Chromatin architecture, a key regulator of gene expression, can be inferred using chromatin contact data from chromosome conformation capture, or Hi-C. However, classical Hi-C does not preserve multi-way contacts. Here we use long sequencing reads to map genome-wide multi-way contacts and investigate higher order chromatin organization in the human genome. We use hypergraph theory for data representation and analysis, and quantify higher order structures in neonatal fibroblasts, biopsied adult fibroblasts, and B lymphocytes. By integrating multi-way contacts with chromatin accessibility, gene expression, and transcription factor binding, we introduce a data-driven method to identify cell type-specific transcription clusters. We provide transcription factor-mediated functional building blocks for cell identity that serve as a global signature for cell types. Mapping higher order chromatin architecture is important. Here the authors use long sequencing reads to map genome-wide multi-way contacts and investigate higher order chromatin organisation; they use hypergraph theory for data representation and analysis, and apply this to different cell types. Aspects of genome structure have been inferred by studying genomic regions that are in close physical proximity. Chromosome conformation capture (3C)-based methods capture these interactions (contacts) through chemical fixation, digestion of DNA, and proximity ligation, followed by sequencing of ligated DNA to identify genomic regions that are in contact. A variety of cell types have now been characterized using Hi-C, a genome-wide 3C-based method, adding substantially to our understanding of genome architecture. However, limitations on read length during sequencing lead to over-representation of simple interactions, predominantly pairwise. Identification of more complex, higher-order interactions can help us build a more complete set of principles of genome architecture.Structural features of the genome are integral to the regulation of gene expression and corresponding generation of cellular phenotypes6, through inference from pairwise contacts7, and on occasion using classical Hi-C8. Ligation-free approaches, such as GAM, SPRITE, and ChIA-Drop, have recently enabled large scale capture of multi-way interactions11, though comparisons of different methods find under- and over-representation of higher order contacts in the absence of proximity ligation13.Multi-way contacts have been identified using targeted 3C-based methods12 to unambiguously identify sets of contacts among multiple loci. Multi-contact 4C sequencing (MC-4C) also uses long-read sequencing to capture contact complexity14, however, it was designed to capture local topology for individual genes and regulatory regions and does not generate multi-way contacts genome-wide. While direct capture of multi-way contacts can clarify higher order structures in the genome, new frameworks are needed to address unique analysis and representation challenges posed by the multi-way data.A recent extension of Hi-C preserves multi-way interactions and uses sequencing of long reads (e.g. Pore-C)12 and constructed hypergraphs to represent the multidimensional relationships of multi-way contacts among loci. Hypergraphs are similar to graphs, but hypergraphs contain hyperedges instead of edges. Hyperedges can connect any number of nodes at once, while edges can only connect two nodes17. Prior work on neural networks highlights the utility of hypergraph representation learning to denoise and analyze existing multi-way contact data and to predict de novo multi-way contacts18. Here, we use incidence matrix-based representation and analysis of multi-way chromatin structure directly captured by Pore-C data (Algorithm 1), which is mathematically simple and computationally efficient, and yet can provide insights into genome architecture.To address this gap, we generated Pore-C data from neonatal and biopsied adult fibroblasts and collected publicly available Pore-C data for B lymphocytes23. Furthermore, the formation of transcription clusters in the nucleus is consistent with small world phenomena in networked systems25.In our hypergraph framework, nodes are genomic loci and hyperedges are multi-way contacts among loci. In our incidence matrices, rows are genomic loci and columns are individual hyperedges. This representation enabled quantitative measurements of chromatin architecture through hypergraph entropy and the comparison of different cell types through hypergraph similarity measures. In addition, we integrated Pore-C with other data modalities to discover biologically relevant multi-way interactions, which we term transcription clusters. The cell-type specific transcription clusters we identified support a role in maintaining cell identity, consistent with prior work on transcriptional hubs or factoriesn-way hyperedges. Incidence matrix: a representation for hypergraphs where rows are nodes and columns are hyperedges. Transcription cluster: a group of genomic loci that colocalize for efficient gene transcription.We use the following definitions. Entropy: a measure of structural order in the genome. Hyperedge: an extension of edges where each hyperedge can contain any number of nodes (multi-way contact). Hypergraph: an extension of graphs containing multiple hyperedges. Hypergraph motifs: an extension of network motifs that describe connectivity patterns of 3-way, 4-way, … , 12. The experimental protocol for Pore-C is similar to Hi-C, including cross-linking, restriction digestion, and ligation of adjacent ends followed by sequencing 12. It also allows us to identify topologically associated domains (TADs) using established methods28. We demonstrate identification of TAD boundaries from decomposed multi-way contacts and show intra- and inter-TAD relationships using multi-way contacts . Colocalization of multiple genomic loci in these areas could help coordinate or increase efficiency of transcription, an idea supported by studies using fluorescence in situ hybridization (FISH) that show colocalization during active transcription19. Simulations also strengthen the idea that genomic loci that are bound by common transcription factors can self-assemble into clusters and form structural patterns commonly observed in Hi-C data31. We refer to these instances of highly concentrated areas of transcriptional machinery and genomic loci as transcription clusters. The colocalization of multiple genomic loci naturally leads to multi-way contacts, but these interactions cannot be fully captured from the pairwise contacts of Hi-C. Multi-way contacts derived from Pore-C reads can detect interactions between many genomic loci, and are well suited for identifying potential transcription clusters . In addition, transcription clusters containing ≥2 genes were significantly more likely to have transcription factors and master regulators in common (p < 0.01). After testing all orders of multi-way transcription clusters together, we also tested the 3-way, 4-way, 5-way, and 6-way (or more) cases individually. We found that all cases were statistically significant (p < 0.01) except for clusters with common transcription factors or master regulators in the 6-way (or more) case for both fibroblasts and B lymphocytes. We hypothesize that these cases were not statistically significant due to the large number of loci, naturally leading to an increased overlap with genes. This increases the likelihood that at least two genes will have common transcription factors or master regulators. Over half of the transcription clusters where the majority of genes contained common transcription factors also contained at least one enhancer in adult fibroblasts (98.2%) and B lymphocytes (87.9%), further suggesting regulatory function within these multi-way contacts34 . That is, we tested whether the identified transcription clusters are more likely to include genes, and if these genes were more likely to share common transcription factors, than random multi-way contacts. We found that the identified transcription clusters were significantly more likely to include ≥1 gene and ≥2 genes than random multi-way contacts  and B lymphocytes   for binding using ChIP-seq data. CTCF specifically mediates chromatin looping and TAD boundary insulation42.We next sought to determine which TFs might be involved in cell type-specific regulation in transcription clusters. For each cell type, we ranked expressed TFs by frequency of binding sites across transcription clusters. Among TFs with the most frequent binding sites, 39% were shared across all three cell types, compared to 72% between adult and neonatal fibroblasts , RNA-seq (R: gene expression), RNA Pol II (P: ChIP-seq), ATAC-seq (C: chromatin accessibility), transcription factor binding motifs (B)1.  for each set of Pore-C data Al ∈ Ado2.  Hl using Algorithm S13.   Construct incidence matrix Tlp, Tlc, and Tls using Algorithm S24.   Identify transcription clusters Sl using Algorithm S35.   Calculate entropy end for6.  dij between pairs Hi and Hj with p ≥ 1 using Algorithm S47.  Compute hypergraph distance αij for hypergraph distance dij using the permutation test in Algorithm S5.8.  Calculate the statistical significance Return: Hypergraph incidence matrices Sl, potential transcription clusters Tlp, transcription clusters Tlc, specialized transcription clusters Tls, and hypergraph distance matrix [dij] with statistical significance [αij].9.  44. Our work here extends the application of hypergraphs, demonstrating a natural way to represent and analyze genome organization across scales.In this work, we introduce a hypergraph framework to study higher-order genome organization from Pore-C long-read sequence data. We demonstrate that higher-order genome architecture can be precisely represented and analyzed using hypergraph theory. Using direct capture of multi-way contacts, we identified transcription clusters with physical proximity and coordinated gene expression. Our framework thus enables study of explicit structure-function relationships that are observed directly from data, without needing to infer multi-way contacts. In engineering and social systems, hypergraph representation of data has revealed higher-order organization principles efficiently45. This approach can also connect genome organization principles to the study of transcription factors and how they govern cell type-specific network architecture, which resembles small world phenomena46. Our results support the idea of cell type-specific formation of transcription clusters that serve as a basis for efficient navigation of information within the nucleus, and thereby reflect a signature of small world architecture. Analogous to the behavior of short-path information propagation in social networks, we posit that transcription clusters act as decentralized nodes, or critical architectures relevant to cell identity. Future work to explore these phenomena systematically will undoubtedly help us understand cell type-specific organization principles. Another exciting direction will be to investigate time series multi-way interactions during cellular transitions such as differentiation and cell reprogramming, with single cell observations. Furthermore, we imagine that multi-way chromatin structure together with spatial transcriptomics will guide us to uncover formation principles in tissue patterning and organogenesis48.Exploring long-range, inter-chromosomal interactions genome-wide offers the opportunity to establish fundamental principles of genome organization. Unbiased capture and study of multi-way contacts can help identify biologically important assemblies that affect transcription, such as transcription clustersPrimary dermal fibroblasts (IR) were obtained from a punch biopsy from one adult male volunteer (age 42 years) with approval from the Institutional Review Board of the University of Michigan Medical School (HUM00135011) and informed consent. No compensation was provided.Human fibroblasts were maintained in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum (FBS), 1X Glutamax (Thermo Fisher Scientific Cat no. 35050061) and 1X nonessential amino acid (Thermo Fisher Scientific Cat no. 11140050). BJ fibroblasts (RRID:CVCL_3653) were purchased from the American Type Culture Collection .12. 2.5 million cells were washed three times in chilled 1X phosphate buffered saline (PBS) in a 50 mL centrifuge tube, pelleted by centrifugation at 500 × g for 5 min at 4 ∘C between each wash. Cells were resuspended in 10 mL room temperature 1X PBS 1% formaldehyde (Fisher Scientific Cat no. BP531-500) by gently pipetting with a wide bore tip, then incubated at room temperature for 10 min. To quench the cross-linking reaction 527 μL of 2.5 M glycine was added to achieve a final concentration of 1% w/v or 125 mM in 10.5 mL. Cells were incubated for 5 min at room temperature followed by 10 min on ice. The cross-linked cells were pelleted by centrifugation at 500 × g for 5 min at 4 ∘C.Protocols for cross-linking were based on Deshpande et al.μL permeabilization buffer. Cells were centrifuged at 500 × g for 10 min at 4 ∘C after which the supernatant was aspirated and replaced with 200 μL of chilled 1.5X New England Biolabs (NEB) cutsmart buffer. Cells were centrifuged again at 500 × g for 10 min at 4 ∘C, then aspirated and re-suspended in 300 μL of chilled 1.5X NEB cutsmart buffer. To denature the chromatin, 33.5 μL of 1% w/v sodium dodecyl sulfate  was added to the cell suspension and incubated for exactly 10 min at 65 ∘C with gentle agitation then placed on ice immediately afterwards. To quench the SDS, 37.5 μL of 10% v/v Triton X-100 (Sigma Aldrich Cat no. T8787-250) was added for a final concentration of 1%, followed by incubation for 10 min on ice. Permeabilized cells were then digested with a final concentration of 1 U/μL of NlaIII (NEB-R0125L) and brought to volume with nuclease-free water to achieve a final 1X digestion reaction buffer in 450 μL. Cells were then mixed by gentle inversion. Cell suspensions were incubated in a thermomixer at 37 ∘C for 18 hours with periodic rotation.The cell pellet was resuspended in 500 μL of cold permeabilization buffer  and placed on ice for 15 min. One tablet of protease inhibitor cocktail was dissolved in 1 ml nuclease free water and 100 μL from that was added to a 500 ∘C for 20 min. Proximity ligation was set up at room temperature with the addition of the following reagents: 100 μL of 10X T4 DNA ligase buffer (NEB), 10 μL of 10 mg/mL BSA and 50 μL of T4 Ligase (NEB M0202L) in a total volume of 1000 μL with nuclease-free water. The ligation was cooled to 16 ∘C and incubated for 6 h with gentle rotation.NlaIII restriction digestion was heat inactivated at 65 ∘C for 18 hours. In order to purify DNA, the sample was transferred to a 15 mL centrifuge tube, rinsing the original tube with a further 200 μL of nuclease-free water to collect any residual sample, bringing the total sample volume to 2.2 mL. DNA was then purified from the sample using a standard phenol chloroform extraction and ethanol precipitation.To reverse cross-link, proximity ligated sample was treated with 100 μL Proteinase K (NEB P8107S-800U/ml), 100 μL 10% SDS (Invitrogen Cat no. 15553-035) and 500 μL 20% v/v Tween-20 (Sigma Aldrich Cat no. P1379) in a total volume of 2000 μL with nuclease-free water. The mixture was incubated in a thermal block at 56 μg of genomic DNA input was used to generate a sequencing library according to the protocol provided for the SQK-LSK109 kit . After the DNA repair, end prep, and adapter ligation steps, SPRI select bead suspension  was used to remove short fragments and free adapters. A bead ratio of 1X was used for DNA repair and end prep while a bead ratio of 0.4X was used for the adapter ligation step. Qubit dsDNA assay  was used to quantify DNA and ~300–400 ng of DNA library was loaded onto a GridION flow cell . For adult fibroblasts, 4 sequencing runs were conducted generating a total of 6.25 million reads (referred to as V1-V4). For neonatal fibroblasts, 4 sequencing runs were conducted generating a total of 11.85 million reads.Purified DNA was Solid Phase Reversible Immobilization (SPRI) size selected before library preparation with a bead ratio of 0.48X for fragments >1.5 kb. The >1.5 kb products were prepared for sequencing using the protocol provided by Oxford Nanopore Technologies. In brief, 1 https://github.com/nanoporetech/Pore-C-Snakemake, commit 6b2f762). The pipeline maps multi-way contacts to a reference genome and stores the hyperedge data in a variety of formats. The reference genome used for mapping was GRCh38.p13 (https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.39/). Each of the four sequencing runs were assigned a sequencing run label and then concatenated. The combined pipeline outputs were used as standard inputs for all downstream analysis.Reads which passed Q-score filtering  after base calling on the Oxford Nanopore GridION  were used as input for the Pore-C-Snakemake pipeline , and hyperedges as contacts among genomic loci. We switch between these different resolutions both for computational efficiency and visual clarity. Most higher order contacts are unique in Pore-C data at high resolution (read level or 100 kb), so for these data we considered unweighted hypergraphs (i.e. ignore the frequency of contacts). For lower resolutions (1 Mb or 25 Mb), we considered edge weights (frequency of contacts) to find the most common intra- and inter-chromosomal contacts.A hypergraph is a generalization of a graph. Hypergraphs are composed of hyperedges, which can join any number of nodesWe performed an additional filtering step while constructing genomic hypergraphs. We first decomposed each multi-way contact into its pairwise combinations at a particular resolution. From these pairwise contacts, we counted the number of times a contact was detected for each pair of loci, and identified the highest frequency locus pairs. Pairwise contacts were kept if they occurred above a certain threshold number, which was set empirically at the 85th percentile of the most frequently occurring locus pairs. For example, in fibroblast data binned at 1 Mb resolution, a locus pair with six detected contacts corresponded to the 85th percentile. Thus all pairs of loci with fewer than six detected contacts were not considered, which increases confidence in the validity of identified multi-way contacts.n-by-m matrix containing values zero and one. The row size n was the total number of genomic loci, and the column size m was the total number of unique Pore-C contacts . Nonzero elements in a column of the incidence matrix indicate genomic loci contained in the corresponding Pore-C contact. Thus, the number of nonzero elements (or column sum) gives the order of the Pore-C contact. The incidence matrix of the genomic hypergraph can be visualized via PAOHvis51. In PAOHvis, genomic loci are parallel horizontal bars, while Pore-C contacts are vertical lines that connect multiple loci  and transcription factor binding site data were then integrated to determine coexpression and coregulation of genes in potential transcription clusters. If a potential transcription cluster candidate had at least two genes present, and these genes had common transcription factors based on binding motifs in the cluster, the potential transcription cluster was determined to be a real transcription cluster. From the set of transcription clusters with common transcription factors, we calculated how many clusters were regulated by at least one master regulator, a transcription factor that also regulates its own gene, and classified these as specialized transcription clusters  was used to scan for motifs within ±5 kb of genes’ transcription start sites. The results were converted to a 22,083 × 1007 MATLAB table, where rows were genes, columns were transcription factors, and entries were the number of binding sites for a particular transcription factor and gene. The table was then filtered to only include entries with three or more binding sites in downstream computations. This threshold was determined empirically and is adjustable in the MATLAB code.Transcription factor binding site motifs were obtained from "The Human Transcription Factors" databaseFrom identified transcription clusters Table , we obta12. ATAC-seq and ChIP-seq data were obtained from the Encyclopedia of DNA Elements (ENCODE) to assess chromatin accessibility and RNA Pol II binding, respectively. These data were compared to read-level Pore-C contacts to determine whether colocalizing loci belong to accessible regions of chromatin and had RNA Pol II binding for both fibroblasts and B lymphocytes. RNA-seq data were also obtained from ENCODE to ensure that genes within potential transcription clusters were expressed in their respective cell types. Additionally, ChIP-seq data for CTCF, RAD21, and SMC3 binding were obtained from ENCODE to evaluate binding preference at transcription clusters. A summary of these data sources is provided in Table Pore-C data for B lymphocytes were downloaded from Deshpande et al.55. We defined a notion of hypergraph entropy to quantify the organization of chromatin structure from Pore-C data. Denote the incidence matrix of the genomic hypergraph as H. The hypergraph Laplacian matrix is then a n-by-n matrix , which can be computed byD and E in the equation) of the hypergraph. If we consider a hypergraph with two hyperedges {v1, v2, v3} and {v3, v4}, the hypergraph Laplacian matrix and the graph Laplacian matrix (based on decomposing each hyperedge into its edge components) are computed as56.Network entropy is often used to measure the connectivity and regularity of a networkL such that 57. Biologically, genomic regions with high entropy are likely associated with high proportions of euchromatin (i.e. less organized folding patterns), as euchromatin is more structurally permissive than heterochromatin60.Inspired by von Neumann graph entropy , we define the hypergraph entropy asWe computed the entropy of intra-chromosomal genomic hypergraphs for both fibroblasts and B lymphocytes as shown in Supplementary Table 63. In order to quantify difference between two genomic hypergraphs G1 and G2 at different scales, we propose to use several hypergraph distance or similarity measures. These measures are based on conversion of hypergraph into a graph representation, see44 for details. Denote the incidence matrices of two genomic hypergraphs by i = 1, 2, construct the adjacency matrices Ai and normalized Laplacian matrices 56. The degree of a node is equal to the number of hyperedges that contain that node. Given these adjacency and normalized Laplacian matrices, we use following three distance measures in our application to determine differences in the two genomic hypergraphs at both local and global scales:Ai,jk implies jk-th entry of the matrix Ai.Hamming Distance: measures local similarity and is based on absolute values of difference between the two adjacency matrices, i.e.,p-norm for difference between ordered set of eigenvalues of the two Laplacians, i.e.,λi,j is the jth eigenvalue of i = 1, 2, and p ≥ 1. In our analysis, we choose p = 2.Spectral Distance: measures global similarity and is based on the 64, i.e.,ϵ ≪ 1 is small constant capturing the influence between neighboring nodes, and n × n diagonal matrix with the diagonal entries S1 and S2 via the Matusita difference as the measure:ϵ, and report the results for ϵ = 10−3.DeltaCon Distance: measures both local and global similarity, and is based on the fast belief propagation method of measuring node affinities using the matrixComparing graphs is a ubiquitous task in data analysis and machine learningFurther details on the properties of these different distances can be found in Supplemental Note p value of 0 compared to an observed insignificant difference between adult and neonatal fibroblasts  . The background distribution therefore can be constructed by measuring the hypergraph distances between G1 and Ri for i = 1, 2, …, N. The proportion of distances that was greater than the distance between G1 and G2 in this background distribution yielded the p value. For this analysis, we again chose N = 1 000 trials. See Similarly, we used a permutation test to determine the significance of the measured distances between two hypergraphs. Suppose that we are comparing two hypergraphs GFurther information on research design is available in the Supplementary InformationReporting SummaryPeer Review File


A challenge during development is to ensure lineage segregation while preserving plasticity. Using pluripotency progression as a paradigm, we review how developmental transitions are coordinated by redeployments, rather than global resettings, of cellular components. We highlight how changes in response to extrinsic cues , context- and stoichiometry-dependent action of transcription factors  and reconfigurations of epigenetic regulators  may confer robustness to naïve to primed pluripotency transition. We propose the notion of Molecular Versatility to regroup mechanisms by which molecules are repurposed to exert different, sometimes opposite, functions in close stem cell configurations. During development the embryo must balance lineage specification against the preservation of plasticity using a limited molecular toolkit. In this Perspective, the authors propose Molecular Versatility as a paradigm for grouping molecular mechanisms that are repurposed through development to exert distinct functions. Mouse peri-implantation development constitutes a prototypical example of such dynamic transitions during which the naïve pluripotent cells of the early epiblast transit to formative and primed pluripotent identities prior to differentiating. During this process, the reconfigurations of the epigenetic/transcriptional programs permit the emergence of distinct molecular features, including the transient competence to form primordial germ cells (PGCs)2. However, the embryonic cells also maintain their ability to self-renew and sustain the expression of certain core pluripotency transcription factors (TFs)3. Therefore, a critical challenge for peri-implantation cells is to robustly acquire novel features while preserving their stemness in constrained developmental space and time. In this Perspective, we exploited recent findings in the pluripotency field to question whether these cellular transitions involve exclusively complete molecular resettings , as traditionally proposed for differentiation processes4, or also alternative mechanisms. Hence, we herein compiled convergent findings depicting how a large battery of molecules are efficiently repurposed to exert strikingly different, sometimes opposite, functions in these closely-related stem cell configurations. We thus propose more broadly that pluripotency progression is also ensured by the fine-tuned redeployment, complementary to the resetting, of a large repertoire of intrinsic components of the cell, ranging from the plasma membrane to the chromatin. Far from a semantic argument, we propose the notion of Molecular Versatility , mouse epiblast cells reside in a naïve state, which progressively transitions to formative (E5.5–E6.5) and primed (E6.5–E7.5) configurations upon implantation  reflecting the naïve epiblast9, and epiblast stem cells (EpiSCs) resembling the primed epiblast of the anterior primitive streak11. Intermediate cellular states were captured, such as the transient Epiblast-like cells (EpiLCs)12. More recently, Rosette-like stem cells (RSCs)13 and pluripotent stem cells harbouring features of formative pluripotency were captured using various culture conditions16  and precisely at the molecular level. Recent attempts combining CRISPR/Cas9 gene disruption, large-scale transcriptomics and computational systems biology revealed that the transition from naïve to formative pluripotency is not based on the action of few master TFs but rather the product of multiple crosstalking components linking at least four signalling inputs with epigenetic and TF networks to rewire embryonic cells19. Here, we selected in the recent literature a battery of molecular mechanisms by which signalling pathways, TFs and epigenetic regulators are repurposed to reach this objective. In addition to the established notion that molecules can exert strikingly different functions in unrelated cell types, we propose the notion of Molecular Versatility to regroup these molecular mechanisms that specifically take place in similar or closely related stem cell configurations during peri-implantation development  exert strikingly different, sometimes opposite, functions in similar or closely-related stem cell configurations . This notion differs from the concept that molecules exert different functions in completely unrelated cell types. Molecular Versatility rather relates to mechanisms occurring during cellular transitions in constrained time and space.Cellular identity: Cellular identity can be defined in multiple ways and recent advances in single-cell analyses have complicated this definition by unveiling substantial transcriptional heterogeneity among cells within traditionally defined cell types138. In this Perspective, cellular identity describes the transcriptional and epigenetic programs that define a given cell type in homeostatic  conditions.20. It has to be noted that some of these signals may be dispensable for embryo development, except under certain conditions (diapause), as reported for LIF21. Naïve ESCs self-renew in a metastable state in the presence of LIF and BMP422 whereas the activation of the WNT pathway prevents their transition towards primed EpiSC23. The combined use of chemical inhibitors (2i) to suppress FGF/MAPK (via MEK1/2) and activate WNT (via GSK3 α/β) signalling instructs a ground state of pluripotency24 that can be partially mimicked by the Netrin-1 signalling pathway25. In contrast, the combined inhibition of FGF/MAPK and WNT signalling results in the capture and maintenance of RSCs in a self-renewing intermediate naïve-primed state13. Moreover, EpiLCs, FS and EpiSCs rely on Activin/Nodal and FGF/MAPK to maintain their undifferentiated state12  and primitive endoderm (PrE) lineagescts Fig. . Even if31. However, this sole FGF4/FGFR2 axis was not sufficient to explain the different functions exerted by the pathway in PrE emergence and Epi maturation. Quantitative single-cell-resolution imaging, combined with gene expression profiling of FGFR mutant/knock-in embryos, elegantly revealed how the stoichiometry of the receptors FGFR1 and FGFR2 is at least partially responsible for these differential actions32. While Epi-biased cells express solely FGFR1, PrE-biased blastomeres co-express FGFR1 and FGFR2. This variation ensures that apparently similar cells respond differently to the same ligand FGF4. The autocrine FGF4/FGFR1 axis is required for epiblast cells to mature towards the primed state while the paracrine FGF4/FGFR1/FGFR2 signalling stabilises the fate of PrE cells. In line with this, the activation of FGF/MAPK signalling in PrE- and Epi-biased cells was described to trigger the activation of different sets of target genes28. Accordingly, the recent development of ERK-kinase translocation reporter, enabling live quantification of ERK1/2 activity at the single-cell resolution in vivo, revealed that, prior to lineage specification, PrE progenitors already harbour higher ERK1/2 activity than Epi progenitors33. Of note, the sensitivity of embryonic cells to FGFs can also be mediated by the differential expression of FGF/MAPK inhibitors such as Dusp4, Dusp6, and Spred1, and the induction of negative feedback loops34 , as reviewed elsewhere37.A first element of response lies in the combined use of the FGF receptors on epiblast (Epi) and PrE progenitors. FGFR2 was long considered to be the main receptor actively promoting PrE emergence as the onset of its expression was detected by E3.5 in PrE-biased cellss34 Fig. . The mod24. However, on the other hand, Chen and colleagues demonstrated, using an inducible KO of both ERK1 and ERK2, that such complete depletion led to rapid genomic instability and compromised ESC self-renewal38. In line with this, the prolonged MEK inhibition was also shown to alter ground state ESC genomic stability39. Therefore, a precise dosage of ERK1/2 activity  seems to dictate very different outcomes in naïve cells. An alternative way to tightly control the effect of ERK1/2 activity in ESCs came from an elegant study from the Brickman lab. The authors reported that the pro-lineage commitment activity of ERK1/2 is reversible, to a certain extent. Following stimulation, ERK1/2 was found to regulate first the transcription and enhancer activity of genes without inducing any changes in the binding of pluripotency TFs but rather by modifying the association of RNA polymerase II and cofactors such as Mediator components with the chromatin. Later on, if the stimulation persists, ERK1/2 finally dismantles pluripotency by directly phosphorylating/destabilising TFs such as Klf4/Nanog and RNA polymerase II at Ser5 residue. In contrast, if stimulation stops, the reduced ERK1/2 activity restores the normal expression of pluripotency proteins. This mode of regulation indicates how the activation of ERK1/2 activity induces a transient window of lineage commitment during which reversion to naïve pluripotency is preserved40. Altogether, these examples underline various ways by which embryonic cells may modulate their response to FGF signals.Another interesting example of Molecular Versatility comes from works on the MEK/ERK factors that were found to exert dual functions in naïve ESCs, respectively promoting (i) self-renewal and (ii) lineage commitment. On the one hand, the chemical inhibition of MEK/ERK is known to constrain ESCs differentiation and to be instrumental for sustaining the ground state of naïve pluripotency41, it subsequently triggers exit from primed pluripotency and mesendoderm differentiation in EpiSCs42. We highlight below some molecular mechanisms that may allow embryonic cells to precisely modulate their responsiveness to Wnt during pluripotency progression.The WNT signalling pathway also exerts strikingly different functions in naïve and primed pluripotent stem cells. While its activation contributes to maintaining naïve pluripotency in ESCs44. More recently, nuclear β-catenin was also found to strengthen the robustness of the transcriptional apparatus by supplying transcriptional co-regulators  at pluripotency loci45. In contrast in the cytoplasm, β-catenin contributes to controlling cell adhesion by connecting cadherins through α-catenin to the actin cytoskeleton47. The use of a TCF-signalling-defective-β-catenin variant demonstrated that its cell-adhesion functions are critical for endodermal and neuronal differentiation46.First, the bi-functional nature of the effector β-catenin per se allows it to exert dual functions in promoting (i) self-renewal but also (ii) priming for differentiation Fig. . β-caten49. In addition, the noncanonical Wnt ligand Wnt5a was shown to exert opposite actions, namely activating or repressing β-catenin/TCF signalling, depending on the receptor it bound to (Ror2 or Frizzled4), indicating that the repertoire of receptors controls the response to WNT pathway50. This phenomenon will be discussed in more detail in the Netrin-1 signalling pathway section. Finally, the secretion of WNT antagonists, such as Dkk1 by the PrE13, and the existence of auto-activating loops, constitute alternative strategies to modulate response to WNT signalling51.Additional layers of regulation contribute to the Molecular Versatility of the Wnt pathway, such as the repertoire of the TCF TFs. In ESCs, TCF1 and TCF3 were shown to exert opposite functions, respectively promoting and destabilising the pluripotent network by competing for DNA binding through virtually identical HMG domains52. During early embryonic development, the pathway is responsible for the specification of mesoderm, endoderm, node, and mesendoderm. In contradiction to this function in differentiation, the pathway also plays important roles in ESCs and EpiSCs  and Unc5b is experimentally modulated 57.The Netrin-1 signalling pathway also permits to highlight Molecular Versatility during embryonic development. Netrins are a conserved family of laminin-related molecules that act chiefly through receptors of two distinct families: the deleted in colorectal cancer and UNC-5 familiested Fig. 25. There58 or robustness to biological processes59 but this apparent redundancy recently appeared as a strong way to generate diverse and specific cellular responses. As an example, in an attempt to understand how the ligands Netrin-1 and Rgma cross-talk to transduce their signals, Robinson and colleagues reported that their simultaneous binding to Neo1 does not lead to competition for binding but to the formation of a ternary super-complex that globally diminishes their functional outputs60. Moreover, by combining theoretical and experimental approaches, the Elowitz laboratory showed how cells perceive absolute but also relative concentrations of multiple ligands to compute multi-dimensional response profiles. In this model, by modifying the stoichiometry of receptors, cells modulate the computations to perform, and therefore the responses to provide to the same combination of ligands61. Mathematical modelling even revealed that such multi ligand/receptor system outperforms seemingly more specific one-to-one signalling architectures in terms of diversity and specificity of responses62. In line with this, this section highlighted different mechanisms by which embryonic cells modulate their response to their surrounding signals.More generally, these results questioned why, rather than using single ligand and receptor couples to dictate different outcomes, signalling pathways comprise multiple ligand and receptor variants that interact promiscuously to generate large sets of distinct signalling complexes. The use of redundant ligands and receptors was proposed to confer regulatory flexibility13, raising fascinating questions about how distinctive properties can be established in the presence of an overlapping set of master TFs. In line with the Molecular Versatility notion, a large fraction of pluripotency TFs were initially found to exert opposite functions in ESCs by promoting (i) self-renewal at endogenous levels but (ii) germ layer formation when ectopically expressed, including Sox2 (neurectoderm)63 and Esrrb/Tbx3 (endoderm)65. A limitation of these studies is that overexpression may show non-physiological activity of TFs as a result of non-specific binding and/or sequestration of factors. However, in the case of Oct4, its endogenous level was also reported to destabilise self-renewal, as illustrated by the fact that Oct4± heterozygous ESCs harbour a more robust pluripotent state than WT ESCs66. Therefore, based on these findings, Loh and Lim proposed to consider naïve pluripotency TFs as “pure lineage specifiers” and pluripotency as an inherently precarious condition in which these TFs compete to generate mutually exclusive lineages. This intriguing concept was slightly contrasting with the model proposed by A. Smith of a “ground” state of pluripotency in which pluripotency TFs rather cooperate to constrain the fluctuations provided by opposing differentiation programs69. Of note, this notion of TF battles was initially described in the hematopoietic system where single multipotent cells activate distinct lineage-affiliated gene expression programs prior to exclusive lineage commitment70.Naïve, formative and primed stem cells are characterised by the shared expression of TFs such as Oct4 and Sox219. In that context, the notion of “Molecular Versatility” presented herein might also provide a basis for unifying those principles. We propose that, during pluripotency transition, the stepwise dismantling of the robust naïve TF network, combined with epigenetic remodeling, allows pluripotency TFs to start exerting alternative functions. Therefore, rather than genuine lineage specifiers, pluripotency TFs may be considered as Molecular Versatile actors, and this intrinsic property leads them to exert both pro-self-renewal and pro-lineage commitment functions in closely-related cellular configurations. We detailed this notion below for Oct4 and Nanog.Recently, computational systems biology approaches conducted on the transition from naïve to formative pluripotency rather proposed that pluripotency progression does not rely solely upon instructions delivered by few master TFs. It rather appears that a cloud of activity involving multiple coordinated and partially redundant inputs operates to destabilise the existing and self-reinforced naïve gene regulatory networkOct4 (octamer-binding transcription factor 4), also known as POU5F1, promotes (i) self-renewal but also (ii) exit from pluripotency and (iii) endoderm/mesoderm formation during early development73. The comparative analysis of Oct4 genome-wide binding revealed its redistribution on distinct enhancers with and by specific cofactors in ESCs  and EpiLCs  but also during endodermal specification (Sox17), indicating how cofactors modulate Oct4 binding and function77. In addition, Oct4 levels need to be tightly controlled, at both transcriptional and post-transcriptional levels, because slight differences can profoundly alter its function78. Reduced Oct4 expression in ESCs was unexpectedly shown to trigger the establishment of a robust self-renewing state in which the Oct4 protein is redistributed on the genome and increasingly bound to enhancer regulatory regions with Nanog71. However, in a primed context in EpiSCs, reduced Oct4 levels destabilises the pluripotent state and promotes the reversion to a naïve state, indicating differential functions for the same Oct4 dosage66. In contrast, at physiological levels, Oct4 triggers the generation of a Nanog-low subpopulation of ESCs that is highly responsive to differentiation cues66, in agreement with findings of exogenous Oct4 expression triggering differentiation79. The Crispr/Cas9 technology, combined with the recent advances of single-cell approaches, will offer a unique opportunity to revisit these concepts by generating knock-in reporter ESCs for multiple pluripotency TFs and analysing the behaviour of single cells harbouring differential endogenous levels of them. In that sense, a recent report indicated that endogenous elevated OCT4 levels strongly biased ESCs towards both neuroectodermal and mesendodermal fates by increasing chromatin accessibility at differentiation-associated enhancers80. Of note, recent evidence also demonstrated the versatility of Oct4 during reprogramming to pluripotency. Silva and colleagues showed first that distinct molecular trajectories to pluripotency required to reach a very precise Oct4 level to be successful81. In line with this view, Schöler’s lab refuted the long-standing dogma of a uniquely essential role of Oct4 during reprogramming. Oct4 overexpression was indeed shown to divert cells from a direct route to pluripotency by triggering aberrant gene activation and also, more importantly, to reduce significantly the developmental potential of iPS cells , were proposed to allow Nanog to bind and activate enhancers of different sets of genes including the germ cell genes Prdm1 and Prdm1487.The TF 88. Blencowe and colleagues identified in particular a conserved AS event in the Foxp1 transcripts, specifically activated in pluripotent cells, that modifies critical amino acid residues within the forkhead domain and alters its DNA-binding specificity. The two resulting FoxP1 isoforms exert opposite effects by activating pluripotency or differentiation genes, respectively90.Of note, alternative splicing (AS) constitutes another mechanism that allows to redirect TFs during pluripotency progression. A large program of ESC specific-AS events, controlled by the RNA-binding proteins MBNL1 and MBNL2, was described to orchestrate pluripotency progressionAltogether, these data indicate a battery of mechanisms by which TFs exert different functions during pluripotency progression.91. Recent multiomics profiling of the transition from naïve ESCs to EpiLCs revealed for example major waves of protein phosphorylations but also epigenetic modifications92. Moreover, the 3D organization of the chromatin is largely modified during the naïve to primed transition, with the appearance of long-range intra- and inter-chromosomal interactions between H3K27me3 marked genes93. Here we present more specifically how epigenetic regulators are repurposed during pluripotency progression. We focus in particular on enhancer and promoter rewiring as well as Trithorax and Polycomb complexes.Epigenetic determinants play a fundamental role during early development and pluripotency progression, as reviewed elsewhere95. This is particularly true in the context of pluripotency progression, where the differences in transcriptional output between naïve ESCs and primed EpiSCs are less dramatic than the alterations observed in chromatin profiles at enhancers97. In line with this, different classes of enhancers have been defined in ESCs and EpiSCs, based on varying levels of H3K4me1, H3K27ac, H3K36me3 and pSer2/5 forms of RNA polymerase II98. Therefore, a critical challenge for embryonic cells is to ensure a coordinated rewiring of enhancers. We detailed below how Molecular Versatility applies to this process.One of the crucial effectors of cell fate transitions is the sequence-dependent binding of TFs to enhancers to regulate gene expression in a cell type-specific manner99. Foxd3 was initially reported as a repressor that decommissions active enhancers of naïve pluripotency genes via the recruitment of Lsd1 and the reduced binding of co-activators like p300  and stage-specific  pluripotency TFs101. In more detail, an elegant study by Blelloch and colleagues reported how the TF Grhl2 orchestrates such enhancer switching to partition the pluripotency network and sustain the expression of a subnetwork of epithelial genes during pluripotency progression, notably by regulating Cohesin localisation101. As depicted in Fig. Interestingly, a complex enhancer switching program was also evidenced during pluripotency progression for genes that are expressed at identical levels in ESCs and EpiSCs, such as Oct4Even if still restricted, these examples highlight how enhancers are rewired during pluripotency progression.102. A complex switch between the distal (pLiz) and proximal (pZdbf2) promoters of the Zdbf2 gene has also been described during the naïve-primed transition103. The Zdbf2 gene is expressed transiently in the early embryo (and in naïve ESCs) via its pLiz promoter and then from pZdbf2 in somatic cells. Even if the precise function of the protein remains largely unknown, this transient transcription was found to set up an epigenetic state that is required later on and programs postnatal growth. Indeed, mouse embryos deficient for the distal pLiz promoter develop normally but completely fail to activate Zdbf2 in the postnatal brain and show reduced growth. Therefore, even if this promoter switch appears dispensable for embryogenesis, it signals essential regulatory information in the adult104. At the molecular level, the transient transcription from pLiz promotes de novo DNA methylation upstream of the pZdbf2 promoter, which antagonises Polycomb-mediated repression. Interestingly, the two promoters use similar enhancers but their respective activity in ESCs and EpiLCs is controlled by contacts mediated by the CTCF protein. The alternative usage of enhancers/promoters represents an elegant example of Molecular Versatility that contributes to sustain stemness but prepares the genome for a robust and coordinated progression towards gastrulation.Promoter switching constitutes an additional way to generate Molecular Versatility during pluripotency progression. The use of two alternative promoters led for example to the production of two isoforms of the protein SET (SETα and SETβ) that were found to exert differential effects on stem cell self-renewal and commitment. SETα has beneficial effects on proliferation and linker chaperone activities without interfering with differentiation, while SETβ is essential for proper differentiation Fig. 102. A co105. TrxG complexes display versatile functions in ESCs, namely coordinating (i) self-renewal or (ii) lineage commitment, depending on the composition of subunits. The core member subunit Wdr5 was described to promote naïve ESCs self-renewal by maintaining global H3K4me3 levels and by cooperating with the Oct4/Nanog/Sox2 circuitry, sharing target genes and regulatory functions106. Ash2l, another core subunit, is also required for pluripotency: Ash2l knockdown in ESCs leads to differentiation and derepression of mesodermal markers107. Conversely, the depletion of the subunit Dpy-30 does not impact ESCs self-renewal but rather impairs their differentiation, particularly along the neural lineage. This phenotype is largely mediated by the erasure of the H3K4me3 mark at bivalent promoters that induces the dissolution of their poised state108. Interestingly, the MLL1 subunit was on the contrary reported to maintain the identity of primed EpiSCs. MLL1 inhibition leads to a global redistribution of the H3K4me1 mark and therefore to a profound rewiring of the enhancer landscape, leading to the spontaneous reversion of primed EpiSCs into naïve ESCs109.TrxG complexes mediate the deposition of the active histone mark H3K4 methylation via their catalytic subunits, the histone methyltransferases SET/MLL111. Accordingly, PRC2- (Eed KO) and PRC1- (Ring1A/B KO) deficient ESCs showed increased expression of differentiation genes112. However, PRC function is far more broad and versatile during pluripotency progression than initially established113.The PRC complexes (PRC2 and PRC1), formed by Polycomb group proteins, play essential roles in pluripotency and development by mediating chromatin modifications. PRC2 is recruited to specific genomic locations and catalyzes deposition of H3K27me3, which in turn recruits PRC1, resulting in the generation of H2AK119ub1 and transcriptional repression. In ESCs, PRC1/2 co-occupy indeed regions marked with H3K27me3, with a large proportion of these sites being proximal to genes of lineage commitment114. In ground state ESCs, PRC2 and H3K27me3 are indeed widely distributed on both euchromatin and heterochromatin, when compared with Serum/LIF ESCs.First, recent integrative proteomic profiling of ground state ESCs revealed a critical function for PRC2 in globally shaping the pluripotent epigenome to avoid the acquisition of primed features such as DNA methylation115.Second, a recent body of work demonstrated the versatile functions exerted by the different subunits of PRC2. By combining single-cell transcriptomics and embryoid body formation, Loh et al. showed that the depletion of the two distinct PRC2 subunits MTF2 and JARID2 led to different phenotypes during exit to naïve pluripotency. MTF2 absence enhanced and accelerated differentiation towards the three lineages, as expected, but JARID2 null ESCs struggled to turn off pluripotency genes and were predominantly converted into early differentiating precursors, with reduced efficiency towards the mesendoderm lineages Fig. 115.116. Targeting PRC2 genes in human ESCs led to pluripotency loss and to spontaneous differentiation towards a meso-endoderm fate. The attempts to convert mouse PRC2-deficient naïve ESCs into primed EpiSCs failed and led to similar differentiation defects as human cells. Even if the precise molecular mechanisms remain to be elucidated, these versatile functions of PRC2 might be attributable to (i) the coordinated relocation of various PRC2 complexes and to (ii) different thresholds for activation of various classes of genes.Moreover, another study highlighted the critical role of PRC2 in promoting the specification of the ectoderm in rodent and human primed stem cells118. In naïve ESC, Cbx7, which is the main PRC1-associated expressed Cbx protein, is required to maintain the undifferentiated state in a robust manner. This Cbx7-containing PRC1 complex represses the transcription of differentiation genes and of the other subunits Cbx2 and Cbx4. Once induced during differentiation, Cbx2- and Cbx4-containing complexes are redistributed to repress a large set of genes, including pluripotency-related loci. In addition, Cbx2/4 deficiency was demonstrated to skew in vivo teratoma differentiation towards the endodermal fate, indicating a specific function in germ layer formation, as also revealed for the other PRC1 subunits Ring1B and Pcgf6120. Thus, Cbx proteins confer distinct target selectivity and functions to the canonical PRC1 complex. In addition, variant PRC1 complexes, that are recruited to target genes mainly independently of PRC2 and H3K27me3, were found recently to be mainly responsible for gene repression in ESCs122.PRC1 was also reported to promote both (i) self-renewal and (ii) lineage commitment in ESCs, with reports highlighting the importance of the composition of its subunits in these versatile functions123. Recent single-cell RNA-seq analyses showed that active genes bound by PRC in ESCs are subjected to a switch between active and repressed states and harbour therefore greater cell-to-cell variation than classical active genes. This phenomenon, by favoring stochastic expression of genes, may play a key role in stem cell physiology  to finely tune its activity and to confer accuracy to the naïve-primed transition. Consistently, Tcf15 expression is transient in the early embryo, readily detectable at E4.5 but turned off by E5.5. The bHLH TF Tfe3, that promotes naïve pluripotency, is rapidly excluded from the nucleus of ESCs by the mTORC1 and lysosome signalling135, highlighting an alternative way to precisely integrate signalling cues.The activity of basic helix-loop-helix (bHLH) TFs is also controlled by multiple signals during pluripotency progression. For instance, Tcf15 was described to prime pluripotent cells for differentiation in response to FGF/MAPK signalling136.Another elegant study from Lowell et al. deciphered how the BHLH TF Id1 preserves pluripotency and avoids premature differentiation during the naïve-primed transition by being multiply regulated. Id1 expression is induced when embryonic cells lose Nanog expression but have not yet acquired Nodal activity. The Id1 protein suppresses FGF/MAPK signalling in order to protect these Nanog-negative cells from differentiation. Then, once Nodal activity is operating in these transitioning cells, Nodal itself suppresses Id1 expression and leads to a rise in to FGF activity contributing to sustaining pluripotency in primed cellsThis perspective presents converging findings demonstrating that a large repertoire of molecules are repurposed to exert different, sometimes opposite, functions in closely-related stem cell configurations during pluripotency progression. We propose to regroup these multiple molecular mechanisms by which signalling pathways, TFs and epigenetic regulators are rapidly rewired with the notion of Molecular Versatility, as summarised in Fig.


Still, changes in transcription also play an important role in the response of white adipocytes to insulin and environmental signals. One transcription factor that is dramatically and rapidly induced in adipocytes by insulin and nutrients is called Early Growth Response 1, or Egr1. Among other functions, it directly binds to promoters of leptin and ATGL stimulating the former and inhibiting the latter. Furthermore, expression of Egr1 in adipocytes demonstrates cell autonomous circadian pattern suggesting that Egr1 not only mediates the effect of insulin and nutrients on lipolysis and leptin production but also, coordinates insulin action with endogenous circadian rhythms of adipose tissue.It is believed that insulin regulates metabolic functions of white adipose tissue primarily at the post-translational level  The details of the transcriptional control of glucose homeostasis in adipocytes are not yet known; however, it has been established that effects of insulin on lipolysis and leptin expression are mediated at least in part, by Early Growth Response transcription factor, Egr1.White adipose tissue (WAT) plays a key role in mammalian physiology and pathophysiology . There aEgr1  is a zinc finger transcription factor that belongs to the family of primary response genes . Like otin vivo and in vitro. Incubation of cultured adipocytes with glucose . Upon TG hydrolysis, FA are circulated in the blood to cells and tissues where they are taken up and used for energy production and synthesis of complex lipids. Despite their fundamental physiological importance, an oversupply of FA is highly detrimental as it causes abnormal lipid partitioning and lipotoxicity which in turn, impairs membrane function, induces ER stress, mitochondrial dysfunction, inflammation, cell death, insulin resistance, and other metabolic disease . The finproblems .Complete lipolysis, i.e., hydrolysis of TG to glycerol and FA, is performed jointly by tri-, di-, and monoacylglyceride lipases . The ratvia Akt-dependent  dissociates from phosphorylated perilipin and activates ATGL . Jointlyependent  and indeependent  mechanisin vivo by such physiological stimuli as feeding, fasting, hypoxia, and physical exercise is accompanied and likely mediated by changes in the ATGL expression  with food intake and energy expenditure (via leptin). Counter-regulation of leptin production and lipolysis may be maintained by other mechanisms as well. Thus, it has been demonstrated that hypoleptinemia may activate hypothalamic-pituitary-adrenal axis to promote lipolysis in fat  and period  genes. CRYs and PERs heterodimerize, translocate to the nucleus, repress BMAL1:CLOCK transcriptional activity and undergo proteasomal degradation. This transcription-translation feedback loop takes about 24 h. In addition, BMAL1:CLOCK drive expression of REV-ERBα/β that inhibit transcription of Bmal1.In diverse organisms, the circadian clock coordinates metabolism with day/night cycles. The core mechanism of the mammalian clock consists of heteromeric transcription complex BMAL1:CLOCK that transcribes cryptochrome  circadian clocks have been described by many research groups in the course of the years [reviewed in  but also, to an endogenous circadian pacemaker in adipocytes, it is well suited to coordinate metabolic and circadian regulation of lipolysis, food intake, and energy expenditure . This rovice versa.In modern humans the situation is reversed. Counter to our diurnal nature, we often work night shifts or travel through multiple time zones. At the same time, food has become more available, and we can take advantage of time-restricted feeding to correct negative metabolic consequences of disordered molecular clock . Thus, d


R-loops are three-stranded nucleic acid structures consisting of an RNA:DNA hybrid and a displaced DNA strand. While R-loops pose a potential threat to genome integrity, they constitute 5% of the human genome. The role of R-loops in transcriptional regulation, DNA replication, and chromatin signature is becoming increasingly clear. R-loops are associated with various histone modifications, suggesting that they may modulate chromatin accessibility. To potentially harness transcription-coupled repair mechanisms in the germline, nearly the entire genome is expressed during the early stages of male gametogenesis in mammals, providing ample opportunity for the formation of a transcriptome-dependent R-loop landscape in male germ cells. In this study, our data demonstrated the presence of R-loops in fully mature human and bonobo sperm heads and their partial correspondence to transcribed regions and chromatin structure, which is massively reorganized from mainly histone to mainly protamine-packed chromatin in mature sperm. The sperm R-loop landscape resembles characteristic patterns of somatic cells. Surprisingly, we detected R-loops in both residual histone and protamine-packed chromatin and localize them to still-active retroposons, ALUs and SINE-VNTR-ALUs (SVAs), the latter has recently arisen in hominoid primates. We detected both evolutionarily conserved and species-specific localizations. Comparing our DNA-RNA immunoprecipitation (DRIP) data with published DNA methylation and histone chromatin immunoprecipitation (ChIP) data, we hypothesize that R-loops epigenetically reduce methylation of SVAs. Strikingly, we observe a strong influence of R-loops on the transcriptomes of zygotes from early developmental stages before zygotic genome activation. Overall, these findings suggest that chromatin accessibility influenced by R-loops may represent a system of inherited gene regulation. Since the discovery of R-loops, one of the most abundant non-B-DNA structures in mammalian genomes , diverseinherited gene regulation’ as general feature of epigenetic inheritance. With R-loops potentially modulating gene expression in somatic cells, they could hypothetically act as intergenerationally epigenetic active elements when present in the germline. The persistence of R-loops in the genome of oocytes at metaphase II and in embryos at the preimplantation stage and at all cell cycles was documented by immunofluorescence. Maternal and paternal pronuclei showed the highest intensities at pronuclear stage 1. The authors hypothesize that the R-loops detected in the early pronuclear stages may be related to epigenetic mechanisms such as histone modifications and chromatin structure and may contribute to the genomic reprogramming that occurs in separate pronuclei during this early zygotic development, and put forward that the dynamics of the R-loop landscape are likely mechanistically linked to zygotic genome activation (ZGA)  . This leon (ZGA) . During on (ZGA) . This glon (ZGA) . Althougon (ZGA) , the reson (ZGA) . In conton (ZGA) . Consist0 births . When coHERV-K10 . SVAs arHERV-K10 . SVAs arHERV-K10 . InteresHERV-K10 .Pan paniscus  sperm heads and demonstrate that R-loops possess the potential to represent a system of ‘inherited gene regulation’  and shipped at ambient temperature. All samples were stored at −25°C/-80°C until further processing.The total ejaculate was centrifuged  and the supernatant was discarded. The cell pellet was resuspended in lysis buffer . The suspension was centrifuged, the supernatant discarded and the previous step repeated. The pellet was resuspended in 1.35 mL lysis buffer, 150 µL 1 M dithiothreitol (DTT) was added for optimal sperm lysis, and the lysate was incubated at 55°C for 30 min.® PCR purification Kit . Libraries were prepared by Novogene using the NEB Next Ultra DNA Library Prep Kit and sequenced on Illumina NovaSeq 6000 PE150 .DRIP was performed as previously described with minor modifications . Brieflyhttps://broadinstitute.github.io/picard/; Broad Institute) and converted using SAMTools (version 1.10). To assign TE-derived reads to individual peaks, the CSEM workflow (http://mitra.stanford.edu/kundaje/akundaje/release/blacklists/hg38-human/hg38.blacklist.bed.gz) were removed using BEDTools (version 2.30.0)  with parameters according to workflow  was used 2.30.0) . Subsequ 2.30.0) . The cus 2.30.0)  and Repe 2.30.0)  datasets 2.30.0)  and Venn 2.30.0) .Total RNA was isolated from prepared sperm heads using the standard TRIzol-based protocol , followed by poly-A enrichment and sequencing by BGI Biotechnology using BGISEQ-500 Transcriptome PE100 (n = 1). RNA-seq reads were aligned to GRCh38 transcriptome using STAR (version 2.7.9a) with ‘--quantMode TranscriptomeSAM’. The RSEM Workflow  was usedTo define the regions displaying a GC skew in the human and bonobo genomes, we applied the SkewR pipeline 1.00 b using the most stringent model for GRCh38 and Mhudiblu_PPA_v0 respectively .https://maayanlab.cloud/Enrichr/) (Gene ontology (GO) Biological Process 2021 enrichments were analyzed by using Enrichr (nrichr/) .http://meme-suite.org/) was used with default settings to analyze the motifs present in R-loops  from MEME Suite  from the GEO database . If neceSince sperm heads best reflect the situation in the male pronucleus of the zygote, it is important to determine the R-loops and transcripts localized in the sperm head. Moreover, the respective localization suggests that this paternal information could be contributed to the oocytes during fertilization . Therefop < 0.001) with the chromosome specific gene density . Regarding the correlation between source genes of the transcripts and R-loops, we detected a strong bias towards protein-coding genes, in which 89,14 ± 0.07% were associated with R-loops, contrasting just 31,83 ± 10,78% of ncRNA genes . To scrutinize the possible conservation of R-loop profiles in closely related primate representatives, we isolated sperm heads from a bonobo ejaculate and DRIP - analyzed the sample as well. Using DRIP-Seq and evaluating the data with STAR-mapping and CSEM to incorporate repetitive DNA regions into peaks annotation we detected 6278 ± 639 peaks covering 4.94 ± 1.37 Mbp of the human sperm genome of which 52.76% ± 2.64% were located in genes. The average GC content of R-loops was 54.99% ± 0.02%. To further investigate the correlation between R-loops and the base composition of the corresponding genomic region, we checked for GC skews in genes associated with R-loops . The ann density . Both thNA genes .Simple Enrichment Analysis for a motif enrichment analysis and detected motifs for the transcription factors (TF) ZNF460 and ZNF135 in more than 20% of human R-loops ) R-loop formation in gene bodies , as can To examine a possible locus-specific conservation of R-loops, we pairwise compared single loci for humans with the orthologue in bonobos for conserved R-loop formation. To this end we subdivided the loci under scrutiny into the abovementioned gene components and regulatory regions. Neither in TSS, nor within exons or TTS a significant number of orthologs being identical between humans and bonobos could be seen. Contrasting to this, 10% of the human introns with R-loops shared an intronic R-loop orthologue in the bonobo . InteresTEs constitute a major part of primate genomes, and thus, intronic sequences. With the likely detrimental effect of insertional mutagenesis into exonic sequences, reduced evolutionary constraints hold for introns, although TEs shape the function of their corresponding introns by triggering differential splicing, premature stop codons and maintaining an open chromatin state . TherefoInterestingly, the enrichment of SINEs concomitant with R-loops is different in humans and bonobos . Therefode novo methylation by DNMT3B1 during early development. Interestingly, some TEs tend to evade the re-methylation during spermatogenesis after a genome wide erasure of epigenetic marks (Previous studies have described the absence of methylation at CGI associated with R-loops and protection from ic marks . During ic marks . Therefoic marks . Noticeaic marks . These fDuring spermiogenesis and beginning with the elongating spermatid stage, human sperm chromatin undergoes a dramatic transition in which histones are largely replaced by protamines. Residual histones in spermatogenesis remain because of an incomplete erasure of somatic and transitional histones, such as H3.3 and TH2B. It is hypothesized that they play a potential role in epigenetic inheritance due to their impact on the chromatin state . In contAlthough residual histones, regardless of their origin during spermatogenesis, should facilitate the formation of R-loops because of potential transcription and an open chromatin state , only a Like canonical histone modifications, R-loops can influence DNA-protein-interactions, and reconstruct the spatial epigenetic landscape due to its three-dimensional structure . This glTo correlate the stage specific transcription patterns following zygote formation with our sperm head R-loop data, we compared the presence of R-loops in different genes with their corresponding stage-dependent expression levels as outlined in In the present study, we unveiled the presence of R-loops in mature sperm of humans and bonobo. In a genome-wide read out from DRIP-Seq experiments, we observed a strong correlation between R-loop abundance and gene density regarding chromosomes. The R-loops present in both primates show a GC bias and an enrichment in gene bodies, particularly in protein-coding genes. Most of the R-loop associated genes even show a strong GC skew. We observed evolutionary conserved R-Loops in orthologous introns of human and bonobo corresponding to potentially early developmental processes. The motif enrichment analysis revealed conserved motifs in R-loops of both taxa. The most enriched motifs are binding sites for TF of RNA polymerase II, which primarily transcribes mRNAs and miRNAs. Furthermore, more than half of the human R-loops show a corresponding transcript in the transcriptome of the mature sperm, which results from transcription during early spermatogenesis, because of a mostly inert transcription in sperm . These fHypothetically and because of their GC skew and repetitive nature, TEs could function as species-specific anchors for R-loops across evolutionary time scales . The priIn vitro gametogenesis starting from pluripotent stem cells may be an obvious strategy to complement sperm with oocyte data and to characterize the role of regulatory R-loops in epigenetic inheritance more completely (During spermatogenesis the histone-to-protamine transition ensures the integrity of the paternal DNA in the spermhead. An incomplete histone-to-protamine transition leaves genomic regions associated with residual histones, leading to an open chromatin state, poised to DNA-RNA interactions . We diffmpletely . Finally


In conclusion, we revealed the underlying mechanism of the biosynthesis of the main taste components in tea plant in response to temperature was mediated by hormone signal transduction factors, which provided novel insights into improving the quality of tea.As the main flavor components of tea, the contents of epigallocatechin-3-gallate (EGCG), theanine and caffeine are regulated by ambient temperature. However, whether the biosynthesis of EGCG, theanine and caffeine in response to temperature is regulated by endogenous hormones and its mechanism is still unclear. In this study, tea cuttings cultivated in the phytotron which treated at different temperatures 15℃, 20℃, 25℃ and 30℃, respectively. The UPLC and ESI-HPLC-MS/MS were used to determine the contents of EGCG, theanine, caffeine and the contents of phytohormones in one leaf and a bud. The results showed that indoleacetic acid (IAA), gibberellin 1(GA1) and gibberellin 3 (GA3) were significantly correlated with the content of EGCG; Jasmonic acid (JA), jasmonate-isoleucine (JA-Ile) and methyl jasmonate (MeJA) were strongly correlated with theanine content; IAA, GA1 and gibberellin 4 (GA4) were significantly correlated with caffeine content at different temperatures. In order to explore the internal intricate relationships between the biosynthesis of these three main taste components, endogenous hormones, and structural genes in tea plants, we used multi-omics and multidimensional correlation analysis to speculate the regulatory mechanisms: IAA, GA1 and GA3 up-regulated the expressions of  EGCG is a main flavor component in tea , and invflavanone 4-reductase (DFR) and anthocyanidin reductase (ANR) genes were up-regulated in tea plants that cultivated in the greenhouse, which promoted the accumulation of catechins and EGCG , abscisic acid (ABA), and JA were positively related to the accumulation of gallated catechin, caffeine, and theanine, and SA was negatively correlated with these compounds in different leaf positions of tea plants . ExogenoThe biosynthesis of taste components in tea plant is not only affected by temperature, but also regulated by plant hormones. However, the internal intricate relationships between the biosynthesis of EGCG, theanine and caffeine and endogenous hormones in response to temperature in tea plant and its underlying mechanism are still unclear. In this study, tea plants were cultivated in artificial climate chamber to control the ambient temperature, the study on the internal relationships between the biosynthesis of EGCG, theanine and caffeine and endogenous hormones, signal transduction factors, transcription factors and structural genes in tea plant at different temperature treatments were explored, in order to provide a new insight into understanding the regulation of fresh leaf quality of tea plant.22.1Camellia sinensis cv. ‘Huangdan’ were purchased from Qianhe Tea Cooperative of Anxi County. The tea cuttings were transplanted into a seedling bag with a diameter of 16 cm and a height of 18 cm, and then moved into an artificial climate chamber located in Fujian Sanan Sino-Science Photobiotech Co., Ltd . Different temperature treatments were started in January 2021. Four different temperature treatments were set: 15°C, 20°C, 25°C, 30°C. Each treatment contained 100 tea cuttings. After 90 days, each 30 tea cuttings were sampled for one biological repetition, and three biological repetitions were performed. The parameters of other environmental conditions in the artificial climate chamber were set as follows: light intensity was 200 µmol·m-2·s-1, air humidity was 70%, CO2 concentration was 750 µmol·mol-1, which were referred to Xiang . The detection method of EGCG and caffeine content was referred to 2.3https://www.agilent.com/). These experiments were repeated three times with similar results (www.bestofbest.top).Using ESI-HPLC-MS/MS methods to measure the content of IAA, 3-Indole butyric acid (IBA), Indole acetyl aspartic acid (IAA-Asp), GA1, GA3, GA4, zeatin, trans-zeatin-riboside (tZR), isopentenyladenosine (iPR), isoamyl alkenyl adenine (iP), ABA, JA, JA-Ile, MeJA, salicylic acid (SA), Methyl salicylate (MeSA). About 200 mg of plant tissue was ground into a fine powder in liquid nitrogen and then extracted twice with acetonitrile and purified with a Poroshell 120 SB-C18 column. The quantification of hormone was determined by LC-MS  . The sequencing platform was DNBSEQ. The reads with low quality, joint contamination and high content of unknown base N were filtered out from raw data to obtain clean reads, then the clean reads were mapped according to reference tea genome of cv. ‘Huangdan’ genome (2.5https://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi/), and the primer sequences are shown in beta-actin (Csβ-Actin) gene as an internal reference gene, the relative expression was quantified by the 2−ΔΔCt method.Integrating the results of significant correlation, transcription factor binding site prediction and the promoter cis-element prediction, we obtain the 36 hub genes. To verify the accuracy of the transcriptome data, 36 hub genes were selected for expression level validation. Primers were designed using Primer3Plus (2.6https://www.omicshare.com/tools/). The top 20 pathways were screened by P<0.05 to draw the GO and KEGG bubble maps.Each sample was composed of three biological replicates. The T-test and correlation analysis were performed on SPSS 24.0. With 16 plant hormones as X variable and EGCG, theanine and caffeine as Y variable, the orthogonal projection to latent structures-discriminant analysis (OPLS) was conducted on SIMCA 14.1. Heatmap was produced on TBtools . Gene on33.1As the main taste components in tea, the contents of EGCG, theanine and caffeine were regulated by temperatures , indicating that the model had a good predictive ability. The OPLS analysis showed that 16 endogenous hormones and theanine varied greatly in abundance in samples treated at different temperatures, which could be clearly distinguished at different groups , indicating that the model had a good predictive ability. As shown in P<0.01). However, the relationship between the endogenous hormones of JA, JA-Ile, MeJA, MeSA and theanine content were strong positive correlated with the temperature changed . IAA, GA4, tZR, GA1, iPR, IBA, ABA had a powerful correlation with caffeine followed the temperature increasing ,  were obtained. GO enrichment analysis of DEGs (P ≤ 0.05) at different temperature treatments. KEGG analysis results showed that DEGs mainly enriched in Phenylpropanoid biosynthesis and Flavonoid biosynthesis, beta-Alanine metabolism, Arginine and proline metabolism and some hormone biosynthesis pathways such as Diterpenoid biosynthesis, alpha-Linolenic acid metabolism, Tryptophan metabolism, Phenylalanine metabolism. . These TFs belong to 36 families, among which the top seven clades were bHLH (24), ERF (24), MYB (16), TALE (14), C2H2 (12), bZIP (11) and WRKY (9). The KEGG pathway analysis on the 189 TFs was mainly enriched in plant hormone signal transduction  were predicted and obtained in 2590 DEGs ], CsC4H (HD.14G0014170), CsCHS , naringenin 3-dioxygenase [CsF3H (HD.01G0028710)] and CsANS  were obtained and the expression of these genes were increased with the temperature went up (CsCHS (HD.10G0022640), CsANS  and CsC4H (HD.14G0014170) and the trend of EGCG content was greater than 0.45. It is worth noting that the expression of CsCHS (HD.10G0022640) was much higher than that of other genes (FPKM>1000), and there was a significant positive correlation to the trend of EGCG content with temperature increased . As a result, 7 genes including CsPAL (HD.02G0024340), CsC4H (HD.14G0014170), CsCHS , CsF3H (HD.01G0028710), and CsANS  were regulated by temperature to promoted EGCG biosynthesis during tea plant cultivating, and CsCHS (HD.10G0022640) was the key gene in regulating the biosynthesis of EGCG at different temperatures.KEGG enrichment analysis showed that 7 genes , glutathione S-transferase [CsGST ], but was negatively regulated by CsgadB (HD.01G0021590) and glutamine synthetase (CsGS (HD.02003370)). There was a significant difference between the expression of CsCA (HD.06G0022520) , CsgadB (HD.01G0021590)  and theanine content (via increasing the expression of CsCA (HD.06G0022520) or down-regulating the expression of CsgadB (HD.01G0021590).There were 7 genes enriched in the pathway of theanine biosynthesis. And the biosynthesis of theanine was positively regulated by CspurA (HD.11G0025240) was negatively respond to temperature changes, which was opposite to the trend of caffeine content (CspurA (HD.11G0025240), which inhibited the decomposition of IMP, and increased the content of IMP, thus promoting the biosynthesis of caffeine.It was obviously that the content of caffeine was significantly changed with the increasing of temperature, but there were few genes in response to temperature changes at transcriptional level. As a decomposition gene of inosinic acid (IMP), the expression of 3.4.3We performed KEGG functional enrichment analysis on 2590 DEGs. There were 5, 5, 3, 5 and 8 genes screened out as the candidates impacting the biosynthesis of auxin, gibberellin, cytokinin, abscisic acid and jasmonic acid respectively, and 15 genes were involved in the plant hormone signal transduction pathways of these five hormones Figure 5via up-regulating the expression of 3 N-hydroxythioamide S-beta-glucosyltransferase [CsUGT74B1 ] and 2 amidase [CsamiE ]. However, the accumulations of IBA and IAA-Asp in tea plants were different from that of IAA, indicating that tea plants may respond to temperature by changing the existence form of auxin. Auxin signals were transmitted to downstream target genes through the expression of CsIAA (HD.03G0012010), SAUR family protein [CsSAUR ] and auxin responsive GH3 gene family [CsGH3 (HD.05001696)].The synthesis and accumulation of IAA was promoted by temperature gibberellin 2beta-dioxygenase [CsGA2ox (HD.15G0016380)]. On the contrary, ent-kaurenoic acid monooxygenase [CsKAO (HD.01G0013530)], ent-kaurene oxidase [CsKO (HD.04G0024060)], gibberellin-44 dioxygenase [CsGA20ox ] were negatively responsive to temperature changes and opposite to the accumulation trend of GA1, GA3 and GA4. We speculated that this result might be caused by the differential expression of these genes at the protein level. Gibberellin also transmitted its signal to downstream genes by inhibiting gibberellin receptor GID1 [CsGID1 (HD.14G0019770)], CsDELLA (HD.09000587) and phytochrome-interacting factor 4 [CsPIF4 (HD.03G0030020)], and regulated the biosynthesis of downstream metabolites.The biosynthesis of GA3 was positively regulated by temperature through upregulating the expression of cytokinin trans-hydroxylase [CsCYP735A (HD.04G0029870)]. While iPR and iP negatively respond to temperature changes by regulating the expression of cytokinin dehydrogenase [CsCKX ], and making cytokinin content to achieve a relatively stable level in tea plant. At different temperature, cytokinin transmitted signals to downstream genes via histidine-containing phosphotransfer peotein [CsAHP (HD.03G0015880)], two-component response regulator ARR-A family [CsARR-A (HD.04G0018610)], and two-component response regulator ARR-B family [CsARR-B (HD.11G0001770)].For cytokinin, the contents of tZR, iPR and iP responded to temperature changes, but the response patterns were different. The biosynthesis of tZR was affected by temperature through upregulating the expression of 9-cis-epoxycarotenoid dioxygenase [CsNCED ] with the temperature increased. Additionally, as a downstream degradation gene of ABA, (+)-abscisic acid 8’-hydroxylase [CsCYP707A ] is highly expressed at high temperature, thus accelerating the decomposition of ABA at high temperature. At different temperature, ABA mediated the synthesis of downstream metabolites by inhibiting serine/threonine-protein kinase SRK2 [CsSnRK2 (HD.12G0004210)] and ABA responsive element binding factor (CsABF (HD.05G0029000)).The accumulation of ABA was inhibited by temperature through negatively regulating the expression of HRAS-like suppressor 3 [CsPLA2G16 (HD.02G0017810)], lipoxygenase [CsLOX2S ], 12-oxophytodienoic acid reductase [CsOPR (HD.05G0023930)] and acyl-CoA oxidase [CsACX (HD.14G0000490)], which were initiated to regulate the biosynthesis of JA. Moreover, the high expression of jasmonate O-methyltransferase [CsJMT (HD.01002773)] accelerated the degradation of JA and promoted the biosynthesis of MeJA. At different temperatures, the JA signal regulated the downstream genes through CsJAZ .In this study, the accumulations of JA, JA-Ile and MeJA were consistent along with the variation of temperature, and which peaked at 20 °C. These observations might be associated with the expressions of 3.53.5.1https://jaspar.genereg.net/) was used to predict 81 TF binding sites. The results showed that a total of 20 transcription factors had binding sites with 15 structural genes in the biosynthesis pathways of EGCG, theanine and caffeine (Score threshold>0.80). The correlation analysis was conducted on the selected hormones, their signal transduction factors, transcription factors and structural genes, and the results were drawn into a network diagram , CsCHS (HD.10G0022640), CsANS  were positively correlated with the content of EGCG. Auxin signal transduction factor CsIAA (HD.03G0012010) was negatively correlated with CsCHS (HD.10G0022640) . The gibberellin signal transduction factor CsDELLA (HD.09000587) was negatively correlated with CsC4H (HD.14G0014170) and CsANS (HD.09G0021220) . It is worth noting that auxin signal transduction factor CsSAUR  and cytokinin signal transduction factor CsARR-A (HD.04G0018610), CsARR-B (HD.11G0001770) had strong correlation with C2H2 family protein [CsC2H2 (HD.04G0027010)], Squamosa promoter binding protein , ethylene responsive element binding factor [CsERF ], Homeodomain-leucinezipper [CsHD-ZIP (HD.05G0006810)], WRKY DNA-binding protein [CsWRKY (HD.09G0023240)], growth-regulating factor [CsGRF (HD.11G0012770)] . All of CsC2H2 (HD.04G0027010), CsSBP (HD.04G0020310), CsbZIP (HD.05G0001910), CsERF  and CsWRKY (HD.09G0023240) had strong correlation with CsIAA (HD.03G0012010) . Gibberellin signal transduction factor CsPIF4 (HD.03G0030020) was positively correlated with CsERF  and CsWRKY (HD.09G0023240) , and CsDELLA (HD.09000587) was positively correlated with CsSBP (HD.04G0020310), CsERF (HD.06G0016330), CsWRKY (HD.09G0023240), CsGRF (HD.11G0012770) . Structural genes of CsC4H (HD.14G0014170), CsCHS (HD.10G0022640), CsANS  on EGCG biosynthesis positively correlated with CsbZIP (HD.05G0001910) and CsHD-ZIP (HD.05G0006810), and negatively correlated with CsC2H2 (HD.04G0027010), CsSBP (HD.04G0020310), CsERF , CsWRKY (HD.09G0023240) and CsGRF (HD.11G0012770).For EGCG, 4 structural genes namely CsCA (HD.06G0022520) and CsgadB (HD.01G0021590) were significantly correlated with theanine content . The correlation of CsJAZ  with CsCA (HD.06G0022520), CsgadB (HD.01G0021590) were more than 0.50. And the pairwise correlations between CsJAZ , CsWRKY (HD.07G0017570), CsAP2 (HD.10G0007680) and CsgadB (HD.01G0021590) were greater than 0.40.As for theanine, the expression of CspurA (HD.11G0025240) was negatively correlated with caffeine content . There was a strongly negative correlation between CsSnRK2 (HD.12G0004210) and CspurA (HD.11G0025240) . The hormone signal factors namely CsIAA (HD.03G0012010), CsSAUR (HD.01G0019200), CsDELLA (HD.09000587), CsARR-A (HD.04G0018610), CsARR-B (HD.11G0001770), CsABF (HD.05G0029000), CsSnRK2 (HD.12G0004210) were correlated with CsC2H2 (HD.02G0015370), CsHD-ZIP (HD.05G0010130), CsWRKY (HD.08002776), CsWRKY (HD.09G0023240) and CsGRF (HD.11G0012770) (0.30<|r|<0.90), CsPIF4 (HD.03G0030020) was significantly related to CsWRKY (HD.09G0023240) . The relationship between this 5 TFs and CspurA (HD.11G0025240) had strong correlation .At different temperature, the expression of Overall, hormones and their signal transduction factors were correlated with transcription factors and structural genes related to the biosynthesis of main taste components in tea plant at different temperatures.3.5.2http://bioinformatics.psb.ugent.be/webtools/plantcare/html/) was used to predict the promoters of 20 transcription factors and 7 structural genes of main taste components synthesis related genes, and various hormone response elements on the promoters were screened  were significantly correlated with the content of EGCG, and C2H2 and SBP were significantly correlated with the content of total flavonoids  can be found below: QZ conducted an experiment, and analyzed the data, and wrote a manuscript. LL, XL, XD, BC, MT, JH, LJW conducted an experiment. WK analyzed the data. QZ, PX, LYW and JL participated in the experimental design and guided the research. LYW, YS and JL reviewed the manuscript. All authors contributed to the article and approved the submitted version.


The apolipoprotein B mRNA-editing catalytic polypeptide-like (APOBEC) family specifies multiple cytidine deaminases. In mammals, a minimum of 5 genes encode APOBECs 1, 2, 3, 4, and activation-induced cytidine deaminase (AID) . This exAlthough deamination of retroviral DNA is likely the primary mechanism of viral inhibition, deamination-independent modes of APOBEC activity have been observed ,13. BecaThe betaretrovirus mouse mammary tumor virus (MMTV) has provided a model for the first in vivo studies of APOBEC3 activity . MMTV reC  motifs in MMTV proviruses that are unable to produce Rem are heavily mutated in BALB/c mice to produce stop codons compared to proviruses that express Rem [-/-Aicda mice with Rem-mutant MMTV. Infection of Aicda-/- mice greatly reduced proviral mutations in WRC motifs, which are known AID-targeting sequences in nuclear immunoglobulin genes [C-target motifs  in MMTV proviruses observed in BALB/c mice also increased in the absence of Rem but, surprisingly, the mA3-type mutations in Rem-null proviruses disappeared when AID was absent. Furthermore, coexpression of Rem in tissue culture cells with either AID or mA3 resulted in proteasomal degradation of AID, but not mA3 [WRress Rem . This diin genes . In contin genes . The mA3 not mA3 . These r not mA3 . MMTV Re not mA3 , consistIn contrast to other APOBEC enzymes, the roles of A2 and A4 proteins remain mysterious. Recent data suggest that these deaminases may have evolved from enzymatic activities to sole use of their nucleic acid-binding properties. Recent work has hinted that A2 and A4 bind to promoter regions to affect transcriptional activity of selected genes . AlternaThe answer most certainly is affirmative. Ample evidence indicates that replication of viruses in APOBEC-expressing cells has led to the appearance of novel viral variants . As noteIn addition to the known effects of APOBECs on HIV-1 variation acting at the level of DNA replication , the CorAlthough SARS-CoV-2 and Ebola are positive and negative sense RNA-containing viruses, respectively, both have been implicated as cross-species transmission events to humans, perhaps from bats . Bats arThe regulation of APOBEC expression is only partly understood. APOBEC cytidine deaminases are part of the innate immune system, yet multiple reports indicate that other functions of innate immunity, such as signaling through the type I IFNs and Toll-like receptors (TLRs), increase levels of the A3 enzymes –39. The Regulation of AID expression reveals the multiple pathways that control APOBEC transcript levels. Treatment of cultured B cells with lipopolysaccharides (LPS)  in conjunction with the cytokine interleukin-4 (IL-4) is known to induce AID . In B ceEvolutionary evidence suggests that APOBECs are advantageous because of the expansion of this gene family in higher organisms and the amplification of the A3 genes in primates. Many of these genes appear to be under positive selection ,30. The Matonaviridae) and SARS-CoV-2 (Coronaviridae), have C-to-U editing typical of APOBECs [C motifs typical of APOBECs. This study also indicated that the vaccine-derived rubella quasi-species were recovered from the nasal cavity, but not in the bloodstream, suggesting that APOBEC-induced mutations could serve as a source of novel viruses for respiratory transmission [Although previous reports have suggested that viruses with DNA replication intermediates are the most affected, more recent experiments argue that RNA-containing viruses, such as rubella  scenario emerges for the role of APOBECs in human cancers, of which approximately 10% are due to viral infections . Interesmyc [Current databases have designated nuclear APOBECs, such as A3A, A3B, and AID, as relevant to human cancer . A3A hasmyc . In addimyc , perhapsmyc . Recentlmyc . These dIn summary, APOBECs induce mutations in both viral and host DNA, but it appears increasingly likely that RNA-containing viruses are mutated by cytidine deaminases. These mutations limit viral replication and transmission. APOBEC-mediated changes on host mRNAs in innate immune cells may provide additional short-term adaptations to inhibit viral infections. Nevertheless, these mechanisms yield viral selection. APOBEC expression in cancers leads to DNA damage and tumor cell death, yet allows for immune escape variants. Indeed, APOBECs are fickle friends.