High throughput sequencing has enabled the interrogation of the transcriptomic landscape of glucagon-secreting alpha cells, insulin-secreting beta cells, and somatostatin-secreting delta cells. These approaches have furthered our understanding of expression patterns that define healthy or diseased islet cell types and helped explicate some of the intricacies between major islet cell crosstalk and glucose regulation. All three endocrine cell types derive from a common pancreatic progenitor, yet alpha and beta cells have partially opposing functions, and delta cells modulate and control insulin and glucagon release. While gene expression signatures that define and maintain cellular identity have been widely explored, the underlying epigenetic components are incompletely characterized and understood. However, chromatin accessibility and remodeling is a dynamic attribute that plays a critical role to determine and maintain cellular identity.Here, we compare and contrast the chromatin landscape between mouse alpha, beta, and delta cells using ATAC-Seq to evaluate the significant differences in chromatin accessibility. The similarities and differences in chromatin accessibility between these related islet endocrine cells help define their fate in support of their distinct functional roles. We identify patterns that suggest that both alpha and delta cells are poised, but repressed, from becoming beta-like. We also identify patterns in differentially enriched chromatin that have transcription factor motifs preferentially associated with different regions of the genome. Finally, we not only confirm and visualize previously discovered common endocrine- and cell specific- enhancer regions across differentially enriched chromatin, but identify novel regions as well. We compiled our chromatin accessibility data in a freely accessible database of common endocrine- and cell specific-enhancer regions that can be navigated with minimal bioinformatics expertise.Both alpha and delta cells appear poised, but repressed, from becoming beta cells in murine pancreatic islets. These data broadly support earlier findings on the plasticity in identity of non-beta cells under certain circumstances. Furthermore, differential chromatin accessibility shows preferentially enriched distal-intergenic regions in beta cells, when compared to either alpha or delta cells.The online version contains supplementary material available at 10.1186/s12864-023-09293-6. The evaluation of the transcriptional landscape through high-throughput bulk RNA sequencing in both mouse and human of major islet cell types has granted a deeper understanding of cellular identity and intercellular crosstalk within the pancreas. This has enabled the detection of distinct gene pattern signatures between major islet cell types in mouse and human –6. HowevChromatin remodeling is a central epigenetic regulator that can be surveyed in order to better understand cell states , 25–28. Assay for transposase-accessible chromatin using sequencing (ATAC-Seq) allows for the unbiased, modification-independent evaluation of chromatin accessibility within cell types and can be run with relatively small sample input , 35. PreepiRomics [See: https://github.com/Huising-Lab/epiRomics]. This package is a novel, publicly available resource that is described in detail elsewhere [epiRomics allows for the visualization of integrated epigenomic data and visualizes putative enhancer regions without the requirement for extensive bio-informatics experience, with the intent of enabling more of our colleagues to tease apart key regions that may drive cell fate switching and maintenance between the major islet endocrine cell types. Through this approach we identified putative enhancer regions at distal-intergenic regions common to all 3 cell types as well as regions selectively accessible only in a single islet cell type and confirmed previously identified mouse pancreatic islet enhancers.We integrated our ATAC-Seq data with high-quality transcription factor and histone binding data from other mouse pancreatic islet studies to evaluate how transcriptional activators and repressors may collectively regulate differential gene expression at promoter-proximal regions. To support the visualization and integration of our ATAC-Seq chromatin data and previously published transcriptome of the FACS-purified alpha, beta, and delta cells alongside select epigenomic datasets from histone marker and transcription factor Chromatin Immuno Precipitation (ChIP) data, we developed an R package, lsewhere . In shorAll mouse experiments were approved by the UC Davis Institutional Animals Care and Use Committee and were performed in compliance with the Animal Welfare Act and the Institute for Laboratory Animal Research Guide to the Care and Use of Laboratory Animals. Animals were humanely euthanized using IACUC-approved methods of euthanasia in accordance with the American Veterinary Medical Association Guidelines for the Euthanasia of Animals. Mice were maintained in group housing (up to 4 mice per cage) on a 12 h light:12 h darkness cycle with water and standard rodent chow provided ad libitum. We adhered to the ARRIVE 2.0 guidelines for pre-clinical animal reporting where applicable. Our experimental design did not call for a control group as we determined the chromatin accessibility between different endocrine cells of the same tissue from the same animals. No animals were excluded from the experiments, and we observed no unexpected adverse events in the animals reported in this study. Blinding and randomization were not applicable to our study.mIns1-H2b-mCherry  or Gcg-CAll mouse experiments were approved by the UC Davis Institutional Animals Care and Use Committee and were performed in compliance with the Animal Welfare Act and the Institute for Laboratory Animal Research Guide to the Care and Use of Laboratory Animals. Animals were humanely euthanized using cervical dislocation as an IACUC-approved methods of euthanasia in accordance with the American Veterinary Medical Association Guidelines for the Euthanasia of Animals.Single-end 50 bp reads were generated after library size selection yielded an average of 450 bp fragments and sequenced as previously described using NexteraDNA library protocol .Reads from each replicate Table-S were evaQuality control metrics were evaluated within raw reads as well as peak calls and compared against ENCODE standards for fraction of reads in peaks (FRiP), leading to the removal of one beta cell replicate with a FRiP score far below 0.3 Table-SA-C 57, , 57, 58.Transcription factor motif analysis and validation against existing ChIP data was performed through a modified script utilizing chromVar , regioneepiRomics, to integrate our chromatin accessibility data alongside aggregated pancreatic islet ChIP and histone data to identify putative enhancer regions, as described [https://github.com/Huising-Lab/epiRomics and an interactive browser of the results from this manuscript is publicly available at: https://www.huisinglab.com/epiRomics_2021/index.html.We developed a novel R package, escribed . The pacepiRomics [Mouse alpha, beta, and delta (GEO: GSE80673), alongside alpha- and delta- transdifferentiated beta (GEO: GSE88778) transcriptomes were integrated into this analysis [piRomics  to identTo determine whether chromatin accessibility patterns differed between islet endocrine cell types, principal component analysis (PCA) was applied to peak calls across all samples. This confirmed that replicates clustered by cell type Fig. A, a findIns2, Gcg, and Sst genes for beta, alpha, and delta cells, respectively , beta , and delta cells   as a reflection of chromatin accessibility. Indeed, cell type-specific chromatin accessibility correlated with gene expression of ely Fig. D-F [4, 6As genes make up a small fraction of the entire genome, we determined the overall distribution of peaks across the annotated genome within each cell type. We defined five regions of interest to further explore – promoter-proximal, intronic, exonic, downstream, or distal-intergenic Fig. A. We idep-value <  = 0.05) were identified between alpha and beta  differentially enriched peaks  Fig. A. A furt kb Fig. Between alpha and delta cells, we identified that 21.29% of differentially enriched peaks occurred promoter-proximally. Another 36.4% of peaks occurred on distal intergenic regions and 35.5% on intronic regions , differential chromatin enrichment on TSS regions positively correlated with changes in gene regulation. Exactly, 50% of genes with differentially enriched chromatin at the TSS had a corresponding increase in gene expression within the same cell type , incongruent (24%), and no expression genes (20%), between alpha and delta cells. We noted a more uniform distribution between alpha (14%) and delta (10%) repressed genes. Fig. E. Upon vate Fig-SB..For the pairwise comparison between beta and delta cells, we again found a similar fraction of congruent (57%), incongruent 32%), and no expression (11%) genes Fig. F. We not2%, and nIns1-driven mCherry expression), but have either a Gcg- or Sst-Cre lineage label, reflective of a lineage history as an alpha or delta cell, respectively. We reasoned that if alpha- or delta- repressed genes are poised beta cell genes, we should expect to observe a stepwise transition in gene expression levels, showing little or no expression in either alpha or delta cells, to intermediate expression in alpha- or delta- transdifferentiated cells, and full expression in beta cells. We confirmed that the majority (83.6%) of alpha-repressed genes showed intermediate expression in the alpha-to-beta-transdifferentiated population, and the highest expression in beta cells (beta cell genes). A subset of genes (16.4%) showed the highest expression in the alpha-transdifferentiated population  in the cell type with chromatin-motif association.Motifs for key transcription factors involved in beta cell identity, such as MafA, were present ubiquitously across most functional regions we defined  Fig. A. In conSst expression in delta cells [We performed the same transcription factor motif enrichment test between alpha and delta cells Fig. B. Of notta cells , was enrta cells  was concta cells , was pre, a transcription factor important for islet development [. Motifs for Insm1 [ – linked to enhancer regions in EndoC-bH1 cells [Between beta and delta cells, no single transcription factor motif overlapped across all five functional categories, nor were there any unique to downstream or exonic regions, as we observed in the prior alpha and delta comparisons Fig. C. Of notelopment , as wellelopment , was conor Insm1  and Nkx6or Insm1 , both keor Insm1 —and Atf3H1 cells —were enrAs we observed motif binding site preferences across promoter, intronic, exonic, downstream, or distal chromatin regions, we wished to confirm how accurately predictive DNA motif binding sites conveys true transcription factor binding. To do so, we once again turned to our aggregated pancreatic islet ChIP datasets. We applied the same motif detection method as above on individual ChIP datasets and on all open chromatin – as derived from our ATAC-Seq consensus peak set –and assessed how well predicted motif binding overlapped with true ChIP peaks from our selected list of ChIP-Seq data. One transcription factor, Rfx6, showed strong (57%) true positive and low 8.34%) false negative values for its DNA-motif’s ability to predict all Rfx ChIP binding sites  histone modifications within islet cell chromatin. We narrowed our definition further by requiring these regions to also have transcription factor binding sites—Pdx1, Nkx6-1, Neurod1, Insm1, Foxa2, Nkx2-2, Rfx6, MafA, Isl1, Kat2b, Ldb1, or Gata6 – defined by islet ChIP data that are either ubiquitously or selectively expressed across the three islet cell types .The high quality ATAC-Seq data derived from this study is the first dataset of its kind from FACS-purified mouse alpha, beta, and delta cells. Moreover, while bulk-ATAC-Seq data from human alpha and beta cells have previously been reported, our data are the first to report on chromatin accessibility of delta cells and combine these cell’s chromatin landscapes to companion transcriptome data. We believe that our data will provide a useful resource that complements our companion transcriptome data that we reported previously using the exact same combination of reporter strains . LeveragPdx1 regulates the expression Slc30a8 through an intronic enhancer [In evaluating the chromatin landscape of alpha, beta, and delta cells, we noted that over half of accessible chromatin in any of the cell types corresponded to promoter-proximal regions ~ 25%) and intronic regions (~ 32%), even though a much smaller fraction of the genome is represented by promoter-proximal sites. This underscores that a substantial portion of regulatory activity occurs directly at genic regions themselves. The enrichment of promoter-proximal and intronic open chromatin we observed in mouse islet cells agrees with previous findings in human studies % and int. The strenhancer  – which enhancer , 98, 99.MafA is a key transcription factor enriched in beta cells that shows abundant chromatin accessibility in both alpha and delta cells  in alpha cells, but is only expressed in beta and delta cells .Additional file 9: Supplemental Figure 5. Evaluating KEGG and gene network enrichment (Alpha versus Delta).Additional file 10: Supplemental Figure 6. Evaluating KEGG and gene network enrichment (Beta versus Delta).Additional file 11: Supplemental Figure 7. Transcription factor binding sites and histone mark overlap.Additional file 12: Supplemental Figure 8. Aggregated transcription factor ATAC Seq and companion RNA-Seq expression in alpha, beta, and delta cells.Additional file 13: Supplemental Figure 9. Further illustration of enhancer calls.Additional file 14: Supplemental Table 1. Quality control metrics across all ATAC-Seq replicates.Additional file 15: Supplemental Table 2. Aggregated dataset description and reference. A: Pancreatic islet ChIP Seq transcription factor data aggregated to identify enhancer and enhancer regions. B: Pancreatic islet histone data aggregated to identify enhancer and enhancer regions. The final approach utilized two histone marks deemed most relevant at delineating putative enhancer regions while taking into account a risk of both false positives and false negatives.Additional file 16: Supplemental Table 3. Validating open chromatin peaks against known pancreatic islet ChIP binding sites. A: Evaluating the extent of open chromatin– as defined by our ATAC-Seq consensus peak set – contained binding sites for known, pancreatic islet transcription factors. Percent of open chromatin with associated binding sites ranged from 0.31-29.07%. The transcription factors Foxa2, Insm1, and Neurod1 had the highest number of binding sites. B: Evaluating the extent of each ChIP-Seq experiment’s binding site calls overlapped with open chromatin. Percent of overlap ranged from 0.35-63.79%. Nkx2.2, Neurod1, and Insm1 had the greatest overlap.Additional file 17: Supplemental Table 4. Validating motif-calling approach against known ChIP binding sites. A: Pancreatic islet ChIP Seq transcription factor peak calls analyzed by the motif-calling method to determine sensitivity and specificity. True positive calls ranged from 0.59-57%, and false positives ranged from 1.19-8.34%. B: Pancreatic islet ChIP Seq transcription factor peak calls limited to open chromatin determined by the consensus peak set analyzed by the motif-calling method to determine sensitivity and specificity. True positive calls ranged from 4.71-65.10%, and false positives ranged from 1.68-8.81%.


Agrobacterium fabrum C58 by identifying 1,916 TSSs. In addition, we completed genomes and phenotyping of Rhizobium rhizogenes C16/80 and Allorhizobium vitis T60/94, identifying 2,650 and 2,432 TSSs, respectively. Parameter optimization was crucial for an accurate, high-resolution view of genome and transcriptional dynamics, highlighting the importance of algorithm optimization in genome-wide TSS identification and genomics at large. The optimized algorithm reduced the number of TSSs identified internal and antisense to the coding sequence on average by 90.5% and 91.9%, respectively. Comparison of TSS conservation between orthologs of the three lineages revealed differences in cell cycle regulation of ctrA as well as divergence of transcriptional regulation of chemotaxis-related genes when grown in conditions that simulate the plant environment. These results provide a framework to elucidate the mechanistic basis and evolution of pathology across the three main lineages of agrobacteria.Agrobacteria are a diverse, polyphyletic group of prokaryotes with multipartite genomes capable of transferring DNA into the genomes of host plants, making them an essential tool in plant biotechnology. Despite their utility in plant transformation, genome-wide transcriptional regulation is not well understood across the three main lineages of agrobacteria. Transcription start sites (TSSs) are a necessary component of gene expression and regulation. In this study, we used differential RNA-seq and a TSS identification algorithm optimized on manually annotated TSS, then validated with existing TSS to identify thousands of TSS with nucleotide resolution for representatives of each lineage. We extend upon the 356 TSSs previously reported in Transcription start sites (TSSs) are fundamental for understanding gene expression and regulation. Agrobacteria, a group of prokaryotes with the ability to transfer DNA into the genomes of host plants, are widely used in plant biotechnology. However, the genome-wide transcriptional regulation of agrobacteria is not well understood, especially in less-studied lineages. Differential RNA-seq and an optimized algorithm enabled identification of thousands of TSSs with nucleotide resolution for representatives of each lineage. The results of this study provide a framework for elucidating the mechanistic basis and evolution of pathology across the three main lineages of agrobacteria. The optimized algorithm also highlights the importance of parameter optimization in genome-wide TSS identification and genomics at large. The study of agrobacteria has revolutionized plant molecular genetics by enabling genomic modification of plants . Their uAgrobacterium, Rhizobium, Allorhizobium, Neorhizobium, Ensifer/Sinorhizobium, Pararhizobium, and Shinella are related at the genus level  (Agrobacterium tumefaciens (G1) and Agrobacterium fabrum (G8), which have traditionally been studied as reference strains with Ti plasmids that lead to crown gall formation in a broad range of plant hosts  . It incl2 . It int ranges . BV3 is st range , 6.All strains of agrobacteria sequenced thus far have multipartite genomes . Most havir gene expression from the oncogenic plasmid. Multiple environmental signals such as pH, phenolic compounds, and sugars are integrated by the master two-component sensor VirG, which upon phosphorylation activates the expression of the other vir genes required for host infection  features. A key step in the regulation of bacterial gene expression is the initiation of transcription, where the RNA polymerase binds DNA at the transcriptional start site (TSS) . TranscrHelicobacter pylori  has emerged as a high-throughput method for genome-wide TSS identification . This apr pylori , Escherihia coli , and Bacsubtilis . In partefaciens  and Sinomeliloti . Biotechmeliloti , 21. ForHelicobacter pylori under five different growth conditions , and minimal media, morpholinopropanesulfonate (MOPS) based medium; however, neither grew well in Reasoner's 2A (R2A) or lysogeny broth (LB) media . Bas. BasA. fB) media . R. rhizvinifera . Both R.pramycin . R. rhizequenced . The genThe study of agrobacteria has largely focused on their unique process of infection, which has led to a detailed understanding of their virulence plasmids. However, the impact of chromosomes and chromids on virulence remains less understood. We aimed to explore the broader transcriptome organization across replicons by identifying TSSs and corresponding promoter structure to inform how agrobacteria virulence has evolved across the three main lineages. Using dRNA-seq data, we identified a total of 6,998 TSSs across the three lineages. Consistent with other Alphaproteobacteria, we observed a conserved promoter structure. Furthermore, we found lineage-specific divergence in TSSs associated with cell cycle regulation, suggesting adaptations in cell cycle control.Genome-scale TSS identification requires expression from operons across replicons . To thisTSSs are often classified as primary, secondary, antisense, internal, or orphan based on proximity to annotated coding sequence (CDS)  as illusA. fabrum C58 with variable read depths. Parameter optimization reduced the number of detected TSSs relative to those predicted when using default parameters, especially for antisense and internal TSS. Examining how parameter optimization affected TSS identification across TSS classes in A. fabrum C58 revealed the greatest reduction of TSSs within the antisense (90.4% reduction), internal (91.3% reduction), secondary (87.2% reduction), and orphan (73% reduction) classes, while the primary TSS (45.5% reduction) class was less depleted  were also found within our data set while also identified an additional 1,687 novel TSSs  in A. vitis T60/94 are also found in the default parameters data sets , 549 (29.9%) in R. rhizogenes C16/80, and 397 (23.7%) in A. vitis T60/94 primary and secondary TSSs expressed exclusively in one condition  for a single gene , and 7.7% were pyrimidines (205 T and 148 C). UTR length appears to be consistent across biovars with a median length of 61 nucleotides  and an ABC transporter (ortholog of atu4661) whose homolog in S. meliloti was shown to be involved in raffinose transport  all located on its second plasmid. As homologs of these genes are also found on both the pSymA and pSymB plasmids of S. meliloti  have multiple TSSs  in our data set. In addition, we completed genomes and phenotyping of BV2 representative R. rhizogenes C16/80 and BV3 representative A. vitis T60/94 that can enable further research in these less well-studied lineages of agrobacteria. Using their completed genomes, we identified 2,650 TSSs (359 TSS/Mbp) in R. rhizogenes C16/80 and 2,432 TSSs in A. vitis T60/94. The total number of TSSs identified per organism is consistent with the 1,907 TSSs  identified in H. pylori , 81-176 with 2,003 TSSs , RM1221 with 2,167 TSSs , and 81116 with 1,944 TSSs   . These s4 TSSs 1,3 TSS/Mbp7 TSSs 1,0 TSS/MbpFull coverage of TSSs for all genes in these organisms will require a better understanding of genome-wide operon induction conditions, especially on plasmids. Genome-wide TSS identification enabled analysis of promoter structure and 5′ UTR features that are consistent with other Alphaproteobacteria representatives. Our TSS identification can also be used toward promoter engineering for synthetic circuits across lineages. These data can contribute to improved identification of transcription factor binding sites and understanding of 5′ UTR contributions to conditional gene expression and regulation in agrobacteria.A. fabrum C58, R. rhizogenes C16/80, and A. vitis T60/94 upstream of putative cell cycle-regulated genes. These findings are consistent with the differential transcriptional regulation programs found in C. cresentus , 523 , R2A , MOPS Minimal Media 6Mo7O24, 4 µM H3BO3, 0.3 µM CoCl2, 0.1 µM CuSO4, 0.8 µM MnCl2, and 0.1 µM ZnSO4, pH 7.0) supplemented with either 0.1% glucose or 0.1% succinate as a carbon source, and LB Miller medium .escribed . A. fabrGrowth kinetics of agrobacterial strains were carried out as previously described with slight modification . BrieflyAgrobacterial strains were tested for antibiotic susceptibility by performing 11 twofold dilutions of each antibiotic  in MGYS across 11 columns of a 96-well plate. The 12th column contained MGYS with no antibiotics. Bacteria were grown in MGYS at 28°C to exponential phase then diluted 50-fold into wells of the 96-well plate. The plate was incubated at 28°C, and OD600 measurements were collected in a BioTek Synergy 4 plate reader  with fast continuous shaking for 48 hours. Antibiotic susceptibility was determined by normalizing the OD600 with a blank MGYS well, then selecting the lowest antibiotic concentration at which the normalized OD600 fell below 50% of the OD600 strain grown in MGYS without antibiotics.R. rhizogenes C16/80 and A. vitis T60/94 genomes were sequenced and assembled as previously described  and GCA_013337045.2 (A. vitis T60/94).escribed . Brieflyssembly” . For A. ng reads . Bandageng reads . Bakta vng reads . NCBI asGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTNNNNNN 3′) that adds a conserved 3′ sequence to the cDNA library. Residual DNA adapters were removed by AMPure XP bead cleanup. Sequencing barcodes were added by qPCR using SsoAdvanced Universal SYBR Green Supermix  to minimize PCR-based bias. Residual primers were removed by AMPure XP bead cleanup. Library extraction metrics are shown in To map TSSs to genome sequences, we developed a custom dRNA-seq protocol based on previous methods that use conditional treatment with TEX . Agrobac' adapter using seqtk .We performed ortholog clustering of protein sequences across the three BV genomes using PIRATE v.1.0.4 . We sele


The field of epigenetics studies the complex processes that regulate gene expression without altering the DNA sequence itself. It is well established that epigenetic modifications are crucial to cellular homeostasis and differentiation and play a vital role in hematopoiesis and immunity. Epigenetic marks can be mitotically and/or meiotically heritable upon cell division, forming the basis of cellular memory, and have the potential to be reversed between cellular fate transitions. Hence, over the past decade, there has been increasing interest in the role that epigenetic modifications may have on the outcomes of allogeneic hematopoietic transplantation and growing enthusiasm in the therapeutic potential these pathways may hold. In this brief review, we provide a basic overview of the types of epigenetic modifications and their biological functions, summarizing the current literature with a focus on hematopoiesis and immunity specifically in the context of allogeneic hematopoietic stem cell transplantation. Every cell in the human body carries the same genetic code, yet only a subset of genes is actively expressed at any given time-point in any given cell, in an intricate process that is orchestrated by epigenetics. In the Greek language, “epi” signifies on, upon, or over. Accordingly, the field of epigenetics studies the processes that affect gene expression without altering the DNA sequence itself, the sum of which is described as the epigenome , 2.Epigenetic modifications include DNA methylation, histone modification, Chromatin remodeling, and non-coding RNA regulation –3. In brMany of these changes can be mitotically and/or meiotically heritable on nascent daughter chromatin strands upon cell division. This results in a type of cellular memory termed epigenetic memory. At the same time, epigenetic modifications are characterized by plasticity in response to factors intrinsic and extrinsic to the cell, such as environmental stimuli –7. Therede novo methyltransferases. DNMT3L lacks enzymatic activity but interacts with other enzymes and plays a role in maternal imprinting , acetylation , phosphorylation (which contributes to chromatin remodeling and assists in DNA repair), ubiquitylation, and others –3, 7. ThLastly, non-coding RNAs (ncRNAs), particularly regulatory ncRNAs, including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), small interfering RNAs (siRNAs) and piwi-interacting RNAs (piRNAs), are transcribed (but non-translated) RNA molecules believed to fine-tune gene expression by contributing to gene silencing. Moreover, non-coding RNAs are known to interact with and guide chromatin-modifying complexes to the appropriate genomic targets –3, 5, 7.Dnmt3a- and/or Dnmt3b-null mice die during gestation or shortly after birth , TET2 (responsible for regulated demethylation), and ASXL1 (involved in chromatin regulation), are the most frequently described mutations in clonal hematopoiesis, including clonal hematopoiesis of indeterminate potential (CHIP) and myeloid malignancies such as myeloproliferative neoplasms (MPN), myelodysplastic syndrome (MDS), and acute myeloid leukemia (AML)  –25. CHIPia (AML) , 27. Speia (AML) –31. In tia (AML) , 33. Epiia (AML) .Dnmt1 deletion in murine HSCs results in rapid death from profound pancytopenia due to absence of all HSCs and progenitors, while low-level Dnmt1 expression results in a marked decrease of lymphoid progenitors and decreased self-renewal capacity in serial transplantation experiments  are characterized by self-renewal and pluripotency, features that are of paramount importance to the biological functions of hematopoiesis and immunity. As multipotent progenitors arise from HSCs and further commit to the myeloid or lymphoid lineage, epigenetic regulators define the major differentiation and maintenance events . In parteriments . Dnmt3a/eriments –43. ASXL KO mice . Tet2-degnancies , 45–48.IFNG and FASL correlate with the severity of acute graft-versus-host disease (GVHD), suggesting they could be used alongside HLA typing to optimize donor selection  recipients have been found to stably maintain the donor’s global methylation status, and differences in global methylation correlate with the evolution of mixed chimerism . Moreoveelection . Apart felection –52. In telection , 54. In election .DNMT3A-driven CHIP, was associated with increased incidence of chronic GVHD and decreased incidence of relapse or progression. Subsequently, a large US-based study of over 1,700 donors over the age of 40 further confirmed these findings. Additional data suggest that donor DNMT3A mutations are independently associated with improved overall survival due to reduced risk of relapse  proteins regulate chromatin dynamics by binding acetylated lysine residues in histones and nonhistone proteins, including transcription factors; given the therapeutic potential, BET inhibitors targeting the acetyl-binding domains of these proteins have been developed . In muriNlrp3/miR-155 double-knockout allo-HSCT recipient mice had no increased protection from GVHD compared with Nlrp3−/− recipients  transplant and compared to T-cells from healthy subjects. Linc00402, a T-cell specific molecule, was found to be differentially expressed in recipients of allogeneic mismatched unrelated as compared to autologous HSCT patients, and in donor T-cells from patients who underwent cardiac transplantation. In contrast, in vitro and murine in vivo data showed that T-cell activation and proliferation are inversely related to Linc00402 expression, and that depletion of Linc00402 impairs the allogeneic stimulation of T-cells ex vivo. The authors hypothesized that higher levels of tacrolimus exposure were the culprit for the preservation of Linc00402 abundance in allogeneic HLA-mismatched HSCT. Importantly, the tissue-specific and allogeneic context-specific expression of this molecule, along with its immune regulatory properties, make for an appealing therapeutic candidate  simultaneously heritable and reversible, 2) responsive to both intrinsic and extrinsic stimuli, and 3) characterized by interdependence between the DNA sequence, transcriptional processes, and the various forms of epigenetic changes. Despite the evident importance of epigenetic modifications in hematopoiesis and alloreactivity, the exact mechanistic underpinnings of how epigenetics operate in each context continue to elude the scientific community. Future challenges exist not merely in uncovering the full spectrum of epigenetic circuits, but equally importantly, in defining exactly how these complex, interactive, and frequently conflicting pathways ultimately affect donor stem cells, immune cell reactivity, and HSCT outcomes. As the field of epigenetics continues to steadily evolve, HSCT patients will undoubtedly benefit from the knowledge that is yet to be fully appreciated.Conception: YK and KC. Literature review: YK, MD, LG, and KC. Manuscript writing: YK, MD, LG, and KC. All authors contributed to the article and approved the submitted version.


Centromeres are no longer considered to be silent. Both centromeric and pericentric transcription have been discovered, and their RNA transcripts have been characterized and probed for functions in numerous monocentric model organisms recently. Here, we will discuss the challenges in centromere transcription studies due to the repetitive nature and sequence similarity in centromeric and pericentric regions. Various technological breakthroughs have helped to tackle these challenges and reveal unique features of the centromeres and pericentromeres. We will briefly introduce these techniques, including third-generation long-read DNA and RNA sequencing, protein-DNA and RNA–DNA interaction detection methods, and epigenomic and nucleosomal mapping techniques. Interestingly, some newly analyzed repeat-based holocentromeres also resemble the architecture and the transcription behavior of monocentromeres. We will summarize evidences that support the functions of the transcription process and stalling, and those that support the functions of the centromeric and pericentric RNAs. The processing of centromeric and pericentric RNAs into multiple variants and their diverse structures may also provide clues to their functions. How future studies may address the separation of functions of specific centromeric transcription steps, processing pathways, and the transcripts themselves will also be discussed. Historically, the centromere is often recognized as the constricted region that “holds” the X-shaped sister chromatids during cell divisions Flemming . FunctioArabidopsis, rice, flies, frogs, chicken, mice, tammar wallaby, and human cells , in which CDEII is AT-rich while CDEI and III are palindromic but are not repetitive , as observed in Rhynchospora pubera  of CENP-A/B/C and salt fractionation, Henikoff’s group has observed drastic CENP-A/B/C configuration differences on alpha-satellite dimers belonging to the same alpha-satellite subfamily that contain only 4–12% differences in sequence , inverted repeats, or non-repetitive sequences  chromatin immunoprecipitation followed by DNA sequencing (N-ChIP-seq) and CUT&RUN datasets show that only a subset of human alpha-satellite HOR units bind CENP-A and assemble kinetochore proteins, and are known as the “active” array (340 kb to 4.8 Mb) , core centromere transcription can promote H3K9ac accumulation, which in turn can prevent heterochromatin formation at this region  and flanking innermost repeats (imr). The core centromere is separated from the pericentric outer repeats (otr) by tRNA arrays  importantly for heterochromatin establishment, which is in turn required for de novo CENP-A establishment on introduced centromere-containing plasmid , which is formed on non-centromeric DNA sequences and has been propagated across multiple generations in humans, show that the new CENP-A-defined core neocentromere becomes enriched in active epigenetic marks, RNA Pol II, and negatively supercoiled DNA, consistent with active transcription. In contrast, there is a spreading of repressive epigenetic marks, e.g., H3K27me3, to the surrounding regions , which combines non-specific adenine (m6dA) methyltransferase footprinting and single-molecule, real-time PacBio DNA sequencing to natively and non-destructively measure nucleosome positions, regularity, and nucleosome repeat lengths (NRLs) on individual chromatin fibers (500 b–2 kb)  on three holocentric sedge C. elegans  with almost no genes, the CENP-A domain intervals and average domain size reduce, suggesting that more non-expressed regions are permissible holocentromere regions for CENP-A to locate , a two-subunit complex containing SSRP1 and SUPT16H, is one of the major regulators of RNA Pol II transcriptional activity. FACT can be retained on DNA while RNA Pol II traverses pass FACT  to manipulate histone modifications, and thus transcription, at the centromere  of S. pombe contains numerous promoters and transcriptional start sites  were more effective in recruiting CENP-A than those with higher activity. Mutants that are defective in restarting stalled RNA Pol II indeed increase CENP-A loading, suggesting that persistent RNA Pol II stalling creates a favorable chromatin environment for CENP-A loading, perhaps through dislodging H3 nucleosomes without eviction of CENP-A or providing a longer time for CENP-A recruitment , and the RNA-induced initiation of transcriptional gene silencing (RITS) complex are important for CENP-A/Cnp1 establishment  and satellite repeats (CentC) are actively transcribed in both strands, and cenRNAs (40–250 nt) interact with CENP-A , the level of cenRNAs is not affected, suggesting that endogenous cenRNAs probably do not exist as dsRNA , in addition to dsRNA  are formed by fusing the upstream 5′-splice site and the downstream 3′-splice site of a pre-messenger RNA (mRNA) through the process of back splicing  derived from both sense and anti-sense strands from three chromosomes have been characterized  is a lncRNA generated from telomere DNA. About 7% of human TERRA is polyadenylated, whereas most of the yeast TERRA is polyadenylated  and RNA short-read sequencing (RNA-seq). The average behaviors of cenRNAs across a cell population may not allow accurate characterization of the nature, number, and variants of cenRNAs in individual cells, especially many cenRNAs are lowly expressed and induced only in specific cell cycle timing (Biscotti et al. Experiments that affect the transcription process will unavoidably affect the corresponding transcript level as well. Directly comparing the centromere, CIN or cell cycle phenotypes by manipulating centromeric transcription and just the cenRNA level can further elucidate the function of each component. The additional phenotypes changes from manipulating transcription could be attributed to the function of the act of transcription, but of course perturbation of transcription has pleiotropic effects that have to be taken into account. Alternatively, manipulation of a particular transcription stage or RNA processing event may unveil the importance of each step. Exploring the characteristics and mechanism of cenRNA in more diverse model organisms will also provide a wider perspective for a potential conserved function.


INSR) is widely expressed throughout development and was previously described as a ‘housekeeping’ gene. Yet, there is abundant evidence that this gene is expressed in a cell-type specific manner, with dynamic regulation in response to environmental signals. The Drosophila insulin-like receptor gene (InR) is homologous to the human INSR gene and was previously shown to be regulated by multiple transcriptional elements located primarily within the introns of the gene. These elements were roughly defined in ~1.5 kbp segments, but we lack an understanding of the potential detailed mechanisms of their regulation. We characterized the substructure of these cis-regulatory elements in Drosophila S2 cells, focusing on regulation through the ecdysone receptor (EcR) and the dFOXO transcription factor. By identifying specific locations of activators and repressors within 300 bp subelements, we show that some previously identified enhancers consist of relatively compact clusters of activators, while others have a distributed architecture not amenable to further reduction. In addition, these assays uncovered a long-range repressive action of unliganded EcR. The complex transcriptional circuitry likely endows InR with a highly flexible and tissue-specific response to tune insulin signalling. Further studies will provide insights to demonstrate the impact of natural variation in this gene’s regulation, applicable to human genetic studies.The insulin signalling pathway is evolutionarily conserved throughout metazoans, playing key roles in development, growth, and metabolism. Misregulation of this pathway is associated with a multitude of disease states including diabetes, cancer, and neurodegeneration. The human insulin receptor gene ( INSR), thus the FOXO-INSR relationship represents a negative feedback loop that may fine-tune levels of signalling . To. To33]. InR in S2 cells and other cell types. The T1 promoter was previously shown to be the most active transcriptional start site in S2 cells, compared to the T2 and T3 promoters [Our previous studies demonstrated that there are active elements, designated enhancers 2–4, located within 2.3 kbp of the main transcriptional start site that show intrinsic action in Kc and S2 cells and/or are affected by signalling inputs dFOXO and 20E. This segment of regulatory elements is interesting because it appears to integrate signalling inputs in an incoherent fashion, with enhancer 2 stimulated by treatments that reduce enhancer 3 activity. We carried out a fine-structure analysis to identify elements sufficient for regulation, with the goal of understanding possible independent or ‘integrative’ activities . All of romoters . The T1 Enhancer 2 demonstrates low intrinsic activity in S2 cells but is strongly upregulated upon overexpression with dFOXO or treatment with 20E. We further subdivided this element into 300 bp and 600 bp elements to test for sufficiency of action . The treEnhancer 3 has a high intrinsic activity in S2 cells and is repressed by both dFOXO overexpression and 20E treatment. The 300 bp and 600 bp fragments derived from enhancer 3 showed overall low activity, suggesting that none of these elements are large enough to recapitulate intrinsic activity . Weak inEnhancer 4 has low intrinsic activity and is stimulated by dFOXO overexpression but not by 20E treatment. The 300 bp subfragments lacked any dFOXO response, but the 600 bp 4ab fragment appeared to exhibit stimulation by dFOXO . InteresInR may include direct and indirect effects; previous ChIP experiments have identified binding within region enhancer 2, 4, and 10 , enhancer 2 is more highly conserved than enhancers 3 and 4, perhaps underscoring the importance of the direct EcR regulatory switch in regulating InR (Having defined the functional elements of onserved . Enhanceting InR .Figure hsp27 and fbp1 and greatly stimulates their expression upon exposure to 20E [InR as well. ChIP-seq identified EcR binding sites within the insulin-like receptor gene in S2 cells on enhancers 2, 4, and 10 (EcR has been shown to regulate hundreds of loci in Drosophila, although many genes controlled by 20E represent secondary or tertiary effects of the hormone. Direct regulation by EcR has been demonstrated in a number of cases. For instance, EcR binds to promoter-proximal regions of e to 20E . This one to 20E . Therefo, and 10 . The onlInR regulation, in particular, the direct regulation by EcR and the range of repression mediated by this factor when not liganded to 20E. Previous studies demonstrated that EcR is found not only at the promoter but also in distal locations, such as those on early genes such as E75, E74, and Broad [InR is, and these studies did not explore whether EcR was functioning as an active repressor in the absence of hormone, although previous studies have found that EcR can indeed associate with corepressors [InR as well. Our findings indicate that within the InR intronic region comprising enhancer 2, EcR locally represses activators found within the 2a segment of the enhancer. In Drosophila, transcriptional repressors have been characterized as ‘short-range’ or ‘long-range’ based on their ability to act on neighboring activators. Short-range repressors like Snail and Giant exert inhibitory effects only when bound within 100 bp of activators, while in contrast, long-range repressors such as Hairy can inhibit activators up to several kilobase pairs of the targeted activators. These distinct regulatory effects are correlated with correspondingly local or broad chromatin modification [InR with a steadier output, suitable for this broadly expressed gene. Such localized repression function may also explain how repressors and corepressors participate in so-called ‘soft repression’ [By making use of transfected reporters in Drosophila cell culture, we uncovered novel aspects of nd Broad . On thespressors ,46. Thusfication ,47–49. Eression’ .InR has been previously identified as an important feedback mechanism that may potentiate insulin signalling in Drosophila as well as mammals [in vivo binding by this transcription factor in Drosophila. A study exploring dFOXO binding in the adult female identified ~700 transcriptional targets, with dFOXO bound to the coding region of InR in adult females [InR gene in S2 cells. Yet, the most prominent peaks on region 10 did not correspond to dFOXO responsiveness, and binding at enhancers 2 and 4, which are stimulated by dFOXO overexpression, was barely above background [C. elegans and JNK in mice, pointing to further complexities of this regulatory system [FOXO regulation of  mammals . Previou mammals  There is females . The pro females . Our preckground . Thus, py system ,54. It iInR. From our current understanding of this complex regulation, we believe that there would be an overexpression of InR during fasting due to the dFOXO activator found at enhancer 2a, and lower expression would be seen during development when ecdysone levels are high. Clearly, to establish this sort of function, we will need to examine the function of the mostly intact, endogenous locus – a task that has become much simpler in an era of CRISPR tools. However, in sum, the use of transfected reporters has allowed us to move considerably beyond our initial assessment, from defining elements that are necessary to elements that are sufficient for certain responses. Thus, this reductionist analysis of each enhancer can help us better understand the regulation of InR. Future work will focus on the endogenous locus, using diverse techniques to understand how these enhancers work as an ensemble. Delving into the mechanisms by which this gene is regulated will help us understand natural variation, providing insights into pathological states, development, and evolution.The use of reporter genes is a widespread and powerful tool for detailed assessment of regulatory regions. However, there are clear limitations to this reductionist approach when trying to gain an understanding of a large and complex regulatory locus. First, the demarcations of individual enhancers are arbitrary, carried out for efficiency in designing transfection assays. We show that many of the defined enhancers lose activity when divided into smaller fragments, thus there is every reason to expect that some of the divisions between the original 1.5 kbp elements fatally subdivided a more complex element. We did, however, find that some elements, notably enhancer 2, were readily subdivided to identify the dFOXO and EcR responsive portions. Furthermore, we were able to test the function of larger regions; by combining enhancer 2 and enhancer 3, we discovered that these enhancers appear to work additively, but with treatment of 20E, it appears that the combined region may be superstimulated, suggesting a synergistic action . On the


Runt-related transcription factor-1 (RUNX1), a key member of the core-binding factor family of transcription factors, has emerged as a novel therapeutic target for cardiovascular disease. There is an urgent need to fully understand the expression pattern of Runx1 in the heart and the mechanisms by which it is controlled under normal conditions and in response to disease. The expression of Runx1 is regulated at the transcriptional level by two promoters designated P1 and P2. Alternative usage of these two promoters creates differential mRNA transcripts diversified in distribution and translational potential. While the significance of P1/P2 promoter-switch in the transcriptional control of Runx1 has been highlighted in the embryogenic process, very little is known about the level of P1- and P2-specific transcripts in adult hearts, and the underlying mechanisms controlling the promoter-switch.To amplify P1/P2 specific sequences in the heart, we used two different sense primers complementary to either P1 or P2 5'-regions to monitor the expression of P1/P2 transcripts. DNA methylation levels were assessed at the Runx1 promoter regions. Rats were grouped by age.The expression levels of both P1- and P2-derived Runx1 transcripts were decreased in older rats when compared with that in young adults, paralleled with an age-dependent decline in Runx1 protein level. Furthermore, older rats demonstrated a higher degree of DNA methylation at Runx1 promoter regions. Alternative promoter usage was observed in hearts with increased age, as reflected by altered P1:P2 mRNA ratio.Our data demonstrate that the expression of Runx1 in the heart is age-dependent and underscore the importance of gene methylation in the promoter-mediated transcriptional control of Runx1, thereby providing new insights to the role of epigenetic regulation in the heart.The online version contains supplementary material available at 10.1186/s12872-023-03583-3. Heart disease is the leading cause of death on a global scale . Many heRunx1 is a member of the core-binding factor family of transcription factors implicated in multiple signaling pathways during normal development and disease . Runx geThe expression of Runx1 is regulated at transcriptional level under the control of two promoters. In vertebrates, all Runx genes contain two alternative promoters, a distal P1 promoter and a proximal P2 promoter , 13. TheThe major protein isoforms produced by P1 and P2 are RUNX1C and RUNX1B, respectively, which differ in their N-terminal amino acid sequences. In the hematopoietic system, the function of Runx1 isoforms has been well studied . RUNX1C The transcriptional activity of Runx1 promoter is affected by gene methylation. Evidence from pluripotent murine embryonic stem cells shows that hypomethylation of P1 promoter is correlated with increased P1 transcriptional activity and increased P1:P2 mRNA ratio, suggesting an epigenetic regulatory mechanism underlying the Runx1 promoter switch and the resulting changes of Runx1 expression . In the In this study we have demonstrated that the expression of Runx1 in the heart, including P1- and P2-mediated transcripts as well as Runx1 protein levels, declined with increasing age in healthy adult rats, and in aged animals there was an alternative usage of Runx1 P1/P2 promoters observed. Furthermore, we have characterized the methylation pattern at two promoter regions of Runx1 gene and demonstrated that older rats had higher degrees of promoter methylation than younger adults. Taken together, these findings show that the alternative usage of Runx1 P1/ P2 promoters plays an active role in adult hearts during aging process and underscore the importance of gene methylation in the regulation of Runx1 expression.Although Runx1 expression has previously been reported to increase following myocardial infarction and contribute to cardiac remodelling, it was unknown whether the baseline Runx1 expression in healthy animals changed with aging (eg. 34-week versus 10-week). Furthermore, the alternative usage of Runx1 promoters P1 and P2 Fig. , suggestWe next investigated whether DNA methylation patterns at Runx1 promoter regions altered with aging (because DNA methylation can reduce gene expression). Bisulfite sequencing analysis Fig. A of RunxTo investigate the alternative usage of two Runx1 promoters during the process of aging, we examined the mRNA levels of P1- and P2-mediated transcripts in 10-, 22- and 34-week hearts. The results shown the course of transcriptional alteration from age 10-week to age 34-week Fig.  and C. WRecent experimental studies on the role of Runx1 in the adverse cardiac remodelling following myocardial infarction have attracted substantial attention of the cardiovascular field , 5. SincOur results provide the first quantification of Runx1 expression in adult rat hearts with different age groups. Using 10-, 22- and 34-week-old rats, we demonstrated an age-dependent decrease in Runx1 mRNA levels derived from both P1 and P2 promoters  and a higher SR content [Although decreased expression of Runx1 was observed in the adult heart, previous studies have demonstrated that Runx1 expression is increased in response to cardiac injury , 39–41.  content . The pro content –44. In t content ; (2) agi content ; and (3) content , 48. In  content . Given t content . AltogetTo investigate the specific contribution of Runx1 P1/P2 promoters in the heart to the modulation of Runx1 expression, we used two different sense primers complementary to either P1 or P2 5'-regions to monitor the promoter specific expression Fig. A and B. As a key transcriptional regulator, RUNX1 interacts with a large number of transcription factors and cofactors, including P300, E2A-PBX1, Src-1. P300 is a kind of the histone acetyltransferases, which induces histone H3 lysine 27 acetylation (H3K27ac) at target gene promoters, enhancers and super-enhancers . YamagucIt is noteworthy that genes with RUNX1-binding sites at their promoter region are overrepresented in a group of genes that become methylated in early life . Since iThe present study shown that although the degree of methylation at P2 region was higher than that of P1, the P1:P2 methylation ratio dramatically increased in aged rats compared with young rats Fig. . This spThe limitation of this study is that it did not include functional analysis to confirm the role of differential methylation but provided only correlative evidence. In the previous study, McCarroll & He et al. have performed functional analysis following myocardial infarction and shown that the up-regulation of Runx1 causes decreased cardiac function , whereasWe have demonstrated for the first time that P1- and P2-mediated Runx1 transcripts decrease with increasing age and highlighted the importance of gene methylation in the transcriptional control of Runx1 expression. Previous studies established that Runx1 overexpression drives cardiac dysfunction by affecting calcium homeostasis in cardiomyocytes after myocardial infarction . A more Male Wistar rats were obtained from Chengdu Dashuo Experimental Animal Co. Ltd, and housed in standard environmental conditions (at 20–22 °C with 12 h light–dark cycle). Rats were fed with standard food  and high purity water. All animal procedures were approved by the Sichuan University Medical Ethics Committee and the study was conducted in accordance with the ARRIVE guidelines. The care and use of animals were in accordance with local and international ethical criteria.The experimental operators themselves did not know the grouping of the experiment, and animals were uniformly assigned by the laboratory staff.The experimental animals were numbered and divided into experimental group or control group by random functions.Health: Experimental animals must be in good health and free of any disease or viral infection. Any animal showing unusual symptoms, such as dyspnea, diarrhea, etc. was excluded from the experiment.Age and Sex: Animals of same age and sex were used to reduce error.−ΔΔCt method after the threshold cycle. The primer sequences used for PCR were list in Table The animals were anesthetized in an induction chamber with 4% isoflurane and 100% oxygen. The anesthetized rats were sacrificed by cervical dislocation and the heart was removed and washed in ice-cold saline (0.9% sodium chloride w/v). Total RNA was extracted by Trizol reagent following the manufacturer’s guidelines. cDNA was isolated by Extraction of FastKing one-step RT-PCR kit . Real-Time PCR was performed by SYBR Green probes . Two different sense primers complementary to either P1 or P2 5'-regions were used to amplify P1/P2 specific sequences. β-actin was used as an internal control. Relative quantification was calculated using the 2Total protein samples were extracted from rat heart tissues mixed with ice-cold RIPA protein lysis buffer . Protein concentrations were detected by the BCA kit . Protein extracts with loading dye were loaded into SDS-PAGE gels. The extracts (30 μg protein) were planished in the lane of 5% gels and separated with 12% SDS-PAGE gels. Bands were transferred into a PVDF membrane, blocked with 5% skim milk at room temperature for 1 h, and dipped into rabbit anti-Runx1 antibodies  and rabbit anti-Vinculin antibodies  overnight at 4 °C followed by 1 h treatment of secondary antibody HRP-labelled goat anti-rabbit IgG  at room temperature. ECL Chemiluminescence substrate  was used to visualize the blots. Band densities were quantified by ImageJ software.http://www.urogene.org/methprimer/index1.html). Nest-PCR amplification with outer and inner primer pairs was used in order that target sequences can be amplified abundantly. PCR mix  was used for amplification. Amplification products were visualized by gel electrophoresis and bands were cut and purified using Generic Agarose Gel DNA Recovery Kit . Pure PCR products were inserted into the pClone007 Simple Vector Kit  and individual clones were sequenced. Alignment and methylation analyses were performed by using QUMA (http://quma.cdb.riken.jp/). The primer sequences used for PCR were list in Table DNA of rat hearts was extracted using Cell/Tissue DNA Kit . The genomic DNA was converted by using sodium bisulfite . After sodium bisulfite conversion, unmethylated cytosines were converted to uracil, whereas methylated cytosines unconverted. Primers to amplify converted genomic DNA were designed by Methprimer , or a 1-way ANOVA (more than 2 groups) were used as appropriate. Dunnett’s posttest was used for multiple comparison. Values of Additional file 1.Additional file 2: Supplemental Material Figure 1. Original Western blot images for Fig.