S. cerevisiae, as a component of chimeric transcription factors. Its ligand, β-estradiol, permits to control the protein translocation into the nucleus and, as a consequence, the expression of the gene(s) targeted by the synthetic transcription factor. Activators that are orthogonal to the yeast genome have been realized by fusing the human estrogen receptor to an activation and a DNA-binding domain from bacteria, viruses, or higher eukaryotes. In this work, we optimized the working of a β-estradiol-sensing device—in terms of detection range and maximal output signal—where the human estrogen receptor is flanked by the bacterial protein LexA and either the strong VP64 (from herpes simplex virus) or the weaker B42 (from E. coli) activation domain. We enhanced the biosensor performance by thoroughly engineering both the chimeric activator and the reporter protein expression cassette. In particular, we constructed a synthetic promoter—where transcription is induced by the chimeric activators—based on the core sequence of the yeast CYC1 promoter, by tuning parameters such as the length of the 5′ UTR, the distance between adjacent LexA binding sites (operators), and the spacing between the whole operator region and the main promoter TATA box. We found a configuration that works both as a highly sensitive biosensor and a sharp switch depending on the concentration of the chimeric activator and the strength of its activation domain.The human estrogen receptor has been used for about thirty years, in the yeast  Its origin can be traced back to the first two synthetic gene circuits published in January 20003. Among the circuits that followed, biosensors became the object of many research works due to their numerous possible applications4. Biosensors have been engineered to respond to several different inputs, e.g., heavy metals6, metabolites7, organophosphates8 2,4-dinitrotoluene9, intracellular xylose10, and arsenic11.Synthetic Biology is a new branch of life science that aims at reengineering living cells such that they carry out new, precise functions12. In the Eighties of the last century, Ma and Ptashne13 realized a collection of yeast chimeric activators that combined either GAL4 or LexA DNA-binding domain (DBD) with one of 15 bacterial activation domains (ADs)—among which there was also B42 that we used in this work. The chimeric activator library was later extended with the inclusion of more bacterial ADs 14. In 1993, Louvion et al.12 engineered the first β-estradiol-inducible chimeric activator (later referred to as GEV) by merging GAL4 DBD with the hormone binding domain of the human estrogen receptor—HBD(hER), where β-estradiol binds—and the strong VP16 AD from the herpes simplex virus type 115. GEV permitted to activate any galactose-inducible promoter in glucose-containing media, where the growth of S. cerevisiae cells is faster. More recently, Mclsaac et al.16 turned GEV into Z3EV by replacing GAL4 DBD with the zinc finger protein Zif268 DBD. Ottoz et al.17, in contrast, modified GEV by using LexA as a DBD and tested four ADs, among which B112 was the most performant. Both works aimed at constructing a system for the control of gene expression in S. cerevisiae without interfering with the original molecular processes that take place in the cells. In Synthetic Biology, such a system is termed orthogonal to the host cell. Finally, Dossani et al.18 built a large library of hybrid promoters consisting of core yeast promoters preceded by a variable number of LexA binding site (operators). Each promoter was activated by LexA-HBD(hER)-VP16 at low (up to 100 nM) concentrations of β-estradiol.In yeast Synthetic Biology, the β-estradiol biosensor has been engineered in various configurations and used, mainly, as a tool to control the synthesis of endogenous and synthetic genes. β-estradiol diffuses through the yeast membrane and does not provoke, per se, toxic effects unless its concentration becomes much higher than 1000 nM19. They are transcription units (TUs), i.e., DNA sequences made of a promoter, a coding region, and a terminator. The receptor expresses constitutively a chimeric activator hosting HBD(hER). The reporter produces a fluorescent protein only in the presence of β-estradiol  and the maximal fluorescence reached by the circuit—which quantifies how strongly a gene can be expressed under β-estradiol induction. Basal fluorescence shall be as close as possible to zero, whereas the maximal fluorescence should equal or even overcome that of the strongest yeast constitutive promoter . In18, these two quantities are merged into a single one, the inducibility, that roughly corresponds to the ON/OFF ratio.Despite all the implementations mentioned above, a common way to characterize a β-estradiol biosensor has not been established yet. In20. The reporter shall host a reasonably weak core promoter preceded by a thoroughly engineered operator cassette. Here, several parameters shall be adjusted  to achieve a good trade-off between basal and maximal fluorescence level.In order to obtain both low basal fluorescence and high response from the same β-estradiol biosensor, its components shall be balanced carefully. In the receptor part, the strength of promoter and AD should be chosen to avoid the overexpression of the chimeric activator, which would likely cause toxicity effectsAs a sensing device, however, a β-estradiol biosensor should be also characterized by its sensitivity and tolerance to the input, which permit to define the detection range over which the biosensor works reliably. None of the β-estradiol biosensors in the literature was evaluated according to these parameters, as if its original function (detecting β-estradiol) had been forgotten. In this work, we propose a general way to assess the performance of a β-estradiol biosensor. This requires estimating: (1) the detectivity (D), i.e., the minimal β-estradiol concentration that is unequivocally detected by the biosensor; (2) the tolerance, i.e., the maximal concentration of β-estradiol at which the biosensor activity is not damaged by toxicity effects; (3) the detection range, which goes from D to T; and (4) the maximal output  level, which tells us if the biosensor can be used to enhance the expression of a target gene up to a desired level.17, we engineered deeply both receptor and reporter in order to find out criteria to optimize the working of the β-estradiol  biosensor(s). Like in17, also in our work the receptor includes the full LexA bacterial protein as a DBD. LexA binds, as a dimer, a 41-nt-long operator that is organized in two halves of 20 nt separated by a single base pair. Thus, the lex operator is usually referred to as lex2Op. We fused LexA to HBD(hER) and, separately, four different ADs. In the absence of β-estradiol, the heat shock protein 90 (Hsp90) sequesters the activator in the cytoplasm upon binding HBD(hER). In contrast, β-estradiol—when present in the cell culture—docks to HBD(hER) and prevents any further interactions with Hsp90, such that the activator translocates into the nucleus19  the constitutive promoter upstream of the activator; (2) the synthetic promoter upstream of the fluorescent protein; and (3) the AD at the C-terminus of the chimeric activator, which recruits RNA polymerase II to the activated promoter.CYC1 core promoter21, preceded by lex2Op sites in a variable number. On these strains, we constructed overall ten types of β-estradiol biosensors.We engineered, first, yeast strains for the expression of yEGFP (yeast enhanced green fluorescent protein). They contained different weak promoters, based on variants of the The initial configuration performed poorly by returning a low output signal in the presence of β-estradiol. We improved and, finally, optimized the biosensor design by making several changes on the promoter of the reporter part. We modified the number of lex2Op, their reciprocal distance, the distance between the complete operator cassette and the main TATA box, and the length of the 5′UTR. Moreover, we tested three constitutive promoters and four ADs of different strength on the receptor side, in order to tune the expression both of the chimeric activator and yEGFP.This work of deep engineering led us to formulate criteria to optimize the β-estradiol biosensor and convert it into a switch responding to the same hormone.22—and B42. The reporter expressed yEGFP upon activation of the synthetic promoter that combined a fragment of the core yeast constitutive CYC1 promoter and a variable quantity of lex2Op sites -AD, where AD was one among: VP16, VP64 , mDR521-805—from the mouse dioxin receptor proteinThere are various ways to evaluate how a biosensor works. Since it represents a YES (or buffer) Boolean gate, the most straightforward parameter would be the gain  or the signal separation . However, each biosensor configuration was characterized via a titration curve, i.e., the fluorescence output was measured for twelve concentrations of β-estradiol  and in the absence of the hormone. Therefore, other quantities appeared more significative: (1) the basal fluorescence, i.e., the fluorescence expressed in the absence of β-estradiol, which quantifies the biosensor leakage; (2) the detectivity (D), that corresponds to the minimal concentration of β-estradiol that is sensed by a biosensor, i.e., the smallest concentration of the input that induces an output signal at least twofold higher than the noise—where the noise is the highest between the background fluorescence  and the basal fluorescence, as defined previously. It should be noted, though, that the background fluorescence has been subtracted from all fluorescence values reported in this work such that, to determine D, we should look for the concentration of β-estradiol that induced an output signal either bigger than  52.45 A.U. or twice as high as the basal fluorescence; (3) the tolerance, which represents the maximal concentration of β-estradiol that is detected unambiguously before the occurrence of toxicity effects; (4) the detection range, which is the interval in the concentration of β-estradiol delimited by the detectivity and the tolerance; (5) the maximal fluorescence signal—which we used as a reference to quantify the effects on the biosensor due to changes in one (or more) of its elements.-52)-truncated_pCYC1min -AD and 7×lex2Op was removed and the 5′UTR shortened from 71 to 24 nt 24 corresponding to 2.44% of that of pCYC1min (and 0.43% of that of pGPD—see Table -52)-truncated_pCYC1min. The first number within the brackets indicates that adjacent lex2Op were separated by two nucleotides , whereas the second notation means that the whole operator cassette was placed 37 nt upstream of the TATA box starting at position -52 (TATA-52).Our initial target was a weak variant of the GPD promoter (pGPD) and tested four ADs: the strong V16, VP64, and mDR521-805 together with the weak B42 .We expressed the chimeric activator in high amount via the strong These initial configurations highlighted some interesting features see Fig. A. First,This first biosensors pointed out a general pattern: strong ADs cause high D  and low tolerance. In contrast, weak ADs determine a lower D and a higher tolerance.Overall, none of the four biosensors was able to detect 0.98 nM β-estradiol. Moreover, as already mentioned above, the highest fluorescence levels were rather modest.-52)-truncated_pCYC1min -VP64 and 7×lex2Op and the viral CMV promoter . We chose the synthetic promoter DEG1t_pCYC1noTATA (19.75% as strong as pGPD-52)-truncated_pCYC1min/core -B42 and 8×lex2Op-AD. They contained a cassette of eight lex2Op (separated by 2 nt—GT) that was followed by either pCYC1min (in two cases) or pCYC1core  at a lower β-estradiol concentration (500 nM) than that of the two pCYC1min-based biosensors . It should also be noted that the mean maximal fluorescence of byMM1378 turned out to be 5.55-fold higher than that of biosensor 1 byMM187  and 2.87-fold greater than that of biosensor 2 byMM198, corresponding to 50.64% of that of pGPD. Furthermore, both byMM1376 and byMM1378 showed a higher detectivity than that of byMM187 (31.25 nM), i.e., D = 7.81 nM and 15.62 nM, respectively.In order to increase the maximal fluorescence signal, we restored, in the reporter part, the full 5′UTR of the see Fig. C. Only osee Fig. C caption-52)_pCYC1core -VP64 and lex2Op and a low detectivity (D = 62.5 nM β-estradiol). By increasing the distance between lex2Op and TATA-52, the maximal fluorescence grew steadily: 5222.21 A.U. (10 nt); 8186.36 A.U. (37 nt); and 14,170.70 A.U.  contribution to the final fluorescence level. Interestingly, the detectivity improved with the distance as well. However, the best value (D = 7.81 nM β-estradiol) was reached already at 37 nt. The basal fluorescence was, in general, rather high. However, no specific relation with the lex2Op-TATA-52 distance could be found.It should be noted that, when lex2Op is 60 nt far from TATA-52)_ pCYC1core -AD and lex2Op_pCYC1core as a reporter part, we constructed two new circuits where the receptor TU consisted of configurations tried in previous experiments, namely pGPD-B42 and pCMV-VP64 . As reported in Fig. After selecting lex2Op(60-TATA-52)_ pCYC1core -VP64 and 2×lex2Op far upstream of TATA-52  of pCYC1core. They were spaced with 2, 15, and 42 nt. The receptor made use of the DEG1t_pCYC1noTATA-VP64 configuration. As shown in Fig. A way to further increase transcriptional activation demands to place several copies of the same operator upstream of the promoter TATA box-52)_ pCYC1core -VP64 and 3×lex2Op_pCYC1core employed in byMM482. The new device returned a maximal fluorescence  even 1.26-fold higher than that of pGPD and the overall broadest detection range (from 1.95 to 2000 nM β-estradiol). Only the basal fluorescence showed a rather high value (1010.08 A.U.), comparable to those of the circuits with only one or two lex2Op _ pCYC1core -VP64 and 3×lex2Op than the other two biosensors 6 (60 nt). Since 3×lex2Op permitted to achieve both a fluorescence level greater than that of pGPD and a high detectability, we decided to investigate if the performance of biosensor 7 could be further improved by varying the separation between two contiguous lex2Op. Thus, we built five more 3×lex2Op where two consecutive lex2Op were separated by 2, 6, 9, 21, and 42 nt with the overall cassette placed 60 nt upstream of TATA-52. Furthermore, for a comparison with biosensor 6 byMM1369, we constructed another biosensor where the three operators were separated by GT and the whole 3×lex2Op cassette lied 138 nt upstream of TATA-52 .Even though biosensor 7 turned out to work remarkably well, it was built on an approximative analysis of biosensors 6. We considered only three possible distances between the two lex2Op . Moreover, byMM1369 (2 nt) had a much longer distance from TATAAs for the basal fluorescence, there was no statistically significant difference among the 6, 15, and 21 nt configuration , whereas 9 nt expressed over 2200 A.U. of fluorescence in the absence of β-estradiol. Forty-two and two nt returned the highest (3934.32 A.U.) and the lowest (595.63 A.U.) value, respectively, whereas 2-GT expressed 1663.96 A.U. Compared to the 2×lex2Op configuration, the basal fluorescence increased in a statistically significant way only for 2-GT and 42 nt , whereas the increment in 15 nt was not significant  and 42 nt (98.33% at 125 nM). Higher basal fluorescence and lower maximal output made the titration curves of 2-GT and 42 nt (byMM1397) clearly different from that of biosensor 7 (byMM381), as apparent in Fig. By looking at the three biosensors containing 2×lex2Op, the addition of the third operator was beneficial both for the maximal fluorescence and the detectivity: 2-GT maximal fluorescence showed a 2.07-fold increase and D went from 250 to 7.81 nM β-estradiol. The improvements on 42 nt performance were even more evident: a 4.22-fold increment in the maximal fluorescence and D from 1000 to 7.81 nM β-estradiol. Less apparent were the improvements on the already highly efficient 15 nt: 1.30-fold augment in the maximal fluorescence and D from 7.81 to 1.95 nM β-estradiol. Therefore, despite causing an increase in basal fluorescence, a third lex2Op provided an overall advancement in the biosensors’ performance , otherwise their titration curves were basically equivalent. Two nt differed from the previous three configuration in four cases only: 0, 0.98, 1.95 and 31.25 nM β-estradiol. Nine nt reached a remarkable maximal output, corresponding to 120.83% of pGPD fluorescence, at only 250 nM β-estradiol. It should be noted, though, that the high error associated with 9 nt measurements made the fluorescence levels between 31.25 and 2000 nM β-estradiol undistinguishable in statistical terms . Finally, there was no significant difference among the five biosensors in the range 62.5–2000 nM (more than one third of the whole measurements), i.e., at the concentrations of β-estradiol where the highest fluorescence values were reported. Thus, the maximal fluorescence values of the five circuits turned out not to be significantly different in statistical terms . Furthermore, each configuration showed high detectability: 1.95  and 3.91 (6 nt) nM β-estradiol . When the distance between adjacent lex2Op was between 2 and 21 nt, every biosensor was characterized by a very broad detection range  and a mean maximal fluorescence value at least 1.20-fold higher than that produced by the strong GPD promoter. Therefore, our device can also be adopted to upregulate gene expression.Taken together, we realized a highly efficient β-estradiol biosensor via the combination of a receptor characterized by the synthetic promoter DEG1t_pCYC1noTATA and the VP64 AD together with a reporter containing a 3×lex2Op cassette 60 nt upstream of TATA-52)_pCYC1core -AD and 3×lex2Op_pCYC1core—and checked if it could lead to the construction of more performant biosensors where pGPD-B42 and pCMV-VP64 took in the receptor part the place of DEG1t_pCYC1noTATA-VP64. Previously, in biosensors 5, both configurations did not work very well by acting on a single lex2Op placed 60 nt upstream of TATA-52.After finding five efficient designs for the promoter in the reporter part, we chose the configuration in biosensor 7—3×lex2Op increased both the maximal fluorescence value (from 26.32 to 65.89% of pGPD one) and the detectivity (from 125 to 3.91 nM β-estradiol) of byMM371. However, it remained overall far from the performance of most of the biosensors 8. The results obtained with pGPD-B42 appeared more interesting. The new biosensor byMM367 had an extremely low basal fluorescence (11.32 A.U.) but needed 31.25 nM β-estradiol to overcome the background fluorescence, which limited its detection range. At 250 nM β-estradiol, byMM367 fluorescence level was comparable to that of byMM369, thus clearly lower (44.15%) that than of byMM381 but, then, increased sharply and reached a remarkable maximal value (122.17% of pGPD one) at 2000 nM β-estradiol  spoil the working of byMM367 with the appearance of toxicity, whereas they have no relevant effects on biosensors containing the configuration DEG1t_pCYC1noTATA-VP64 in the receptor and one up to three lex2Op in the reporter  between 0 and 2000 nM β-estradiol to turn OFF and ON effectively—without any problems for the cells—the expression of a target gene.29. Bi- or tripartite fusion proteins hosting the docking site for a small molecule permit, furthermore, to control the circuit working from the outside. HBD(hER) has allowed the construction of several chimeric transcription factors responding to β-estradiol, a hormone well-tolerated by the yeast S. cerevisiae. In this work, we focused on a set of synthetic activators where the bacterial LexA had the function of DBD and it was fused to HBD(hER) and an AD of viral, bacterial, or even mammalian origin. As previously mentioned, this chimeric protein is not new and several variants—together with their target promoters built ad hoc—have been adopted33. We constructed ten different types of β-estradiol biosensors in order to find an optimal configuration that combined a very high fluorescence expression (higher than that reached by the strong GPD promoter) and a broad detection range. To this aim, we had to assess different configurations of the receptor part (the constitutive promoter and the AD) and engineer target promoters in the reporter part. In our analysis, the best promoter, in the reporter, was made by the core CYC1 sequence (which keeps the three TATA boxes and the full 5′UTR) preceded by three lex2Op operators. Adjacent lex2Op shall be separated by 2 up to 21 nt and the 3×lex2Op cassette is placed 60 nt upstream of TATA-52. On the receptor side, we found two useful configurations. The best biosensor configuration demands to fuse LexA-HBD(hER) to the strong VP64 AD and express it under the synthetic constitutive DEG1t_pCYC1noTATA promoter. In this way, the maximal fluorescence level overcomes that of the GPD promoter (1.38-fold higher when 6 nt separate two lex2Op) and the detection range goes from 1.95 to 2000 nM . In contrast, by replacing VP64 with B42 and DEG1t_pCYC1noTATA with pGPD, we obtain a perfect switch that expresses, at 2000 nM β-estradiol, more fluorescence than pGPD and shows a negligible leakage in the absence of β-estradiol.Chimeric proteins made of domains that are not expressed in yeast are likely to be orthogonal to the yeast genome and, therefore, represent good candidates for wiring the TUs present in a synthetic circuit.17, our main reference, we can see that our promoter leads to a stronger gene expression with a lower number of lex2Op (three instead of eight). Hence, we might achieve a further enhancement in gene expression by adding more lex2Op. The core promoter in17 was a minimal version of pCYC1 that retained a single TATA box starting at position -46 with respect to the TSS (not at -52 because TATA-22 was deleted) and had a long 5′UTR (77 nt of which the last 41 nt came from the plasmid MCS—multiple cloning sequence). The distance between two adjacent lex2Op was 6 nt , whereas the lex2Op cassette lied only 22 nt upstream of TATA-46, i.e., much less than in our target promoter. On the receptor side, Ottoz et al. obtained their best results by using B112 AD and the pACT1 promoter. When using VP16, they reported toxicity effects between 8 and 31 nM β-estradiol. Interestingly, our optimized biosensors did not show any toxicity despite the fact that VP64 was expressed under DEG1t_pCYC1noTATA that is 1.37-fold stronger than pACT1. This seems to point out that toxicity is not caused only by the kind and the amount of the ADs expressed in the cells. Strong ADs in high concentration are, indeed, supposed to prevent the synthesis of vital genes—and lead to cell death—by reducing the availability of RNA polymerase II molecules20. However, different chimeric activators that are made of dCas9:gRNA (guide RNA) or dCas12a:crRNA (CRISPR RNA) fused to VP64 or the stronger VPR have been expressed in S. cerevisiae under pGPD without inducing any toxicity effects27. Therefore, we think that we still have to fully understand what causes toxicity, in yeast cells, in the presence of β-estradiol and LexA-HBD(hER)-AD. Only this knowledge will permit us to include, in a safe and reliable way, this system inside more complex synthetic gene networks that respond to a combination of multiple inputs.By comparing our results to those by Ottoz et al34). Every plasmid, which hosted a different transcription unit, was assembled with the Gibson method35. To this aim, the integrative backbone was cut-open (5 µg in a 30 µl solution) with the restriction endonucleases Acc65I (NEB-R0599S) and SacI (NEB-R0156S) to remove the MCS. At the end of the digestion, the two enzymes were heat-inactivated (20 min. at 65 °C). Every biological part  was amplified from their original plasmid via touchdown PCR36 that was carried out by using Q5 Hot Start high-fidelity DNA polymerase (NEB-M0493S). Primers were designed to guarantee a 40-nt-overlap between adjacent DNA sequences  were transformed with the plasmids that resulted from the Gibson assembly via a thermal shock (30 s at 42 °C)36. All plasmids were sequenced at Genewiz Inc., Suzhou (China), to check the correctness of the DNA sequences corresponding to the different TUs.The plasmids realized in this study —EUROSCARF 10000M, Johann Wolfgang Goethe University, Frankfurt, Germany. Genomic integration was carried out according to the lithium-acetate protocol, as described in37, and required to linearize 5 µg of plasmid DNA with either the enzyme StuI (NEB-R0187V), to cut inside the URA3 marker, or BstEII (NEB-R0162S), to cleave the LEU2 marker. Transformed cells were grown for two days at 30 °C on plates  containing a synthetic defined selective medium: SD-URA or SD-LEU. All yeast strains engineered in this work are listed in Table Our plasmids were integrated into the genome of the yeast 38. The standard deviation was determined through the error propagation formula.RNA extraction and purification from yeast cells  were carried via the YeaStar RNA kit (Zymo Research-R1002). cDNA was synthesized via the HiFiScript cDNA Synthesis Kit (CWBIO-CW2569M). The primers used to amplify a portion of LexA, Hsp90, and the reference ACT1 transcript are reported in Table Yeast strains (byMM2 and byMM367) were grown in complete synthetic defined medium (SDC) at 30 °C and 240 RPM for 14 h. Cell concentration (OD600) was then measured such that cell solutions could be diluted to OD600 ~ 0.2 in 30 mL SDC. Yeast cells were grown for 20 h, and OD600 was measured every 2 h with an Eppendorf BioPhotometer device.Yeast cells were grown, first, for 14 h at 30 °C and 240 RPM in SDC. Cells were then 1:100 diluted in 2 ml SDC supplemented with varying concentrations of β-estradiol . They grew for 20 h at the same conditions described above. Before the FACS experiment, cells were 1:20 diluted (in SDC). To measure fluorescence intensity, we used a BD FACSVerse . The FACS machine set-up was checked via the QC  program using fluorescent beads (BD FACS uiteTM CS&T Research Beads—17495). Every yeast strain was measured three times in different days. During each experiment, 10,000 events were collected.39. The mean background fluorescence, measured on the chassis strain (byMM2) that does not contain any fluorescence source, was subtracted from the fluorescence intensity associated with each engineered strain.The flowcore R-Bioconductor package was used to analyze the data from BD FACSVerseSupplementary Information.


Sonic hedgehog (Shh) is essential for limb development, and the mechanisms that govern the propagation and maintenance of its expression has been well studied; however, the mechanisms that govern the initiation of Shh expression are incomplete. Here we report that ETV2 initiates Shh expression by changing the chromatin status of the developmental limb enhancer, ZRS. Etv2 expression precedes Shh in limb buds, and Etv2 inactivation prevents the opening of limb chromatin, including the ZRS, resulting in an absence of Shh expression. Etv2 overexpression in limb buds causes nucleosomal displacement at the ZRS, ectopic Shh expression, and polydactyly. Areas of nucleosome displacement coincide with ETS binding site clusters. ETV2 also functions as a transcriptional activator of ZRS and is antagonized by ETV4/5 repressors. Known human polydactyl mutations introduce novel ETV2 binding sites in the ZRS, suggesting that ETV2 dosage regulates ZRS activation. These studies identify ETV2 as a pioneer transcription factor (TF) regulating the onset of Shh expression, having both a chromatin regulatory role and a transcriptional activation role. The embryonic limb bud is known to be patterned by a Shh morphogen gradient, though how Shh expression is activated remains less clear. Here the authors show that Etv2 acts as a pioneer transcription factor to mediate accessibility of the ZRS enhancer and initiate Shh expression. A limited number of transcription factors (TFs), known as pioneer factors, possess the ability to open closed chromatin and allow subsequent TFs to bind the opened chromatin, initiate gene expression and specify fate decisions3. The mechanism of chromatin modification appears to vary from TF to TF4. Pioneer TFs, represented by FOXA1, ASCL1, SOX2, OCT3/4, and KLF4, target closed nucleosomal DNA and can induce a local opening of chromatin, establishing a permissive state for transcription4. Other TFs such as c-MYC, MYT1L, and SCL do not bind closed chromatin, but modify open chromatin, allowing downstream TFs to bind the DNA and activate transcription3. The majority of classically-defined TFs, such as those identified by reporter gene assays, do not have chromatin modification capabilities and function by binding to chromatin domains that were made available by the chromatin-modifying TFs5.Regulation of chromatin structure constitutes a critical aspect of gene regulation. “Closed” or silent chromatin is occupied by nucleosomes and are inaccessible to most transcriptional activators, whereas “open” or active chromatin can be recognized by a cohort of transcriptional activators and is responsive to transcriptional activation cues7. More recently, this system has been used to enhance our understanding of epigenetic mechanisms, changes in chromatin structure, and non-coding regulatory sequences that control cell type-specific gene expression in developing embryos11. Sonic Hedgehog (SHH) is expressed in the posterior margin of developing limb buds, called the zone of polarizing activity (ZPA), and regulates anterior-posterior patterning and proliferative expansion of chondrogenic progenitor cells in the limb13. Ablation of the Shh gene results in loss of distal-posterior skeletal elements including the posterior four digits in the mouse14, and ectopic expression of Shh in the anterior limb bud causes formation of extra anterior digits (see 12 for review). Localized expression of Shh in the limb bud can be divided into three phases: initiation, maintenance/expansion, and termination. During the initiation phase, Shh expression is induced in a limited cell population located at the posterior margin of limb buds  9.75 and E10.25 in forelimb and hindlimb buds, respectively)15. SHH induces nascent limb bud cells to form polarized progenitor pools as a ZPA signal12. Shh expressing cells contribute to the distal posterior skeletal elements of the limb, including the two posterior digits16. During limb outgrowth, the Shh expression domain expands in the distal posterior region as its expression level peaks at E11.5 (the maintenance phase) and extinguishes by E12.5 (the termination phase).Limb development has been used as an experimental paradigm to decipher fundamental developmental principles that govern morphogenesisShh expression is regulated by a 1.7 kb cis-regulatory module, termed the ZPA regulatory sequence (ZRS) located approximately 0.85 Mbp upstream from the Shh transcription start site20. Targeted deletion of the ZRS in the mouse results in a failure to express Shh in the limb bud and disrupts the formation of the distal-posterior skeletal elements of the limb21. Multiple polydactyl mutations in human and other animals have been mapped within the ZRS region, underscoring the importance of the ZRS in Shh expression and limb morphogenesis22.Limb bud-specific Shh expression26. ETS/ETV family TFs also act through the ZRS to regulate Shh expression at E11.5, during the maintenance/expansion phase of Shh expression28. These studies suggested ETS1 and GABPa as the activating members of the ZRS. Furthermore, ETV4, an ETS family repressor, was shown to negatively regulate transcription through the ZRS. Prior to Shh expression, fibroblast growth factor (FGF) signaling from the distal limb primes the ZRS to a poised but inactive state in cells across the distal limb mesenchyme. ETV4, a repressor ETS protein induced by FGF8, prevents Shh expression in the anterior limb bud by recruiting the histone deacetylase HDAC2, while GABPa, an activator ETS protein, activates Shh expression in the posterior limb bud by recruiting the histone acetyltransferase p300. This antagonism of TFs was proposed as a mechanism to limit Shh expression to the posterior limb mesenchyme30. Although these studies highlight our current understanding of Shh regulation, these findings are limited to the maintenance and expansion phases of Shh expression, and our knowledge regarding the mechanisms that initiate Shh expression in limb buds remains incomplete31.Studies over the last two decades have identified positive and negative regulators of the ZRS. HAND2 and HOXD13 proteins directly bind to the ZRS and activate 36. Etv2-mutant embryos are lethal by E9.5 due to an absence of endothelial and hematopoietic lineages. As Etv2 mutants do not survive until the limb development stages, the role of ETV2 in limb development has not been previously described38. In the present study, we demonstrate that Etv2 expression precedes that of Shh expression and that ETV2 and SHH are coexpressed in the developing limb bud. We provide evidence using overexpression and loss-of-function strategies to demonstrate that ETV2 binds the ZRS in vivo, relaxes the chromatin and promotes transcriptional regulation of Shh expression. Further, using ATAC-seq analysis, we determined that ETV2 regulates the chromatin landscape globally in the limb bud and acts as a pioneer factor during limb development. We also show that ETV2 acts as a transcriptional activator through the ZRS region and is antagonized by ETV4 and ETV5 transcriptional repressors. Our data places Etv2 as an upstream regulator of Shh expression and a pioneer TF that globally regulates chromatin landscape during limb development.ETV2 (ETS variant 2) is a member of the ETS/ETV family. Studies from our laboratory and others have demonstrated that ETV2 is a master regulator of the hematoendothelial lineagesEtv2 is a critical regulator of hematoendothelial lineages34. To evaluate whether Etv2 is expressed during later organogenesis of an embryo, we pursued a lineage tracing strategy. We engineered a mouse line with a tamoxifen-inducible Cre under the control of the 3.9 kb-Etv2 promoter (Etv2-CreERT2) crossed to the Rosa26-ZsGreen reporter line  and E10.0 (29 somites) embryos  than the rapidly-degraded mRNAs, EYFP can be used as a short-term lineage tracer to detect the population of cells that expressed Etv2 in a limited time frame. Close examination of the forelimb buds of these embryos revealed the presence of the EYFP signal at the posterior margin of the limb buds, confirming that the 3.9 kb hemato-endothelial enhancer/promoter of Etv2 also regulated Etv2 expression in the limb bud and that Etv2-expressing cells contributed to the posterior population of the limb buds ; and a non-endothelial population that was found only in the ventro-posterior region of the limb bud . Etv2-EYFP+ cells did not co-express desmin (DES), a myotome marker  embryos. At E10.5, Etv2CKO and control heterozygous embryos were obtained at a Mendelian ratio . Etv2CKO embryos demonstrated a severe reduction of hindlimb size and loss of Shh expression in the developing limb buds, while rostral development of the embryos appeared normal  to assess proliferation, and apoptosis was examined using the TUNEL assay. The number of pHH3 positive cells started to decline in Etv2CKO limb buds at E10.25 and was severely reduced by E10.5  was utilized to examine the global chromatin accessibility in limb bud cells  and another that lacked Etv2 expression (unsorted E10.5 Etv2CKO hindlimb cells) 44. Of these regions, 5,178 regions were evolutionarily conserved (average phastCons score > 0.8); these regions were ranked according to the fold change in ATAC-seq signal  Fig. . We idennal Fig.  and 873 Shh expression), cells from Shh-EGFP E10.5 anterior hindlimbs , EGFP+ cells from Shh-EGFP E10.5 posterior hindlimbs , and EYFP+ cells from Etv2-EYFP transgenic E10.5 hindlimbs and forelimbs  were collected and processed for ATAC-seq. Posterior cells from Etv2CKO hindlimbs at E10.25 and E10.5  and posterior cells from E10.25 wild-type hindlimbs  were also included. ChromVAR was utilized to investigate the chromatin accessibility of TF binding sites in the genomic intervals identified above44. ChromVAR used the deviation scores to represent the relative abundance of TF-associated ATAC-seq reads in each sample and the TF activity. The Principal Component Analysis (PCA) was performed on the TF deviation scores to investigate the global TF activity of each sample  and non-expressing populations (Etv2CKO and E9.5 hindlimb)  Fig. . These rp-value < 1e-5) across these samples, we found that the binding motifs of known limb development-related TFs such as LHX1/2, ISL1, and MYF5 showed higher deviation scores (indicating increased chromatin accessibility) in the Etv2-EYFP+ samples (E10.5 forelimb EYFP+ and E10.5 hindlimb EYFP+), whereas the binding motifs for HOX and GATA factors showed higher deviation scores in the Etv2− populations (E9.5 hindlimb and Etv2CKO). Thus, the chromVAR analysis revealed distinct differences in the accessibility of specific TF binding sites in the presence or absence of ETV2. Notably, E9.5 hindlimb, E10.25 and E10.5 Etv2CKO samples shared similar TF associated chromatin accessibility patterns, suggesting that Etv2CKO limb bud cells maintained the chromatin structure of an early developmental stage in the absence of Etv2 (see the clustering results shown at the top of panel C).Taking a closer look at 122 TFs that showed significantly different deviation scores  in the Shh-EGFP+ cells in the posterior part of the E10.5 hindlimb (E10.5 Posterior), E10.5 hindlimb Etv2-EYFP+ cells (E10.5 HL EYFP+), and E10.5 forelimb Etv2-EYFP+ cells (E10.5 FL EYFP+), where Etv2 was expressed  were split into four groups according to their chromatin accessibility in E9.5 HL, which does not express Etv2, and E10.5 posterior, which expresses Etv2, respectively , compared with the group of ETV2 motifs that are closed in both conditions (group 00) (25.5% vs. 12.5% for Limb-Enhancer Genie and 2.1% vs. 1.4% for p300 ChIP-seq), suggesting that the relaxation of chromatin accessibility at limb enhancers was globally correlated with relaxation of ETV2 binding sites.The observation of the correlation of the chromatin relaxation and expression of ely Fig. . We founely Fig. . Moreove27. Primer sets that amplify the regions outside of the ZRS (region a) and inside the ZRS (regions b-d) were used for PCR  assay. Within the ZRS region, five putative ETS binding sites having a core sequence of AGGAA(G/A)T and two putative ETV binding sites having a core sequence of AGAAA have previously been defined as ETS#1-5, ETVA and ETVB . Using this system, Etv2 was induced in the HoxB6 lineage by two injections of doxycycline at E9.5 and E10.5. Whole-mount analysis of E11.5 Etv2OE embryos  showed expression of EGFP in areas consistent with the reported HoxB6-Cre activity41 . The nucleosomes outside of the ZRS were not displaced, indicating that the nucleosome-displacing effect was specific to the ZRS (see the non-boxed region in the Anterior OE vs. WT track). Furthermore, the Lmbr1 gene promoter, which was examined as a control, did not show displacement of chromatin . In conclusion, these results demonstrated specific increase of chromatin accessibility at the ZRS when ETV2 is overexpressed.The results of ATAC-seq analysis were verified by quantitative PCR using the primers corresponding to regions a-d indicated in Fig. tv2 Fig. , and thehttps://github.com/gongx030/seatac)50, to compare the 640-bp-width V-plots of 41,656 ETV2 motif-centric regions between WT and Etv2OE samples and identified 430 regions that had significantly increased chromatin accessibility from WT to Etv2OE over the ETV2 motifs 48. The V-plot is a dot-plot showing how sequencing reads with different fragment sizes distribute surrounding one or a set of genomic region(s). The SeATAC uses a VAE  to learn the latent representation of ATAC-seq V-plots using a CNN  based encoder and a devolution decoder. The aggregated V-plots of these 430 regions showed an increased chromatin accessibility of ETV2 centric regions in Etv2OE compared with WT  that activate Shh30. Using this reporter assay system, we tested whether ETV2 can be the postulated activating factor, which is antagonized by ETV4 and ETV5. ETV4 and ETV5 did not activate or suppress the ZRS by themselves but were able to suppress the ETV2-dependent reporter activation in a dose dependent fashion  and in vivo (ChIP) assays. The V-plot analysis of ETV2 motif centric regions in WT and Etv2OE samples showed that inducing Etv2 increased the chromatin accessibility at the ETV2 sites, which is consistent with the notion that the effect of ETV2 is not limited to ZRS but is global.Our first discovery defined a mechanism of ETV2 function as a pioneer factor to regulate the chromatin landscape in limb development. We demonstrated by multiple genetic and biochemical assays that ETV2 recognizes and relaxes the closed chromatin structures globally and promotes the downstream limb development program. Using ZRS as a representative ETV2 target, we demonstrated that chromatin relaxation correlated with the ETV2 dosage. In normal development, the chromatin of ZRS was completely closed at E9.5 but became widely accessible in the cells from posterior domain of the hindlimb at E10.5. The anterior portion remained closed at E10.5. The switching of ZRS chromatin state in the posterior domain occurred around E10.25, which showed intermediate accessibility between E9.5 and E10.5 posterior hindlimbs. In the These results strongly suggested the role of ETV2 as a global chromatin regulator in limb development, ZRS being one of the targets. Open chromatin was associated with ETV2 expression and loss-of-function of ETV2 resulted in closed chromatin, while overexpression of ETV2 enhanced accessibility. Collectively, these results supported our hypothesis that ETV2 functions as a pioneer factor at the ZRS.28. ETV2 may require such a poised state to modify the chromatin landscape at the ZRS. We also recognize the possibility that other factors may also have an epigenetic role in the regulation of the ZRS and Shh expression in the developing limb and it will be further examined in future experiments. HOXD13, which was shown to have a pioneer function is one of these candidates52. Our in vitro studies did not support that ETV2 physically interacts with HOXD13 or HAND2. The interrelationship of ETV2 with other TFs that have pioneer function or transcriptional activation function warrants future research. ETV2’s role in other mesodermal lineages  is intriguing in light of its ability to alter chromatin accessibility. It has been shown that ETV2 alone, or in combination with other factors is able to reprogram fibroblasts, skeletal muscle, and amniotic cells to the endothelial lineage57. Such master regulatory role suggests that ETV2 may be able to relax completely closed chromatins at the relevant target loci.Whether ETV2 can open the chromatin from a completely inaccessible state remains to be investigated. Recent analysis of histone modifications at the ZRS showed that FGF signaling in the distal limb bud primed the ZRS, maintaining a poised, but inactive state broadly across the distal limb mesenchymeShh expression. In addition to the chromatin-regulatory activity, ETV2 was able to bind to ZRS and activate transcription through ZRS in a reporter gene assay. The activity of ETV2 was antagonized by negative TFs ETV4 and ETV5. Etv2 was expressed in the developing limb buds preceding Shh and was co-expressed with Shh in the posterior domain of the limb bud. Conditional knockout of Etv2 in the limb bud resulted in loss of Shh expression and reduced expression of SHH signaling targets, Gli1 and Ptch1. Limb-specific overexpression of Etv2 resulted in an ectopic expression of Shh and ectopic SHH signaling. This led to the development of preaxial polydactyly resembling human and animal mutations22. Furthermore, we demonstrated that known mutations of the ZRS associated with preaxial polydactyly resulted in enhanced binding of ETV2 to the ZRS. Based on these data, we propose that the collective dosage of ETV2 activity regulates the strength of ZRS-Shh system and contributes to the patterning and outgrowth of the limb bud.Our second discovery defined ETV2 as the TF of the ETS/ETV family members that is essential for initiation of ZRS-LacZ reporter transgenic mice at the Shh expression maintenance phase suggested that the ETS/ETV family TFs regulated the ZRS27, this report fell short of identifying the ETS/ETV TF that regulates ZRS. It was hypothesized that the collective activities of ETS/ETV factors, namely ETS1, ETS2, GABPa, ETV4 and ETV5 regulate Shh expression in the limb bud27. However, both Ets1 and Ets2 were dispensable for the development of the embryo proper60. Even when both Ets1 and Ets2 were deleted, embryos only exhibited endothelial cell defects and limbs developed normally61. Gabpa knockout animals also did not show limb defects . Thus, previous studies did not identify the ETS/ETV family member responsible for Shh expression. ETV2 distinguishes itself from previously studied ETS/ETV family members in that loss or overexpression of Etv2 alone affects limb development. Indeed, it is one of the few TFs along with Hand2 that a single gene knockout causes severe limb defects. Furthermore, our transcriptional assays indicated that ETV2, but not ETS1 or ETS2, could activate transcription through ZRS. In this light, it is interesting to note a recent report that a mutation of ETV2 was linked to human polydactyly62. Although the effect of the mutation in the reported patient on ETV2 activity is not known, it underscores the key regulatory role of ETV2 in limb development.Although previous analysis of ZRS activities using the Shh, suggesting that ETV4/5 is antagonizing the transcriptional activator of Shh during limb patterning30. Our data are consistent with the notion that ETV2 is the positive regulator of Shh that antagonizes ETV4/5 activity and establish the anterior-posterior identity of the digits.Our analyses also revealed the antagonism of ETV2 and ETV4/5 in the transcriptional assay. It has been reported that loss of ETV function results in anterior expansion of Shh and that it regulates initiation phase of Shh expression. Gabpa, Ets1, and Ets2 were expressed later than Shh in a broader population than the Shh expressing population in the limb bud and did not explain the establishment of the initial localized expression of Shh63. ETV2 fills this role. It is possible that ETV1, ETV2, and GABPa regulate expansion and maintenance of Shh expression through enhancers made accessible by ETV2.Another distinguishing feature of ETV2 is that it is expressed earlier than Our third discovery was the definition of global chromatin accessibility changes according to limb development. Our ATAC-seq data and PCA of multiple samples revealed that there was a dramatic global change of chromatin accessibility between E9.5, E10.25, and E10.5, and between the ETV2-expressing and the non-expressing cells. Associated with the chromatin accessibility change, the profile of accessible TF binding sites changed globally. The known limb enhancers overlapped with the putative ETV2 binding sites that were closed in E9.5 HL and open in E10.5 posterior tissues, suggesting that the relaxation of chromatin accessibility at limb enhancers was correlated with relaxation of ETV2 binding sites not only at ZRS but also globally.64. This pre-patterning phase was necessary for the subsequent establishment of signaling centers, such as Shh-expressing ZPA and Fgf8-expressing AER64. ETV2-dependent global changes of chromatin accessibility coincide with this time window. This temporal correlation and the Etv2CKO phenotypes suggest that global changes of chromatin landscape triggered by ETV2 promoted the changes of transcriptional regulatory network from a pre-patterning mode to an organizing center-dependent patterning mode by priming the proliferative limb progenitors to be responsive to morphogen signals. Development of tissues and organs starts with specification of a small progenitor population, which subsequently undergoes patterning and proliferation for morphogenesis. Such global changes of chromatin landscape, which we demonstrated in limb progenitors, may be a common regulatory mechanism for progression of developmental processes in various organs.Genetic studies demonstrated that limb progenitors set up an anterior-posterior polarity during the initial 12 h from the onset of outgrowthShh being a prominent target. We propose a model whereby ETV2 functions at multiple steps of gene activation  and the Institutional Animal Care and Use Committee  at the University of Minnesota.Etv2 knockout mouse37, Etv2-EYFP reporter line40, Etv2-Cre transgenic line40, floxed Etv2 allele (Etv2fl/fl)65 were previously described. The Etv2-CreERT2 construct was generated by fusing the CreERT2 coding region to the Etv2 3.9 kb regulatory region39 and generating a transgenic animal. ROSA26-LacZ, ROSA26-ZsGreen1,ROSA26-STOP-rtTA-IRES-EGFP, Shh-EGFP-Cre16, and HoxB6-Cre41 lines were obtained from the Jackson Laboratories. The iHA-Etv2 transgenic line was generated by blastocyst chimera formation using ES cells that harbored a doxycycline-inducible Etv2 expression cassette66.Animals were housed in a mouse facility with 12 h dark/light cycle, ambient temperature and humidity. Transgenic technologies were performed at the Mouse Genetics Laboratory at the University of Minnesota. The Etv2 was generated by crossing HoxB6-CreTg/Tg; Etv2+/− males with Etv2fl/fl females65. Conditional mutant mice  and heterozygous littermates  were compared.For embryonic analysis, mice were bred, and timed pregnancies were generated. A posterior lateral plate- and limb mesoderm-specific knockout of Etv2 in limb mesoderm, first, a transgenic mouse harboring HA-tagged Etv2 under the control of tetracycline-inducible promoter was generated from iHA-Etv2 ES cells. This mouse was bred with the HoxB6-Cre driver line, and a compound heterozygous male  was bred with ROSA26-STOP-rtTA-IRES-EGFP females to obtain triple transgenic embryos . At E9.5 and E10.5, pregnant dams were injected intraperitoneally with 25 mg/kg of doxycycline and harvested at E11.5 or 15.5 for analysis. In the triple transgenic embryos, rtTA and EGFP were expressed only in the HoxB6-Cre lineage, and the timing of HA-ETV2 expression could be controlled by administration of doxycycline (Dox). Littermates that do not carry the iHA-Etv2 or the rtTA-IRES-EGFP transgenes were used as controls.For targeted overexpression of NIH3T3 cells were purchased from American Type Culture Collection (ATCC)  and were cultured in Dulbecco’s Modified Eagle’s Medium with 10% calf serum with additives according to the protocol published by ATCC.Etv2-EYFP males were sacrificed and embryos were collected in ice-cold PBS. Embryos were examined using epifluorescence microscopy and EYFP positive and negative embryos were separated. Limb buds were excised at the base of the limb buds and either pooled or processed separately. Limb bud tissues were digested in 200 μl of TripLE (ThermoFisher 12605010) at 37 °C in two cycles of 5 min incubation followed by trituration. Cells were cooled on ice for 5 min between incubations. Digestion was stopped with 1 ml of medium with 10% fetal calf serum that was filtered through a 50 μm mesh filter (Partec). Cells were collected by centrifugation and stained with staining medium containing 0.2 μg each of CD31-APC, Tie2-APC, CD45-APC and 0.5 μg anti CD16/CD32, and EYFP positive, APC negative live cells were sorted on FACSAria (BD). Cells from EYFP negative embryos were used as a negative control for FACS sorting.Timed pregnant CD1 females bred with 6 of dissociated cells were suspended in 200 μl of lysis buffer and processed according to the manufacturer’s protocol. Chromatin was sonicated with five 10 sec pulses at 20% power using Sonic Dismembrator model 500 (Fisher). Two μg of antibodies or control IgG was used for immunoprecipitation, and the chromatin-antibody complexes were separated using Dynabeads Protein G (Invitrogen). Crosslinking was reversed and recovered DNA was analyzed by qPCR corresponding to regions a, b, c, and d of ZRS  using the buffer system provided in the ChIP assay kit (Millipore). 1 × 10ZRS Fig.  and the 40. All limb sections were made transversely  unless noted otherwise. Antibodies and dilutions used are listed in Supplementary Table Immunohistochemical analyses of sections were performed as previously described67.Alcian Blue skeletal staining and whole mount in situ hybridization were performed as previously describedSections were prepared and stained using in situ cell death detection kit (Roche) for TUNEL staining.68.RNA extraction was performed using the Qiagen Micro RNeasy kit (Qiagen) according to the manufacturer’s protocols. qRT-PCR was carried out using SuperScript III Reverse Transcriptase (ThermoFisher) and Taqman probes (ThermoFisher). Three biological replicates were prepared for each experiment and each sample was analyzed by real-time PCR in triplicate. Whole mount in situ hybridization was performed as previously described69. For ATAC-PCR analysis, 0.94 ng of the library was amplified in each well with primer pairs used for ChIP analysis . The deviation scores and the TF variability were derived by using chromVAR’s computeDeviations and computeVariability functions. The pathway analysis was performed using peaks clustered together with the ZRS region genomic interval, and were annotated using ChIPseeker72. The geneID obtained from ChIPseeker was used as the gene set to perform GO enrichment analysis using clusterProfiler73 to obtain enriched pathways.Cells were prepared as described in the FACS procedure. ATAC reaction was performed as previously described using the Tn5 transposase (Illumina) and libraries were created at the University of Minnesota Genome Centersis Fig. . The GAPhttps://github.com/gongx030/seatac)50 for the detection of genomic regions with differential chromatin accessibility and nucleosome positions. SeATAC employed a conditional variational autoencoder framework to model the ATAC-seq-specific V-plot while addressing the batch effect in the ATAC-seq data, allowing an unbiased comparison across multiple samples. The convolutional neural network (CNN) blocks used in the encoder network allowed SeATAC to robustly estimate the posterior distribution of the latent variables by considering ATAC-seq specific fragment size profile, resulting in superior performance on several tasks such as detecting differential V-plot, recovering nucleosome positions, detecting nucleosome changes and calling TFBS with differential chromatin accessibility.We used a variational autoencoder model implemented in R package SeATAC -HA vectors were expressed using the TNT Quick Coupled Transcription/Translation System  according to the manufacturer’s protocol. DNA oligonucleotides corresponding to wild-type ZRS sequence or ZRS sequence with combinations of inactivating mutations in putative ETS, HAND2, or HOXD13 binding sites (see Supplementary Table NIH3T3 cells were plated at 20000 per well of a 48 cluster plate overnight and transfected on the next day using Lipofectamine 3000 Reagent (ThermoFisher). After 24 h of incubation, cells were washed in PBS and Luciferase activity was measured using Dual-Luciferase ® Reporter Assay System (Promega). Each sample was transfected in quardruplicate, and experiments were repeated at least three times to confirm reproducibility. Empty vector was added to equalize the total amount of DNA transfected when applicable.23 by PCR (see Supplementary Table KpnI-BamHI fragment including the vector backbone of pGL4-TATA-ZRS23.Genomic DNA fragments corresponding to regions i (1-656), ii (657-1401), and iii (1402-1682) of ZRS were amplified from pGL4-TATA-ZRSP-values lower than 0.01 were determined to be significant. The above analyses were done with Prism 4.0 software (GraphPad Software).Data represent average of more than three replicates (replicate numbers are indicated in the figure legends) and SEM. Statistical tests used are indicated in the figure legends. For quantitative PCR analysis, at least three biological replicates were prepared for each experiment, and samples were analyzed using real-time PCR in triplicate. Transcription assays were performed in triplicate, and each experiment was repeated at least three times.Further information on research design is available in the Supplementary InformationReporting Summary


The Farnesoid X Receptor (FXR) is a nuclear receptor that regulates the expression of several genes involved in the metabolism of bile acids (BAs) which is essential for normal liver function. In this study, we used the CRISPR/Cas9 system to generate a novel FXR knockout mouse model and demonstrate that FXR deletion in hepatocytes is associated with a global reduction in chromatin accessibility. The loss of chromatin accessibility was predominantly localized to promoter-associated transcription factor motifs, such as the NFγ/CBP and the KLF/SP1 family of pioneer transcription factors. Importantly, we demonstrate that the loss of FXR mediated chromatin accessibility contributes to dysregulation in bile acid and circadian homeostasis in hepatocytes.ex5Δ: Nr1h4ex5Δ/ex5ΔFxr) generated through CRISPR/Cas9. Consistent with previous Fxr knockout models, we found that ex5ΔFxr mice develop late-onset HCC associated with increased serum and hepatic BAs. FXR deletion was associated with a dramatic loss of chromatin accessibility, primarily at promoter-associated transcription factor binding sites. Importantly, several genes involved in BA biosynthesis and circadian rhythm were downregulated following loss of FXR, also displayed reduced chromatin accessibility at their promoter regions. Altogether, these findings suggest that FXR helps to maintain a transcriptionally active state by regulating chromatin accessibility through its binding and recruitment of transcription factors and coactivators.The Farnesoid X Receptor (FXR) belongs to the nuclear receptor superfamily and is an essential bile acid (BA) receptor that regulates the expression of genes involved in the metabolism of BAs. FXR protects the liver from BA overload, which is a major etiology of hepatocellular carcinoma. Herein, we investigated the changes in gene expression and chromatin accessibility in hepatocytes by performing RNA-seq in combination with the Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) using a novel FXR knockout mouse model ( Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and the third leading cause of cancer-related mortalities worldwide . The higNr1h4) signaling [Shp/Nr0b2) and the endocrine hormone FGF 15/19, both of which are directly regulated by FXR. In the liver, BA-dependent activation of FXR induces expression of Nr0b2, an atypical nuclear receptor that lacks a DNA binding domain. Nr0b2 acts as a corepressor for the nuclear receptors HNF4α and LRH-1 which in turn repress the transcription of Cyp7a1, the rate-limiting enzyme of the classical BA synthesis pathway [Fgf15/19, which is secreted and circulates to the liver to activate the hepatic FGF receptor 4 (FGF4). The activation of FGF4 represses Cyp7a1 gene transcription via extracellular regulated protein kinases 1/2 (ERK1/2)/cJun of the mitogen-activated protein kinase (MAPK) pathway [The dysregulation of bile acid (BA) homeostasis is a major driving force of NAFLD development and progression ,7. BAs pignaling . FXR is ignaling ,11,12. Fignaling . The mai pathway . In the At the transcriptional level, FXR regulates gene expression by binding to FXR response elements (FXREs) either as a monomer or a permissive heterodimer with Retinoid X Receptor (RXR) ,16. The ex5∆: Nr1H4ex5∆/ex5∆Fxr). We utilize the Assay for Transposase Accessible Chromatin sequencing (ATAC-seq) in combination with RNAseq to examine the consequences of loss of FXR on chromatin accessibility and its relationship to changes in gene expression, and transcription factor binding in hepatocytes. We find that the ex5∆Fxr mice develop a late-onset HCC with complete penetrance, as well as elevated serum and hepatic bile acids. Mechanistically, we demonstrate that FXR deletion is associated with a dramatic loss of chromatin accessibility at specific transcription factor binding sites, primarily at the promoter region of target genes. We show that FXR binds within the promoter or distal intergenic regions at its target genes and that the deletion of FXR is associated with loss of chromatin accessibility resulting in transcriptional dysregulation of its target genes. Collectively, these findings provide key insights into the transcriptional dynamics associated with FXR regulation of genes.In this study, we used the CRISPR/Cas9 system to generate a novel FXR knockout mouse model (Fxr-null mice (ex5∆: Nr1H4ex5∆/ex5∆Fxr) were generated using the CRISPR/Cas9 genome editing by the London Regional Transgenic and Gene Targeting facility. Briefly, zygotes generated from in vitro fertilization of C57BL/6NCrl oocytes were microinjected with Cas9 mRNA  and an exon 5 directing gRNA . The hepatocytes were further washed using low glucose DMEM containing 5% FBS, prior to resuspension in the cryopreservation media  at a concentration of 1 × 10g for 3 min at 4 °C with brakes turned off. After removing the supernatant, the hepatocytes were resuspended in 10 mL of ice-cold nuclei isolation buffer  and left on ice for 5 min. Then, the hepatocytes were centrifuged at 400× g for 5 min with brakes on. The nuclei were stained with trypan blue, visualized under microscope, and counted using a cell counter. Approximately 200,000 nuclei were used for tagmentation in the Tn5 buffer  using 10 µL of Tn5. The tagmentation was performed at 37 °C for 30 min with shaking at 700 rpm. The DNA was immediately isolated using the Zymo DNA clean and concentrator-5 (Cat no. D4013). Then, PCR was performed using the illumina i5 and i7 indexing primers containing adaptors for 8–12 cycles ; 72 °C 5 min, 4 °C indefinitely). The PCR amplified DNA was cleaned using the Zymo DNA clean and concentrator -5, double size selected using Ampure XP beads (Cat no. A63880) and quantitated using Collibri library quantitation kit (Cat no. A38524100). The libraries were analyzed for fragmentation via Agilent bioanalyzer and sequenced using illumina NovaSeq high throughput sequencer .A vial of cryopreserved hepatocytes was removed from −80 °C freezer and immediately placed in a 37 °C water bath for 3 min. A 10 μL aliquot of the hepatocytes was taken to measure viability using trypan blue. A minimum viability of 80% was required prior to proceeding with tagmentation. Immediately after 2 min at 37 °C, the thawed hepatocytes were washed using 10 mL of pre-warmed D-PBS in a 14 mL falcon tube. The hepatocytes were centrifuged at 50× For the RNA-seq, the sample quality was assessed using the Agilent 2100 Bioanalyzer. Qualifying samples were then prepped following the standard protocol for the NEBnext Ultra ii Stranded mRNA (New England Biolabs) at the University of British Columbia. Sequencing was performed on the Illumina NextSeq 500 with Paired End 42 bp 3 42 bp reads, with a depth of 50 million reads per sample. The raw data was aligned to the mm10 mouse genome using the STAR aligner and the gene list was generated using cufflinks. A list of differentially expressed genes was generated using q < 0.05 as the cutoff for significance. The heatmap was generated using the Bioconductor gg-plot addon for the R software and Morpheus from broad institute. For the TCGA analysis, the data was downloaded using the firehose website, and analyzed using the R-software.Total RNA from liver tissues was extracted using an RNAzol solution  as per the manufacturer’s protocol. The cDNA was synthesized using the Applied Biosystems Reverse Transcription Kit as per manufacturer’s protocol. For RT-PCR, cDNA was PCR amplified using primers from g) at 4 °C for 15 min and the supernatant was retained. Protein concentrations were determined using the Bradford assay. For Western blot, 50 μg protein samples were loaded onto a 4–12% gradient Bis-Tris NuPAGE gel , subjected to SDS-PAGE, and transferred onto a PVDF membrane. PVDF membranes were incubated in blocking buffer consisting of 5% skim milk in PBS for one hour and hybridized overnight with the appropriate primary antibody at the indicated dilution. After five ten-minute washes in blocking buffer, membranes were hybridized for one hour with the appropriate secondary antibodies. The membranes were then washed 5 times in blocking buffer and the blots were developed using the Clarity Western ECL Substrate  and imaged using the ChemiDoc XRS imaging system . The primary antibodies were used in this study are listed in For protein extraction, whole livers/hepatocytes were homogenized in 1 mL of ice-cold RIPA lysis buffer  containing 1× Halt Protease Inhibitor Cocktail . Lysates were incubated on ice for 15 min, centrifuged at maximum speed  for 10 min with rotation at room temperature. The homogenate was then lysed, sonicated, and incubated with 50 μL of premixed protein A/G DYNABEADS overnight. The DYNABEADS were then washed and the resulting chromatin was eluted using the elution buffer . The eluted chromatin was reverse-crosslinked and the resulting ChIP DNA was analyzed by qPCR using primers outlined in The chromatin immunoprecipitation assay was performed as previously described . Brieflyhttps://chip-atlas.org (accessed on 24 May 2022)). For ATACseq, the BAM files were sorted, indexed and filtered for maq quality (>30), mitochondrial reads and read duplicates using ChIPseq and ATACseq Processing and Peak calling Software . CAPPS was also used to call peaks using MACS2, generate the fragment size distribution graph via picards, and generate BigWig files. Appropriate fragmentation size distribution was essential for downstream analysis. CAPPS is a two-part data analysis software package with a GUI and is written in python and R. CAPPS streamlines pre-processing and data analysis of ATAC-seq and ChIPseq datasets.STAR and bowtie2 were used for the alignment for RNAseq and ATAC-seq datasets, respectively, to the mm10 genome. Cufflinks was used for differential gene expression analysis. All ChIP-seq data were obtained from the ChIP-atlas database . Homer was used for Motif analysis (findMotifgenome.pl) and for annotating peaks around promoter or distal intergenic regions (annotatepeak.pl). Bedtools, DeepTools and CAPPS-Data Analysis were used to generate heatmap plots, perform data overlaps and for pathways analysis. All peak summit plots were generated using IGV.Differential peak analysis between control and p values over 0.05 were deemed not significant. Significance is indicated as follows: *, p < 0.05; **, p < 0.01; ***, p < 0.001; NS: not significant. GraphPad PRISM 5.0 was used for generating the Kaplan–Meier curves and the graphs.All Western blots are representative of at least duplicate experiments. Statistical analyses were performed using GraphPad Prism 5 using the Student’s T test (2 groups), or ANOVA with Tukey post hoc (3 groups or more). All Fxr exon 5 alleles were sequenced and a 47 bp deletion was identified resulting in a frame-shift mutation  between 8 and 15 months of age, relative to age and sex-matched control animals (Gehan-Breslow-Wilcoxon test p < 0.001)  . Consisthe liver . These oex5∆Fxr livers using the classic collagenase-perfusion technique with the addition of a percoll density gradient to increase the purity and viability of hepatocytes [ex5∆Fxr hepatocytes , whereas regions that gained accessibility upon the loss of FXR were found in the distal intergenic and intronic regions of the genome  of the 1592 FDR adjusted peaks correspond to chromatin regions that gain accessibility in ex5∆Fxr hepatocytes. The most dramatic loss in chromatin accessibility in ex5∆Fxr hepatocytes was found at the promoters of Deaf1 . Motif analysis on regions gaining accessibility failed to generate any statistically significant motifs. In contrast, 159 motifs were enriched in peaks that lose accessibility with FXR deletion in hepatocytes  (Klf) family of transcription factors were highly enriched in regions that become inaccessible upon FXR deletion (The observation that chromatin loses accessibility with FXR deletion prompted us to investigate if access to transcription factor binding is reduced in  < 0.05) A. Consisdeletion A. NF-Y ideletion B. Combinex5∆Fxr hepatocytes is the DR1 motif, a consensus motif for PPAR/RXR heterodimers  and H3K4 trimethylation (H3K4me3) activating histone modifications, which are markers of open chromatin. Surprisingly, upon FXR deletion loss of RXRα recruitment, as well as H3K27ac and H3K4me3 activating histone marks was found at Nr0b2 and Cry1 promoters  also have FXR binding sites. Interestingly, the majority of FXR binding was found 1–3 kb from the TSS, which indicates that FXR plays a critical role in regulating promoter-specific activity at target genes. Further analysis indicated that approximately 32.44% of downregulated and 26.33% of upregulated genes in ex5∆Fxr hepatocytes contain FXR binding sites  have binding sites in the promoter and 44 genes (18.8%) have binding sites for FXR in the distal intergenic regions. However, only 17 genes (or 7.2%) of the 234 dysregulated genes possessed an FXR binding site at both the promoter and distal intergenic regions. These findings agree with the observation that the majority of the FXR binding events are localized within the promoter or distal intergenic regions of target genes , which increases the risk of HCC development [An overlap of the RNA-seq and ATAC-seq dataset identified dysregulation in FXR signaling and bile acid homeostasis, as well as the onset of hepatocellular carcinoma which is in agreement with previous studies ,24,26. Ielopment ,43,44. Telopment .Overall, these findings indicate that the loss of FXR causes HCC from a combined dysregulation in the bile acid, circadian and insulin signaling pathways via a loss of promoter accessibility and activity at genes relevant to these pathways.


Cell differentiation and acquisition of specialized functions are inherent steps in events that lead to normal tissue development and function. These processes require accurate temporal, tissue, and cell-specific activation or repression of gene transcription. This is achieved by complex interactions between transcription factors that form a unique combinatorial code in each specialized cell type and in response to different physiological signals. Transcription factors typically act by binding to short, nucleotide-specific DNA sequences located in the promoter region of target genes. In males, Leydig cells play a crucial role in sex differentiation, health, and reproductive function from embryonic life to adulthood. To better understand the molecular mechanisms regulating Leydig cell differentiation and function, several transcription factors important to Leydig cells have been identified, including some previously unknown to this specialized cell type. This mini review summarizes the current knowledge on transcription factors in fetal and adult Leydig cells, describing their roles and mechanisms of action. Localized in the testicular interstitium, Leydig cells are the principal source of testosterone and insulin-like 3 (INSL3), two hormones that regulate male reproductive development and function. In mammals, there are at least two distinct populations of Leydig cells, fetal Leydig cells (FLC) and adult Leydig cells (ALC), which are responsible for the synthesis of steroid hormones in the prenatal and postnatal testes, respectively . SteTranscription factors (TFs) are fundamental to the regulation of gene expression. They are specialized proteins that recognize and bind to regulatory DNA sequences, modulating the rate of gene transcription [reviewed in ]. TFs tyIn recent years, the development of novel and powerful methodological approaches in molecular genetics has led to the emergence of new information regarding the role of TFs in the regulation of Leydig cell differentiation and function, and by extension, in male fertility and reproductive health. In this mini review, we provide a brief overview of the roles and mechanisms of action of some of the most characterized TFs in Leydig cells. We have adopted the most recent classification of TFs, which is based both on amino acid sequence homology and the tertiary structure of their DNA-binding domains . Using tThe activator protein 1 (AP-1) is a dimeric complex that includes members of the JUN, FOS, activating transcription factor (ATF), and musculoaponeurotic fibrosarcoma (MAF) families of TFs . Among tStar) gene, which is activated by cJUN ] gene, involved in the initiation and maintenance of sperm production, is also controlled by cJUN, JUNB, and FOSL2, and by a cJUN/cFOS cooperation (Fdx1) promoter is activated by a cJUN/SF1 cooperation , cAMP response element modulator (CREM), and CRE-activating transcription factor (ATF-1). CREB factors homodimerize and heterodimerize with other CREB members and with other bZIP TFs, such as AP-1 members . CREB far region , 14. Morcription . CREB al LH/cAMP . Cklfsf2ig cells . TherefoStar transcription alone and in cooperation with SF1 and GATA4 .Members of the CCAAT/enhancer binding protein (C/EBP) subfamily contain a bZIP DNA-binding domain and regulate gene expression by binding to the sequence (A/G)TTGCG(C/T)AA(C/T) as homo- or heterodimers . C/EBPβ nd GATA4 –19. C/EBig cells . The NurTFs belonging to the nuclear receptor class respond to extracellular and intracellular signals to regulate gene expression. They also regulate cellular functions within the cytoplasm . In thisVia their double zinc finger DNA-binding domain, NR2F factors bind as monomers to the nuclear receptor element AGGTCA and its variants. They also bind as dimers to direct (DR), inverted (IR), and everted (ER) repeats separated by 1-12 nucleotides  subfamily consists of three members: chicken ovalbumin upstream promoter transcription factor I , COUP-TFII  and COUP-TFIII . NR2Fs have been implicated in various physiological and developmental processes by regulating the expression of numerous genes . Vileotides .In vivo studies using mouse models have shown that COUP-TFII is crucial for Leydig cell development and male reproductive function  into 5α-androstane-3α,17β-diol (3α-diol), is activated by COUP-TFII in cooperation with MEF2 , and as heterodimers with RXR to a DR5 sequence . DeSF1 gene in humans and in mouse models where adrenal and gonadal development and function are impaired   , Cyp19a1 family comprises two members: critical region on the X chromosome gene 1  and small heterodimer partner . They lack the typical zinc finger DNA-binding domain and therefore act mainly as transcriptional repressors by inhibiting the activity of other TFs , 91. BotDax1-deficient mice, testis cord organization is compromised and FLC development is arrested GATA(A/G) in the promoter region of target genes. Of the six GATA factors, GATA4 is the most abundant in Leydig cells in vivo (The six GATA members (GATA1 to 6) are crucial for the development and function of several tissues, including the male gonad . GA in vivo –102. Its in vivo . Conside in vivo , 104.Sf1-Cre mouse line, which expresses the Cre recombinase in several tissues including Leydig, Sertoli and adrenal cells, was used to conditionally inactivate Gata4. The resulting males were undervirilized and had small testes lacking mature sperm   is the only member of the FOXA subfamily present in the testes, mainly in ALC , 109. SoPdgfra) , that inPdgfra) . In cAMPoduction . These fThe Myocyte Enhancer Factor 2 (MEF2) factor subfamily comprises four members (MEF2A-2D) that share two highly conserved domains, a MADS box and a MEF2 domain, involved in dimerization and DNA binding [reviewed in ]. MEF2 fNur77 (Gsta1-4 (Star (involving a MEF2/GATA4 cooperation) (Akr1c14 (through a cooperation with COUP-TFII)  , and AkrUP-TFII) . The com3GAA) in the promoter region of target genes. So far, STAT5B is the only STAT factor identified in Leydig cells  family consists of seven proteins [reviewed in ]. Cytokiig cells . In thesig cells . STAT5B ith cJUN . STAT5B promoter .Star, Hsb3b, and Cyp11a1 , which is an important modulator of reactive oxygen species levels, especially in aging Leydig cells –117. Fur Cyp11a1 , 119. Fi Cyp11a1 , 31, 120in vitro analyses of regulatory elements of genes expressed in Leydig cells. Although we are far from fully understanding all the signals, pathways, and TFs involved, technological advances and novel mouse models will certainly lead to significant discoveries in the coming years.As described in this mini review, several TFs belonging to different classes and families are pivotal to ensure proper Leydig cell differentiation and function. This underscores the complex regulatory mechanisms involved. Most of the knowledge acquired so far has relied on KM wrote the first draft of the manuscript. All authors contributed to the article and approved the submitted version.Supported by a grant from the Canadian Institutes of Health Research (funding reference number MOP-81387) to JT. KM is the recipient of a studentship from the Fonds de recherche du Québec-Santé.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.


The excessive production of reactive oxygen species (ROS) can lead to single nucleic acid base damage, DNA strand breakage, inter- and intra-strand cross-linking of nucleic acids, and protein-DNA cross-linking involved in the pathogenesis of cancer, neurodegenerative diseases, and aging. G-quadruplex (G4) is a stacked nucleic acid structure that is ubiquitous across regulatory regions of multiple genes. Abnormal formation and destruction of G4s due to multiple factors, including cations, helicases, transcription factors (TFs), G4-binding proteins, and epigenetic modifications, affect gene replication, transcription, translation, and epigenetic regulation. Due to the lower redox potential of G-rich sequences and unique structural characteristics, G4s are highly susceptible to oxidative damage. Additionally, the formation, stability, and biological regulatory role of G4s are affected by ROS. G4s are involved in regulating gene transcription, translation, and telomere length maintenance, and are therefore key players in age-related degeneration. Furthermore, G4s also mediate the antioxidant process by forming stress granules and activating Nrf2, which is suggestive of their involvement in developing ROS-related diseases. In this review, we have summarized the crosstalk between ROS and G4s, and the possible regulatory mechanisms through which G4s play roles in aging and age-related diseases. ROS can lead to single nucleic acid base damage, DNA strand breakage, inter- and intra-strand cross-linking of nucleic acids and protein-DNA cross-linking.G4 is a four-stranded nucleic acid structure formed by guanine-rich DNA and RNA sequences with Hoogsteen hydrogen bonding.The structure and biological regulatory role of G4s can be affected by cations, helicases, transcription factors, G4-binding proteins, and epigenetic modifications.How do ROS affect the stability of G4 and G4-mediated biological regulation?What are the mechanisms through which G4s regulate the transcription and translation of ROS-related genes?Are G4s potential therapeutic targets in ROS-mediated aging and related diseases?The imbalance between the production and clearance of reactive oxygen species (ROS) triggers extensive damage to cellular components such as nucleic acids, proteins, and lipids . Low lev2O2-induced oxidative stress triggers the cytoplasmic accumulation of G4s, wherein they interact with some proteins to form “stress particles” that alter mRNA translation . With an increased understanding of the regulatory role of G4s in the process of SGs forming, drugs targeting G4s also have a new potential clinical value.The formation of SGs are associated with neurological diseases, myopathies, and tumors –146. Thu147Low to moderate levels of oxidative stress activate antioxidant and detoxification genes that contain the antioxidant response element (ARE) in their promoters, which is the binding site of the Nrf2 transcription factor , 149. Th+, which is close to several putative TF-binding sites. This suggests the presence of a natural G4 structure in the promoter region of Nrf2 . It also binds selectively to the telomeric DNA G4 and generates singlet oxygen post-irradiation, which then oxidizes and cleaves guanine residues in the G4 and region. ZnAPC and TMPyP4-C14 have shown similar effects [Photodynamic therapy (PDT) is a minimally invasive cancer treatment compared to surgery, chemotherapy, and radiotherapy . Double-180 effects , 182 (TaG4s are involved in various neurodegenerative diseases such as Alzheimer’s disease (AD) and Parkinson’s disease (PD) Fig. . The G4sOxidative stress is a regulatory element in aging and various neurological disorders , associaThe presence of G4s in the G-rich regions of the C9orf72 gene may recruit cellular hemin to form G4/hemin DNAzyme, which is associated with oxidative damage during neuronal degeneration  Fig. 8)8). In thG4s are involved in regulating telomere length, gene transcription, translation, and epigenetic changes in the chromatin. The formation, stability and regulatory role of G4 structure are affected by various intracellular factors and epigenetic modifications. The unique structure and distribution of G4s provide new insights into the role of oxidative stress in regulating gene expression. ROS can affect the formation or dissociation of G4 motifs by reducing their thermal stability, altering the original G4 structural pattern, and influencing other chromatin structures at transcriptionally active sites such as R-loops and D-loops. G4s located at transcriptionally active sites are involved in base repair after ROS-induced DNA damage and thus promote gene transcription by recruiting associated proteins and TFs. Furthermore, G4s located in the 5′UTR or 3′UTR regions of mRNA are also involved in regulating translation under oxidative stress. These findings suggest that G4s are critical to ROS-mediated gene transcription and translation. In addition, G4s can improve ROS clearance and protect DNA from unwanted ROS by promoting the formation of SGs in the cytoplasm or activating Nrf2 translation. Thus, G4s may also be involved in cancer, aging, and degenerative disorders that are closely related to excessive ROS production and are promising therapeutic targets for these disorders.Nevertheless, the current research on G4s are mainly descriptive, and the mechanisms underlying the regulation of G4s in response to ROS are largely unknown and need to be elucidated. For example, the optimal levels of intracellular ROS that regulate G4 formation and stability need further exploration. Following physical or chemical stimulation, whether ROS enhances G4-mediated tumor killing is not yet known. In additional, as mentioned above, G4s are involved in the formation of SGs, However, the specific role of G4 in regulating the biological function of SGs needs further experimental verification. In sum, the further exploration of these questions will contribute to understand the relationship between ROS and G4, and then provide some ideas for finding the new mechanism of G4-mediated biological regulation.


The 3D genome organization and its dynamic modulate genome function, playing a pivotal role in cell differentiation and development. CTCF and cohesin, acting as the core architectural components involved in chromatin looping and genome folding, can also recruit other protein or RNA partners to fine-tune genome structure during development. Moreover, systematic screening for partners of CTCF has been performed through high-throughput approaches. In particular, several novel protein and RNA partners, such as BHLHE40, WIZ, MAZ, Aire, MyoD, YY1, ZNF143, and Jpx, have been identified, and these partners are mostly implicated in transcriptional regulation and chromatin remodeling, offering a unique opportunity for dissecting their roles in higher-order chromatin organization by collaborating with CTCF and cohesin. Here, we review the latest advancements with an emphasis on features of CTCF partners and also discuss the specific functions of CTCF-associated complexes in chromatin structure modulation, which may extend our understanding of the functions of higher-order chromatin architecture in developmental processes. The genome stores the complete genetic information of living organisms, and the 3D genome is commonly regarded as genomic DNA sequence folding in three dimensions or higher-order chromatin organization inside a cell’s nucleus. Importantly, the dynamic of three-dimensional (3D) structure of the genome is closely associated with modulation of gene expression and genome function , which pHierarchically, the topological structures of 3D genome are organized at four levels, comprising chromosome territories, A/B compartments, topologically associating domains (TAD), and chromatin loops  A. CurrenCCCTC-binding factor (CTCF), serving as the central organizer, plays a key role in 3D genome organization. CTCF is highly conserved across vertebrate species but absent in plants, C. elegans, and yeast . CTCF haIn addition to cohesin, extensive studies have revealed numerous partners, which work in close collaboration with CTCF in shaping the chromatin structures. Most of these partners are transcription factors that are involved in cell-type-specific transcriptional regulation and chromatin remodeling processes. CTCF is developmentally regulated, and interaction between the CTCF and these lineage-specific protein partners confers various functions during cell development and differentiation, ranging from embryonic stem cells (ESCs) to immune and muscle cells. Furthermore, recent studies emphasized that RNA can also interact with CTCF, and these interactions are essential for facilitating CTCF-mediated genome organization. The interplay between CTCF and its RNA partners has also been found to be involved in specific biological processes such as X chromosome inactivation. Here, we review recent advances in the discovery of CTCF partners and also discuss the specific functions of CTCF–partner complexes in the regulation of chromatin structure , which sRegarding the formation of the basic three-dimensional structural loops, the “loop extrusion model” has been proposed by several groups B 67,68,,68,69. AFbn2, as a model for study. Interestingly, direct observation of dynamic Fbn2 TAD chromatin loops via super-resolution live-cell imaging revealed that cohesin extrusion loops within TADs fail to bridge two CTCF boundaries approximately 92% of the time, suggesting that a single CTCF boundary can also create functional interactions [Cohesin, a circular protein complex, was originally identified in eukaryotic mitosis for its function in sister chromatids cohesion . Moreoveractions .Recently, several other factors, such as WAPL and NIPBL-MAU2, have been identified to participate in mediating loop formation or expansion. WAPL promotes the release of cohesin from DNA template, which restrains loop formation. Depletion of WAPL, in turn, increases the residence time of cohesin on chromatin, where cohesin bypasses CTCF binding sites and generates larger loops ,15. On tRecently, several studies have performed systematic investigation of CTCF’s partners. Hu et al. took advantage of 1306 ChIP-seq data for 431 human protein factors and characterized the genome-wide DNA-binding patterns of these factors, including transcription factors, histone variants, and histone-modifying enzymes, as well as CTCF, in 23 cell lines . All facFurthermore, Marino et al. applied affinity purification coupled with high-resolution LC–MS/MS analysis for large-scale identification of CTCF-specific binding partners . In the WIZ gene result in embryonic lethality, and heterozygous deletions increase anxiety-like behaviors in mice [CTCF has been reported to interact with RNA polymerase II both in vivo and in vitro , which i in mice ,23. WIZ  in mice . In addi in mice .Car2 in erythrocytes by binding to the enhancer and promoter upstream of the Car2 gene, respectively [T and B cells comprise the main forces of adaptive immunity of the immune system, and T cells play a major role in the body’s anti-infection, anti-tumor, and autoimmune diseases. Naïve T cells can differentiate into Th1, Th2, and Th17 cells expressing IFN-γ, IL-4, and IL-17, respectively. Kim et al. showed that Th17 lineage differentiation is restrained by the Th2 locus, and the regulation is attributed to the interaction between Oct-1 and CTCF, which mediates the interchromosomal contacts between the locus control region (LCR) of the Th2 cytokine locus on chromosome 11 and the IL-17 locus on chromosome 1 . The higectively .MyoD and Myf5, acting as fundamental helix-loop-helix transcription factors, are required for myogenic initiation during early embryogenesis and functionally complement each other . MyoD inThe zinc finger transcription factor Yin Yang 1 (YY1) is essential for both early embryogenesis and adult tissue development , and biaThe Y-box DNA/RNA binding factor (YB-1) is a multifunctional protein involved in transcription, replication, and RNA processing, and several studies have identified it as a CTCF partner. Chernukhin et al. demonstrated that YB-1 can physically and functionally interact with CTCF to repress the transcription of c-myc . In addiXiao et al. have shown that Myc-associated zinc finger protein (MAZ) is a physically interacting partner of CTCF, and it can function as a genome architecture protein, one that participates in genome organization. Remarkably, MAZ shares core properties with CTCF, including insulation activity and interaction with cohesin subunit Rad21, supporting the fact that MAZ and CTCF have complementary roles in organizing genome structure . In addiIn addition, several other protein partners of CTCF have been identified; nevertheless, the detailed mechanisms underlying the roles of CTCF/partner complex in regulation of 3D genome structure still require further information. For example, Kaiso is a bimodal transcription factor that recognizes methylated CpG dinucleotides or conserved unmethylated sequences . The Kaiso binding sites exist adjacent to CTCF binding sites, and the Kaiso–CTCF interaction negatively regulates CTCF insulator activity . AdditioThe nucleosome is the basic unit of chromatin, consisting of histone octamers  and 146 base pairs (bp) of DNA. In addition to these classic histone variants, many other variants have been found, such as H2A.X, H2A.Z, H3.5, and H4.G . MoreoveThe nuclear receptor superfamily is a family of ligand-activated transcription factors that regulate cell growth and differentiation by establishing links between signaling molecules and transcriptional responses . WarwickIn addition to binding to DNA, several recent studies confirmed that CTCF also has the ability to bind to RNA. Moreover, CTCF targets thousands of transcripts throughout the genome and has a higher binding affinity for RNA than DNA . ZF1 andCurrently, high-throughput-sequencing-based methods, such as UV-crosslinking immunoprecipitation and deep sequencing (CLIP-seq), have been developed to identify CTCF-bound transcripts systemically . AdditioUntil now, several CTCF’s RNA partners have been identified, and their regulatory roles in chromatin structure provide novel insights into 3D genome organization. X-chromosome inactivation (XCI) is a classical epigenetic reprogramming process that is essential for mammalian development . StudiesIn addition, interactions between CTCF and multiple ncRNAs, such as the steroid receptor RNA activator (SRA), Wrap53, HOTTIP, and GATA6-AS1, have been identified, playing potential roles in shaping 3D genome structure. For example, Yao et al. revealed that CTCF/SRA/p68 (DEAD-box RNA helicase) complex can stabilize the interaction between CTCF and cohesin . CTCF reProtein post-translational modifications (PTMs), functioning as a key mechanism for increasing proteome diversity, play critical roles in nearly all biological processes. Indeed, many studies indicate that PTM enzymes, such as PARP, SUMO, CK2, PLK1, and LATS, are also CTCF’s protein partners. In fact, CTCF is regulated by serving as a substrate for these PTM enzymes. PTMs of CTCF are associated with dynamic regulation of the stability and function of CTCF in response to an external or internal stimulus A,B.Poly(ADP-ribosyl) ation (PARylation) is mediated by poly(ADP-ribose) polymerase (PARP) , and an CTCF protein can be modified by small ubiquitin-like proteins, including SUMO 1, 2, and 3. Currently, two major SUMOylation sites of CTCF, located in the COOH and NH2 terminal domains, separately, have been resolved. SUMOylation of CTCF commonly contributes to its repressive functions, such as repression of the cMYC P2 promoter activity . SpecialMoreover, it is widely accepted that phosphorylation is a functional determinant of transcription factors and appears to be one of the most studied forms of PTM. The phosphorylation profile of CTCF is dynamic during development and cell differentiation . CK2-medThe orderly folding of the genome in the three-dimensional space of the nucleus is critical for developmental processes, and the 3D genome folding is dynamic at different developmental stages. Significantly, the loop extrusion model explains the basic features of loop formation and genome folding, opening a new window into chromatin organization and genome architecture. According to this model, two key players CTCF and cohesin work together to regulate genome folding into TADs and loops. Indeed, a large number of studies demonstrated that protein factors and RNAs are implicated in chromatin structure regulation by interacting with CTCF. These partners act to shape nuclear structure in a general or a specific manner, and these new findings provide crucial information for decoding the 3D genome structure and its dynamics, as well as elucidating a causal relationship between dysregulated high-order chromatin structure and developmental processes.At present, a large number of protein and RNA partners of CTCF have been identified through systemic screening approaches, including ChIP-seq, LC–MS techniques, and the DeepLncCTCF model ,60,77,86Compared to protein partners, findings related to RNA partners of CTCF are relatively limited. However, a growing amount of evidence indicates that ncRNAs also play crucial roles in shaping the 3D genome. Early in 1989, Nickerson et al. made the concept that RNA may function as a structural component, and participate in organizing the higher-order structure of chromatin . RecentlLiquid–liquid phase separation (LLPS) is a process that separates a homogeneous liquid solution of macromolecules, such as proteins or nucleic acids, into two distinct phases: dense and dilute . NumerouTaken together, the function of the CTCF–protein and CTCF–RNA interactions in the genome organization has become an important research focus, and recent findings advance our understanding of CTCF/partner function in shaping 3D genome structure. Furthermore, experimental and computational techniques are improving rapidly. Thus, more partners, functioning as structural components of the nucleus, are expected to be explored.