Fruit ripening is a highly regulated and complex process involving a series of physiological and biochemical changes aiming to maximize fruit organoleptic traits to attract herbivores, maximizing therefore seed dispersal. Furthermore, this process is of key importance for fruit quality and therefore consumer acceptance. In fleshy fruits, ripening involves an alteration in color, in the content of sugars, organic acids and secondary metabolites, such as volatile compounds, which influence flavor and aroma, and the remodeling of cell walls, resulting in the softening of the fruit. The mechanisms underlying these processes rely on the action of phytohormones, transcription factors and epigenetic modifications. Strawberry fruit is considered a model of non-climacteric species, as its ripening is mainly controlled by abscisic acid. Besides the role of phytohormones in the regulation of strawberry fruit ripening, a number of transcription factors have been identified as important regulators of these processes to date. In this review, we present a comprehensive overview of the current knowledge on the role of transcription factors in the regulation of strawberry fruit ripening, as well as in compiling candidate regulators that might play an important role but that have not been functionally studied to date. Solanum lycopersicum) is the model organism. Climacteric ripening is characterized by the requirement of the phytohormone ethylene and a burst in cellular respiration, and many regulators involved in its regulation have been described so far (Fragaria vesca and Fragaria × ananassa respectively) have become the model, is not dependent on ethylene or a respiration burst but is mainly regulated by abscisic acid (ABA)  and epigenetic modifications, which are in turn regulated by external and internal stimuli . Those rd so far . In contid (ABA) .Strawberry is a popular fruit crop thanks to its flavor, aroma and nutritional value, with a huge impact on the agricultural economy of many countries. Furthermore, its extracts are known to produce cytotoxic effects on several human cancer lines  and agaiBesides the function of different phytohormones in the regulation of strawberry fruit ripening , the rolFvAGL62/FvAGL80 promoting auxin biosynthesis in the endosperm of fertilized seeds  biosynthesis is initiated in achenes and transported to the receptacle. It has been recently and elegantly reported the role of the complex of type I MADS-box genes ed seeds . Guo and hormone . The syn hormone . In addiompleted . Later dg stages . ABA is g stages .The role of other hormones during the regulation of strawberry ripening has also been studied, although their implications are not totally well understood. For example, ethylene is known to regulate the expression of genes involved in cell wall degradation and ripening-related metabolic pathways , being lcis-epoxycarotenoid dioxygenases (NCEDs), which use 9-cis-violaxanthin and 9′-cis-neoxanthin as substrates to form xanthoxin in a limiting reaction. Other regulatory steps include one of the first reactions in the pathway catalyzed by zeaxanthin epoxidase (ZEP) and the ABA catabolism mediated by CYP707A (Ripening Inducing Factor (FaRIF) has been reported to play a key role in the regulation of strawberry fruit ripening , a basic leucine zipper (bZIP) TF. Furthermore, the delayed ripening progress of FaRIF-silenced fruits was complemented when treated with exogenous ABA, supporting a positive feedback loop regulatory mechanism between ABA and FaRIF in the control of the ripening process. Besides ABA, the downregulation of FaRIF resulted in alterations in the expressions of genes involved in the metabolism of other hormones, including auxin and ethylene biosynthetic and signaling genes , transport (FvLAX1 and FvPIN5) and signaling (FvARF7 and FvIAA20) pathways were upregulated in fvsep3 fruits. Furthermore, fvsep3 mutation also resulted in a misregulation of GA pathway genes, such as the biosynthetic FveGA3ox and the catabolic FvGA2ox genes, as well as the receptor FvGID1b  genes expressed in strawberry fruits and seven AUX/IAA, were downregulated in both or any of the ripening stages studied. Interestingly, and despite the normal fruit appearance, FaMADS9-silenced fruits showed a reduction in the ABA content, which correlates with the downregulation of FaNCED1, FaNCED2 and FaNCED3 biosynthetic genes . They are synthesized at the endoplasmic reticulum and later transported into the vacuole for storage mainly by glutathione S-transferases (GSTs)  . Among ts (GSTs) . Finallys (GSTs) . Next, wFaMYB1 and its regulation upon anthocyanin biosynthesis  towards the biosynthesis of anthocyanins (ANS and UFGT), resulting in the accumulation of pelargonidin-3-glucoside   , being tby MYB10 . Howeverby MYB10 , no signce versa . RemarkaMYB10 as the main cause producing skin and flesh color variations in different species of Fragaria genus in nature (MYB10 have been described explaining the lack of anthocyanin in fruits from different accessions of F. vesca so far: (1) a G35C (W12S) SNP  in the FaMYB10-2 promoter that induces a higher expression of MYB10, probably contributing with some putative regulatory cis-elements to the promoter that were identified, such as ABA-, MeJA- and sugar-responsive elements, as well as MYB binding motifs and enhancers  SNP , (2) an , described as a candidate for the regulation of PAs biosynthesis (PACLOBUTRAZOL RESISTANCE 1 (FaPRE1), an atypical HLH transcription regulator characterized by the absence of the basic domain with DNA-binding activity  and RAP/GST1, probably through the regulation of FaMYB10  and FaTTG1, which orthologs in Arabidopsis, i.e. AtTT2, AtTT8 and AtTTG1, respectively, physically interact and regulates PA biosynthesis  and hydroxycinnamic acid derivatives, and higher PAs contents , FvbHLH33, and FvMYC1. Furthermore, all those MYBs, as well as FvMYB45 and FvMYB77, but with the exception of FvMYB75, could bind to the CHS2 promoter. In the case of DFR2 promoter, FvMYB11 and FvMYB21 could bind it by themselves; FvMYB10 and FvMYB75 could bind it although only in the presence of FvMYC1; and FvMYB22, FvMYB64 and FvMYB105 also required the presence of coregulators, in particular FvbHLH3, FvbHLH33, or FvMYC1. Moreover, when these three MYBs, FvMYB22, FvMYB64 or FvMYB105, were transiently co-expressed with FvbHLH33, they also induced CHS2 and DFR2 gene expression and PAs accumulation in strawberry fruits , which mediates the response to low temperature phosphorylating MYB10 and CHS proteins. This modification results in a reduction of MYB10 transcriptional activity and the proteasome-mediated degradation of CHS1, therefore negatively regulating the anthocyanin biosynthesis .FaWRKY11, which is a positive regulator of fruit resistance against Botrytis cinerea, can also promote the expression of MYB1 and MYB10, although fruits in which this TF were transiently overexpressed or silenced did not display any evident color phenotype  and trehalose-6-phosphate synthase 7 (FaTPS7) were also differentially expressed. Furthermore, FaMYB44.2 directly interacts with FaSPS3, FaSUS1 and FaHXK2 promoters and forms protein complexes with other members of its family, i.e., FaMYB44.1, FaMYB44.3, as well as with phenylpropanoid-related TFs such as FaMYB1, FabHLH3 , FabHLH33 and FaTTG1. In the current proposed model, FaMYB44.2 and FabHLH3 form a complex that negatively regulates FaSPS3 expression and therefore sucrose biosynthesis. However, Wei and collaborators also showed that this repression is impaired by FaMYB10, which competes for FabHLH3 binding during ripening , hormone signaling , and general ripening regulation (FaGAMYB).Among the TFs described to play a role in the regulation of sugar metabolism in strawberry fruits  influence strawberry flavor and aroma, essential traits for fruit quality. More than 360 VOCs have been identified in strawberry fruit, but it is generally considered that only a part of them are able to influence the organoleptic properties. These compounds constitute a diverse group, including esters, aldehydes, alcohols, ketones, terpenes, furanones and alkanes. During strawberry ripening most acids, esters, furan, ketones, lactones and terpenes increase their levels, while most alcohols, aldehydes, alkanes, and furanones exhibit a decrease . Among aMany volatile compounds, including esters, are derived from fatty acids (FAs) through the LOX pathway, which starts with the transformation of linoleic (18:2) and linolenic (18:3) acids into their hydroperoxide derivatives by β-oxidation carried out by lipoxygenases (LOXs) . HydropeFaMYB9 and FaMYB11 also regulate the content of volatile C6 and esters compounds respectively . Specifically, FaMYB9 regulates the content in hexanal and (E)-2-hexenal, which can contribute to the grassy flavor of unripe fruits -furanone  and 2,5-dimethyl-4-methoxy-3(2)H-furanone , which are considered to generate a caramel-like aroma  and contfuraneol . Furtherfuraneol .FaCAD1 and FaEGS2. A transactivation assay also showed that FaEOBII directly binds to FvCAD1 promoter. Interestingly, FaEOBII is in turn positively regulated by FaMYB10  , was downregulated in FaRIF silenced fruits  family. FaDOF2 positively regulates y FaDOF2 . InteresaAAT1-2) . Finallyd FaDOF2 . Furtherd fruits .In summary, the biosynthesis of different aroma-related compounds is regulated by a complex gene regulatory network (GNR) involving different types of TFs , and the PGs FaPG1 and FaADPG2. Moreover, the expression of enzymes responsible for modifying the cell wall coding genes was also altered, including FaEXP1, FaEXP2, FaEXP3, FaPME38, FaPME39 and different FaAGPs, which encodes for arabino galactan-proteins  and FaNAC042 is induced during fruit development and ripening. Furthermore, their expression was downregulated after fruits were treated with 1-Nordihydroguaiaretic acid (NDGA), an inhibitor of ABA biosynthesis, supporting their potential role as regulators of strawberry fruit ripening, although only FaRIF has been functionally validated so far among these candidate genes  and FaMYB576 from the MYB family  or dominant-negative (nor and cnr) mutations  or ChIP (Chromatin Immunoprecipitation) sequencing, with the exception of a targeted analysis by ChIP-qPCR to identify the direct regulation of FvWRKY48  and an if FaDOF2 . This isy plants , includiy plants . Howeverutations . These rCS-G, DP, and CM-P conceived and wrote the manuscript. All authors contributed to the article and approved the submitted version.This work was supported by grants from the European Research Council (ERC-2014-Stg 638134 to DP), the Spanish Ministry of Science and Innovation (RTI2018-097309-A-I00 and PID2021-123677OB-I00 to DP) and the Junta de Andalucía (UMA20-FEDERJA-093 and POSTDOC21_00893 to CM-P). We thank Plan Propio from the University of Málaga for financial support.We thank Danelle K. Seymour for her suggestions to improve the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Interestingly, gsdf-A and gsdf-B transcription were mainly activated by dmrt1-A (dsx- and mab-3-related transcription factor 1) and dmrt1-B, respectively. Loss of either gsdf-A or gsdf-B alone resulted in partial male-to-female sex reversal and loss of both caused complete sex reversal, which could be rescued by a nonsteroidal aromatase inhibitor. Compensatory expression of gsdf-A and gsdf-B was observed in gsdf-B and gsdf-A mutants, respectively. Subsequently, we determined that in tissue culture cells, Gsdf-A and Gsdf-B both interacted with Ncoa5 (nuclear receptor coactivator 5) and blocked Ncoa5 interaction with Rora  to repress Rora/Ncoa5-induced activation of cyp19a1a . These findings illustrate that Gsdf-A and Gsdf-B can regulate male differentiation by inhibiting cyp19a1a transcription in hexaploid gibel carp and also reveal that Gsdf-A and Gsdf-B can interact with Ncoa5 to suppress cyp19a1a transcription in vitro. This study provides a typical case of cooperative mechanism of duplicated genes in polyploids and also sheds light on the conserved evolution of sex differentiation.Although evolutionary fates and expression patterns of duplicated genes have been extensively investigated, how duplicated genes co-regulate a biological process in polyploids remains largely unknown. Here, we identified two  gsdf  homeologs (gsdf-A and gsdf-B) cooperatively induce male differentiation by inhibiting cyp19a1a  transcription in hexaploid gibel carp (Carassius gibelio). Loss of either gsdf-A or gsdf-B alone results in partial male-to-female sex reversal and loss of both causes complete sex reversal, which can be rescued by a nonsteroidal aromatase inhibitor. Compensatory expression of gsdf-A and gsdf-B is observed in gsdf-B and gsdf-A mutants, respectively. Moreover, we determine that in vitro, Gsdf-A and Gsdf-B both interact with Ncoa5 (nuclear receptor coactivator 5) and block Ncoa5 interaction with Rora  to repress Rora/Ncoa5-induced activation of cyp19a1a. These findings reveal the potential molecular mechanisms underlying gsdf homeologs-mediated male differentiation in polyploid fish.Polyploidy generates extra chromosome sets and duplicated genes. However, how the duplicated genes co-regulate a biological process in polyploids remains largely unknown. Here, we reveal that two  Polyploidy or whole-genome duplication (WGD) provides extra substrates for genomic evolution and is thus considered to be an important driving force for genetic diversity, trait innovation, and ecological adaption –5. The mCarassius gibelio), a cyprinid fish with a wide distribution across Eurasia We are sorry that we cannot be more positive about your manuscript at this stage. Please do not hesitate to contact us if you have any concerns or questions.Yours sincerely,Manfred SchartlGuest EditorPLOS GeneticsGregory BarshEditor-in-ChiefPLOS GeneticsReviewer's Responses to QuestionsComments to the Authors:Please note here if the review is uploaded as an attachment.Reviewer #1: Review about Wang et al.; PLoS GeneticsTwo duplicated gsdf homeologs cooperatively regulate male differentiation by inhibiting cyp19a1a transcription in a hexaploid fish.In their study, Wang et al. have identified two gsdf homeologous genes in the hexaploid gibel carp. They further propose to better characterize their regulation and function regarding to gonad development.First, having in mind to decipher how duplicated genes co-regulate a biological process  in a polyploid species, they show that the transcription of gsdfA and gsdfB is mainly activated by dmrt1a and dmrt1b respectively, suggesting asymmetrical evolution to explain the expression divergence in the context of the two sub-genomes. Then, functional characterization is carried on through generation of gsdf mutants, leading to partial or total sex reversion. The cooperative ability of the two gsdf homeologs to regulate male differentiation is then shown. Using cell culture system, gsdf interactions with Ncoa5 and subsequent transcriptional modulation of Cyp19a1a is further demonstrated.All in one, although the whole story presented in this paper draft is interesting in terms of (i) evolutionary biology , and (ii) mechanistic/physiology (how gsdfs exert their function(s)), I think some major issues need to be addressed before this draft is ready for publication in PLoS Genetics.Major Issues:-Characterization of gsdf homeologs and alleles/dynamic transcription of gsdfA/Bare mainly activated by dmrt1A/B respectively.Co-evolution of the two subgenomes (regarding to gsdfs regulation by Dmrt1) is indeed an interesting aspect of that paper.-The analysis might benefit from a dN/dS analysis (gsdf and dmrt1) to check whether one or the other homeologs are under selection. This might tell us more about the co-evolution. It should be then discussed if necessary.-In silico analysis: authors need to tell us more about the predicted dmrt1/sf1-binding sites -At the end, we need to know if this differential regulation is due to the evolution (divergence) of the Dmrt1s only, or of the targets only, or co-evolution of both.-Cytoplasmic localization of the Gsdf proteins is OK for me, although we know it is a secreted protein that will diffuse from one cell to others, and bind at cell membranes. It might accumulate in some cells before being excreted; this should be told and discussed.-Disruption of gsdfA/B results in cyp19a1a upregulation and aromatase inhibitor treatment rescues the male to female sex reversal.That part is OK for me.-Figure 3A/3B is very complex and I am not sure it helps much here. I would move it to supplemental data.-Figure 4E: it is difficult to compare that figure 4E with what has been shown in figure 2B: in 2B, basal relative expression of Gsdfs is nearly not detectable (at 25 dph), while that basal expression is quite high in 4E (same stage). Reference to (E) is actually not well written in the figure legend.So, please unify the relative expressions (2B/4E) or explain that discrepancy.The rest is OK for me, although at one point you will need RNA in situs to show that Gsdf, Ncoa5 and rora are indeed co-expressed to validate the physiological relevance of the inferred interactions.-Identification of GSDF-NCOa5 interaction via yeast two hybrid assay and co-immunoprecipitation.-Well, although I could be at first convinced by the yeast two hybrid assay, I am nevertheless very concerned about the fact that the full open reading frame of Gsdf was used as a bait. Indeed, if I am right the whole ORF usually encodes for the pro-mature peptide. Then to be active the pro-domain has to be cleaved to release the mature gsdf active peptide. In these conditions, using the un-cleaved Gsdf, I am not certain that the found interactions are relevant. This is an issue.-The same question now stands for the antibody that was prepared from (most of) the whole sequence; and that might also recognize the pro-domain instead of the mature gsdf peptide.-NCOa5 participates in cyp19a1a regulation via interaction with Rora.-Like for Sf1 and Dmrt1 predicted binding sites, potential Rora binding sites should be described with more details: statistics concerning the homology to the matrix and so on.The rest of that part seems OK for me.-Ncoa5 participates in cyp19a1a regulation via interaction with Rora.-Regulations and interactions were established in cells lines after transfection experiments. While the experiments performed for that part are quite OK, we should not forget the physiology behind, and how to interpret these results “physiologically”.Indeed, while Figure 8 compile the whole story, it is difficult for me to understand how a TGF-beta ligand, that is an excreted molecule that usually binds at the cell surface, would here have an activity inside of the nucleus together with Ncoa5 and Rora. To my knowledge this is impossible.Then to make the necessary connexion between the results in cell lines together with what the physiology would allow, it is to my opinion necessary to show co-localization of the Gsdf-Ncoa5-Rora complexes inside of the nucleus.Reviewer #2: Gsdf is a member of transforming growth factor β (TGF-β) superfamily which has been implicated in male sex differentiation of multiple teleost species. Despite of its critical role in testis differentiation, the specific molecular pathway of Gsdf-mediated sex differentiation remains elusive. In this MS, the authors identified two duplicated gsdf homeologs genes (gsdf-A and gsdf-B) in the gynogenetic hexaploid gibel carp, and found that the transcription of gsdf-A and gsdf-B is activated by dmrt1-A and dmrt1-B, respectively. By loss-of-function experiments, the authors demonstrated that two gsdf homeologs cooperatively regulate male differentiation by inhibiting cyp19a1a transcription. By in vitro analyses, the authors demonstrated that Gsdf-A and Gsdf-B interact with Ncoa5 to block Ncoa5 interaction with Rora, inhibiting Rora/Ncoa5-induced activation of cyp19a1a.Generally, this study is interesting and provides a special mechanism of gsdf in regulating male sex determination and differentiation. However, the following issues should be addressed before the article is accepted.Major concerns:1) As we know, Gsdf is a secretory protein which belongs to the transforming growth factor β family, and it is supposed to function with its receptor. In this MS, the author demonstrated a direct interaction between Gsdf-A/B and Ncoa5. Is there a TGF- β type II receptor involved in this regulatory process by binding gsdf?2) Usually, the male and female pathway genes display obvious sexually dimorphic expression. If both Ncoa5 and Rora are involved in sex differentiation, why there is no difference in the expression of ncoa5 and rora between females and males in the Figure 7A. Further, in Figure 7B, overexpression of gsdf led to downregulation of roar, why there was no difference in the expression of rora between females and males in the Figure 7A?3) An important finding of this work is that in females Ncoa5/Rora induced activation of cyp19a1a independent of Foxl2/Sf1-cyp19a1a pathway. We all know that mutation of Foxl2 lead to female to male sex reversal. The specific function of Ncoa5 in fish and whether it is involved in fish sex differentiation has not been explored. For this reviewer, it is hard to believe Ncoa5/Rora-cyp19a1a and Foxl2/Sf1-cyp19a1a pathway is independent in female sex differentiation.4) In Figure 2D and 2E, the authors demonstrated that Dmrt1 and Sf1 activate gsdf expression through binding to their potential binding sites in the gsdf promoter, it is better to determine which site is important for gsdf activation. It is also better to demonstrate that Dmrt1 and Sf1 are co-expressed in gsdf expressing cells.Miner concerns:Line 172：“Expression plasmids of Sf1-A/Sf1-B, Dmrt1-A, Dmrt1-B, and an empty expression plasmid were used as controls” should be “Expression plasmids of Sf1-A/Sf1-B, Dmrt1-A, Dmrt1-B were constructed, and an empty expression plasmid was used as controls”.Line 555: “mediaand” should be “medium”.Line 556: “luc” should be “luciferase reporter gene”.Line 633: A repeated copy of “under the accession number of” should be deleted.Line 904: “exam” should be “examine”.Line 908: “indicates” should be “indicate”.Line 921: “transcriptions” should be “transcripts” or “mRNA expression”, and the same for line 934.Line 958: The letter “e” in the Figure legend should be “(E)”.Line 980: “activates the promoter activity of gsdf-A/gsdf-B”, the promoter described here should be the “cyp19a1a promoter”.Line 1071：“noca5” should be “ncoa5”.Reviewer #3: This is an interesting and well-conducted study showing the role of a member of the transforming growth factor beta (TGF-ß) signaling pathway, gonadal somatic cell-derived factor (gsdf) to be involved in male differentiation in the hexaploid gibel carp (Carassius gibelio). This species was used as a system to investigate the mechanisms that duplicate genes use in a developmental process such as sex differentiation. Authors demonstrate the presence of two homeologues of gsdf, termed gsdf-A and gsdf-B that cooperatively regulate male sex differentiation by interacting with the nuclear co-activator factor 5 (Ncoa5) to suppress gonadal aromatase (cyp19a1a) gene expression. In lower vertebrates, it is well established that aromatase activity is necessary for estrogen production and female development. The study is very complete and includes the molecular characterization of gsdf-A and gsdf-B genes, expression during gonad development, transcriptional regulation, and functional analysis by wisely combining induced gynogenesis using males with or without a male determinant contained in supernumerary microchromosomes and loss-of-function analysis by the production of single or double mutants by means of CRISPR technology. Authors convincingly show that disruption of either gsdf-A or gsdf-B results in partial sex reversal while disruption of both homeologs results in complete male-to-female sex reversal. Furthermore, male-to-female sex reversal in double mutants is due to stimulation of cyp19a1a, the effects of which can be inhibited by treatment with a non-steroidal aromatase inhibitor. Authors identify Ncoa5 as interaction partner of Gsdf and show that gsdf binding of Ncoa5 prevents the latter to interact with Ncoa to upregulate cyp19a1 transcription. The study nicely shows how both forms of gsdf cooperate towards male sex differentiation. I have some comments that may help to improve the ms.L27 and Throughout the ms. The term “homeologous”, used in polyploidy plant research, may not be familiar with some readers, who may confuse it with “homologous”. Please explain that homologous genes resulting from allopolyploidy are commonly referred to as “homoeologs”. Here you use the term “homeologs”, which I am not sure how common it is. All this may create confusion. Please provide a clear definition of the term and its possible variants right from the start.L. 91-93. “a variant of gynogenesis”. This needs to be better explained to readers. Please indicate ploidy level of each progenitor in the initial cross. Also explain whether there is a dose-dependent relationship between the microchromosomes and the percent of males.L109. I am not sure if it would be more appropriate to speak about “sex determination” rather than to “sex differentiation”. Duplicates of gsdf has been implicated in sex determination. In fact, in lines 101-102 authors write “Members of the transforming growth factor-β (TGF-β) signaling pathway have been identified as being vastly involved in sex determination”.L151. Gsdf-A expression during sex differentiation peaked at 250 dph while the expression of Gsdf-B peaked at 120 dph. However, gonadal morphological differentiation between males and females occurs around 40 dpf. How then it is possible that Gsdf-A and B are drivers of sex determination/differentiation?L166-168. Consider rephrasing the sentence to clearly indicate that the identified upstream sequences of gsdf-A and gsdf-B were considered the potential promoter sequences; otherwise it seems that the binding sites per se are the promoter regions.L191. Indicate how did you ensure that the female gibel carp was devoid of MSM.L263. Delete “obviously”.L276. Add “nonsteroidal” before “aromatase inhibitor”.L277. Add “enzyme activity” after “Cyp19a1a”.L279. Explain why there were approximately 15% of the fish in which male-to-female sex reversal could not be prevented.L282. Upregulation of foxl2b in the testis of gsdf-A/gsdf-B double mutants (MSM+) subjected to letrozole treatment comes as a bit of surprise since usually foxl2a and Cyp19a1a expression goes hand in hand due to the regulatory positive feedback loop involving these two genes. Please clarify.L317. How can you be sure that Ncoa5-A had no role in sex differentiationL394. It comes as a bit of surprise that no further explanation of the different functions of gsdf-A and gsdf-B are discussed. This is relevant to the study but these functions are not properly explained. This is relevant in view of the overall aim of the paper. It should be stated whether the contribution of each homeologue is similar, if there is any indication that one has more relevance than the other in male differentiation.L421. “Thus, dysfunction of gsdf triggers upregulation of cyp19a1a and subsequently leads to the inhibition of dmrt1 and activation of foxl2”. I would rephrase a bit this sentence because in this study the whole chain of events is not shown. So I suggest indicating that, as shown in previous studies, on one hand upregulation of cyp19a1a would lead to dmrt1 inhibition while on the other it would upregulate foxl2.**********Have all data underlying the figures and results presented in the manuscript been provided?PLOS Geneticsdata availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.Large-scale datasets should be made available via a public repository as described in the Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********what does this mean?). If published, this will include your full peer review and any attached files.PLOS authors have the option to publish the peer review history of their article , and click on the Fetch/Validate link next to the ORCID field.  This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager.In the meantime, please log into Editorial Manager at If you have a press-related query, or would like to know about making your underlying data available , please see the end of this email. If your institution or institutions have a press office, please notify them about your upcoming article at this point, to enable them to help maximise its impact. Inform journal staff as soon as possible if you are preparing a press release for your article and need a publication date.Thank you again for supporting open-access publishing; we are looking forward to publishing your work in PLOS Genetics!Yours sincerely,Manfred SchartlGuest EditorPLOS GeneticsGregory BarshEditor-in-ChiefPLOS Geneticswww.plosgenetics.orgTwitter: @PLOSGenetics----------------------------------------------------Comments from the reviewers (if applicable):Reviewer's Responses to QuestionsComments to the Authors:Please note here if the review is uploaded as an attachment.Reviewer #1: Well, all my concerns have been addressed and discussed, although it was requiring quite a bit of additional work.I do think this paper draft has been much improved, and that it is now ready for publication.I have to add that it is a nice piece of work, and that is was real pleasure to review it.Congratulation!Reviewer #2: In this revised manuscript, the authors have carefully considered the reviewer’s comments and provided new evidences. Co-localization results of dmrt1/sf-1 with Gsdf along with mutation of Dmrt1 binding sites on gsdf promoter further supported the regulation of Dmrt1 on gsdf promoter in vitro. Additionally, new in situ expression data of rora/ncoa5 showed their co-expression with Gsdf and Cyp19a1a, respectively. These results strongly supported the regulation of Rora/Ncoa5 on cyp19a1a and validated the physical interaction between Gsdf and Ncoa5. Together the additional experiments and careful editing have significantly improved the quality of the manuscript. Overall, the authors have taken all the suggestions in consideration and have satisfactorily addressed all of my concerns. In one word, the authors have done a commendable job at revising the manuscript and have successfully improved it.Attached below were a few minor mistakes:Line 276: “are shown” should be “were shown”.Line 611: The process concerning generation of gsdf mutants has been moved into revised Figure S5, it is not in Figure 3 now. Please revise “shown in Fig 3.” as “shown in S5 Fig.”Line 613: “Fig 1A and 3B” here should be “Fig 1A and 1B”.Line 644: “roarα-B” should be “roraα-B”.Reviewer #3: The authors have successfully addresed all comments and clarified the doubts. This is a good paper suitable for publication.**********Have all data underlying the figures and results presented in the manuscript been provided?PLOS Geneticsdata availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.Large-scale datasets should be made available via a public repository as described in the Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********what does this mean?). 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Distinct patterns of functional markers on the D2 plot, indicating its ability to compartmentalize functional genome regions, are observed. Furthermore, enrichments of transcription‐related markers are concatenated into a cross‐species transcriptional activation model, where the nucleus is divided into four areas: active, intermediate, repress and histone, and repress and repeat. Based on the trajectories of the genomic regions on D2 plot, the constantly active and newly activated genes are successfully identified during olfactory sensory neuron maturation. The analysis reveals that the D2 plot effectively categorizes functional regions and provides a universal and transcription‐related measurement for the 3D genome.The execution of biological activities inside space‐limited cell nuclei requires sophisticated organization. Current studies on the 3D genome focus on chromatin interactions and local structures, e.g., topologically associating domains (TADs). In this study, two global physical properties: DNA density and distance to nuclear periphery (DisTP), are introduced and a 2D matrix, D 2 algorithm is developed to detect two physical properties, DNA density and distance to nuclear periphery, from the reconstructed genome structures. Based on them, D2 plot is constructed to reveal the spatial positions of genetic and epigenetic markers. Furthermore, a cross‐species transcriptional activation model on D2 plot is summarized, which is able to reflect expression levels.The D Nevertheless, most of these interaction‐derived structures focus on local spatial organizations, lacking a universal ability to compare distal regions. Although compartments are genome‐wise structures, they fail to correlate a given region to a specific biological function without additional functional data. While some researchers use interdisciplinary approaches to delineate the chromatin structure, their methods continue to focus on interactions. Therefore, universal measurement for a 3D genome with functional correlation is required to elucidate the structural basis of genome function.DNA molecules are highly condensed inside cell nuclei to compact into limited space, with the necessary loci exposed for active transcription.1 The  Specifically, the densely packed heterochromatin is less accessible and transcriptionally repressed, whereas euchromatin, which is less condensed, exhibits more active transcription. Several studies have shown that DisTP is positively correlated with transcriptional activity. The lamina‐associated domains (LADs), located at the nuclear periphery, are believed to repress gene expression. Experimental evidence has reinforced the idea that reduced proximity to the nuclear lamina is usually accompanied with higher transcriptional activity, while increased proximity to the nuclear lamina results in more repressed transcription. Previous works have clustered the genomic segments into groups with different DisTP (1 Mb resolution), either according to the results of experimentation or those of simulation. By computing the correlation with genetic markers, such as histone modifications, they found that the inner groups were more likely to enrich for active markers compared with the peripheral groups.DNA density (hereafter referred to as density) and distance to nuclear periphery (DisTP) are two primary physical properties that are related to transcriptional activities in genome spatial organization. A negative correlation between density and transcriptional activity has been implied by several nuclear structures in previous studies.7, 82, to compute the two properties: density and DisTP, and integrated them as a 2D matrix, D2 plot, for mapping functional markers at the genome‐wide scale. We identified distinct enrichment patterns of functional markers on the D2 plot and proposed a cross‐species transcriptional activation model on D2 plot. Our study revealed a novel analysis procedure for correlating nuclear organization with gene transcriptional activities and provided a new perspective for the study of the 3D genome structure.Owing to the lack of appropriate techniques for detecting the physical properties in genome‐wide scale with high resolution, the extent to which density or DisTP are connected to transcriptional activities, and the analysis comprising the properties for the comprehensive description of genome structure and function are unclear. We developed an algorithm, D22.12 algorithm computed Density and DisTP at the genome‐wide scale in high resolution  and the experimental LAD data, thereby verifying the fitness of DisTP . Rods of nocturnal animals adopted an inverted radial organization, in which euchromatin resided at periphery and heterochromatin preferred the interior. Inverted distributions between the computed DisTP of rods and that of other cell types were observed . Specifically, for DisTP, the periphery regions showed lower SD for both human and mouse cells  and DisTP (y‐axis), named D2 plot . D2 plot was composed of physical states , the rectangular bins with specific values of density and DisTP . The enrichment scores of all markers are shown in Figure For joint analysis, we constructed a 2D matrix of density  and trimethylation of lysine 9 on histone H3 (H3K9me3), respectively.25 On y Figure , as conf2 plot. We found that long repeats, including long terminal repeats and long interspersed nuclear elements , preferred the inner high‐density regions or periphery regions , CTCF, and YY1. They are believed to cooperate in the construction of genomic structures via the use of a previously proposed loop extrusion model.29 The2.32 plot, we selected 16 transcription‐related markers and performed the hierarchy cluster on physical states . As shown in FigureTo link transcription activity to the D2 plot to reveal their transcriptional patterns , and repress and repeat (repressed states marked by long repeats) areas. Then we assigned these four areas back to the Ds Figure . The pat , but density values declined significantly , repressed to active (RA), and constantly repressed (CR), which revealed the dynamic regulation of gene expression during OSN development.After establishing the correlation between the transcriptional level and the DFigureNext, we investigated the enrichments of functional elements in the three modes. Compared to the background, the percentages of exons in CA and RA were remarkably higher, while that of CR was lower Figure6A, in a2 plot, the housekeeping genes persistently enriched at the inner low‐density regions, while the L1 repeats enriched at the periphery , harboring 19 housekeeping (HK) genes (mainly located at CA), 10 ORs (at RA), and 129 L1 repeats (at CR) Figure . The act Correspondingly, their activation indexes increased during development , to inner high‐density (developing OSNs), and then toward lower density (mature OSNs), in consonance with their activation process  on the Dlization,28 wer2 plot among different human and mouse cells. This model revealed that the distance to the periphery was negatively correlated with the transcriptional activities of genes, which seemingly contrasted to the center‐positioned nucleoli that were mainly composed of heterochromatin. The significantly low genome coverage (<5%) of nucleolus‐associated domains might render these regions neglected in our model. To examine the fitness of our model to reflect gene activation, mouse olfactory neurons at three differentiating stages were analyzed, and our model successfully identified the activated genes based on the change of density and DisTP. However, the underlying mechanism has not been explored. We assume that the translocation of the selected genes between distal regions with different density and DisTP is unfavorable, owing to the high cost of energy. Alternatively, the changes of local chromatin modifications, such as histone modification, assembling into distinct condensates through phase separation, and simultaneously altering surrounding density or DisTP, is feasible.In this study, we proposed a cross‐species transcriptional activation model on the Dur model.34 To 2 model of mouse cells, albeit being derived from mouse forebrain neurons, is capable of linking the structure with gene expression during OSN development, verifying its broad fitness and feasibility. Nonetheless, further verification and application of this model in other species is required, but these are currently unavailable owing to the lack of high‐quality single‐cell Hi‐C data. Our model would be applicable to most species, where sophisticated Mb‐scale spatial organization is essential for regulating gene expression. It might be helpful to elucidate human tumorigenesis analysis, which usually involves dramatic alteration of the genome structure.Notably, the D2 model allows for universal measurements of the genome structure and correlates the genomic structure with its function. Nonetheless, we speculate that physical properties of DNA act more as microenvironments to facilitate or repress gene transcription activity rather than direct and decisive factors, as protein structure to its function. In summary, our study paves the way for further methodological exploration to link genome structure with its function.Our study provides a new perspective for 3D genome analysis. Previous studies mainly focused on well‐known structures such as loops or TADs, which only revealed the spatial adjacency of focal structures. Contrarily, our D42 algorithm, which rapidly and accurately computed the DNA density and DisTP values based on the reconstructed genome structure. D2 algorithm can be found at https://github.com/xjtu‐omics/D2.Python script D2.py implemented the D2 algorithm. Genome structures from two research groups were collected in this study . Then, they used a genome reconstruction algorithm, hickit, which was similar to NucDynamics and enabled the construction of diploid cells at a relatively higher resolution (20 kb).Reconstructed genome structures, which were generated from single‐cell Hi‐C, were the main input for the Dy , to ensure the average number of DNA particles within a cube was approximately the same across cells. This predetermined parameter was not sensitive for further analysis, because the following analysis concentrated on the differences between the density and DisTP of genomic regions , while the change in this parameter increased or decreased density or DisTP universally. The segmentation was constructed according to the cube length and covered the particles. Then the spatial coordinate of particles was replaced using the cube coordinate. This normalization was based purely on DNA density, but the nucleic radius  was adequately normalized .To combine density and DisTP for further systematic analysis, a 2D density–DisTP matrix, the D2 plot, genetic data were weighted and averaged by the probability of the genomic segment appearing at the physical state, as shown belowaE is the computed enrichment score of the genomic marker in the physical state, a. gNV is the z‐scored normalized enrichment score of a genetic marker at the genome segment, g. gaP is the probability of the genome segment g appearing in the state a, defined as the ratio of the number of cells whose genomic segment g located at the state a with respect to the total cell number. Afterward, the enrichment scores were normalized by z‐score normalization.To calculate the marker enrichment scores on the DEa′ is the alternative enrichment score derived from the average density and DisTP at physical state, a. aG is the collection of genomic segments whose average density and DisTP were located at state a. N(aG) is the number of collections. The average values delineated the bulk activities of a cell type more optimally, but were unable to represent the raw density and DisTP detected from the single cell. For example, the average values could not reflect the sparse distribution, for example, the multimodal distribution.Through this procedure, the density and DisTP of single cells were determined. There was another way of computing the enrichment scores, where the density and DisTP were averaged firstp‐value < 0.01: 98.11–99.88%). Then, the enrichment score analysis with average density and DisTP was repeated and it was found that it exhibited similar patterns to Figure To test if the average density and DisTP would give similar enrichment patterns, the dip test was first carried out for unimodal distribution. All genomic bins were unimodal for both density and DisTP  and marker enrichment score (y), as followsSd,p is the computed property strength of property p at DisTP d. For density, the x input for linear fitting is the collection of all densities at a given DisTP and y is the corresponding marker enrichment score. For DisTP, x is the collection of the given DisTP and its nearby DisTP, and y is the corresponding enrichment score. The property strength reflected the association between the physical properties and the transcription level.The property strength reflected the intensity of impact of density or DisTP on the transcription level. The active markers were selected and the property strength was computed at a given DisTP as the slope between property changes  M19 release.The mouse reference genome (GRCm38) and gene annotations (ALL) were downloaded from the GENCODE (https://www.gencodegenes.org/human/) 39 release.The human reference genome (GRCh37) and gene annotations (ALL) were downloaded from the GENCODE  were indexed by 20 kb genomic bins. For unphased data, the data were copied to two haplotypes.ChIP‐seq sequenced protein binding sites. ChIP‐seq data of transcription factors  and histone modifications  were collected. These data, with different types of processed files, were collected from ENCODE. Here the fold change was utilized over the control file, because it provides whole genome protein binding information. This file was formatted as BigWig and was transformed to a bedgraph file using the UCSC script bigWigToBedGraph. Then bedtools intersect were used to find the intersected regions between the index file and the marker bedgraph file. Next, the fold change of all 20 kb bins was weight‐averaged and they were indexed according to the index file.The repeat data were obtained from RepeatMasker. Owing to the low resolution of the 3D genome, only broadly distributed repeats would be statistically significant for enrichment. Therefore, repeats with less occurrences were filtered out. Only repeats with more than 20 000 occurrences were left. The remaining repeats with the index file were intersected and then their percentage at a given genomic bin was calculated, and finally they were indexed in the aforementioned procedure. Because chromatin states were discrete states, intersections, calculated percentages, and indexed were performed through processes similar to those of the repeats. Each genomic bin had a value for each chromatin state, representing the length of the state within that bin.Chromatin states described the transcriptional states of genomic loci. They were calculated using HMM and based on chip‐seq data.38 BecThe CpG data were downloaded from ENCODE, formatted as bedMethyl. Sites were filtered out without reads. The remaining sites were intersected with the index file, the median CpG percentages were calculated in a given bin, and finally they were indexed using the aforementioned procedure. Because these data were discrete like genomic repeats, the data were intersected, calculated, and indexed in the same way as the repeats. Notably, the bin size was 100 kb for the used mES cells.DamID‐seq identified protein binding sites by expressing the proposed DNA‐binding protein as a fusion protein with DNA methyltransferase. Using DamID‐seq to detect the binding sites of Lmn‐B1 (Lamin‐B1), the main component of nuclear lamina, is a popular method of detecting LADs. The mESC LAD experimental data were utilized.39 BecTo validate DisTP, experimental LAD data were compared to the probability of appearing at the nuclear periphery (percentages of cells whose given genomic bin had DisTP below 2). As they were both indexed by the same index file, they were associated with their index. The outliers were eliminated using three‐sigma limits.n = 8), the possible values for simulated LAD data are too sparse at 100 kb resolution. Therefore, the nearby bins were concatenated to 2 Mb resolution, in order to provide continuous percentages. The number of 2 Mb genomic bins is 1103. The two‐sided Pearson correlation was computed using scipy.stats.pearsonr.Noteworthy, due to the small number of available cells  was conducted, to identify the values of density that were more stable.The authors declare no conflict of interest.2 algorithm with the help of X.Y. Y.C. downloaded, analyzed, and interpreted the data in current studies. P.J. and T.W. provided help for analyzing data. Y.C. was the major contributor in writing the manuscript. T.G. helped with the benchmark. X.Y., D.X., and K.Y. revised the manuscript. K.Y. supervised the whole program. All authors read and approved the final manuscript.Y.C. developed the DSupporting InformationClick here for additional data file.


However, the function of TE-derived ACRs in the regulation of gene expression in the rice genome has not been well characterized. In this study, we examined the chromatin dynamics in six types of rice tissues and found that ~8% of ACRs were derived from TEs and exhibited distinct levels of accessibility and conservation as compared to those without TEs. TEs exhibited a TE subtype-dependent impact on ACR formation, which can be mediated by changes in the underlying DNA methylation levels. Moreover, we found that tissue-specific TE-derived ACRs might function in the tissue development through the modulation of nearby gene expression. Interestingly, many genes in domestication sweeps were found to overlap with TE-derived ACRs, suggesting their potential functions in the rice domestication. In addition, we found that the expression divergence of 1070 duplicate gene pairs were associated with TE-derived ACRs and had distinct distributions of TEs and ACRs around the transcription start sites (TSSs), which may experience different selection pressures. Thus, our study provides some insights into the biological implications of TE-derived ACRs in the rice genome. Our results imply that these ACRs are likely involved in the regulation of tissue development, rice domestication and functional divergence of duplicated genes.Growing evidence indicates that transposons or transposable elements (TEs)-derived accessible chromatin regions (ACRs) play essential roles in multiple biological processes by interacting with  Zea mays) by Barbara McClintock [Gypsy superfamily and the Copia superfamily, long interspersed nuclear elements (LINEs), and short interspersed nuclear elements (SINEs). The Class II TEs, referred to as DNA transposons, transpose via a “cut and paste” mechanism with a DNA as an intermediate, they can be further grouped into several superfamilies based on their transposase proteins and sequence structures, such as CACTA, Mutator, Tc1/Mariner, et al. In addition, a new type of DNA transposon, Helitron, can transpose via the “rolling circle replication” model [Polintons, transposing in a self-synthesizing manner has been found in several eukaryotic species, like protists, fungi, and animals [Transposable elements (TEs) have been the subject of much debate since they were first discovered and described as “controlling elements” in maize  such as alternative promoters and enhancers essential for the regulation of gene transcription, and alteration of chromatin features of nearby genes, thereby being involved in various biological processes [The jumping of TEs frequently disrupts genome structures, resulting in genome instability, and induces some deleterious mutations in the host genome . The hosrocesses ,19. Thestrans-acting factors during growth and development and in response to environmental cues in mammals and plants [Open chromatin, also referred to as accessible chromatin, represents unique chromatin regions with less nucleosome occupancy or nucleosome depletion (nucleosome-free regions) . It usuad plants ,22. Opend plants ,25,26,27d plants . Moreoved plants .Accumulating evidence has shown that TEs can potentially contribute to the formation of open chromatin owing to partially/fully overlapping open chromatin in mammalian and plant genomes ,29,30,31However, relationships between TEs and accessible chromatin regions (ACRs) haven’t been well characterized in rice as compared with other plants like maize. To this end, we analyzed the dynamics of chromatin accessibility in six rice tissues, associated accessible chromatin regions (ACRs) with different TE superfamilies, and characterized the genomic features of corresponding TEs and ACRs in rice. We also investigated the role of TE-derived ACRs in the regulation of tissue-specific and duplicated gene expression. Our study provides some insights into the contribution of TEs in ACRs formation, thereby advancing our understanding of the biological implications of TE-derived ACRs in the rice genome.To identify TE-related accessible chromatin regions in rice, we used the published ATAC-seq (Assay for Transposase-Accessible Chromatin with high throughput sequencing) data derived from six tissues , includihAT and Helitron covered ca. 25% of the full ACR length (the length of ATAC peak) on average, while PIF_Harbinger and Tcl_Mariner exhibited the least coverage on ACRs. This was possibly caused by the short length of their DNA sequences. Most Gypsy can fully cover the overlapping ACRs. These results showed that most ACRs covered the junctional regions of TE/non-TE DNA, which is similar to the findings in mouse [Mutator, hAT, and Gypsy exhibited more coverage of ACR summits than others , which can be derived from TE sequences [PIF_Harbinger and Tcl_Mariner were significantly enriched in the ACR boundary. And the number of Mutator and hAT was higher in the center region of pACRs compared with dACRs.  or tissue-specific  ACRs, according to the entropy values , preferentially expressed in root (RT); a hAT transposon related ACR was located near the TSS of NL1 with higher expression levels in young panicle (YP), which is a GATA type transcription factor related to the panicle development [Gypsy retrotransposon-derived ACR was located in the upstream region of OsBISAMT1, a gene encoding S-adenosyl-L-methionine related to defense responses, which was specially expressed in young leaf (YL) [ACRs have been reported to play vital roles in the regulation of gene expression in eukaryotic genomes by interacting with  factors ,37. Howe factors . We theny values . Comparey values B. Moreovy values B, while ckground C. After ckground , suggestckground D. As shoelopment ; a Gypsyeaf (YL) .Collectively, our results show that TE-derived ACRs may play vital roles in the regulation of tissue-specific gene expression, thereby being involved in the tissue development in rice.To investigate how the presence of TEs affects chromatin accessibility, we plotted normalized ATAC-seq read counts across ±2 kb of the center of ACRs with and without TEs , and fouw) and cultivated rice accessions (πc). According to πw/πc values, we identified 187 putative domestication sweeps, containing 270 TE-derived ACRs (~4%)  [It is well known that the transposition activity of TEs potentially leads to various genomic mutations during evolution . To explRs (~4%) F. Indeed%)  ,51,52,53Taken together, these results indicate that TE-derived ACRs may have coevolved with nearby genes during artificial and natural selection, thereby functioning in the formation of favorable agronomic traits in rice.n = 561) with TE-derived ACRs at ±500 bp of the TSS ; subgroup 2, duplicated gene pairs with TE-related ACRs around the TSSs for one copy and regular ACR for the other copy (n = 532); subgroup 3, duplicated gene pairs with only one copy having TE-related ACRs around the TSSs (n = 509) (Ks (synonymous substitutions per synonymous site) among duplicated gene pairs and observed the descending order of Ks distribution changes among duplicated genes in three subgroups: subgroup 1 < subgroup 3 < subgroup 2  and older gene duplicates . To assess whether genes with the absence/presence of TE-related ACRs around TSSs were subjected to different intensities of selective constraints, we calculated Ka (nonsynonymous substitutions per nonsynonymous site)/Ks values for gene pairs, and found that most of the Ka/Ks were less than 1  D. After n = 509) , indicatbgroup 2 E, indicas than 1 F. For suectively F.These results suggest that TE-derived ACRs related gene pairs are primarily subjected to purifying selection, and a combination of TEs and ACRs is associated with the strength of the selection pressure.TEs can induce a wide range of genomic alterations, including chromosome rearrangement, epigenetic regulation, and insertion mutagenesis , resultiD. melanogaster [LTR_Copia, it was reported some solo-LTRs tend to keep TF-specific CREs [trans-acting factors. Variation of TE-derived CREs could reflect differentiation of TE activities among different organisms during genome evolution.Global identification of ACRs helps to mine functional CREs like promoters, enhancers, et al. Characterization of TE-derived ACRs helps to identify CREs associated with TEs, thereby advancing understanding of roles of TEs in the regulation of gene expression. Accumulating evidence shows variations in the formation of TE-derived CREs among different organisms. For instance, nearly 30% of TEs containing active elements, with 45% and 20% of them belonging to LTR retrotransposons and DNA transposons, respectively, were found in the classic model organism nogaster ; 25% of nogaster ,69; Abounogaster . Similarnogaster . Comprehfic CREs , indicatThe degree of chromatin openness correlated negatively with the density. This is possibly caused by the overall hypermethylation of TEs in plant genomes ,72,73, wNL1 and OsBISAMT1 were found to have tissue-specific TE-derived ACRs in their promoters . Samtools (v1.9) [For the ATAC-seq and ChIP-seq data, PCR duplicates were removed using Picard MarkDuplicates (s (v1.9)  was useds (v1.9)  based ons (v1.9) .Public BS-seq data generated from young leaves of Zhenshan97 were used for the DNA methylation assay . The raw8 --no model --shift -50 --extsize 100 --q 0.01. Bedtools (v2.29.0) [https://github.com/oushujun/riceTElib (accessed on 20 May 2022). ACRs with more than 50% of their length covered by a TE sequence were defined as TE-derived ACRs, and the corresponding TEs were also considered as ACR-related TEs. A custom Python script was used to calculate the normalized ATAC read counts within the designated genomic regions and genes.MACS2 software (v2.1.4)  was usedv2.29.0)  was usedv2.29.0)  with ricA total of 83,087 ACRs were obtained by merging all ACRs in each of the six rice tissues according to their genomic coordinates, using the merge function from bedtools (v2.29.0) . The ATAhttp://plantregmap.gao-lab.org/cis-map.php, accessed on 8 June 2022), which were calculated by multiple genome alignments of 63 different plants [https://snp-seek.irri.org/_download.zul, accessed on 8 June 2022). For the wild rice, the resequencing data of 5 O. rufipogon plants were obtained from the public literatures [w/πc) were set as thresholds for putative domestication sweeps, as described in the previous study [The evolutionary conservation of ACRs was measured using phastCons conservation scores downloaded from PlantRegMap  [http://rice.uga.edu, accessed on 10 June 2022) were blasted against themselves with an E-value < 1 × 10−10. The collinear blocks and syntenic gene pairs were identified using MCScanX [DupGen_finder was used to match duplicated gene pairs, and the transposed duplicated gene pairs were detected using the Zea mays genome as their outgroups. Ka, Ks and Ka/Ks values of each duplicated gene pair were calculated following the public pipeline on GitHub . Ks values >  5.0 were excluded from further analyses because of the saturated substitutions at synonymous sites [p value > 0.05 were also removed.The different modes of duplicated genes were identified using the ne 2022) . Briefly MCScanX  with defus sites . Gene pahttps://meme-suite.org/meme/tools/meme-chip, accessed on 12 June 2022) [The sequences of designated ACRs were used to identify motifs using the MEME-ChIP module of the MEME Suite Programs (ne 2022) ,105, witne 2022)  as known


Fibrosis, a process caused by excessive deposition of extracellular matrix (ECM), is a common cause and outcome of organ failure and even death. Researchers have made many efforts to understand the mechanism of fibrogenesis and to develop therapeutic strategies; yet, the outcome remains unsatisfactory. In recent years, advances in epigenetics, including chromatin remodeling, histone modification, DNA methylation, and noncoding RNA (ncRNA), have provided more insights into the fibrotic process and have suggested the possibility of novel therapy for organ fibrosis. In this review, we summarize the current research on the epigenetic mechanisms involved in organ fibrosis and their possible clinical applications.The online version contains supplementary material available at 10.1186/s12967-023-04018-5. Fibrosis is a reparative or reactive process characterized by the formation and deposition of excess fibrous connective tissue that results in progressive architectural remodeling in nearly all tissues and organs, including the liver, kidney, lung, heart, and skin . In the In the past, fibrosis was once considered unidirectional, but a growing amount of evidence now suggests that fibrosis can be reversible under specific circumstances . Until nth carbon of cytosine blocks the binding of transcription factors (TFs) by occupying the major groove of DNA. These two epigenetic regulations change the accessibility of DNA to TFs, thus influencing the subsequent transcription process [The gene expression process, a highly conserved process in which a genotype gives rise to a phenotype, is well established and consists of unwinding and exposure of the DNA helix, transcription, RNA splicing, translation, and posttranslational modification. Each step of this process is under the precise control of epigenetic factors. First, chromatin remodeling can move, remove or alter nucleosomes by the action of chromatin remodeling complexes, a group of adenosine triphosphate (ATP)-powered protein complexes. Then, histone modifications open DNA-histone interactions as covalent posttranslational modifications of amino acids near the N-terminal ends of histone proteins . After t process . Noncodi process , 16. EacIn this review, we provide a detailed and updated review of epigenetics in fibrosis, from mechanism to clinical practice, with the hope of offering a comprehensive understanding of fibrogenesis and its treatments with regard to epigenetics. We mainly focus on epigenetic modifications in fibrotic diseases to clarify the fundamental mechanism, classify the downstream pathways involved and develop potential therapies of fibrosis.Previous research has significantly increased our understanding of genetic susceptibility to fibrotic diseases. Sequence variants in genes for surfactant proteins , polymorphisms in MUC5B or TOLLIP, and mutations in telomere genes  are associated with an increased risk of idiopathic pulmonary fibrosis (IPF) , 18. PolHowever, the concordance rate for some fibrotic diseases in monozygotic twins is low and that common genetic variants are not always observed in patients, indicating that genetic predisposition is insufficient to explain disease development and suggesting a potential role of epigenetics as the missing link that connects the environmental exposure to disease development.Interestingly, epigenetics and genetics are inextricably linked. On the one hand, sequence polymorphisms can influence epigenomic landscapes, and epigenetic factors are frequently mutated in diseases. Epigenetic mechanisms, on the other hand, regulate genome stability and mutability. In IPF, rs35705950, a MUC5B promoter variant, was discovered to disrupt a CpG motif, resulting in a significant increase in MUC5B expression by inhibiting DNA methylation . With ATChromatin remodeling is a process using the energy of ATP hydrolysis to destabilize, move, or restructure nucleosomes. Chromatin remodeling complexes contain four different families, SWI/SNF, ISWI, CHD, and INO80, but share a relatively conserved ATPase domain. The result of their actions on nucleosome arrays can be classified into two categories: site exposure, where the site for DNA-binding protein (DBP) becomes accessible, and altered composition, where the nucleosome content is modified by histone variant replacement or eviction .Chromatin remodelers are poorly studied in fibrosis since the mechanism of Chromatin remodeling is not clear. The SWI/SNF family, the most studied group of chromatin remodelers, contains two catalytic ATPase subunits, BRM (Brahma/SMARCA2) and BRG1 (Brahma-related gene 1/SMARCA4). A serieOther studies have also found that BRG1 in fibroblasts, hepatic stellate cells, renal epithelial cells, etc. regulate fibrosis through the TGF-β pathway or the Wnt pathway , 36. A rHistones are proteins that provide structural support to form nucleosomes. Each nucleosome consists of two identical subunits, and each subunit contains four histones: H2A, H2B, H3, and H4, which are also recognized as core histones. H1 is located at the gate of core histones and functions to link and stabilize two nucleosomes. Histones pack DNA into chromatin and are thus crucial in the transcription of DNA by deciding which segment is exposed and can be accessed , 39.Four types of histone regulation that have been identified in recent decades, acetylation , methylaThe acetylation of histones is one of the earliest identified histone modifications. Acetylation negatively charges the lysine residues of the N-terminal histone tail to repel the negatively charged DNA and causes chromatin structure relaxation. The opened chromatin conformation allows transcription factors to bind and gene expression to increase , 47. AceHAT consists of three major families: general control nonderepressible 5 (Gcn5)-related N-acetyltransferases (GNATs), p300/CBP, and MYST proteins –52, amonThe role of p300 in fibrosis has been verified in multiple studies  and nicotinamide adenosine-dependent (NAD) enzymes. Class IV HDACs contain only one member, HDAC11, which shares sequence domains with class I and class III HDACs. HDACs epigenetically alter the gene transcription process via the deacetylation of core histones. They increase the positive charges on histones and possibly strengthen histone-DNA interactions and repress transcription. However, whether HDACs can directly activate transcription and the exact detailed mechanisms by which they regulate transcription remain to be clarified .HDACs can regulate fibrosis via fibroblast proliferation, senescence, and ECM production –74. SeveHDAC1 and HDAC2 coexist to form Sin3, NuRD, and CoREST complexes . HDAC3 cRecruitment of HDAC4, HDAC5, and HDAC7 promotes the deacetylation of H3 and H4 histones. They can enhance fibroblast proliferation by inhibiting thy-1 and promoting fibroblast activation through downregulation of peroxisome proliferator-activated receptorγ coactivator-1 (PGC-1) in IPF –86. TheyClass III HDAC and SIRT has been found to involve in nonhistone protein modifications in fibrosis and only a few studies have revealed its role in histone modifications . SIRT6 cThe studies described above have illustrated the multifunctional and diverse mechanisms of HDACs by targeting various genes in the processes of fibroblast proliferation, apoptosis, ECM deposition, and degradation. Notably, HDACs act as fundamental regulators participating in epigenetic modifications, thus making them a generally recognized potential treatment target for fibrosis.Compared to histone acetylation, methylation has been characterized as a more complex entity since distinct histone lysine residues may have various functions when methylated. Additionally, different densities of methylation on the same residue may vastly differ in their functions , 97. UnlCompared to histone acetylation, methylation has been characterized as a more complex entity since distinct histone lysine residues may have various functions when methylated. Additionally, different degrees of methylation on the same residue may vastly differ in their functions , 97. UnlEnhancer of Zeste Homolog 2 (EZH2) is a histone methylase, together with embryonic ectoderm development (EED) and suppressor of zeste 12 (SUZ12), forming polycomb repressive complex 2 (PRC2) to mediate H3K27me3, which is essential for stable silencing  and ubiquitously transcribed tetratricopeptide repeat on chromosome X . In recent studies, repression of EZH2 and activation of JMJD3 were demonstrated to work together in TGF-β-induced fibrosis, repressing H3K27me3 and thus increasing profibrotic gene expression . The dirSignificantly, different methylases can work together or interfere with other epigenetic factors, establishing a crosstalk network. A set of studies found that pulmonary fibrosis was regulated by G9a/EZH2-mediated H3K9me3/H3K27me3, interacting with DNA methylation in a bidirectional and mutually dependent manner to reinforce COX-2 and CXCL10 epigenetic silencing , 109. DNIn addition to EZH2, another methylase, G9a, catalyzes the methylation of H3K9, and this modification serves as a binding site for chromodomain protein heterochromatin protein 1 (HP1), thus generating local heterochromatin  , 117. JMMLL family proteins usually act in the histone methyltransferase complex COMPASS, which consists of ASH2, RBBP5, WDR5, and hDPY30  refer to the CpG-rich regions of DNA, which are often associated with transcription start regions and promoters. Most CGIs remain unmethylated in somatic cells, promoting gene expression, while methylation of CGIs can cause robust transcriptional repression, forming long-term monoallelic silencing, such as X inactivation and genomic imprinting , 138. TrDNA methylation commonly co locates in organ fibrosis Table . To idenRasal1 and Klotho are uniquely methylated in renal fibrosis, where Rasal1 and Klotho have been revealed to play a role in fibroblast proliferation and ECM production . Under pSeveral genes are highlighted explicitly in liver fibrosis, such as PTEN and PPARγ. PTEN hypermethylation mediated by DNMT1 caused the diminution of PTEN expression, followed by the activation of the PI3K/AKT and ERK pathways, blocking cell proliferation and ECM gene expression in activated HSCs . DescribIn pulmonary fibrosis, the roles of COX-2 and thy-1 in epigenetic regulation have already been established –156. TheFriend leukemia integration 1 (FLI1) has already been identified as an antifibrotic gene hypermethylated in SSc fibroblasts. The FLI1 proximal promoter region can be methylated and bind to MeCP2, which then recruits HDAC to the promoter . MeCP2 wIn recent years, with the help of technological advances in identifying DNA hypermethylation, other common targets of fibrosis have been detected; for example, hypermethylation in the promoter region of tuberous sclerosis complexes 1 and 2 (TSC1 and TSC2) , bone moAlthough most experiments have focused on hypermethylation in the promoter region in fibrosis, global DNA methylation analysis has also found that some profibrotic gene promoters are hypomethylated, resulting in increased gene expression. In these specific studies, the expression of DNMTs is controversial. The reason for the discrepant findings is still unclear but may be related to the different cell types or experimental conditions used , 175. HoNoncoding RNAs, which are transcribed from DNA but are not translated into proteins, are related to epigenetics and can be grouped in three categories: short ncRNAs, long ncRNAs and circular ncRNAs.MicroRNAs (miRNAs) are short noncoding RNAs of ~ 22 nucleotides that mediate gene silencing by guiding argonaute (AGO) proteins to target sites in the 3’ untranslated regions (UTRs) of mRNAs . miRNA-lHistone modifications have been revealed to play a role in the downregulation of miR-133a expression in cardiac fibrosis since HDAC1 and HDAC2 are present in the miR-133a enhancer regions . DNA metLong noncoding RNAs (lncRNAs) refer to RNA transcripts with a length > 200 nt that do not encode proteins . LncRNAsMost lncRNAs play roles in fibrosis through miRNAs as ceRNAs in posttranslational regulation, while others regulate chromatin structure, nuclear translocation, and the binding of transcription factors at the transcription level  , 203, vaDNMT inhibitors are types of epigenetic therapy that have been under development for a long period of time. The most commonly used interventions in preclinical studies of fibrosis mainly include 5-aza-2'-deoxycytidine and 5-aza , 209. ThIn recent years, research on miRNA therapies has emerged . PotentiHowever, none of the interventions mentioned above have been applied for any fibrotic disease in clinical trials due to their limitations in two aspects: the uncertainty of the therapeutic effect of epigenetic therapies in fibrotic diseases and possible adverse effects. The preclinical research of epigenetics in fibrotic diseases is relatively immature compared with that in oncology. Studies evaluating the therapeutic effect are far from sufficient. Different results may be found in studies of different fibrosis models, different stages of fibrosis, and different dosages of drugs. Thus, further studies of the complex apparent regulatory network are necessary. Only after fully understanding each pathway can the effectiveness of its therapeutic targets be determined. Another problem involves the adverse effects of epigenetic interventions. The currently available epigenetic therapies do not target a specific gene or cell type, which may induce unexpected results. Therefore, specific delivery systems and CRISPR technology may provide solutions with higher specificity.In past decades, studies have revealed the vital role epigenetic regulation plays in organ fibrosis . With thThe epigenomics project is already in full swing. The mapping of detailed human DNA methylomes, histone modification, and nucleosome positioning maps in healthy and diseased tissues facilitates both basic research and the clinical application of epigenetics in fibrotic diseases. Ultimately, the transformation from biological to clinical research will enable epigenetic regulation to achieve greater value in predicting, diagnosing, and treating fibrotic diseases.Additional file 1: Table S1. lncRNAs involved in fibrosis of different organs.


Nuclear lipid metabolism and metabolites play important roles in regulation of lipid–lipid, lipid–gene, lipid–chromatin, lipid–membrane and lipid–protein interactions to maintain the nuclear microenvironment, three‐dimensional chromatin architecture, gene expression and transcription and biological function. This Editorial highlights the value of lipid–gene interaction in the identification and development of biomarkers and targets and emphasizes the significance of inter‐regulation between lipids and genes in innovation and application of precise therapies for patients. Regulatory functions of nuclear lipid dynamics and biophysics modify transcriptomic expression, and modification (lipotranscriptome) can be a new approach for discovery and development of disease‐specific diagnoses and therapies, although there are several challenges to be overcome. Better understanding of how lipid‐based changes of nuclear functions and transcriptomic profiles modify clinical phenomes will provide new insights to understand molecular mechanisms of diseases and to develop spatiotemporal molecular medicine diagnostics and therapeutics. The rapid development of methodologies allows us to provide new insights for monitoring the dynamics of lipid metabolism, associated gene transcription, specific protein activation and molecular network regulation. Lipid metabolism in diseases is an important part of clinical and translational medicine and has been selected as a thematic issue. Dysregulation of lipid metabolism contributes to mitochondrial injury and inter‐organelle dysrfunction,The interaction between lipids and genes within the nucleus influences functions of the genome without changing the nucleotide sequence (lipotranscriptome), as an epigenetic modification (epitranscriptome). Appropriate expression, transcription and translation of mRNA require proper quality and quantity of multiple factors and formulation of fluid dynamics within the nucleus to regulate and balance the interaction and binding between molecules. Specifically, the amount and function of lipids localized in nuclear membranes, nucleoli, nuclear matrix and chromatin contribute to the construction of inner nuclear membrane (INM) and the function of RNA–DNA activities.Lipid elements and metabolism regulate gene expression, DNA duplication and transcription directly by lipid binding to nuclear transcriptional proteins and receptors, and/or indirectly by modulating the intra‐nuclear microenvironment, membrane biophysics or other intra‐cellular mechanisms. In patterns distinct from those induced by inflammatory mediators and pathogens,Another mechanism by which lipids directly act with RNA is through lipid membrane binding with RNA through the G‐quadruplex formation and riboregulation of guanine residues in short RNAs, which are dependent upon RNA nucleotide content, base pairing and length.NLDs are important for lipid appearance, transformation, storage and function in the nuclei and contribute to the INM formation and the maintenance of nuclear homeostasis and microenvironment. Different from cytoplasmic lipid droplets responsible for structural and functional connection between intra‐cellular organelles, NLDs separate the nuclei from other organelles to segregate nuclear energy and function, although molecular mechanisms of NLD formation and origination vary among cell types.Advances in the understanding of the clinical and translational medicine roles of gene‐lipid interaction require further definition of the biochemical structures and stability of small lipid elements and metabolites during biological processes and in response to microenvironmental perturbations. It will be important to define the binding sites of lipid elements to nucleosomes or chromatins, for example, molecular size and structure, affinitive specificity, regulators and function‐dependent biophysics, so as to advance the discovery and development of new therapies. It will be important to clarify whether lipid‐chromatin interactions‐associated processes and participants are measurable and are disease phenome‐specific. It is still unclear if transcriptional factors and regulators involving cytoplasmic lipid metabolism, lipid droplet formation and organelle membrane biophysics have a role in the structural and functional dynamics of NLDs. There is an urgent need to characterize direct and indirect effects of NLDs in gene expression and transcription, biological associations between nuclear and cytoplasmic lipid metabolism and droplet biochemical properties and intercommunication between nuclear and cytoplasmic lipid microenvironments. Advances will require technical advances to develop simple and repeatable methods that are sufficiently sensitive to dynamically monitor changes of nuclear lipid contents, precise enough to spatiotemporally track the heterogeneity of the lipid atlas within nuclei and between nuclei and cytoplasm and sophisticated enough to define the interaction and links between nuclear lipidomics and transcriptomics. To translate nuclear lipid systems biology and lipotranscriptomics research into clinical practice, it will be important to better understand the relationship of nuclear lipid structure and function with disease classification, stages, phases, phenomes, responses to interventions and prognoses.In conclusion, nuclear lipid metabolism and metabolites play important roles in regulation of lipid–lipid, lipid–gene, lipid–chromatin, lipid‐membrane and lipid‐protein interactions to maintain the nuclear microenvironment, three‐dimensional chromatin architecture, gene expression and transcription and biological function. Regulatory functions of nuclear lipid dynamics and biophysics modify transcriptomic expression, and modification (lipotranscriptome) can be a new approach for discovery and development of disease‐specific diagnoses and therapies, although there are several challenges to be overcome. Better understanding of how lipid‐based changes of nuclear functions and transcriptomic profiles modify clinical phenomes will provide new insights to understand molecular mechanisms of diseases and to develop spatiotemporal molecular medicine diagnostics and therapeutics.The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.


Long non-coding RNAs (lncRNAs) exert central pathophysiological roles through the regulation of gene expression both at transcriptional and post-transcriptional levels. The characterization of lncRNAs’ interactome is disclosing several new mechanisms that control disease onset and progression thus opening the way to the development of new pioneering therapeutic approaches. Regarding the lncRNA HOTAIR, found upregulated in several cancers and in liver fibrosis, it has been proved as a potential therapeutic target. HOTAIR acts as a ceRNA for several miRNAs and it directly interacts with chromatin remodelling complexes (e.g. PRC2 and LSD1/NuRD complexes). In this regard, we recently reported the transcription factor SNAIL-mediated recruitment of HOTAIR/PRC2 complex on specific chromatin sites causing epithelial genes’ repression through epigenetic chromatin modifications. Conversely, HOTAIR is repressed by the liver-enriched transcriptional factor HNF4a that binds to both HOTAIR promoter and distant enhancer and impairs the formation of a chromatin loop between these genomic regions.In a therapeutic perspective, we design and validated the first example of a dominant negative lncRNA molecule (HOTAIR-sbid) that covers the HOTAIR portion involved in the interaction with SNAIL while is devoid of the domain of interaction with EZH2. Functionally, HOTAIR-sbid expression impairs SNAIL/EZH2/endogenous HOTAIR interaction; thus, PRC2 complex is not recruited on SNAIL-target chromatin sites . Accordingly, the cells rescue an epithelial phenotype, reduce EMT and, in turn, migratory, invasive and anchorage independent growth abilities. This approach promises high level of specificity and limited off-target effects. Future investigations should enhance RNAs’ stability and should design strategies for the delivery of these molecules to specific target cells. Long non-coding RNAs (lncRNAs), an important class of RNAs more than 200 nucleotides long, that acquired attention only in the last decades due to their subtle phenotype, are now recognized to exert central pathophysiological roles. The efforts in highlighting their functions, structures and interactors  and in the development of experimental approaches to detect these interactomes, revealed their pivotal role in regulating gene expression both at transcriptional and post transcriptional level. In particular this apply to lncRNAs involved in several tumours’ onset and dissemination where a remarking contribution of basic and applied research now opens the way to the development of new pioneering therapeutic approaches.The lncRNA Hox Antisense Intergenic RNA (HOTAIR) represents one of the most studied and characterized lncRNAs; it is encoded within the Homeobox C (HOXC) locus and is found upregulated in several cancers , 2, in CIn parallel, HOTAIR was found to directly interact with chromatin remodelling complexes like Polycomb repressive complex 2 (PRC2) and the LSD1/NuRD complex . In thisConversely, the liver-enriched transcriptional factor HNF4a, in order to drive hepatocyte differentiation and promote mesenchymal to epithelial transition (MET), negatively regulates HOTAIR expression through its binding to both HOTAIR promoter and distant enhancer. This in turn impairs the formation of a chromatin loop between these genomic regions that promotes HOTAIR transcription .In a therapeutic perspective, accumulating evidence revealed that ncRNAs are potential druggable targets, due to their functions and structure. In this frame, the majority of the reports evaluated the effect of lncRNA knockdown in preventing disease onset and progression, including cancer. The most recognized and shared approach is based on the use of shRNAs that induce a downregulation of lncRNA expression by RNA interference. This strategy allows a general silencing of the lncRNA but does not selectively target specific functions. Differently, we recently reported the first example of a dominant negative RNA molecule that competes with the endogenous HOTAIR lncRNA in a specific function. This molecule, named HOTAIR-sbid (for Snail-binding domain), covers the HOTAIR portion involved in the interaction with SNAIL while is devoid of the domain of interaction with EZH2. Molecularly, HOTAIR-sbid was shown to impair SNAIL/EZH2 interaction and the SNAIL binding to the endogenous HOTAIR. Therefore, PRC2 complex is not recruited on SNAIL/HOTAIR target sites and SNAIL/HOTAIR-dependent epigenetic transcriptional repression of epithelial genes  is impeded. Functionally, this dominant negative-based strategy, reflects on the rescue of an epithelial phenotype, with reduction of migratory, invasive and anchorage-independent growth in HCC cells and notably prevents TGFβ-induced EMT in hepatocytes . These r


Yersinia, to subvert host defenses. However, because the T3SS is energetically costly and immunogenic, it must be tightly regulated in response to environmental cues to enable survival in the host. Here we show that expression of the Yersinia Ysc T3SS master regulator, LcrF, is orchestrated by the opposing activities of the repressive H-NS/YmoA histone-like protein complex and induction by the iron and oxygen-regulated IscR transcription factor. While deletion of iscR or ymoA has been shown to decrease and increase LcrF expression and type III secretion, respectively, the role of H-NS in this system has not been definitively established because hns is an essential gene in Yersinia. Using CRISPRi knockdown of hns, we show that hns depletion causes derepression of lcrF. Furthermore, we find that while YmoA is dispensable for H-NS binding to the lcrF promoter, YmoA binding to H-NS is important for H-NS repressive activity. We bioinformatically identified three H-NS binding regions within the lcrF promoter and demonstrate binding of H-NS to these sites in vivo using chromatin immunoprecipitation. Using promoter truncation and binding site mutation analysis, we show that two of these H-NS binding regions are important for H-NS/YmoA-mediated repression of the lcrF promoter. Surprisingly, we find that IscR is dispensable for lcrF transcription in the absence of H-NS/YmoA. Indeed, IscR-dependent regulation of LcrF and type III secretion in response to changes in oxygen, such as those Yersinia is predicted to experience during host infection, only occurs in the presence of an H-NS/YmoA complex. These data suggest that, in the presence of host tissue cues that drive sufficient IscR expression, IscR can act as a roadblock to H-NS/YmoA-dependent repression of RNA polymerase at the lcrF promoter to turn on T3SS expression.The type III secretion system (T3SS) is an appendage used by many bacterial pathogens, such as pathogenic  Yersinia pestis and the closely related enteropathogen Yersinia pseudotuberculosis. H-NS is a histone-like protein suggested to repress horizontally-transferred virulence genes. Here we show that in Y. pseudotuberculosis, H-NS and its binding partner YmoA facilitate oxygen-dependent regulation of the Ysc T3SS by the transcription factor IscR. As oxygen availability is low in the intestine where the T3SS is not required for Yersinia colonization, and higher in extraintestinal tissue where the T3SS is critical for virulence, these data suggest that the Ysc T3SS was integrated into the pre-existing H-NS and IscR regulatory networks to optimize bacterial pathogenesis.In facultative pathogens, horizontally-acquired virulence factors must be integrated into existing regulatory networks that respond to environmental cues. The Ysc type III secretion system (T3SS) is encoded on a virulence plasmid carried by the plague agent  Yersinia pseudotuberculosis is one of three human pathogenic Yersinia spp. that use the T3SS to inject effector proteins into host cells that dampen host immune responses, facilitating extracellular growth  cluster, and cluster-less apo-IscR  cells were harvested for each replicate and cell pellets were stored at −80°C. DNA was fragmented by resuspending samples using IP buffer  and sonicated at 25% Amplitude 15s on/59s off for a total of 8 cycles per sample. After sonication, lysates were treated with micrococcal nuclease and RNase-A for 1hr at 4°C. Lysates were clarified via centrifugation at 13,000 rpm for 15 min at 4°C. Lysates were pre-cleared using Dynabeads Protein A/G for 3hr at 4°C. Immunoprecipitation was performed by adding Sigma monoclonal mouse anti-FLAG M2 antibody to samples and incubated overnight at 4°C. Dynabeads Protein A/G were added to samples and washes were performed to remove non-specific binding. After H-NS-DNA or IscR-DNA complexes were eluted, samples were placed at 65°C for 5 hr to reverse crosslinks. DNA was then purified using Qiagen PCR purification kit and input samples were diluted 1:100 while samples treated with antibody or control samples not treated with the antibody were diluted 1:5 and qPCR was performed to assess IscR/H-NS binding to promoters of interest. Percent input was calculated by the following equation: 100*2^(CTinput—CT+AB).Cells were grown for 3 hrs at 26°C or 37°C with shaking at 250 rpm and protein/nucleic acids were crosslinked using 1% formaldehyde at 26°C or 37°C for 10 min. Crosslinking was quenched with the addition of ice cold 0.1 M glycine and incubated at 4°C for 30 min. 32 x 1[ODS1 Textsuf promoter is not influenced by temperature. Fig D in S1 Text. YmoA affects LcrF dependent type III secretion activity. Fig E in S1 Text. The YmoAD43N mutant protein is expressed. Fig F in S1 Text. IscR binding to the yscW-lcrF promoter is dispensable in the absence of ymoA. Table A in S1 Text. Strains used in this study. Table B in S1 Text. Y. pseudotuberculosis primers used in this study. Table C in S1 Text. Plasmids used in this study.Fig A in S1 Text. 3xFLAG tag allows for detection of H-NS using FLAG antibody and does not affect H-NS ability to repress LcrF. Fig B in S1 Text. IscR does not regulate YmoA or H-NS expression. Fig C in S1 Text. IscR enrichment at the (DOCX)Click here for additional data file.