Dicer1. The rodent-specific B2 SINE family is highly abundant in the mouse genome and elements have been previously characterized to exhibit promoter, insulator, and non-coding RNA activity. Our work establishes a new role for B2 elements as inducible enhancer elements that influence mouse immunity, and exemplifies how lineage-specific TEs can facilitate evolutionary turnover and divergence of innate immune regulatory networks.Regulatory networks underlying innate immunity continually face selective pressures to adapt to new and evolving pathogens. Transposable elements (TEs) can affect immune gene expression as a source of inducible regulatory elements, but the significance of these elements in facilitating evolutionary diversification of innate immunity remains largely unexplored. Here, we investigated the mouse epigenomic response to type II interferon (IFN) signaling and discovered that elements from a subfamily of B2 SINE (B2_Mm2) contain STAT1 binding sites and function as IFN-inducible enhancers. CRISPR deletion experiments in mouse cells demonstrated that a B2_Mm2 element has been co-opted as an enhancer driving IFN-inducible expression of  The cellular innate immune response is the first line of defense against an infection and is initiated by the activation of transcriptional networks that include antiviral and pro-inflammatory genes. While innate immune signaling pathways are generally conserved across mammalian species, the specific transcriptional networks are increasingly recognized to show differences across lineages . These dTransposable elements (TEs) are increasingly recognized as a source of genetic elements that shape the evolution of mammalian innate immune responses . TE-deriAIM2 inflammasome genes  response in primary mouse macrophage cells. We screened for TEs showing epigenetic signatures of inducible regulatory activity, and identified a rodent-specific B2 subfamily as a substantial source of IFN-inducible regulatory elements in the mouse genome. As a case example, we used CRISPR to characterize a B2-derived IFN-inducible enhancer that regulates mouse To examine how TEs contribute to mouse type II IFN signaling regulation, we re-analyzed two independent transcriptomic and epigenomic datasets of primary bone-marrow-derived macrophages (BMDMs) that were stimulated with recombinant interferon gamma (IFNG) or untreated for 2 or 4 hr . These d2 fold change (log2FC)>1), which enriched for canonical genes associated with the IFNG response  and IFN-stimulated response element  motifs within the STAT1 ChIP-seq peaks  to either ISRE or GAS motifs (–201) as well as the RLTR30B_MM  and RLTR30E_MM  endogenous retrovirus subfamilies  family, which is highly abundant in the mouse genome. B2 SINE elements are divided into three subfamilies, including B2_Mm2 , B2_Mm1a , and B2_Mm1t . B2 SINE elements have been characterized to show a wide range of regulatory activities in mice, including acting as promoters , insulat–52, odds ratio = 9.13) than interferon-repressed genes (IRGs) or nonresponsive genes, compared to unbound B2 elements or random genomic regions . These B2_Mm2 elements show significantly higher localization near ISGs , we identified 530 B2_Mm2 elements predicted to interact with 457 mouse ISGs  model , which i–9; Dicer1) (Hspa1b) (Nfkbid)  , SET dom Dicer1) , DOT1-li Dicer1) , fumarat Dicer1) , heat sh(Hspa1b) , and NFK(Nfkbid) .Dicer1, which is an endonuclease responsible for recognizing and cleaving foreign and double stranded RNA that has been linked to innate immunity  shows biochemical hallmarks of enhancer activity including inducible STAT1 and H3K27ac signal as well as constitutive binding by CTCF and RAD21 , consistent with inducible regulation of Dicer1 by JAK-STAT signaling, potentially through the STAT binding site present in B2_Mm2.Dicer1.To experimentally test the potential enhancer activity of B2_Mm2.Dicer1immunity . We firsreatment . Given tDicer1 expression levels and inducibility by IFNG in knockout and WT clones. WT clones showed consistent inducible expression, while both knockout clonal lines showed a complete lack of inducible expression  . The deletion of the element did not affect inducibility of other ISGs in the 5 Mb locus including the nearby highly induced SerpinA3 ISGs locus  . FocusinGs locus . This innditions .Dicer1 when testing for differential expression between IFNG-treated KO and WT cells  between individual clones   . Althouger donor  supporteB2 SINE elements are abundant in the mouse genome and they have been widely studied due to their substantial influence on genome regulation and evolution. B2 elements have contributed non-coding RNAs inducible by stress or infection , splicinGiven the abundance of B2 elements and their potential to cause pathological regulatory rewiring, many B2 elements are targeted for SETDB1/H3K9me3-mediated epigenetic repression which inhibits their regulatory potential . TherefoDICER1 locus. While we did not uncover consistent evidence supporting IFNG-inducible regulation of human DICER1, these observations align with the concept of convergent regulatory evolution, in which similar expression patterns are perpetuated by the co-option of lineage-specific TEs  were retained using samtools v1.10  with FDR adjusted p-value <0.05  from primary murine BMDMs stimulated with 100 ng/mL IFNG for 2 or 4 hr  or 10 ng v0.11.8  and Mult v0.11.8 , and tri v0.11.8  with optls v1.10 . Alignedls v1.10  annotatils v1.10  with opt v1.26.0 . For mosue <0.05 . We addicode v38  with thektrim = r k=34 mink = 11 hdist = 1 qtrim = r trimq = 10 tpe tbo’. Library quality was assessed using FastQC v0.11.8  from primary murine BMDMs  were dow v0.11.8  and Mult v0.11.8 , and tri v0.11.8 . Low qua v0.11.8 , and dup v0.11.8 . Peak ca v0.11.8  using op Browser . Where p Browser  using opdatabase .To identify TE families enriched for STAT1 and H3K27ac peaks, we used GIGGLE v0.6.3  to creat2FC, respectively, and retained the top 750 genes. We additionally randomly subset for 750 nonresponsive genes. The absolute distance to the nearest ISG, IRG, or nonresponsive gene was determined for all STAT1-bound B2_Mm2 elements using BEDTools v2.28.0  or 1 (B2 box-and-whisker). For all motif analyses, binding motif position-weight matrices for STAT1 and CTCF were obtained from the JASPAR CORE 2018 vertebrate database . A union set consisting of mouse and human-to-mouse ISGs was generated, and each ISG was identified as mouse-specific, human-specific, or shared according to induction status. To determine how broadly B2_Mm2 has shaped murine innate immune responses, we identified 344 unique B2_Mm2 elements fully overlapping enhancers predicted to interact with 706 ISGs using the ABC model with a minimum ABC score of 0.001. The proportion of ISGs predicted to interact with a putative B2_Mm2 enhancer were plotted according to species status. We independently identified 926 ISGs with at least one of 655 STAT1-bound B2_Mm2 elements (irrespective of ABC) within 50 kb of the transcriptional start site.We used BioMart with human Ensembl v105 annotation  to identJ774A.1 mouse cells were purchased from ATCC and were cultured in DMEM supplemented with 1 X penicillin-streptomycin and 10% fetal bovine serum. J774A.1 cells were routinely passaged using 0.25% Trypsin-EDTA and cultured at 37 °C and 5% CO2. All IFNG treatments were performed using 100 ng/mL recombinant mouse IFNG (R&D Systems #485-MI-100). Cells were confirmed to be Mycoplasma-free by the Barbara Davis Center for Childhood Diabetes BioResources Core Molecular Biology Unit at the University of Colorado Anschutz Medical Center. The identity of the cells was verified using the ATCC Cell Line Authentication Service (STR profiling).All treatments were carried out using a 4 hr time period. IL-4 (Sigma-Aldrich #I1020-5UG) was added to a final concentration of 1 ng/mL, recombinant IFNA (R&D Systems #12100–1) to a final concentration of 1000 U/mL, recombinant IL-2 (R&D Systems #402 ML-020) to a final concentration of 100 ng/mL, and recombinant IL-6 (Sigma-Aldrich #I9646-5UG) to a final concentration of 20 ng/mL in accordance with manufacturers’ recommendations. RNA was extracted using an Omega Mag-Bind Total RNA Kit (Omega Bio-Tek #M6731-00) and analyzed via RT-qPCR.Two gRNA sequences were designed to flank each side of B2_Mm2.Dicer1 in order to delete the element and generate knockout J774A.1 cells via SpCas9 (Integrated DNA Technologies #1081060). All gRNA sequences were also verified to uniquely target the locus of interest using the UCSC BLAT tool  against E. coli (New England Biolabs #C2987H). Plasmid DNA was harvested using the EZNA Omega Plasmid DNA Mini Kit I (Omega Bio-Tek #D6942-02), and the sequence of each construct was verified by Sanger sequencing . Sequencing results were visualized by aligning to the mm10 reference genome using BLAT  with four different combinations of the gRNAs to target B2_Mm2. One set of guides was found to produce the expected doubles-stranded cuts on both sides of the element in the bulk electroporated cell populating using gel electrophoresis. Clonal lines were isolated using the array dilution method and screened for the expected homozygous deletion using primers flanking the B2_Mm2.Dicer1 element. Clonal lines homozygous for the deletion were further validated using one flanking primer and one primer internal to B2_Mm2.Dicer1. To determine deletion breakpoint sequences, PCR products flanking each deletion site were cloned into a sequencing vector using the CloneJET PCR Cloning Kit (Thermo Fisher Scientific #K1231) and transformed into 5-alpha Competent ing BLAT . We idenDicer1 expression in WT and knockout cell lines. WT J774A.1 cells used in RT-qPCR are all biological replicates that underwent the same single cell seeding process as the KOs to serve as a control. Forward and reverse primers were designed for CTCF, Dicer1, and Gbp2b. Each set of primers was designed using a combination of tools from NCBI Primer BLAST  was used to quantify er BLAST , Benchlier BLAST . RT-qPCRThe Zymo Quick RNA Miniprep Plus Kit (Zymo Research #R1504) was used to extract RNA from J774A.1 cells for all treatments except for the cytokine panel which used the Omega RNA Extraction Kit (Omega Bio-Tek #M6731-00). WT J774A.1 cells used in RNA-seq and all downstream analysis were clones that underwent single-cell expansions of from wild-type J774A.1 cells. All RNA lysates and single-use aliquots of extracted RNA were stored at –80 °C until library preparation. RNA integrity was quantified with High Sensitivity RNA TapeStation 4200 (Agilent). Libraries were generated using the KAPA mRNA HyperPrep Kit (KAPA Biosystems #08098123702) according to the manufacturer’s protocol. The final libraries were pooled and sequenced on a NovaSeq 6000 as 150 bp paired-end reads (University of Colorado Genomics Core).--rna-strandness RF’. Only uniquely aligned fragments were retained, and technical replicates were merged using samtools v1.10  with accession number GSE202574.https://genome.ucsc.edu/s/coke6162/B2_SINE_enhancers_Horton_et_al and https://github.com/coke6162/B2_SINE_enhancers  feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: (i) Decision letter after peer review:eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Molly Przeworski as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Kenji Ichiyanagi (Reviewer #3).Thank you for submitting your article "Mouse B2 SINE elements function as IFN-inducible enhancers" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.There was consensus among the reviewers that the topic is of broad interest and the data were rigorously generated. The reviewers, however, also felt that some of the claims require additional support. A request for new analyses of the current dataset in hand could potentially blunt these concerns. Depending on the results of these additional analyses, a single new experiment would be required to support the inference that the focal B2 element acts as a Dicer1 enhancer. Please see below for specific revisions requested.Essential revisions:1) It is not clear whether the Dicer1 locus is unique. Are there other loci that have both a nearby B2_Mm2 element and a binary difference between inducibility in mouse versus human cells? It would be helpful to understand whether there other B2_Mm2 insertions that could contribute to a mouse-specific IFGN-sensitivity. Adding DEseq values from human RNAseq data the authors already use (current references 10 and/or 37) for identifiable human orthologs to Table S7 would thus strengthen their conclusions. If there are many potential candidates, the authors should discuss the rationale for selecting Dicer1 in particular.2) The results of Serpina3g and Serpina3F gene expression in the authors' knockout cells are very interesting. However, the authors focus almost exclusively on Serpina3g and Serpina3F, which makes it difficult to understand what is happening genome wide. Are other IFNΓ-induced genes (including those not on chromosome 12) similarly affected at the level of basal or induced transcription? How many genes are different in WT versus KO cells, both at basal and induced states? Does this correlate with their CUT&TAG data shown in Figure 5? By focusing only on nearby genes (Serpina3g and Serpina3F), the authors hint that this may be a long-range regulatory effect, "potentially mediated by the CTCF binding activity of the element" that they removed. But by only focusing on two nearby IFNΓ-induced genes, their data do not rule out the  possibility that there may be a more indirect role for this TE site or Dicer1 in basal transcription of IFNΓ-induced genes or IFNΓ-mediated gene expression.3) The specificity of the KO effect on the Dicer1-Serpina region of chromosome 12 is not clear. Without analysis of the complete RNA-seq and CUT&RUN datasets, it is difficult to rule out a more global effect . If these new analyses yield evidence of specificity of the KO lines, the reviewers will be satisfied. If not, the reviewers request an additional manipulation: KO of an intron element of equivalent size to the original deletion, KO of a different B2 element – apparently there is one 2kb away, or even better, replacement of the B2 element with one that lacks cGAS motifs . Determining whether there are changes in the basal or induced levels of Dicer1/Serpina genes in this additional line would serve as an important control for the KO experiment. Providing more data on other genes throughout the genome in WT and KO cells, which the authors have generated but do not include in the manuscript, would help distinguish between these models.4) There are high levels of POLR2A occupancy at the B2_Mm2.Dicer1 element in induced WT cells. Could this be a Pol2 pause site? Could deletion of this element lead to a change in Pol2 occupancy and change Dicer1 expression independent of enhancer activity? To probe such questions, the reviewers requested that the authors directly test the possibility that the intronic B2 element actually acts as a regulator of splicing or transcriptional elongation. Careful analysis of the Dicer1-mapping reads from the RNA-seq data – or RT-qPCR – could resolve this concern.5) Figure 4F – The authors claim that "deletion of B2_Mm2.Dicer1 also has a significant repressive effect on the IFNΓ-inducible expression of Serpina genes." However, the basal levels of Serpina3f/Serpina3g are significantly reduced upon this deletion compared to WT. Furthermore, expression of Serpina genes in the KO cell lines significantly increase upon IFNΓ stimulation, suggesting that they still show inducible expression despite the B2_Mm2.Dicer1 deletion. The authors should compare the magnitude of induction before and after stimulation between the WT and KO cell lines to determine if there is indeed a repressive effect on inducible expression of Serpina genes.eLife. Your revised article has been evaluated by Molly Przeworski (Senior Editor) and a Reviewing Editor.Thank you for resubmitting your work entitled "Mouse B2 SINE elements function as IFN-inducible enhancers" for further consideration by The reviewers appreciated your many additional experiments/analyses as well as the edits to the text. The manuscript has been improved substantially but there are some remaining issues that need to be addressed.1. All three reviewers felt that the response to Critique#1 was insufficient. There are several places in the manuscript referring to the significance of the Mouse B2 SINE elements contributing to lineage-specific immune response. For example, the introduction highlights that "a key open question is whether the co-option of TEs as immune regulatory elements is evolutionarily widespread as a mechanism driving divergence of innate immune responses."The reviewers (or at least two of them) did not expect to see additional KO experiments but did expect the authors to highlight a handful of other examples where STAT1 binding to a proximal B2 SINE element is found in a mouse-specific ISG only. If no other such examples are available to highlight, then it's currently difficult to discern how generalizable this relationship is between rodent-specific B2 SINE elements and mouse-specific ISGs.Furthermore, the authors highlight a limitation of the current human cell dataset – specifically the limitation of sampling gene expression only 24 hours after interferon treatment (new paragraph starting line 310) in human cells. However, in line 232, the same dataset is used to support the earlier statement that "the human ortholog DICER1 does not show IFNΓ-inducible expression in human primary macrophages …mouse DICER1 shows a significant 50% upregulation in response to IFNΓ in primary mouse BMDMs…."This earlier statement is substantially weakened by the final Results paragraph. This issue needs to be resolved to support the major claim of the paper that a lineage-specific TE is responsible for a lineage-specific immune response, echoed in the abstract: "B2 elements…exemplifies how lineage-specific TEs can facilitate evolutionary divergence of innate immune regulatory networks."2. In the response to reviewer comments under critique#2, it was stated that "…the other differentially expressed genes in the KOs most likely represent off-target/stochastic changes, that are commonly seen across separate clonal isolations." And as communicated in the manuscript: Line 288: "The other dysregulated genes showed no discernable physical or functional pattern and also showed high variability between individual clones…consistent with intrinsic clonal transcriptional variation…" Whether this is true for all 101 genes should be clarified. It seems surprising given that at least some genes should be indirect targets of Dicer1. Finally, does Dicer1 show less variability than these other genes? If so, that should be stated.3. Finally, one reviewer was concerned that the intronic location of B2 SINE means that the authors cannot delineate whether the element acts as an enhancer or instead a regulator of transcriptional elongation. Essential revisions:1) It is not clear whether the Dicer1 locus is unique. Are there other loci that have both a nearby B2_Mm2 element and a binary difference between inducibility in mouse versus human cells? It would be helpful to understand whether there other B2_Mm2 insertions that could contribute to a mouse-specific IFGN-sensitivity. Adding DEseq values from human RNAseq data the authors already use (current references 10 and/or 37) for identifiable human orthologs to Table S7 would thus strengthen their conclusions. If there are many potential candidates, the authors should discuss the rationale for selecting Dicer1 in particular.Dicer1 example is unique or part of a larger species-specific network of genes regulated by B2 elements. As suggested, we have re-analyzed a publicly available human RNA-seq dataset to identify human ISGs in CD14+ monocytes stimulated with IFNΓ for 24 hours. A more detailed description of our analysis is provided below. In summary, we classified mouse ISGs based on whether those genes were also ISGs based on the human RNA-seq data, and integrated mouse Hi-C data to predict enhancer/gene interactions. We found that B2_Mm2 elements are associated nearby hundreds of mouse-specific ISGs, consistent with a role in regulating a network of mouse ISGs. However, we note several caveats below, including the observation that B2_Mm2 elements are also associated with many non mouse-specific ISGs, and cannot be causally tied to gene regulation without additional experimental perturbation.We agree with the reviewers that it would be useful to investigate whether other B2 elements contribute to mouse-specific IFN-inducible expression, which may indicate whether the p-value < 0.05, log2 fold change > 0), 1453 of which had a 1:1 ortholog assignment to a mouse gene based on ENSEMBL Biomart . We integrated the mouse and human datasets to classify mouse genes into 3 categories:Using RNA-seq data of IFNΓ-stimulated human CD14+ monocytes (GEO accession GSE84691) , we identified a total of 2314 human ISGs (FDR adjusted i) "mouse-specific ISGs" ii) "shared ISGs" iii) "human-specific ISGs" .DICER1 does not appear to be induced . To compare this set to mouse ISGs, we used ISGs defined from BMDMs stimulated with IFNΓ for 4 hours from the Piccolo et al. dataset (GSE84517) analyzed in our previous submission . From this dataset, we defined 2720 mouse genes as ISGs . We compared this set of genes to the 1453 human ISGs defined above . Out of the 2720 mouse ISGs, 2266 genes (83.3%) were only ISGs in mouse (including 1467 genes with a 1:1 human ortholog and 799 genes with no 1:1 ortholog), and 454 (16.6%) were ISGs in both mouse and human. Conversely, out of the 2314 human ISGs, 1860 genes (80.4%) were only ISGs in human (including 999 genes with a 1:1 mouse ortholog and 861 genes with no 1:1 ortholog). The relatively low fraction of ISGs shared across species is consistent with a previous study comparing ISGs induced by type I interferon α across vertebrates , where a core of 62 ISGs were conserved across species .The DESeq2 values for this dataset are now reported in Supplementary file 1. Notably human We next sought to determine how broadly B2_Mm2 has shaped murine innate immune responses using our list of mouse-specific, human-specific, and shared ISGs. We first assigned predicted enhancers to their predicted targets using the Activity-by-Contact (ABC) model , which incorporates both epigenomic signal and Hi-C 3D interaction data to predict enhancer-gene targets. As input into the ABC model, we used publicly available ATAC-seq and Hi-C data (PRJNA694816)  from murine BMDMs stimulated with IFNΓ for 2 hours along with the H3K27ac ChIP-seq and RNA-seq datasets included in the manuscript to identify putative enhancer-gene contacts. We identified 50264 putative enhancer-ISG contacts attributed a minimum ABC likelihood score of 0.01, with an average of 14 enhancers for each generepresented in our list of mouse- and human-to-mouse ISGs. We subsequently identified 393 "mouse-specific" 142 "human-specific", and 64 "shared" ISGs associated with at least one B2_Mm2 enhancer. A list of all mouse and human-to-mouse ISGs along with the top predicted B2_Mm2-derived enhancer can be found in Supplementary file 7.Dicer1 (a mouse-specific ISG) with an ABC likelihood score of 0.127508 (Supplementary file 7). This finding is consistent with the idea that B2_Mm2 elements have facilitated the evolution of the mouse-specific ISG regulatory network. However, we also found that B2_Mm2 elements are predicted to regulate 64 out of 454 (14.1%) genes that are shared ISGs in both mouse and human, and 142 out of 999 (14.2%) of genes that are only ISGs in human  were predicted to be regulated by at least one B2_Mm2 element. We confirmed that the B2_Mm2.Dicer1 element was predicted by ABC to target in human . Additioin human . This inThere are a few notable caveats with this analysis. (1) the human RNA-seq dataset was generated by a different lab and derived from cells stimulated with IFNΓ for 24 hours, whereas the two mouse RNA-seq datasets collected cells 2 or 4 hours after IFNΓ stimulation. Previous studies have shown that transcriptional responses to type I and II IFNs vary across timepoints . Genes that are not induced in human cells after 24 hours may potentially be induced at 4 hours. As such, the number of shared ISGs is likely an underestimate. Careful analysis of human and mouse datasets derived from cells collected at similar timepoints may improve identification of species-specific ISGs and potentially result in a larger difference in the number of B2_Mm2 elements predicted to drive species-specific ISG expression. (2), we used a relaxed ABC likelihood score threshold of 0.01 such that the number of B2_Mm2-derived enhancer-gene contacts identified likely represent the maximum possible using these data. These predictions also did not distinguish between elements that show constitutive or IFN-inducible regulation, so it is possible that some B2 elements may have act as constitutive rather than IFN-inducible enhancers. (3) we were able to confidently identify only 1453 (62.8%) human-to-mouse, one-to-one ISG orthologs. Careful analysis of all potential orthologs and paralogs (such as species-specific gene family expansions) may better reveal the full extent to which B2_Mm2 has contributed to species-specific immune regulatory evolution.In summary, while our reanalysis is indeed consistent with a slightly increased enrichment of B2_Mm2 elements near mouse-specific ISG , there are many caveats that we feel are outside the scope of this study to address and therefore we have opted not to include these analyses in the study.Dicer1 intron for several reasons that were outlined in the main text, including the species-specific IFN-inducible expression of Dicer1 and strong epigenomic signature of inducible enhancer activity  of the specific B2_Mm2 element. We have clarified our process for selecting the element as below, incorporating the revised ABC analysis to assign enhancers to genes through 3D interactions as described above.We initially decided to study the B2_Mm2 within the p-value <0.05, log2 fold change > 0), we identified 530 B2_Mm2 elements predicted to interact with 457 mouse ISGs  (Supplementary file 7). Compared with a set of human ISGs from human CD14+ monocytes , 393 of these 457 (86%) genes were only ISGs in mouse, and the remaining 64 (14%) were ISGs in both mouse and human.“Having established that B2_Mm2 elements are an abundant source of IFNΓ-inducible STAT1 binding sites in the mouse genome, we asked whether any of these elements have been co-opted to regulate expression of individual ISGs. We first assigned predicted enhancers to their predicted targets using the Activity by Contact (ABC) model , which incorporates both epigenomic signal and Hi-C 3D interaction data to predict enhancer-gene targets. As input into the ABC model, we used publicly available ATAC-seq and Hi-C data from murine BMDMs stimulated with IFNΓ for 2 hours (PRJNA694816)  and H3K27ac ChIP-seq and RNA-seq data from . Focusing on a permissive set of 2720 ISGs from  . While the human ortholog DICER1 does not show IFNΓ-inducible expression in human primary macrophages  , mouse Dicer1 shows a significant 50% upregulation in response to IFNΓ in primary mouse BMDMs . This indicates that Dicer1 is a mouse-specific ISG and likely acquired IFNΓ-inducible expression in the mouse lineage, potentially due to the co-option of the B2_Mm2 element as a species-specific IFNΓ-inducible enhancer. The intronic B2_Mm2 element (B2_Mm2.Dicer1) shows biochemical hallmarks of enhancer activity including inducible STAT1 and H3K27ac signal as well as constitutive binding by CTCF and RAD21 . The element provides the only prominent nearby STAT1 binding site and is not present in rat or other mammals . Therefore, we hypothesized that the B2_Mm2.Dicer1 element was co-opted as an IFNΓ-inducible enhancer of mouse Dicer1.”From this set, we decided to focus on a specific B2_Mm2 element located on Chromosome 12 within the first intron of 2) The results of Serpina3g and Serpina3F gene expression in the authors' knockout cells are very interesting. However, the authors focus almost exclusively on Serpina3g and Serpina3F, which makes it difficult to understand what is happening genome wide. Are other IFNΓ-induced genes (including those not on chromosome 12) similarly affected at the level of basal or induced transcription? How many genes are different in WT versus KO cells, both at basal and induced states? Does this correlate with their CUT&TAG data shown in Figure 5? By focusing only on nearby genes (Serpina3g and Serpina3F), the authors hint that this may be a long-range regulatory effect, "potentially mediated by the CTCF binding activity of the element" that they removed. But by only focusing on two nearby IFNΓ-induced genes, their data do not rule out the  possibility that there may be a more indirect role for this TE site or Dicer1 in basal transcription of IFNΓ-induced genes or IFNΓ-mediated gene expression.We agree that a more global assessment of the transcriptome-wide changes is necessary to fully understand the direct and indirect effects of the B2_Mm.Dicer1 element. However, the RNA-seq dataset for WT and KO cells generated in our initial submission was not suited for this comparison because (i) they were generated in different batches, and (ii) the WT control was a pool of WT J774 cells rather than clonal controls. Therefore, we generated new RNA-seq data where WT and KOs were treated in the same batch, using 3 additional control WT/unedited clones that were carried through the limited dilution process. For each WT (N=3) and KO (N=2) independently derived clonal line, we carried out 3 experimental replicates of untreated cells and cells treated for IFNΓ for 4 hrs, and harvested RNA for RNA-seq. These were all conducted in the same round of experiments to avoid potential batch effects.Dicer1 in both untreated and IFNΓ-induced conditions. We first conducted DESeq2 pairwise differential expression analysis considering all replicates, WT (N=9) vs KO (N=6) in untreated cells showed Dicer1 downregulation with log2FC = -0.43, FDR adjusted p-value = 9×10-4  while this inducibility was ablated in KO cells .We re-analyzed our new RNA-seq data to address the concerns raised by reviewers' comment (2) and comment (3). Consistent with our previous analysis, KO cells showed significantly reduced expression of 10-4 see . In IFNΓ0-15 see . As befoDicer1 compares to other genes affected genome-wide by the knockout. Comparing IFNΓ-treated WT to KO cells, Dicer1 was the 102nd most dysregulated gene . In untreated cells, Dicer1 was ranked 1741 out of differentially expressed genes based on FDR adjusted p-value . In other words, in untreated KO cells, there are 1740 genes that show a more significant change than Dicer1. In contrast, in IFNΓ-treated KO cells, there are just 101 genes that show a more significant change than Dicer1. In both conditions, the other dysregulated genes are located across all chromosomes and did not show any clear functional patterns or enrichment. We did not observe correlations between these genes and our CUT&TAG data, with the caveat that our CUT&TAG was performed on just one KO clone (KO1) and the pooled WT cells. We expect that CUT&TAG data would correspond to RNA-seq data if derived from the same clone.We next examined how Dicer1 transcription. While it is a potentially interesting scenario that the observed dysregulation of other genes is an indirect effect of Dicer1 downregulation, the untreated KO cells showed only a modest downregulation of Dicer1 (log2FC = -0.43) which is may not sufficiently alter Dicer1 protein levels or function. The functional consequence of IFNΓ-inducible regulation on Dicer1 would be interesting to follow up in a future study.Based on the global distribution across the genome, the other differentially expressed genes in the KOs most likely represent off-target/stochastic changes, that are commonly seen across separate clonal isolations. We routinely use CRISPR KO and observe similar levels of off-target effects by RNA-seq even across control lines, presumably due to the process of clonal isolation. We have observed greater on-target gene expression differences when using CRISPRi (dCas9-Krab) to target enhancers in pooled cells , but we decided not to use CRISPRi for this element, reasoning that the element is located within the gene intron and dCas9-Krab binding could impede Summary of changes– Figure 4B-E is updated to use numbers from the NA-seq reanalysis– Main text updated as followsDicer1 element in both knockout clones and 3 control wild-type clones which were also isolated by limiting dilution. Consistent with the RT-qPCR results, we found that Dicer1 showed significant IFNΓ-inducible upregulation in all WT clones but that this induction was completely ablated in B2_Mm2.Dicer1 KO clones . Notably, the RNA-seq normalized count data revealed that levels of Dicer1 were also significantly reduced in untreated knockout cells . This indicates that the B2_Mm2.Dicer1 element regulates both basal expression levels of Dicer1 and inducible expression by IFNΓ. Focusing on the IFNΓ-treated condition, Dicer1 was significantly downregulated in KO cells compared to WT cells cells . Genome-wide, there were 101 genes that showed greater significance than Dicer1 when testing for differential expression between IFNΓ-treated KO and WT cells . The other dysregulated genes showed no discernable physical or functional pattern and also showed high variability between individual clones, consistent with clonal transcriptional variation typical of the limiting dilution process .”“We used RNA-seq to study the genome-wide effects of the B2_Mm2.3) The specificity of the KO effect on the Dicer1-Serpina region of chromosome 12 is not clear. Without analysis of the complete RNA-seq and CUT&RUN datasets, it is difficult to rule out a more global effect . If these new analyses yield evidence of specificity of the KO lines, the reviewers will be satisfied. If not, the reviewers request an additional manipulation: KO of an intron element of equivalent size to the original deletion, KO of a different B2 element – apparently there is one 2kb away, or even better, replacement of the B2 element with one that lacks cGAS motifs . Determining whether there are changes in the basal or induced levels of Dicer1/Serpina genes in this additional line would serve as an important control for the KO experiment. Providing more data on other genes throughout the genome in WT and KO cells, which the authors have generated but do not include in the manuscript, would help distinguish between these models.As described in our response above for Reviewer Critique #2, we have generated RNA-seq data for 3 new control lines generated by taking wild-type cells through clonal isolation. We agree with the reviewers that a "negative control KO" would be the best control, however in our past experience with CRISPR we find that most off-target/non-specific expression changes arise due to the process of clonal isolation. We also repeated the experiments and RNA-seq from our 2 KO lines such that our comparisons would not be confounded by batch effects.Dicer1 is consistently IFNΓ-inducible in the controls but not inducible in the KOs, with lower basal and induced levels . However, and importantly, we found that Serpina3f and Serpina3g did not show the same pattern of regulation we observed previously (significantly reduced untreated and IFNΓ-induced expression in KO cells). In the new round of RNA-seq, we found that Serpina3f/g did not show significantly or consistently reduced expression in untreated KO cells (Supplementary file 8). These results conflict with our previous claim that Serpina3f and Serpina3g are regulated by the B2_Mm2.Dicer1 element, and instead suggest that our previous observation was an artifact of clonal variation and the extremely strong (log2fc > 10) IFNΓ-inducibility of Serpina3g within each genotype  and Serpina3f . It is likely that our previous observation was due to the fact that our KO1/2 RNA-seq datasets were generated in a separate experimental batch than the WT control, which was a pooled set of cells. Furthermore, our chromatin interaction analysis (described in response to Reviewer Critique #1) predicts that the B2_Mm2.Dicer1 element targets Dicer1, but does not target the Serpina genes. Taken together, our new controls support a specific regulatory effect of the element on Dicer1 but not the Serpin genes (as previously claimed). As such, we have removed our claims that Serpin genes are affected by the B2_Mm2.Dicer1 knockout from the main text. While our re-analysis indicates that the B2_Mm2.Dicer1 element does not have long-range enhancer activity as we previously concluded, this does not affect the major claims of our study. While the long-range distal enhancer activity was potentially an interesting observation, the fact that B2_Mm2.Dicer1 has a clear and reproducible regulatory effect on the more proximal gene Dicer1 is consistent with our central claim that B2_Mm2 elements act as IFNΓ-inducible enhancers.Our new RNA-seq analysis of the 3 clonal WT lines and 2 KO lines confirmed that The following paragraph was removed from the main text:Serpina genes. In mouse, Serpina is a family of inflammatory genes represented by a large cluster of 14 murine paralogs, located 330 – 1000 kb from B2_Mm2.Dicer1. In particular, we found that Serpina3f and Serpina3g (approximately 500 kb from B2_Mm2.Dicer1) show a 1-2 orders of magnitude reduction in basal and induced gene expression in knockout cells compared to WT cells . The relatively long range of this regulatory activity is not uncommon in vertebrate genomes  and is potentially mediated by the CTCF binding activity of the element.Our RNA-seq analysis revealed that deletion of B2_Mm2.Dicer1 also had a significant repressive effect on the IFNΓ-inducible expression of 4) There are high levels of POLR2A occupancy at the B2_Mm2.Dicer1 element in induced WT cells. Could this be a Pol2 pause site? Could deletion of this element lead to a change in Pol2 occupancy and change Dicer1 expression independent of enhancer activity? To probe such questions, the reviewers requested that the authors directly test the possibility that the intronic B2 element actually acts as a regulator of splicing or transcriptional elongation. Careful analysis of the Dicer1-mapping reads from the RNA-seq data – or RT-qPCR – could resolve this concern.Dicer1 transcription separately from its function as an inducible enhancer, and thank the reviewer for the suggestion. As shown in Figure 5, deletion of the B2_Mm2.Dicer1 element does remove Pol2 occupancy over the element and reduces overall signal over the locus, consistent with enhancer activity but not mutually exclusive with pausing activity. If the intronic B2_Mm2.Dicer1 element acts as a regulator of splicing, we would expect changes in isoform expression. As suggested, we manually inspected aligned RNA-seq reads from all WT and KO untreated/treated samples. Qualitatively, we observed no evidence of differential splicing or exon skipping when looking at aligned fragments from WT J774 and B2_Mm2.Dicer1 KO J774 cells (see below).We agree that it would be interesting if the B2_Mm2.Dicer1 altered Dicer1 transcripts. As suggested by the reviewers, if the B2_Mm2.Dicer1 element acts as a pause site, it may alter splice site or polyadenylation site usage and cause measurable differential expression of specific Dicer1 splice variants in KO cells. To test this, we ran Stringtie v2 to conduct transcript assembly using the RNA-seq reads from each WT and KO individual sample, then used the ‘--merge’ flag to generate a merged gene annotation file representing isoforms from all samples. In parallel we also generated merged GTF files created using alignment files only from WT or B2_Mm2.Dicer1 KO samples. All exons identified in the fully merged GTF file are represented in the WT- and KO-specific GTF files. At the transcript level, all Dicer1 isoforms in the fully merged GTF file are also represented in the WT- and KO-specific GTF file. Together, this indicates that there are no isoforms that are unique to either KO and WT cells . This revealed several transcripts that all show similar trends to the gene-level analysis (see Supplementary file 9), where expression is reduced in both basal and IFN-treated conditions in the KO, and inducible expression is lost. If the element acted as a pause site affecting elongation, we would have expected unrestricted Pol2 elongation in both conditions and therefore greater expression levels in the KO in either or both basal and treated conditions. However, we only observed reduced expression of transcripts in all conditions in the KO, which is most consistent with activity as an enhancer.We have uploaded these alignments and accompanying Stringtie annotation files to an updated UCSC Genome Browser session . These analyses did not provide strong evidence supporting splicing changes driven by the KO, although a major caveat is that the isoforms were analyzed using short-read sequencing and therefore may not be accurately assembled or quantified, and high-coverage long-read sequencing may be required for more accurate isoform quantification.Dicer1 promoter.In addition to analyzing our RNA-seq data as suggested by the reviewers, we also looked for evidence of ChIP-seq binding at the B2 element by pausing associated factors including NELF and CDK9 using published datasets atalogued by the mouse Cistrome ChIP-seq binding site database. We did not find evidence for binding by any canonical pausing factors at either the B2 element or the B2 element: http://dbtoolkit.cistrome.org/?specie=mm10&factor=tf&interval=chr12%3A104742467-104742646#plot_resultDicer1 promoter: http://dbtoolkit.cistrome.org/?specie=mm10&factor=tf&interval=chr12%3A104%2C751%2C526-104%2C751%2 C993#plot_resultNELF KO PRO-seq and NELF/CDK9 ChIP-seq dataset from mouse macrophages either untreated or stimulated with LPS from  and inspected the B2_Mm2.Dicer1 region  in our IFNΓ-treated WT and KO cells, as well as use of nascent transcription (PRO-seq), are necessary to directly investigate Pol2 pausing. However, given that did we did not observe any clear differences at the transcript level, we feel that our findings are most consistent with the element acting as a typical inducible cis-regulatory enhancer, and investigation of pausing would be outside the scope of the study.Overall, these analyses do not provide strong support for the element acting as a pause site, but do not completely rule out the possibility. For example, it is possible that the element serves as a pause site in vitro, and is only released by NELF and other factors specifically under IFNΓ conditions, driving inducible elongation of We have added our analysis of isoform-level changes to the main text as follows:“Given the B2_Mm2.Dicer1 element is bound by POLR2A in WT cells, we examined whether the B2_Mm2.Dicer1 element may alter transcription by affecting usage of different splice sites or polyadenylation sites, which would be consistent with pause site activity. We examined transcript isoform-level expression changes in KO cells in both untreated and treated conditions and found multiple transcripts that showed the same trend as the gene-level analysis, where most expressed transcripts are downregulated in both basal and IFNΓ-treated conditions and show lack of inducibility in KO cells (Supplementary file 9). These findings are consistent with the element acting primarily as an IFNΓ-inducible enhancer without any major effect on alternative splicing.”5) Figure 4F – The authors claim that "deletion of B2_Mm2.Dicer1 also has a significant repressive effect on the IFNΓ-inducible expression of Serpina genes." However, the basal levels of Serpina3f/Serpina3g are significantly reduced upon this deletion compared to WT. Furthermore, expression of Serpina genes in the KO cell lines significantly increase upon IFNΓ stimulation, suggesting that they still show inducible expression despite the B2_Mm2.Dicer1 deletion. The authors should compare the magnitude of induction before and after stimulation between the WT and KO cell lines to determine if there is indeed a repressive effect on inducible expression of Serpina genes.Dicer1, but revealed no consistent effect on Serpina3f/a3g. This suggests that our previous finding of SerpinA3g was an artifact likely due to clonal variation and/or batch effect, as our reanalysis using new control clones that were isolated by limited dilution no longer showed a consistent effect on the Serpina genes. Therefore we have removed our findings on the enhancer's long-range regulation of Serpina3g and focus on the effect of enhancer activity on Dicer1. We do not believe this alters our central claims, which is that B2_Mm2 elements are an abundant source of IFNΓ-inducible enhancers, which typically regulate proximal genes within 50 kb of the gene.We thank the reviewers for encouraging us to further validate the regulatory effect on the Serpina genes. In our original study, the WT and KO cell lines were treated and sequenced in different batches, which confounded our comparison. As we describe in our answer to reviewer comment (3), we have re-generated and re-analyzed RNA-seq data from multiple WT and KO clonal lines in both untreated/treated conditions, with all data generated in the same experimental batch. This reanalysis confirmed the specificity of the enhancer's inducible regulation of The reviewers appreciated your many additional experiments/analyses as well as the edits to the text. The manuscript has been improved substantially but there are some remaining issues that need to be addressed.1. All three reviewers felt that the response to Critique#1 was insufficient. There are several places in the manuscript referring to the significance of the Mouse B2 SINE elements contributing to lineage-specific immune response. For example, the introduction highlights that "a key open question is whether the co-option of TEs as immune regulatory elements is evolutionarily widespread as a mechanism driving divergence of innate immune responses."The reviewers (or at least two of them) did not expect to see additional KO experiments but did expect the authors to highlight a handful of other examples where STAT1 binding to a proximal B2 SINE element is found in a mouse-specific ISG only. If no other such examples are available to highlight, then it's currently difficult to discern how generalizable this relationship is between rodent-specific B2 SINE elements and mouse-specific ISGs.We thank the reviewers for the suggestion to highlight examples of species-specific mouse ISGs predicted to be regulated by B2_Mm2 elements. We identified 393 B2_Mm2 elements predicted regulate mouse-specific ISGs based on chromatin state and interaction ). We have added the information on these candidate elements and their target gene as a new sheet in Supplementary File 7. We also highlighted 5 additional examples in new Figure 3 supplements , based on high ABC predicted interaction scores and published associations with immunity. We also conducted GO enrichment on these 393 genes and identified significant enrichment of terms related to immune responses, which we have also reported in a new sheet in Supplementary File 7. We have added the following paragraph to the main text:p-value = 6.023×10-9; Supplementary file 7). We identified multiple examples of predicted B2_Mm2 target genes with established immune functions that showed mouse-specific IFNΓ-inducible expression , including dicer 1 ribonuclease III (Dicer1)  , SET domain containing 6, protein lysine methyltransferase (SETD6) , DOT1-like histone lysine methyltransferase , fumarate hydratase 1 (Fh1) , heat shock protein family A (Hsp70) member 1B (Hspa1b) , NFKB inhibitor δ (Nfkbid) .”“The 393 mouse-specific ISGs predicted to be regulated by B2_Mm2 elements were significantly enriched for multiple immune related functions  in human cells. However, in line 232, the same dataset is used to support the earlier statement that "the human ortholog DICER1 does not show IFNΓ-inducible expression in human primary macrophages …mouse DICER1 shows a significant 50% upregulation in response to IFNΓ in primary mouse BMDMs…."This earlier statement is substantially weakened by the final Results paragraph. This issue needs to be resolved to support the major claim of the paper that a lineage-specific TE is responsible for a lineage-specific immune response, echoed in the abstract: "B2 elements…exemplifies how lineage-specific TEs can facilitate evolutionary divergence of innate immune regulatory networks."DICER1 did show IFNΓ-inducible expression in this other dataset. Thus, the evidence for inducible expression of human DICER1 was inconsistent but we felt it was important to include this additional analysis. There are several factors that could drive this observation, including the fact that these studies were conducted by different groups from cells from different donors. We recognize that this observation weakens our original claim stating that B2 elements drive lineage-specific expression and "evolutionary divergence of innate immune regulatory networks." However, our finding is consistent with conclusions from other groups  that lineage-specific TEs can contribute to regulatory turnover of transcription factor binding sites and/or convergent evolution.During the first revision, we found that the human DICER1 locus harbors STAT1 binding sites, despite not showing IFNΓ-inducible expression in primary monocytes . While it is possible the STAT1 binding sites are nonfunctional, this prompted us to analyze RNA-seq data of IFNΓ-stimulated monocytes from another group  and saw that Dicer1 inducibility by IFNΓ in monocytes from other species, which would be interesting but outside the scope of this study. Furthermore, given that we identified 393 other B2 elements predicted to act as species-specific enhancers , we expect that a substantial fraction are driving lineage-specific divergence of inducible gene expression.We emphasize that B2 elements are still driving lineage-specific evolution of the cis-regulatory architecture underlying the IFNΓ regulatory network. But, at the gene expression level, different B2 elements may drive lineage-specific divergence or maintenance/turnover (replacement of existing sites)  or convergent regulatory evolution, which are important mechanisms of regulatory evolution . Distinguishing the last two possibilities would require examining We have rewritten the final results paragraph to clarify that this idea:DICER1 locus. Our analysis of RNA-seq data from human primary monocytes treated with IFNΓ for 24 hrs  indicated that human DICER1 expression is not induced by IFNΓ . However, ChIP-seq data from IFN-treated monocytes from the same group  showed multiple inducible STAT1 binding sites within the human DICER1 locus, including one originating from a primate-specific TE (LTR27) . Although these binding sites do not correlate with inducible DICER1 expression in the matched RNA-seq dataset, they suggest human DICER1 may be inducible under different conditions. An analysis of an independent dataset generated from another donor  supported the inducible expression of DICER1  (Supplementary file 1). Thus, while the evidence for inducible human DICER1 expression is inconsistent, our analyses indicate that human DICER1 has independently evolved primate-specific binding STAT1 binding sites, which may also confer inducible regulation.”“Considering that the B2_Mm2 enhancer is specific to rodents, we examined the regulatory landscape of the human We added the following paragraph to the discussion:DICER1 locus. While we did not uncover consistent evidence supporting IFNΓ-inducible regulation of human DICER1, these observations align with the concept of convergent regulatory evolution, in which similar expression patterns are perpetuated by the co-option of lineage-specific TEs . Therefore, as B2_Mm2 elements shaped the evolution of rodent immune regulatory networks, individual co-option events may have mediated either divergence or preservation of gene expression patterns.”“We identified hundreds of B2_Mm2-derived enhancers that are predicted to regulate genes displaying IFNΓ-inducible expression in mouse cells but not human cells, which supports their role in facilitating lineage-specific evolution of the IFNΓ-inducible regulatory network. However, we also identified a subset of target genes that show inducible expression in both species, suggesting independent evolution or turnover of regulatory elements that could serve similar regulatory functions as the B2_Mm2 enhancers. For instance, we identified an intronic STAT1 binding site derived from a primate-specific TE in the human We have also edited the last sentence of the abstract as follows to be consistent with our Dicer1 findings:Dicer1. The rodent-specific B2 SINE family is highly abundant in the mouse genome and elements have been previously characterized to exhibit promoter, insulator, and non-coding RNA activity. Our work establishes a new role for B2 elements as inducible enhancer elements that influence mouse immunity, and exemplifies how lineage-specific TEs can facilitate evolutionary turnover and divergence of innate immune regulatory networks.”“Regulatory networks underlying innate immunity continually face selective pressures to adapt to new and evolving pathogens. Transposable elements (TEs) can affect immune gene expression as a source of inducible regulatory elements, but the significance of these elements in facilitating evolutionary diversification of innate immunity remains largely unexplored. Here, we investigated the mouse epigenomic response to type II interferon (IFN) signaling and discovered that elements from a subfamily of B2 SINE (B2_Mm2) contain STAT1 binding sites and function as IFN-inducible enhancers. CRISPR deletion experiments in mouse cells demonstrated that a B2_Mm2 element has been co-opted as an enhancer driving IFN-inducible expression of 2. In the response to reviewer comments under critique#2, it was stated that "…the other differentially expressed genes in the KOs most likely represent off-target/stochastic changes, that are commonly seen across separate clonal isolations." And as communicated in the manuscript: Line 288: "The other dysregulated genes showed no discernable physical or functional pattern and also showed high variability between individual clones…consistent with intrinsic clonal transcriptional variation…" Whether this is true for all 101 genes should be clarified. It seems surprising given that at least some genes should be indirect targets of Dicer1. Finally, does Dicer1 show less variability than these other genes? If so, that should be stated.Dicer1 which would be interesting. Given that the role of Dicer1 is mRNA degradation, we expect any indirect targets to increase in expression after Dicer1 knockout, and 35/101 of the genes were. We have included these numbers in the revision. However, we emphasize that CRISPR KO experiments often result in large unintended transcriptional changes and we cannot exclude the possibility that these changes are due to clonal variation or off-target effects.We agree with the reviewers that some of these genes are potentially indirect targets of We have added the following paragraph to the resultsDicer1 when testing for differential expression between IFNΓ-treated KO and WT cells . Out of these 101 genes, 24 showed higher variability than Dicer1 (based on DESeq2 log2foldchange standard error) between individual clones , consistent with intrinsic clonal transcriptional variation revealed by the limiting dilution and/or CRISPR editing process . 35 of these genes showed upregulation in the KO cells, suggesting that they could be silencing targets of Dicer1 that become upregulated upon Dicer1 downregulation. However, given the relatively modest effect of Dicer1 especially in the untreated condition, further experiments would be necessary to establish these genes as targets of Dicer1.”“Genome-wide, there were 101 genes that showed greater significance than 3. Finally, one reviewer was concerned that the intronic location of B2 SINE means that the authors cannot delineate whether the element acts as an enhancer or instead a regulator of transcriptional elongation.We agree that we cannot exclude the possibility that the element acts as a regulator of transcriptional elongation due to its position in the intron. We have added this caveat in our results at the end of the paragraph describing this analysis:“However, further experiments such as CDK9 inhibition and profiling of nascent transcription in stimulated conditions  are necessary to establish whether the element affects transcriptional elongation.”ReferencesGenome Biol 21:16.Choudhary MN, Friedman RZ, Wang JT, Jang HS, Zhuo X, Wang T. 2020. Co-opted transposons help perpetuate conserved higher-order chromosomal structures. Mol Biol Evol 19:1114–1121.Dermitzakis ET, Clark AG. 2002. Evolution of transcription factor binding sites in Mammalian gene regulatory regions: conservation and turnover. Nat Genet 51:1664–1669.Fulco CP, Nasser J, Jones TR, Munson G, Bergman DT, Subramanian V, Grossman SR, Anyoha R, Doughty BR, Patwardhan TA, Nguyen TH, Kane M, Perez EM, Durand NC, Lareau CA, Stamenova EK, Aiden EL, Lander ES, Engreitz JM. 2019. Activity-by-contact model of enhancer-promoter regulation from thousands of CRISPR perturbations. ELife 6. doi:10.7554/eLife.29736Gressel S, Schwalb B, Decker TM, Qin W, Leonhardt H, Eick D, Cramer P. 2017. CDK9-dependent RNA polymerase II pausing controls transcription initiation. Eur J Cell Biol 91:48–52.Jolesch A, Elmer K, Bendz H, Issels RD, Noessner E. 2012. Hsp70, a messenger from hyperthermia for the immune system. Cell Rep 33:108504.Kealy L, Di Pietro A, Hailes L, Scheer S, Dalit L, Groom JR, Zaph C, Good-Jacobson KL. 2020. The Histone Methyltransferase DOT1L Is Essential for Humoral Immune Responses. Nat Struct Mol Biol 22:396–403.Laitem C, Zaborowska J, Isa NF, Kufs J, Dienstbier M, Murphy S. 2015. CDK9 inhibitors define elongation checkpoints at both ends of RNA polymerase II-transcribed genes. Nat Immunol 12:29–36.Levy D, Kuo AJ, Chang Y, Schaefer U, Kitson C, Cheung P, Espejo A, Zee BM, Liu CL, Tangsombatvisit S, Tennen RI, Kuo AY, Tanjing S, Cheung R, Chua KF, Utz PJ, Shi X, Prinjha RK, Lee K, Garcia BA, Bedford MT, Tarakhovsky A, Cheng X, Gozani O. 2011. Lysine methylation of the NF-κB subunit RelA by SETD6 couples activity of the histone methyltransferase GLP at chromatin to tonic repression of NF-κB signaling. Cell 167:1170–1187.Long HK, Prescott SL, Wysocka J. 2016. Ever-Changing Landscapes: Transcriptional Enhancers in Development and Evolution. Blood Adv 6:3821–3834.McCann KJ, Christensen SM, Colby DH, McGuire PJ, Myles IA, Zerbe CS, Dalgard CL, Sukumar G, Leonard WJ, McCormick BA, Holland SM. 2022. IFNγ regulates NAD+ metabolism to promote the respiratory burst in human monocytes. Drosophila. PLoS Comput Biol 2:e130.Moses AM, Pollard DA, Nix DA, Iyer VN, Li X-Y, Biggin MD, Eisen MB. 2006. Large-scale turnover of functional transcription factor binding sites in Nat Biotechnol 40:1807–1813.Nahmad AD, Reuveni E, Goldschmidt E, Tenne T, Liberman M, Horovitz-Fried M, Khosravi R, Kobo H, Reinstein E, Madi A, Ben-David U, Barzel A. 2022. Frequent aneuploidy in primary human T cells after CRISPR-Cas9 cleavage. Science 373:231–236.Poirier EZ, Buck MD, Chakravarty P, Carvalho J, Frederico B, Cardoso A, Healy L, Ulferts R, Beale R, Reis e Sousa C. 2021. An isoform of Dicer protects mammalian stem cells against multiple RNA viruses. Immunity 39:454–469.Qiao Y, Giannopoulou EG, Chan CH, Park S-H, Gong S, Chen J, Hu X, Elemento O, Ivashkiv LB. 2013. Synergistic activation of inflammatory cytokine genes by interferon-γ-induced chromatin remodeling and toll-like receptor signaling. Cell Rep 16:3121–3129.Qiao Y, Kang K, Giannopoulou E, Fang C, Ivashkiv LB. 2016. IFN-γ Induces Histone 3 Lysine 27 Trimethylation in a Small Subset of Promoters to Stably Silence Gene Expression in Human Macrophages. Toxoplasma gondii. PLoS Pathog 17:e1010081.Souza SP, Splitt SD, Sànchez-Arcila JC, Alvarez JA, Wilson JN, Wizzard S, Luo Z, Baumgarth N, Jensen KDC. 2021. Genetic mapping reveals Nfkbid as a central regulator of humoral immunity to Genome Res 24:1963–1976.Sundaram V, Cheng Y, Ma Z, Li D, Xing X, Edge P, Snyder MP, Wang T. 2014. Widespread contribution of transposable elements to the innovation of gene regulatory networks. Sci Rep 12:18211.Westermann L, Li Y, Göcmen B, Niedermoser M, Rhein K, Jahn J, Cascante I, Schöler F, Moser N, Neubauer B, Hofherr A, Behrens YL, Göhring G, Köttgen A, Köttgen M, Busch T. 2022. Wildtype heterogeneity contributes to clonal variability in genome edited cells. Zecchini V, Paupe V, Herranz-Montoya I, Janssen J, Wortel IMN, Morris JL, Ferguson A, Chowdury SR, Segarra-Mondejar M, Costa ASH, Pereira GC, Tronci L, Young T, Nikitopoulou E, Yang M, Bihary D, CaicciNature 615:499–506.F, Nagashima S, Speed A, Bokea K, Baig Z, Samarajiwa S, Tran M, Mitchell T, Johnson M, Prudent J, Frezza C. 2023. Fumarate induces vesicular release of mtDNA to drive innate immunity.


The importance of estrogenic signaling for a broad spectrum of biological processes, including reproduction, cancer development, energy metabolism, memory and learning, and so on, has been well documented. Among reported estrogen receptors, estrogen receptor alpha (ERα) has been known to be a major mediator of cellular estrogenic signaling. Accumulating evidence has shown that the regulations of ERα gene transcription, splicing, and expression across the tissues are highly complex. The ERα promoter region is composed of multiple leader exons and 5′-untranslated region (5′-UTR) exons. Differential splicing results in multiple ERα proteins with different molecular weights and functional domains. Furthermore, various post-translational modifications (PTMs) further impact ERα cellular localization, ligand affinity, and therefore functionality. These splicing isoforms and PTMs are differentially expressed in a tissue-specific manner, mediate certain aspects of ERα signaling, and may work even antagonistically against the full-length ERα. The fundamental understanding of the ERα splicing isoforms in normal physiology is limited and association studies of the splicing isoforms and the PTMs are scarce. This review aims to summarize the functional diversity of these ERα variants and the PTMs in normal physiological processes, particularly as studied in transgenic mouse models. Estrogens are steroid sex hormones that are critical for the development of reproductive organs and reproductive functions primarily in females. In addition to reproduction, estrogenic signaling also plays important roles in cardiovascular physiology, homeostatic regulation of energy balance, and a variety of social and learning behaviors. Traditionally, the actions of circulating estrogen were believed to be mediated mainly by binding to two specific receptors, estrogen receptors α (ERα) and estrogen receptors β (ERβ), in which liganded ERs activate gene transcription through binding to the genomic element called the estrogen-response element (ERE), either as a homodimer or heterodimer with coactivators. Notably, apart from their well-known roles in transcriptional regulation, estrogens also mediate rapid signaling cascades called membrane-initiated pathways, a new mode of action via membrane ERs and a G-protein-coupled estrogen receptor .ERα and ERβ belong to the nuclear receptor superfamily of ligand-inducible transcription factors, which also contains the receptors for other steroid hormones including glucocorticoids, mineralocorticoids, progestogens, androgens, retinoic acid and thyroid hormone. The structure of the nuclear receptor is characteristic and well conserved among the subfamilies, consisting of a variable N-terminal ligand-independent transactivation domain , a DNA-binding domain (DBD), a hinge domain and a C-terminal ligand-binding domain (LBD) and a ligand-dependent transactivation domain (AF-2) .A number of ERα splicing variants have been described without a corresponding understanding of the physiological functions of each of those isoforms. Alternative splicing is an important molecular mechanism that enables the production of a variety of different transcripts from a single gene by selectively arranging coding exons from pre-mature mRNA. Many of them are reported particularly in cancers and tumor cells, but some of them are also expressed constitutively in normal tissues. In this review, we will primarily focus on the identified functional diversity of ERα variants in physiological conditions. For the reviews on an extensive list of ERα variants in cancer, we refer the readers to previous excellent reviews ,2,3,4.Alternative promoter usage enables the generation of multiple mRNA species from a single gene. ERα genes across species shares highly complex organization in the promoter region. At least four leader exons and 12 internal exons in mice ,6 Figur; four leIn addition to full-length ERα or ERα66, a number of ERα splice isoforms have been reported in normal tissues and pathological conditions , and they are often co-expressed with full-length ERα. In this review, we prioritize ERα variants that are expressed in normal physiological conditions. In this chapter, we discuss their physiological functions primarily derived from in vitro studies, but put emphasis on knowledge from in vivo studies. However, since splice variants and full-length ERα share the same exons as each other, there is an extremely limited number of studies to tease out splice variant-specific physiological functions. Furthermore, due to limited access to human tissues, the majority of in vivo observation comes from rodent studies. Although little is known about how the expression of ERα splicing variants is regulated, we include a discussion of the regulatory mechanisms when available. A 46-kDa isoform lacking first 173 N-terminal amino acids or AF-1 was first found in MCF-7 mutant human breast cancer cell lines and named “ERα46” for its molecular weight 46 kDa, which shares an identical DNA sequence with ERα66 for the remaining portion . SequencTwo molecules have been reported to be involved in the regulation of ERα46 expression at the transcription and splicing levels. Ohe et al. have shown that the high-mobility group A protein 1a (HMGA1a) is involved in the alternative splicing of ERα to induce ERα46 expression in MCF-7 mammary carcinoma cells . HMGA1a ERα46 expression was confirmed in normal human tissues including endometrium, ovary, liver, skeletal muscles, lung, kidney, and adrenal gland, but not the pituitary . The ratERα36 was found in MCF-7 breast cancer cells, which lacks both activation function domains, retains the DNA binding domain and a part of the ligand binding domain, and has a unique addition of 27 amino acids on the C-terminus encoded by a previously unknown exon . This vaAt the subcellular level, ERα36 is located at the plasma membrane ,18. ERα3Ohshiro et al. reported that a nuclear receptor-box-containing full-length protein, called nuclear protein E3-3 (NPE3-3), binds to ERα . When th2-dependent transcriptional activity of ERαΔ3-6 is significantly lower than that of wild-type (WT) ERα [The E(WT) ERα . The exp(WT) ERα .One must be careful when ERαV or ERαΔ3-6 is studied in Western blot (WB) because its molecular weight is close to those of ERα36 and ERα-LBD, mentioned next. These two splice isoforms have to be carefully characterized in WB analysis, depending on the ERα antibodies, against different epitopes. Currently, there is no report for the identification of the rodent counterpart of ERαV. However, ERα WB studies often reported bands below 40 kDa by antibodies against either the ERα N-terminus or C-terminus that is missing from ERα36, and they are expressed differentially in multiple tissues and in different subcellular fractions ,36,47.Recently, Strillacci et al. reported an ERα isoform lacking the N-terminal domains including AF-1, DBD, and a part of hinge region, in breast cancer cell lines; they named this ERα-LBD because it is composed of LBD and AF-2 . The tra2 did not change their subcellular localization [N-terminally truncated ERα products, NTERPs, which encode splicing variants lacking the N-terminal domain through the hinge domain, have been reported in mouse reproductive organs, brain, kidney, and pituitary . The endlization .2-ERα interaction, E2-induced transactivation, and nuclear localization of ERα [TERP-1 and 2 were found in female rat pituitary . Their pn of ERα . Mouse Tn of ERα ,26. The In the rat pituitary, three splicing isoforms are reported to be differentially expressed during development . The aut2-dependent uterine development and the expression of ERα target genes are not fully blocked in ERα-Neo KO mice [2 effect on endothelial NO production was maintained in the ERα-Neo KO mice while such actions were abolished in complete ERα KO mice [2-dependent response against vascular injury was maintained in ERα-Neo KO mice [Since ERα splicing isoforms share DNA sequence with full-length ERα, the deletion of any exons of the isoforms will also affect the expressions of other ERα isoforms including full-length ERα. However, there is a mouse model in which ERα AF-1 is deleted. Thus, in this mouse model, the expression of full-length ERα is disrupted but those of other ERα isoforms including ERα46 are maintained. Lubahn et al. first reported ERα gene knockout in mice by replacing the majority of first coding exons with a Neomycin-resistance gene; thereafter it is called ERα-Neo KO mice . Later,  KO mice ,52, indi KO mice . The E2- KO mice , while s KO mice ,55. ThesERα alternative splicing variant expressions show distinct temporal dynamics, tissue-specific patterns, and developmental changes. The regulatory mechanisms of ERα alternative splicing have been largely unknown except for a few examples (HMGA1 and BARX2 for ERα46 and NPE3-3 for ERαV). In addition to understanding the distinct physiological functions of those isoforms, it is important to analyze the mechanisms behind these differential expression profiles.In addition to differential splicing, PTMs of ERα add another layer of functional diversity in ERα biology. Multiple phosphorylation sites and other PTM sites have been reported in ERα proteins . In thisSerine 118 (S118) is the most widely studied phosphorylation site of human ERα that is located in the AF-1 domain. S118 phosphorylation is important for the dimerization of ERα and the induction/suppression of several ERα target genes ,60. S118The mouse counterpart of human ERα S118 is S122. A genetic mouse model harboring the amino acid substitution of serine to alanine at the 122 (S122A) of ERα has been generated so that site 122 is no longer phosphorylated. Mutant S122A ERα female mice show normal uterine weight, normal expressions of estrogen-regulated genes, normal estrogen-induced phosphorylation of Akt, and normal serum levels of estradiol and testosterone . ERα sigSerine at the 212 located in the ERα DBD is also a target of phosphorylation. The phosphorylation status of this site determines the transactivation of the distinct group of genes via ERE when they are overexpressed in Huh-7 cells . This seThis serine residue of human ERα is conserved in mouse ERα at serine 216. A mutant mouse harboring an amino acid substitution of the non-phosphorylated form (S216A) has been generated, and was analyzed for inflammatory regulation of microglia . The S21Arginine at the 260, located in the ERα DBD, is a methylation target. The methylated ERα is localized exclusively in the cytoplasm, and this methylation is required for some of the extranuclear functions of ERα such as the activation of PI3K and Src pathways ,69.2-regulated gene transcription is largely preserved in the R264A ERα mutant uterus, while the mutation disturbed the membrane ERα-mediated actions of estradiol such as the rapid dilation of mesenteric arteries and the acceleration of endothelial repair of carotid [The mouse counterpart of the R260 of human ERα is R264. A genetic mouse model with an amino acid substitution from arginine (R) to alanine (A) has been generated so that this site is no longer methylated. R264A ERα mutant mice show normal bone physiology, normal sex hormone levels, and no body weight phenotype . Althoug carotid . Recentl carotid . This re carotid . Althoug carotid . Thus, pIn addition to genomic ERα signaling pathway via direct/indirect interactions with genome, estrogens activate rapid, membrane-initiated ERα signaling cascades. Plasma membrane-bound ERα is palmitoylated at the cysteine 447 residue (C447) ,72. The 2 prevents bone demineralization, which is significantly impaired in the mutant mice, indicating that this effect is primarily exerted by membrane-bound ERα [The mouse counterpart of the C447 of human ERα is C451. The physiological roles of the palmitoylation of C451 were tested in mouse models with a point mutation at C451 to non-palmitoylable alanine (C451A) ,74. Thisound ERα .2 binding and the receptor dimerization in MCF-7 cells, and the interaction with kinases containing SH2 domains such as Src and HER-2 [Tyrosine 537 (Y537) is located in the ERα LBD/AF-2 domain. Phosphorylation of Y537 regulates End HER-2 ,77. Y537nd HER-2 .The mouse counterpart of the Y537 human ERα is Y541. Simond et al. generated a mouse model with a Y-to-serine (S) point mutation at 541 residue causing constitutive activation of ERα . The mutRecently, we found the presence of a new ERα variant that has a particular physiological role in mice . In thisImportantly, our transgenic mice with selective downregulation of ERα66* isoform caused biased physiological consequences . While tWe have discussed the physiological functions of ERα splice variants and PTMs independently. PTMs of the splice variants remain largely unexplored. Considering that some splicing variants and PTMs share cellular and physiological functions, it is not surprising that PTMs of ERα splicing variants impact their functions. In fact, ERα36 is phosphorylated by IKKε at Serine 167 . StironeA revolution of RNA sequencing technology has revealed an unexpectedly wide range of splice events, and how dynamically alternative splicing is changed in different physiological and pathological contexts ,102. HowThrough the extensive functional studies for ERα since its cloning, the structure of the ERα protein has been subdivided into six functional domains (A to F domains). However, a significant part of ERα is intrinsically disordered, where a protein does not have a rigid 3D structure and the functionalities seem to be context-dependent. The majority of transcription factors possess intrinsically disordered protein (IDP) domains, which are more likely to undergo PTMs and alternative splicing than structured domains . ERα is


New Emerging Functions of Transcription Factors and RNA-Binding Proteins in the Development of Hematological Malignancies” on Frontiers in Oncology.Hematological malignancies such as acute or chronic leukemias and lymphomas belong to a group of cancers that affect the blood, bone marrow and peripheral lymphoid organs and continue to present significant challenges for diagnosis and treatment primarily because of their diversity and heterogeneity. Recent research has shed light on the roles of transcription factors (TFs) and RNA-binding proteins (RBPs), that both are intimately linked to the development and progression of hematological malignancies because they control the generation, stability and translation of mRNA. This editorial aims to summarize the findings and conclusions from a set of six articles available in the Frontiers Research Topic “Benyoucef et al. describe how Transcription Factors (TFs) regulate this by translating signals from extrinsic factors into specific gene expression programs. Any aberration or mutation that alters the function of TFs will affect HSCs and their ability to self-renew or differentiate and thus bear the risks to trigger transformation processes that lead to a malignancy. When TFs are mutated or activated in hematological malignancies, they are responsible for specific gene expression patterns that are different from those found in normal cells. These aberrations can be measured and, in many cases, initiate a leukemia or lymphoma or drive their progression. However, they are not only characteristic for certain types of leukemia, but they provide a typical, recurring signature, that can be used for diagnosis or to make a prognostic estimate.The functionality and longevity of hematopoietic tissue from which leukemia and lymphoma can emerge is ensured by a tightly controlled balance between self-renewal, quiescence, and differentiation of hematopoietic stem cells (HSCs) into the many different blood lineages. Zhang et al.). Their article reveals new actionable therapeutic targets such the protein “Fifth Ewing Variant” (FEV), which was found to be activated in 30% of primary samples from patients with an ongoing acute myeloid leukemia (AML) and in nearly all samples from patients with an AML relapse after therapy. FEV belongs to the ETS family of TFs and regulates the homing and expansion of AML cells by activating the expression of integrin α4. Of interest is the observation that when integrin α4 is blocked with the antibody natalizumab (NZM), migration and colony-forming abilities of leukemia blasts and leukemic-initiating cells (LICs) are reduced suggesting that the link between FEV and integrin α4 can be a therapeutic target for AML.A new example for TF action in hematological malignancies is given by , which catalyses the removal of methyl groups from Histone H3 lysine 4, and thereby enables chromatin compaction and transcriptional repression. Zhao et al. reviews the structural and functional characteristics of Poly(rC)-binding proteins (PCBPs) and hnRNP K. These proteins belong to a subfamily of RNA binding proteins known for their role in hematopoietic cell growth, differentiation, and tumorigenesis. PCBP1-4 and hnRNP K share the so-called K Homology (KH) domain first identified in the human hnRNP K and is an evolutionarily conserved sequence of 70 amino acids. The KH domain can bind to specific mRNA molecules and regulates their stability or their alternative splicing or affect their translation. Interestingly, PCBPs are involved in both myeloid acute and chronic leukemias and also in lymphoid malignancies affecting major oncogenic pathways involving the oncoprotein c-MYC, the tumor suppressor TP53 and regulators of cell cycle progression.While TFs regulate the abundance of mRNAs and other transcripts, RNA-binding proteins participate in the control of gene expression by regulating mRNA processing, -transport, -stability, and -translation. The article from DDX3X gene were found in B-cell lymphomas, particularly those with c-MYC translocations. Notably, these mutations were almost exclusively observed in males and not in females, and the male homologue DDX3Y (located on the Y chromosome) was never found to be mutated in any malignancy. Lacroix et al. summarize in their review new findings indicating that loss of function of DDX3X assists the initial process of B-cell lymphomagenesis, but the completion of lymphomagenesis requires DDX3 activity and in the absence of a function DDX3X leads to upregulation of DDX3Y. The findings suggested that DDX3Y could serve as a cancer cell-specific target for developing adjuvant therapies for male patients with DDX3X mutations in B-cell lymphomas.Another RNA binding protein, which has recently gained notoriety as a new player in hematological malignancies, is the RNA helicase DDX3X. Somatic loss of function mutations in the X chromosome-located Ma et al. investigated MDS patients with SF3B1 mutations, which are considered a favorable prognostic biomarker. The study reviewed 140 MDS patients from the Zhejiang province of China and found that RUNX1, EZH2, NF1, and KRAS/NRAS mutations significantly impacted overall survival (OS) in addition to the commonly co-mutated TET2, ASXL1, and DNMT3A genes. Based on these findings, the researchers developed a risk scoring model that outperformed the widely used International Prognostic Scoring System (IPSS-R). This personalized prediction model categorized patients into low-risk and high-risk groups, providing a more accurate assessment of their 3-year overall survival.The third review on RNA binding proteins focuses on myelodysplastic syndrome (MDS), a heterogeneous disorder of the blood cells. Specifically, The research showcased in this Research Topic represents significant progress in unraveling the intricate roles of transcription factors and RNA-binding proteins in hematological malignancies. Advancements in gene-editing technologies, such as CRISPR-Cas9, and the discovery of small molecules that selectively inhibit TF and RBP interactions hold promise for ever better precision medicine approaches in hematological malignancies. It is clear that studying these proteins provides new insight that will pave the way for the development of innovative therapeutic strategies and hold great potential for improving the diagnosis, treatment, and management of patients with hematological malignancies.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.