GCN2, PERK, PKR, and HRI. eIF2α phosphorylation downregulates mRNA translation initiation  Translation in eukaryotes is the highly regulated process of converting the coding sequence contained in mRNAs into polypeptides. The translation process is exceedingly complex and is conducted primarily by the 80S ribosome alongside numerous accessory and regulatory proteins. Eukaryotic initiation factors (eIFs) control the initiation stage of translation where mRNA and the start codon recognising eIF2 ternary complex (a heterotrimeric complex required for the initiation of translation) load onto the 40S small ribosomal subunit . This isiMet). The high affinity of tRNAiMet for the eIF2 complex is dependent on the complex being loaded with GTP (iMet loading. Recycling is carried out by the guanine nucleotide exchange factor (GEF) eIF2B. First, eIF2B removes eIF5 from eIF2 which remains bound following dissociation from the ribosome (iMet to bind eIF2 to reform the eIF2 ternary complex (The eIF2 heterotrimeric complex required for translation initiation consists of three subunits [eIF2α (EIF2S1), eIF2β (EIF2S2) and eIF2γ (EIF2S3); with GTP . Followiribosome . eIF2B t complex .The eIF2α subunit of eIF2 can be phosphorylated at serine 51 by one of four kinases: General Control Non-derepressible-2 (GCN2), Protein Kinase double-stranded RNA-dependent (PKR), PKR-like Endoplasmic Reticulum Kinase (PERK) or Heme-Regulated Inhibitor HRI; . These fA hallmark of the ISR is the upregulation of the basic leucine zipper (bZIP) transcription factor Activating Transcription Factor 4 ATF4; . This isATF4, previously known as CREB2, was initially described as a transcriptional repressor of the cAMP response element CRE; , howeverThe ISR has been characterised to output two contrasting outcomes. If the ISR is activated at low levels or for a short amount of time, pro-survival pathways are upregulated; if the ISR is activated at high levels or for an extended amount of time, apoptotic pathways can be upregulated . The choThe choice between survival and apoptosis under the ISR must be a regulated process and likely candidates involved in this regulation to be investigated in this review are categorised into three sections: ATF4-interacting proteins, PTMs and target genes. The aim of this review is to comprehensively search the literature available on ATF4 to provide a resource relevant to ATF4 regulation mechanisms.th of November 2022.All searches were conducted up until the 15Homo sapiens ATF4).For interaction studies, PubMed was searched using the following keywords: (ATF4 OR ATF-4 OR CREB2 OR CREB-2 OR ATF/CREB) AND (dimer OR heterodimer OR homodimer OR homodimeric OR heterodimeric OR heterodimerization OR two hybrid OR two-hybrid OR protein dimerization). Inclusion was allowed only for mammalian encoded ATF4. Further to this, the EMBL-EBI IntAct database  was usedFor post-translational modifications, three databases were searched; Uniprot , PhosphoFor ATF4 target genes, PubMed was searched with the following keywords: (ATF4 OR CREB2 OR ATF/CREB) AND (ChIP OR chromatin immunoprecipitation). Only mammalian encoded ATF4 was allowed. For inclusion in the results table, the genes of interest required two independent observations. A complete list of all observed ATF4-interactors, target genes and PTMs can be found in An author (GN) conducted initial searches and created a database of articles which met inclusion criteria. Two authors (GN and GRM) then read abstracts to determine whether they met the inclusion criteria. We extracted information on ATF4’s interaction partners, the organisms/cell lines the experiment (s) were conducted in, the methods employed, experimental design and statistical analysis. Special attention was given to publications using CREB2 to ensure antibodies used in older experiments were indeed against ATF4.Studies were included if they were (i) peer-reviewed primary research articles , (ii) written in English, (iii) were conducted at the protein level with mammalian sequence ATF4. Only mammalian ATF4 was allowed  ATF4 were excluded).For interaction studies, there needed to be evidence at the protein level of a physical interaction between mammalian ATF4 and the binding proteins. This included methods such as yeast two hybrid, FRET and pull-downs.in vivo/ex vivo binding of ATF4 to the gene promoter/enhancer using ChIP PCR, ChIP-Seq or reChIP/co-ChIP. Less robust and indirect evidence, such as knock-downs of ATF4 being correlated with gene target expression level changes alone, were not included if that target was only shown under those conditions.For gene targets, we included genes that showed differential regulation with changes in ATF4 expression (evidenced or well-established methods of ATF4 induction) that showed evidence of For post-translational modifications, all observed human ATF4 post-translational modifications were allowed. Modifications that were inferred by species similarity alone were removed.Forty four interacting partners of ATF4 were identified in a targeted PubMed database search, with an additional 65 provided by the IntAct database . In totaATF4 gene targets that were also identified as physical interactors of ATF4 were DDIT3/CHOP, TRIB3, CEBPB, CEBPD, CEBPG, ATF3, JDP2, and NFE2L1. Apart from TRIB3, these are all bZIP transcription factors. ATF5 and ATF6 are two more bZIP transcription factors found as ATF4 targets although they were not found to interact with ATF4. ATF4 targets that were characterised as implicated in apoptosis numbered 11, namely, BECN1, DPF2, G0S2, GHITM, MCL1, NLRP1, NOXA/PMAIP1, PUMA/BBC3, SNAI2, TP53BP2/ASPP2, and DNAJA3. Targets characterised as involved in autophagy are LC3B/MAP 1LC3B, ATG3, ATG7, SQSTM1/P62, BECN1, and WIPI1. Many target protein products that localise to mitochondria were identified; MTHFD2, GPT2, ALDH18A1, ALDH1L2, ALDH2, DNAJA3, GHITM, LONP1, PCK2, and TMEM11.A nuclear exporter of tRNA, XPOT, and 15 tRNA synthetases were identified as ATF4 target genes; AARS, WARS, EPRS, GARS, IARS, LARS, NARS, SARS, VARS, YARS, CARS, FARSB, HARS, NARS, and TARS. Amino acid transporters; SLC7A11, SLC3A2, SLC7A1, SLC7A5, and SNAT2 were also identified as ATF4 target genes.While we identified a broad array of ATF4 target genes, it is clear that subsets of these genes will be only transcribed when ATF4 is bound to a specific binding partner. As ATF4 can heterodimerise with a range of other TFs, mostly bZIP domain containing , it suggOur systematic review identified 234 putative ATF4 target genes  but thisProteins that were found to both interact with ATF4 and their genes are targets of ATF4 are of interest. TRIB3, DDIT3, CEBPB, CEBPD, CEBPG, JDP2 and NFE2L1 meet this criteria. Of these, Tribbles homolog 3 (TRIB3) was the only protein identified that was not a bZIP TF. TRIB3 is a pseudokinase that is able to interact with ATF4, it inhibits transcriptional activity of ATF4, DDIT3 and CEBPB . DNA damATF3, ATF4, DDIT3, and PMAIP1 gene promoters. ATF4 binding to these promoters was inconsistent, however it is interesting that ATF4 was found to bind it’s own gene promoter in some cases. Furthermore, ATF3-ATF4 heterodimers were found to bind and upregulate mRNA expression from the gene for pro-apoptotic protein NOXA/PMAIP1 (Activating transcription factor 3 (ATF3) is considered an integral part of the ISR , it is aA/PMAIP1 .The CCAAT-enhancer-binding proteins (CEBPs) CEBPB, CEBPD, and CEBPG are bZIP TFs identified as dimerisation partners and target genes of ATF4. CEBPB is involved in immune responses, metabolism and it can induce cell-cycle arrest (reviewed in JUN dimerisation protein 2 (JDP2) is another bZIP TF identified as an ATF4 target gene and ATF4 dimerisation partner, it has been found to inhibit ATF4 transcriptional activity for some target genes including asparagine synthetase ASNS; . NuclearAn outstanding question is to what extent different ATF4 dimerisation partners control particular subsets of ATF4 target genes. ATF4 dimerisation partners each will have their own regulation mechanisms. For example, ATF4 heterodimerisation partner JUN is a bZIP TF that is induced by a broad range of extracellular stimuli. JUN has been found to be required for cell-cycle progression and to protect cells against apoptosis . Thus, iThe endoplasmic reticulum (ER) stress induced unfolded protein response (UPR) activates the ISR and ATF4 through the eIF2α kinase PERK. However, ER stress induced UPR also activates other transcription factors such as XBP1 and ATF6 . XBP1 anCasein kinase 2 (CK2) has been highlighted as an important regulator of ATF4 and ATF4-interacting CEBP TFs . CK2 wasATF4 is targeted for ubiquitin-mediated proteasomal degradation by βTRCP, dependent on phosphorylation of ATF4 at serine 219 . RecentlRET kinase was found to phosphorylate ATF4 at threonine residues 107, 114, 115, and 119 and caused a decrease in transcription of pro-apoptotic ATF4 target genes NOXA and PUMA . HoweverATF4 was found to be acetylated within the range of amino acids 270 to 300 by CREBBP , CREBBP It has long been known that ATF4 is a key regulator of apoptosis induction . SupplemSeveral ATF4 target genes were found to localise to the mitochondria which may act as an apoptosis signalling hub. The target gene DNAJA3/TID1 is a mitochondrial localised chaperone that has both short and long splicing variants. The long isoform of DNAJA3 for example can promote apoptosis whereas the short isoform supresses apoptosis . FurtherCytochrome c release can also be driven through the BCL/BAX pathway, which is dependent on the disruption of BCL-2/BAX heterodimers and the resultant formation of BAX oligomers on the mitochondrial surface. One target gene of ATF4 is G0S2, a mitochondrial protein that prevents formation of BCL2-BAX heterodimers thereby promoting apoptosis through BAX oligomerisation . AdditioDAPK2 gene can produce an evolutionary conserved isoform with a C-terminal leucine zipper, DAPK2β, that interacts with ATF4 . DAPK2 and DAPK3 are two closely related serine/threonine protein kinases, of which DAPK3, also known as ZIP kinase, contains a leucine zipper and interacts with ATF4 . The DAPith ATF4 . Overexpith ATF4 . Kawai eith ATF4 . An intrOf interest Several identified ATF4-interacting proteins  play a rvia the PERK-eIF2α pathway.Different cell types may have differential susceptibility to ATF4-induced apoptosis. This may apply to mature fully-differentiated neurons as they are generally non-dividing essential cells that cannot be replaced . There hvia chromatin architecture and histone modifications surrounding target genes may alter ATF4 regulation and target specificity and may be the result of multiple diverse pathways which are distinct from the ISR and ATF4. The four eIF2α kinases that induce ATF4 through the ISR may have a role in tailoring ATF4 action through non-canonical substrate phosphorylation, but this has yet to be sufficiently explored. Throughout this review and literature search, it is apparent that the exact method of ISR induction, whether through UPR activation, starvation or tRNA synthetase inhibition, is likely to have very distinct downstream effects which may manifest in unique transcriptional responses by ATF4. This work summarises the various options available for ATF4 regulation, and the high degree of plasticity – what is still lacking is determining how ATF4 is guided to certain gene targets by upstream signalling.The extensive options for ATF4 dimerisation partners illustrate the complexity of ATF4 regulation. PTMs provide an additional layer of complexity, perhaps further shaping ATF4 preferences for subsets of target genes. Furthermore, genome organisation What is also apparent is that the diversity of cell types used in various studies has produced an equally diverse set of results. The 234 gene targets we have identified may represent a ‘core’ portfolio of ATF4 targets which may be greatly augmented under certain conditions and in certain cell types. In one scenario, cellular apoptosis would be considered advantageous for a multicellular organism where irreparably stressed (for example) hepatic cells could be replaced. In contrast, extensive apoptosis in terminally-differentiated mature neurons that cannot be replaced would be detrimental to an organism. It is a reasonable conclusion therefore that the decision to commit to apoptosis will be cell-type-specific in higher eukaryotes. Comparative analysis of the regulation of ATF4 in apoptosis-able and apoptosis-unable cells may be a promising avenue to better identify the mechanisms controlling ATF4-mediated apoptosis. This knowledge may help in cancer research to identify cancerous cells that could have circumvented ATF4-mediated apoptosis or cell-cycle arrest.GN conducted the initial literature search and then drafted the manuscript. GM and GN then read manuscripts and refined inclusion criteria. GM contributed and edited the manuscript and created figures. All authors contributed to the article and approved the submitted version.This work was supported by the University of Dundee.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.https://www.frontiersin.org/articles/10.3389/fnmol.2023.1112253/full#supplementary-materialThe Supplementary material for this article can be found online at: Click here for additional data file.Click here for additional data file.Click here for additional data file.