A new temperature stress test machine (TSTM) was developed to improve temperature control accuracy and efficiency. As there is no uniform standard for the threshold value of TSTM, quite different threshold values are used in the test, which results in the influences of the threshold value on the evaluation of thermal stresses and crack risk of concrete not being determined. To illustrate the importance of an appropriate threshold value, different threshold values were used to evaluate the influences on the thermal stresses and cracking resistance of concrete specimens under a complete restraint test with semi-adiabatic temperature development. The results show that the maximum compressive stress of a concrete specimen with a threshold value 3 με was slightly larger than that of 1.5 με when the growth rate of tensile stress of the concrete specimen with the threshold value 3 με was slightly greater than that of concrete specimen with the threshold value 1.5 με. Based on the combination of crack risk coefficient and restraint degree, a new system for evaluating the crack resistance of concrete was proposed, in which different threshold values were used to estimate their influences on the crack risk of concrete. Thus, an appropriate range of threshold values could be determined. Cracks in young concrete not only affect the appearance and performance of the structure, but also the ability of the structure to resist external corrosive substances, which thus leads to the reduction of the durability of structures, ranging from dams, massive foundation slabs, bridge decks and piers, to beams used for buildings ,2. When The cracking frame mainly concentrated on the stress and strain development of concrete under temperature control and self-generated shrinkage deformation ,11. MoreCE and SE represent the elastic modulus (MPa) of the concrete specimen and steel bar respectively, while CA and SA represent respectively the sectional area (m2) of the concrete specimen and steel bar on both sides of the cracking frame. As known in Equation (1), the restraint degree of the concrete specimen decreases gradually from 100% if the elastic modulus of early-age concrete increases from 0 to 50 GPa and steel bar keeps a constant value 200 GPa. The restraint degree can change from 80% to 100% if the section size of concrete specimen is the same as that of steel bar on both sides [However, the cracking frame cannot ensure that the concrete specimen keeps its original length when the elastic modulus increases with the curing time, instead of which the incremental stiffness ratio of the concrete specimen and the steel bars reduces the restraint degree. The restraint degree specimen  can be cth sides . TherefoTo control the 100% restraint, threshold value  was applIn this paper, several different threshold values were adopted to measure the stress development under the same temperature history. Compressive stresses and tensile stresses were separated to analyze the impacts of threshold values on the test results at the representative moments. A crack risk of coefficient and the restraint degree are combined to estimate the cracking risk of concrete. When the new estimation method was applied in the data from existing literature ,27,28,29As shown in The temperature stress test system was conducted to simulate the real ambient temperature and environmental conditions of structures. The isothermal conditions were also kept at a constant temperature 20 ± 1 °C with the air-conditioning. Meanwhile, the laboratory’s interior walls were faced with the thermal insulating layer to avoid the disturbance of environmental temperature. All specimens were poured and cured under the same condition, so maturity of the specimens has the same relationship with the curing age. The measured distance is 1000 mm at the middle of the concrete specimen. The total length is 1500 mm and the side length of the quadratic cross-section is 150 mm .Before the concrete specimens were cast, two layers of plastic foil were snugly fitted into the mold. Apart from this sealing method, the upper template pasted the insulation layer was placed onto the specimens to obtain an enclosed condition. The temperature of the upper template was identical to that of the inner specimens, as shown in One end of the restrained specimen was connected to a stepping motor through a universal joint, and the other end was fixed. The specimen would drive the universal joint to move when the specimen length changed with the temperature history. Then the stepping motor would push or pull the universal joint to its original position when the absolute value of the total strain of the restrained specimen exceeded the threshold value ,25,36, aThe temperature stress tests were performed for the low-heat cement concrete, which was used in the dam structures, including low-heat Portland cement P·LH 42.5, the first-grade fly ash (35% replacement cement by fly ash), nature sand and crushed limestone (maximum grain size of 20 mm). −6 m/°C) and temperature difference.In addition to two layers of plastic foil snugly fitted into the mold when the concrete specimens were cast, the cover was made of temperature-control template plus insulating layer, as shown in As shown in As shown in To compare the effects of different threshold values on thermal stresses, the heating and cooling stages are separated to analyze. The restraining tensile stress development during the cooling stage is presented in σ/ctf) exceed 0.5 [For the early-age concrete specimen, the frequent compression and tension will damage the specimen , but theceed 0.5 . This isceed 0.5 . Howeverceed 0.5 ,43,44.crackσ/tf) is taken as the evaluation criterion that represents the ratio between the cracking stress crackσ and the tensile strength of concrete specimen. The following Equation (2) was defined as the crack risk coefficient η1 of concrete [To illustrate the influences of different threshold values on the tensile capacity of the concrete specimen , the relconcrete .(2)η1=σfix(t)σ can be measured by the TSTM while the restraint degree Rγ [η2.σ(t) and t(t)f represent the stress and tensile strength at time t respectively, while fix(t)σ denotes the 100% restraint stress at time t.The complete restraint stress egree γR  from difη2 can be used to evaluate the influences of different threshold value on the crack risk of concrete in this study. Apart from that, it can also be used to estimate the risk of cracking.Now the specimen is 100% restraint, soAs shown in Altoubat  studied The cracking capacity of early-age concrete is also affected by the factors such as temperature development, water-cement ratio, and structure size, which will affect the mechanical properties of early-age concrete, and a series of studies have been conducted ,29,32. TAs shown in As observed in the figure, the initial tensile stress rises at a growth rate of about 0.015 MPa/h when the cooling rate is 0.15 °C/h. The stress and deformation of specimens showed a linear stress-strain relationship and the stress and temperature could also be in a simple linear relationship, i.e., 0.1 MPa/°C. When the cracks occurred, the tensile stress had not reached the tensile strength.As outlined above, different threshold values have different effects on the compressive and tensile stresses during the heating and cooling phases. The temperature-control system in TSTM has been improved, which can raise and lower temperature with very high precision. The setup could quickly control the temperature of concrete specimens with a high-accuracy temperature measurement. Different threshold values have different influences on the thermal stress. No matter if it is in the temperature-rise or temperature-fall period, the compressive/tensile stress growth rate of threshold value 3 με was slightly higher than that of threshold value 1.5 με. This is mainly because of the rapid growth of elastic modulus of concrete at early age. Under semi-adiabatic temperature history, the maximum compressive stress of concrete specimens with threshold values of 1.5 and 3 was −0.33 MPa and −0.31MPa, while the cracking stress ratio was 1.61 MPa and 1.71 MPa, respectively. Different threshold values have mild influences on the whole thermal stress development when the elastic modulus starts to have a basically stable value.Compared with the experiment results of TSTM, the cracking stress ratio of concrete specimens with threshold value 1.5–3 με was centralized between 0.75–0.8 while the cracking stress ratio of concrete specimens with threshold value 0–1.5 and 3–10 με was relatively discrete. The new evaluation method


Crowd counting is of significant importance for numerous applications, e.g., urban security, intelligent surveillance and crowd management. Existing crowd counting methods typically require specialized hardware deployment and strict operating conditions, thereby hindering their widespread application. To acquire a more effective crowd counting approach, a device-free counting method based on Channel Status Information (CSI) is proposed. The wavelet domain denoising is introduced to mitigate environment noise. Furthermore, the amplitude or phase covariance matrix is extracted as the eigenmatrix. Moreover, both the spatial diversity and frequency diversity are leveraged to improve detection robustness. At the same experimental environment, the accuracy of the proposed CSI-based method is compared with a renowned crowd counting one, i.e., Electronic Frog Eye: Counting Crowd Using WiFi (FCC). The experimental results reveal an accuracy improvement of 30% over FCC. In some overpopulated countries, the contradiction between the limited indoor space and large population is becoming increasingly prominent. Thus, it is of vital significance to implement crowd counting in public places, e.g., libraries, museums, shopping malls and college classrooms, which are with limited resources and strong mobility. In the meantime, it is a crucial and challenging task to acquire the human traffic or accurately calculate the population in some particular circumstances. Therefore, signal changes caused by human motion has been utilized to acquire crowd counting . Since cNumerous crowd counting approaches have emerged over the past decades, e.g., video-based recognition, infrared-based induction, and non-image-based localization. However, these methods all require specialized hardware deployment and strict operating conditions which hinder their wide deployment. First, video-based recognition has the advantages of high-accuracy, rapidness and low-cost, and is applicable to various commercial and security fields. However, it is encountered by some constrains, e.g., many blind spots cannot be monitored and the environmental requirements are high . Second,The legacy crowd counting methods not only consume manpower and materials, but also encounter the statistical error. In recent years, Wireless Sensor Network (WSN) technology has been gradually applied from theoretical research to industries. Besides, some network technologies, e.g., Wi-Fi., are also utilized in the field of crowd counting. The Received Signal Strength Indicator (RSSI) could realize crowd counting from the perspective of localization  and estiThe contradiction between limited indoor space and large population necessitates crowd number counting . MeanwhiWe present a device-free indoor people-counting method based on CSI. Since CSI is relatively stable in the static environment and sensitivity to human bodies, we leverage it to exactly achieve the crowd/people-counting.We utilize the linear transformation to obtain available phase information. In addition, the wavelet denoising is introduced to mitigate environment noises  and get relatively transparent CSI measurements. For multi-dimensional sample data, we extract the amplitude or phase covariance matrix as the eigenmatrix. Since covariance matrix can not only describe multi-dimensional data, but the diagonal elements represent the variance of each dimension.We attempt to combine both space diversity provided by MIMO and frequency diversity supplied by OFDM subcarriers, to enable more robust and accurate counting.We validate a monotonic relationship that lies between the CSI variations and crowd size. In addition, we utilize the percentage in the extension covariance matrix of amplitude and phase as baseline that estimate this relationship. Meanwhile, we compare the differences and similarities between phase and amplitude information in crowd counting.The main contributions of our work are listed as follows:CSI can evaluate the channel information on each subcarrier, and characterize the frequency selective fading characteristics of Wi-Fi channels. In addition, CSI contains the amplitude and phase information on each subcarrier, thereby enhancing richer frequency domain information. Next, we summarize the existing works of the CSI form the aspect of phase and amplitude.The amplitude-based detection. An amplitude-based scheme has attracted more attention in recent years since it is sensitive to adjacent humans, while unrelated background noise remains relatively stable. In this context, Xiao et al.  proposedThe Amplitude and Phase-based detection. Despite the fact that quite a few works have studied CSI for device-free detection, most previous studies only utilized amplitude information but not phase information. However, in , it was Although there are prior works that utilize the CSI amplitude and phase information to conduct detection of moving humans, they typically ignore the relationship between the variation of CSI amplitude or phase and the number of moving people. In our work, an explicit relationship description is concentrated. In addition, we should also seek a baseline to indicate the relationship. Meanwhile, to further illustrate that the phase information is not only available, but is also more sensitive to the environment factors than amplitude information. Therefore, we attempt to respectively utilize the amplitude and phase information to achieve the counting, and exploit the frequency diversity and spatial diversity of CSI to obtain more accurate and robust counting result.First, we obtain CSI observations by different numbers of volunteers and, then, filter out both phase and amplitude noise from original CSI observations through wavelet denoising. It is worth noting that the phase information needs linear transformation.Second, following data preprocessing, we further extract the covariance matrix as the eigenvector from both the amplitude and phase information, respectively.Finally, since multiple transmit and receiver antennas combine into different streams, CSI consists of these streams, which constitute the spatial diversity of CSI. Meanwhile, the multipath effect exists indoors, which makes different subcarriers provide frequency diversity for CSI. This will also make the covariance characteristic vectors more reliable. Therefore, these works will enhance robustness, accuracy, and reliability of our method.Although standard wireless network cards provide RSSI information, the RSSI is only a rough estimate of the wireless channel, and it does not involve a specific number of antennas and subcarriers. Nowadays, some common IEEE 802.11n standard commercial wireless network cards have begun to emerge, which could provide detailed amplitude and phase information on different subcarriers in the form of CSI. The CSI is a type of physical layer information on the subcarrier scale, referring to the channel characteristics of a communication link. This type of information describes how the signal passes through the air from transmitter to receiver, and reflects the fading factor of signal on each transmission path, environmental degradation, signal scattering, and power attenuation with distance, etc.y, x, H and N are respectively denoted as the receive vector, the transmit vector, the channel matrix and the additive white Gaussian noise (AWGN) vector.In the narrow-band flat fading channel, the OFDM system in the frequency domain is modelled asNext, the CSI message, which represents the channel response of multiple subcarriers, is divided into 30 groups. Hence, the CSI value with Environmental factors  might appear with outliers in the CSI measurements, and these outliers would affect the detection performance to some extent. Thus, the measurements of amplitude and phase of CSI will be the basic input for our method, which would be through a wavelet transform denoising process beforehand. The wavelet transform denoising removes the observation value with larger deviations and meanwhile restore original signals as much as possible.R represents a real number set.Given the original signal The associated inverse transformation formula In the following, A suitable feature plays a key role. Nowadays, various statistical features ,23,24 haA and B are utilized to denote the amplitude and phase covariance matrix, respectively, i.e.,i and j, respectively.In the following, Both ith subcarrier can be expressed ast and frequency difference w, respectively.Since there is a random noise and unsynchronized time clock, the raw phase information is unavailable, as shown in To remove the impact of random noise, the linear transformation can be written asD is the dilatation coefficient and q is percentage.Our work aims to achieve crowd counting indoors  settings at the Xi’an University of Technology, that is, the relationship between the number of moving people and CSI amplitude and phase variances is found, respectively. In PEM, presented in , the perWe adopt wavelet transforms to remove the random noise, and then extract both the CSI amplitude and phase covariance matrix as the feature vector.k by k and column j of All elements in the CSI amplitude or phase covariance matrix D are set to “1”, which is called matrix expansion. The size of the expansion is related to the D. After dilation, the M. The matrix M is occupied by more “1”, and usually comes along with the CSI changes drastically.The elements around M is counted, and the percentage of non-zero elements in the matrix M of each subcarrier is calculated by The number of “1” in the matrix The aforementioned crowd counting approach can be listed as follows:Algorithm 1 Crowd Counting based on Channel State InformationRequire: Sample Data       Value of Covariance Ensure: Percentage of Element 1:the covariance matrix is extracted from wavelet transformed data2:fordo3:k is calculated    the integet 4:M is dilated // the element in row k and column j is set to be “1”    the matrix 5:foru = Ddo    6:forv = Ddo        7:M is dilated // the element in a radius of D is set to be “1”           the matrix 8:end for        9:end for    10:end for11:forPdo12:forSdo    13:M = MM of each subcarrier        14:q = q/        15:end for    16:end forp, q indicate the number of transimit and receive antennas, respectively.Nowadays, multiple antennas are adopted in more and more popular MIMO communication systems, since the signal strength variability can be reduced based on small-scale fading compensation. In an MIMO system, both the transmitter and receiver have multiple antennas, and each combination of receiving and transmitting antennas can be regarded as a stream. CSI consists of these streams. In addition, each stream implies a spatial choice. That is, these streams provide spatial diversity for CSI. Due to different propagation paths of diverse streams in the indoor environment, the CSI received by different antennas are differentiated. Therefore, all streams As such, without enhancing the bandwidth and transmission power, multiple antennas can improve the reliability of spatial diversity ,28. FiguTo evaluate the performance of proposed approach, a real experiment platform is built at the elevator. We utilize the AP-link wireless router with two-antennas as transmitter and the PC with three-antennas as receiver, which form monitoring area. As illustrated in Since CSI information is highly sensitive to environmental factors. If too much people closely walk with each other in the monitoring area, it inevitably appears signal occlusion. Therefore, in this paper, the sensing range is 25 mIn this work, the CSI phase or amplitude covariance matrix is extracted to achieve crowd counting. R is constant. Among them, the percentage reveals the relationship between the number of people and CSI variations. Although there is great difference in the percentage when the number of people is different, it would not induce detection errors. D), respectively.The dilatation coefficient is a scaling factor, which used to expand the percentage. We random choose integer 0–20 as scale factor, and this factor is not affected by the environmental change. D is excessively either high or low, then it will affect the detection results. However, when D is equal to 5, 10 and 15, although there exists a monotone increase between percentage and number of people, the curve track is different. Therefore, the different dilation coefficients will bring different experimental results. Many experimental results show that When Crowd counting plays a key role in many applications, but existing counting methods usually require specialized hardware deployment and strict use of conditions which hinder their wide deployment. Therefore, a Device-Free Indoor people-counting Method based on Channel Status Information is proposed in this paper. The experimental results show that a monotonic relationship lies between the CSI variations and crowd size in indoor environments . Meanwhile, from the similarities and differences of amplitude and phase changes that CSI phase has higher detection accuracy and sensitivity. Comparing the proposed method with FCC systems in the same experimental environment, it can be observed that the proposed method can detect more people and have higher counting accuracy, regardless of either the amplitude or phase covariance matrix as the feature vector. In the next step, a method should be proposed to accurately estimate the population in the special environment with more people. Moreover, the more accurate method will be studied when the target has different speeds.


The aim of this study was to investigate the TCR repertoire of peripheral blood CD4+ T cells in IgG4-RD.CD4+ T cells were constructed by 5′-rapid amplification of cDNA ends (5′-RACE) and sequenced by Illumina Miseq platform. The relative similarity of TCR repertoires between samples was evaluated according to the total frequencies of shared clonotypes (metric F), correlation of frequencies of shared clonotypes (metric R), and total number of shared clonotypes (metric D).The peripheral blood was collected from six healthy controls and eight IgG4-RD patients. TCR β-chain libraries of CD4+ T cell repertoire were comparable between healthy controls and IgG4-RD patients, while the proportion of expanded and coding degenerated clones, as an indicator of antigen-driven clonal expansion, was significantly higher in IgG4-RD patients. There was no significant difference in TRBV and TRBJ gene usage between healthy controls and IgG4-RD patients. The complementarity determining region 3 (CDR3) length distribution was skewed towards longer fragments in IgG4-RD. Visualization of relative similarity of TCR repertoires by multi-dimensional scaling analysis showed that TCR repertoires of IgG4-RD patients were separated from that of healthy controls in F and D metrics. We identified 11 IgG4-RD-specific CDR3 amino acid sequences that were expanded in at least 2 IgG4-RD patients, while not detected in healthy controls. According to TCR clonotype networks constructed by connecting all the CDR3 sequences with a Levenshtein distance of 1, 3 IgG4-RD-specific clusters were identified. We annotated the TCR sequences with known antigen specificity according to McPAS-TCR database and found that the frequencies of TCR sequences associated with each disease or immune function were comparable between healthy controls and IgG4-RD patients.The clonal expansion and diversity of CD4+ T cells from eight IgG4-RD patients, TCR repertoires of IgG4-RD patients were different from that of healthy controls in the proportion of expanded and coding degenerated clones and CDR3 length distribution. In addition, IgG4-RD-specific TCR sequences and clusters were identified in our study.According to our study of CD4 Pathologic features of IgG4-RD include dense lymphoplasmacytic infiltration enriched in IgG4-positive plasma cells, storiform fibrosis, and obliterative phlebitis , 2. The  IgG4-RD –7. ThereThe vast majority of T cells express αβ T cell receptors (TCRs), which interacts with peptide-MHC complex presented by antigen-presenting cells , 9. DuriThe analysis of the TCR repertoire has been challenging due to its enormous diversity. During the past decades, the TCR repertoire was analyzed by CDR3 spectratyping, which involves amplification of CDR3 by RT-PCR using V and J gene-specific primers, and separating the amplicons by polyacrylamide gel electrophoresis , 13. Now+ T cells from IgG4-RD patients in depth. We compared the characteristics of CD4+ T cell repertoire between healthy controls and IgG4-RD patients, including expansion and coding degeneracy levels of each clonotype, CDR3 length distribution, and usage of TRBV and TRBJ genes. In addition, we analyzed relative similarities of TCR repertoires between individuals, identified IgG4-RD-specific CDR3 amino acid sequences, and clustered the TCR clonotypes based on sequence similarities to reveal disease-specific clusters. Finally, we analyzed the antigen specificities of TCR clonotypes according to the McPAS-TCR database.Here, using the approach of high-throughput sequencing, we studied the TCR repertoire of peripheral blood CD4We included eight newly diagnosed and untreated IgG4-RD patients, and six healthy controls matched for sex, age, and ethnicity. All of the enrolled patients satisfied the 2011 comprehensive diagnostic criteria for definite IgG4-RD . The pat+ T cells were enriched by positive magnetic-bead selection  according to the manufacturer’s instructions. RNA was extracted from CD4+ T cells using TRIzol (Invitrogen).Peripheral blood mononuclear cells (PBMCs) were isolated from fresh blood by standard Ficoll-Hypaque procedures. CD4TCR β-chain sequences were amplified by 5′-rapid amplification of cDNA ends (5′-RACE), using SMARTer® RACE cDNA Amplification Kit (Clontech). The total RNA input was 1 μg. UPM primer was used as 5′ primer, and TRBC-specific primer, with the sequence “TCTGATGGCTCAAACACAGCGACCT,” was used as 3′ primer. PCR reaction contained 3 μl cDNA, 20 pmol 5′ and 3′ primers, 4 μl 2.5 mM dNTPs, 2.5 U pfu polymerase, and 10 μl 5 × pfu buffer, with the final volume of 50 μl. PCR conditions were 95 °C for 4 min (min), followed by 25 cycles of 94 °C for 30 s, 58 °C for 30 s, and 72 °C for 10 s, and a final extension of 72 °C for 5 min. The amplified TCR β-chain products were then cooled to 4 °C. TCR β-chain sequencing libraries were constructed with NEBNext® Ultra™ DNA Library Prep Kit for Illumina (NEB) and underwent quality control using Bioanalyzer High Sensitivity DNA chip (Agilent). TCR β-chain libraries were sequenced on Illumina Miseq platform (2 × 300 bp).θ of 0.5) and visualized by plotting each event by its t-SNE dimension 1 and dimension 2 in a dot plot.Raw data were processed by Cutadapt software v1.9.1)  to remov.1  to rehttp://www.cytoscape.org/) [TCR repertoire similarities between individuals were evaluated by the following metrics using VDJtools : 1) geope.org/) . IgG4-RDpe.org/) . We anno geope.orpe.org/) , “circlipe.org/) , and “Vepe.org/)  were uset test for the variables following a normal distribution and the Mann-Whitney U test for the variables not following a normal distribution. Correlations between nonnormally distributed variables were analyzed by the Spearman rank correlation test. Outliers identified in this study fulfilled both the Dixon criterion and the Grubbs criterion. Bootstrap resampling was conducted with the following procedures: First, we generated 1000 bootstrap samples by randomly sampling the data from a healthy control or IgG4-RD patients with replacement. Each bootstrap sample had the same sample size as the original dataset. Then, we calculated the mean values in bootstrap samples, analyzed the distribution of bootstrap means according to density plot, and estimated the mean and 95% confidence interval accordingly. The existence of outliers was assessed by bootstrap-based outlier detection plot (Bootlier plot), which is constructed by bootstrapping the statistic “mean-trimmed mean” (MTM) and plotting its distribution [t test with a pooled resampling method for group comparison, according to the recommendation by Dwivedi et al. for small sample size studies [p < 0.05 was considered statistically significant.Differences between the groups were analyzed by Welch’s ribution . The exiribution . We perf studies . For mulThe demographic and clinical characteristics of the individuals enrolled in this study were summarized in Table + T cell clones was assessed by the frequency of clones within a sample. Several clearly expanded CD4+ T cell clones were detected in the background of hundreds of low-frequency clones in each sample . Therefore, we defined the clones with a frequency of ≥ 0.01% to be expanded clones; and the clones with a frequency of ≥ 0.1% to be highly expanded clones. The proportion of both expanded clones and highly expanded clones were comparable between healthy controls and IgG4-RD patients . The proportion of highly expanded clones: healthy controls, 0.080% ± 0.059%; IgG4-RD patients, 0.081% ± 0.054%; Welch’s t test, p = 0.963). We further evaluated the diversity of CD4+ T cell repertoire of each individual based on the Shannon-Wiener index and found that the TCR repertoire diversity was comparable between healthy controls and IgG4-RD patients . The degree of expansion of CD4t test, p = 0.684).Next, we analyzed the coding degeneracy level of each T cell clonotype, which is a measurement of the number of unique nucleotide sequences encoding a single CDR3 amino acid clonotype, resulting from the degeneracy of genetic code . Here, w+ T cells from peripheral blood. The proportion of expanded (frequency ≥ 0.01%) and coding degenerated (coding degeneracy level ≥ 2) clones was significantly higher in IgG4-RD patients , which suggests the antigen-driven clonal expansion of CD4+ T cells in IgG4-RD.Based on the fact that the antigen specificity of TCR is determined by the amino acid sequence, the antigen-driven clonal expansion of T cells should increase the frequency of all the TCR nucleotide clonotypes encoding for the same CDR3 amino acid sequence. Therefore, the expanded and coding degenerated clones are likely driven by antigen-specific expansion, while antigen-nonspecific expansion increases only clonal frequencies, not coding degeneracy levels . We obset test with a pooled resampling method, which gave similar results as the previous analysis by Welch’s t test  and combined the sequences from the same group together. Analysis by the Mann-Whitney U test revealed a significant difference in CDR3 length distribution between healthy controls and IgG4-RD patients (p < 0.001).We further investigated the CDR3 length distribution of CD4+ T cells were identified from the 14 individuals. Among them, 233,328 clonotypes were found in healthy controls, 176,225 clonotypes were found in IgG4-RD patients, and 18,129 clonotypes were shared between healthy controls and IgG4-RD patients  with a Levenshtein distance of 1 . All the+ T cell clonotypes, we referred to the McPAS-TCR database, which assembled all the TCR sequences with known antigen specificity based on the published literature and classified the immune functions into 4 categories: pathogens, autoimmune, cancer, and allergy [+ T cell repertoire of our dataset. TCR repertoires were downsampled to 158,416 sequences per sample, and the frequencies of sequences associated with each disease were shown in Fig. In order to reveal the antigen specificity of CD4 allergy . AccordiWe also looked up the IgG4-RD-specific sequences identified above Table b in the + CTLs, which drives the inflammatory and fibrotic processes [+ T cells in the pathogenesis of IgG4-RD have been demonstrated by this model. Here, using next-generation sequencing, we investigated the TCR repertoire of CD4+ T cells from IgG4-RD patients in-depth, in order to reveal the characteristics of immune repertoire in IgG4-RD.The pathogenesis of IgG4-RD has been proposed that Tfh cells induce IgG4 class-switching and differentiation of plasmablasts and plasma cells , 32, androcesses , 32. The+ T cells was comparable between healthy controls and IgG4-RD patients, revealed by the proportion of TCR clonotypes in each expansion level, as well as the diversity of TCR repertoire calculated by the Shannon-Wiener index Additional file 4. : Comparison of TRBV gene usage between healthy controls and IgG4-RD patients.Additional file 5. : Comparison of TRBJ gene usage between healthy controls and IgG4-RD patients.Additional file 6. : Comparison of the 100 most frequently-used TRBV-TRBJ combinations between healthy controls and IgG4-RD patients.Additional file 7. : Bootstrap resampling for the frequency of sequences associated with each immune function. Bootstrap resampling was applied to the following parameters: the frequency of TCR sequences associated with pathogens, autoimmune, cancer, and allergy. Left panel: The distribution of bootstrap means of each variable in healthy controls and IgG4-RD patients. Estimated means and 95% confidence intervals of each variable were also displayed on the plot. Middle panel: Bootlier plot of each variable in healthy controls and IgG4-RD patients. Results of Bootlier test were also displayed on the plot. Right panel: Group comparison by nonparametric bootstrap t-test with pooled resampling method. Bootstrap t values were calculated according to Dwivedi et al. [i et al. . The dis


Preparation of organic–inorganic hybrids with conventional conjugated polymers such as polyfluorene (PF) and poly(3-hexylthiophene) (P3HT) were demonstrated via the facile blending in solution by employing polyhedral oligomeric silsesquioxane (POSS) having heterogeneous alkyl substituents. From the optical measurements, it was shown that the modified POSS derivatives played a critical role in facilitating amorphous state of polymer matrices. Interestingly, although inter-strand interaction decreased after POSS addition in the hybrid films, thermal stability can be enhanced in the presence of the modified POSS with long alkyl chains. Furthermore, it was demonstrated that carrier mobilities through the hybrid film was minimally reduced by POSS. These results suggest that POSS should be a versatile building block to form hybrid with various types of polymers for enhancing durability without loss of electronic properties of organic components. By mixing organic molecules and inorganics at the nano level, robust materials, called organic–inorganic hybrids, are created, which have multiple functions originating from both components . BecausePolyhedral oligomeric silsesquioxane (POSS) has attracted attention for preparing functional hybrids ,8,9,10 aHerein, we report the influence on electronic properties and enhanced thermal stability of hybrids composed of conjugated polymers by loading POSS derivatives having dual types of alkyl substituents. Three types of heterogeneous POSS derivatives with two kinds of alkyl substituents were synthesized, and. from the solution method, polymer hybrids with conventional conjugated polymers such as polyfluorene (PF) and poly(3-hexylthiophene) (P3HT) were prepared by loading octa-substituted alkyl POSS. The series of measurements for optical and thermal properties and carrier-transport ability revealed that the heterogeneous POSS derivatives can improve thermal stability without critical losses of other properties. This is the first example, to the best of our knowledge, demonstrating the applicability of POSS “element-block” for fabricating hybrids with conjugated materials without losses of optoelectronic properties of conjugated polymers.iso-butyl (iC4) and cyclopentyl (CP) groups on POSS have relatively lower affinity toward conjugated polymers and induced loss of thermal stability, while the octadecyl (C18) group can enhance thermal stability of the matrices . It. It34]. Luminescent properties were also examined with the hybrid films . In the Next, thermal stability of the hybrid films was evaluated with thermogravimetric analysis TGA, . Degrada−3 cm2 V−1 s−1. Compared to each pristine polymer, significant changes in the mobility were not observed. Furthermore, the carrier mobilities decreased with an increasing external electrical field with similar extents  experiment in which the transient photocurrent generated with a laser pulse was monitored by an oscilloscope  40,41,4,441,42.  extents . TypicalIt was demonstrated that POSS “element-blocks” enable transformation of conjugated polymers into thermally-stable hybrid materials without critical losses of optical and electronic properties provided by the organic components. This was accomplished by POSS cages controlling the solid-state packing within the hybrid composition. Moreover, by selecting the type of substituents as the longer alkyl chain on POSS, miscibility was enhanced, indicating that hybrid formation based on POSS “element-blocks” possess a wide applicability to various polymer matrices. This information on property–structure relationships would be helpful for designing further effective fillers for modulating optoelectronic functions as well as thermal properties of conjugated polymers. In the development of organic opto-electronic devices, reinforcement of durability is still one of big issues to be overcome. Our concept and materials could be valid to satisfy these demands.


ZBTB16 locus encoding PLZF, is repressed by Polycomb (PcG) and H3K27me3 in naive hMSCs. At the pre-osteoblast stage of differentiation, the locus lost PcG binding and H3K27me3, gained JMJD3 recruitment, and H3K27ac resulting in high expression of PLZF. Subsequently, PLZF was recruited to osteogenic enhancers, influencing H3K27 acetylation and expression of nearby genes important for osteogenic function. Furthermore, we identified a latent enhancer within the ZBTB16/PLZF locus itself that became active, gained PLZF, p300 and Mediator binding and looped to the promoter of the nicotinamide N-methyltransferase (NNMT) gene. The increased expression of NNMT correlated with a decline in SAM levels, which is dependent on PLZF and is required for osteogenic differentiation.The PLZF transcription factor is essential for osteogenic differentiation of hMSCs; however, its regulation and molecular function during this process is not fully understood. Here, we revealed that the  Human mesenchymal stem cells (hMSCs) possess self-renewal and multi-lineage differentiation potential toward osteogenic, chondrogenic and adipogenic specification . TherefoEnhancers are cis-acting DNA regulatory elements that function as transcription factor (TF) binding platforms, increasing the transcriptional output of target genes through chromatin topological changes involving enhancer-promoter looping . BindingZBTB16 gene locus encodes a BTB/POZ domain and zinc finger containing TF known as PLZF  as atterning . These sZBTB16 (PLZF) locus is bound and repressed by PcG proteins and extensively H3K27 tri-methylated (H3K27me3) in naive hMSCs. Upon osteoblast commitment of progenitor cells (pre-osteoblast stage), H3K27me3 demethylation takes place through JMJD3  recruitment to the ZBTB16 locus, followed by extensive H3K27 acetylation and PLZF expression. Interestingly, upon expression, PLZF binds to a subset of enhancers, which gain H3K27 acetylation and correlates with induced expression of nearby genes important for osteogenic differentiation and function. Intriguingly, an initially PcG-repressed enhancer within the ZBTB16 locus becomes active in pre-osteoblasts, gaining PLZF, p300 and Mediator binding. By use of Chromosome Conformation Capture combined with high-throughput sequencing (4C-seq)  and regulate its expression during osteogenic differentiation.Through the use of genome-wide ChIP-sequencing and expression analysis, we now present evidence for a novel function of PLZF at developmental enhancers directing osteogenic differentiation of hMSCs. Interestingly, we find that the (4C-seq) , we showZBTB16 (PLZF) gene locus is an important event during osteogenic differentiation. PLZF regulates osteogenic differentiation of hMSCs through binding at gene enhancers and thereby it positively affects transcription of lineage-specific genes. The enhancer, EnP, localized within the ZBTB16 locus is an example of a latent developmental enhancer that becomes active upon differentiation and regulates NNMT expression in a PLZF-dependent manner through Mediator and RNA-PolII recruitment and enhancer-promoter looping.Taken together, our data reveal that the activation of the To understand the transcriptional events that control the osteogenic differentiation of hMSCs, we performed RNA-seq analysis for global expression levels and ChIP-seq analysis for histone marks known to be associated with transcriptionally repressed (H3K27me3) and active  gene loci. We looked for the changes taking place at an early time point of differentiation (10 days) as compared to naive hMSCs (day 0). BMP4, BMP6, IGF2, IGFBP2; gene products known to promote osteogenic differentiation  Leptormation , 3) ZBTBelopment . Exampleelopment , H3K27meelopment .ZBTB16 locus including intragenic exons and 3’UTRs   already at day 2 of differentiation which corresponds to pre-osteoblasts. We therefore analyzed the ZBTB16 locus for the presence of PcG proteins and H3K27me3 levels at day 2 of osteogenic differentiation. Interestingly, we observed a loss of H3K27me3 and binding of the PRC2 subunit SUZ12 already in pre-osteoblasts (ZBTB16 locus and high expression of the PLZF (The tterning . Intrigutiation) . Observieoblasts . These dthe PLZF  was an eRUNX2, often referred to as the master regulator of bone formation  and SOX5/8 (chondrocytic commitment) and SPP1 (osteopontin) (SP7 (osterix) and BGLAP , markers of the mineralization stage  were repmmitment). In addiopontin)  were stropontin) , while Son stage  were stide novo motif analysis of the DNA sequences within the PLZF peaks, compared to sequences from negative control regions, revealed a significant occurrence of a TACAGC motif (E = 1.1 × 10−81), which is highly similar to the TAC(T/A)GTA PLZF motif identified by Ivins et al.  and immature osteoblasts (day 10 of differentiation). We identified 2,282 PLZF peaks that were observed only in immature osteoblasts . The anas et al.   and PRC2 (SUZ12) as well as the H3K27me3 repressive mark catalyzed by PRC2 . In contActivating transcription factors often recruit histone acetyl transferases (HATs) leading to H3K27 acetylation as part of the gene activation mechanism . To inve−8, Fisher’s exact test) and osteoblasts  , which can be detected by global 5’ end RNA sequencing (CAGE). In the FANTOM5 project, this technique was used to create an atlas of 43,011 CAGE-predicted active enhancer regions across numerous cell types (432 primary cell types and 241 cell lines) and tissues (135 tissues) . When coct test)  (it shouct test) .To further investigate the relationship between PLZF recruitment to enhancers and changes in H3K27ac genome wide, we performed siRNA-mediated PLZF knockdown in naïve hMSCs followed by induction of osteogenic differentiation, and H3K27ac ChIP-seq. We tested three different siRNA oligos targeting PLZF . All thrExamples of regions showing a gain of H3K27ac in a PLZF-dependent manner are shown as ChIP-seq tracks in To further gain insight to the transcriptional changes taking place in the absence of PLZF during osteogenic differentiation, we performed a whole transcriptome analysis by RNA-seq after siRNA-mediated PLZF knockdown in hMSCs. There were 1,897 genes differentially regulated upon osteogenic induction in control siRNA-transfected hMSCs compared to 1,184 genes differentially regulated in PLZF knockdown cells. Only 44%  of these genes overlapped between control siRNA and PLZF knockdown cells . As showZBTB16 locus itself (Enhancer within PLZF locus bound by PLZF) and decided to further characterize it as an example of a PLZF-bound osteogenic enhancer. To validate, that the PLZF-bound intragenic EnP element correspond to a functional enhancer, we examined the presence of histone marks and gene regulatory factors known to bind enhancers by ChIP QPCR. First, we analyzed a number of relevant histone modifications and confirmed that the EnP element gained H3K4me1 and H3K27ac in pre-osteoblasts as compared to naive hMSCs, but contained low levels of H3K4me3 and H3K36me3 compared to other regions within the ZBTB16 locus (ZBTB16 locus in pre-osteoblasts correlating with transcription of the gene (ZBTB16 locus (ZBTB16 locus represents a latent (no H3K4me1 and no H327ac) PcG repressed enhancer in naive hMSCs which gains the characteristics of an active enhancer in pre-osteoblasts.Interestingly, among the PLZF-bound genomic regions, we identified the s itself . Multipl16 locus . The gaithe gene . We obta16 locus . It is w16 locus . Moreove16 locus . We ther16 locus . Taken tZBTB16 locus (CtE) that did not show PLZF binding. There was a complete absence of GFP fluorescence in hMSCs infected with the CtE-GFP element or empty vector control  homeostasis. NNMT functions in a biochemical reaction where it transfers the methyl group from SAM to nicotinamide and converts SAM to SAH (S-adenosyl-homocysteine)   (Aksoy eysteine) . To inveZBTB16 locus, which regulates the expression of NNMT and thereby SAM homeostasis upon osteogenic differentiation of hMSCs.Overall, these results provide evidence for a dynamic activation and function of a lineage specific developmental enhancer EnP present within the NNMT expression. We tested three different siRNA oligos to target NNMT and found all three oligos showed significant knockdown efficiency  normally observed during osteogenic differentiation suggesting a block in differentiation.To further characterize the effect of NNMT on osteogenic differentiation of hMSCs, we used siRNA to knock-down ficiency . As showNNMT expression. Therefore, we first investigated if PLZF knockdown had any influence on NNMT expression. Interestingly, the knockdown of PLZF negatively influenced NNMT gene induction  within this locus that is repressed by PcG and H3K27me3 in naive hMSCs but becomes highly active at an early stage of osteogenic differentiation of hMSCs. Our data also demonstrate the differentiation-specific looping of EnP to its target promoter of the ntiation .ZBTB16 expression (data not shown). These observations suggest that PLZF functions at an early state of hMSCs differentiation and promotes the transition from the naive stem cell stage to a more committed state for all three lineages. Therefore, to obtain specific gene expression patterns that characterize the three different lineages and their functions, other cell-type-specific TFs must operate together with PLZF at enhancers in a context dependent manner. Recently, the genome-wide binding profile for Runx2 was characterized in mouse pre-osteoblastic cell lines and suggested a possible link of this TF to enhancer function  and gene regulatory factors such as Mediator, p300 and PLZF. Intriguingly, a reporter assay in which EnP was integrated in the genome of hMSCs cells showed that EnP functions only upon induction of differentiation. This suggests that the EnP enhancer element in the context of a GFP reporter also require lineage-specific factor(s) such as PLZF for its activity.EnP that lies within the ZBTB16 locus that we found to be in contact with the promoter of the NNMT gene covered an area around 50 kb and included introns 3–5 which showed a strong enrichment for H3K27ac and H3K4me1 upon osteogenic differentiation and gained PLZF binding at several positions. These characteristics suggest that this ZBTB16 intragenic region could represent a cluster of several active enhancers  levels through methylation, using SAM as a methyl donor  were purchased from Lonza . Cell purity and their ability to differentiate into osteogenic, chondrogenic and adipogenic lineages were tested by Lonza. Cells were positive for CD105, CD166, CD29, and CD44. Cells tested negative for CD14, CD34 and CD45. Cells were cultured according to manufacturer’s instructions using mesenchymal stem cell growth medium (MSCGM) (Lonza MSCGM: PT-3238) supplemented with one MSCGM SingleQuots (PT-4105). Differentiation was induced using StemPro osteogenesis (Gibco A10072-01), chondrogenesis (Gibco A10071-01) or adipogenesis (Gibco A10070-01) differentiation kit as per manufacturer’s instructions. Cells were harvested at the indicated time points for ChIP, RNA, 4C-seq and protein using appropriate buffers as described below.Mission siRNA oligos were ordered from Sigma. Three different oligos were tested and sequences are provided in the 6 cells were mixed in the transfection mix and incubated for another 10 min. Cells in the transfection mix were seeded in dishes  with normal HMSCB media. Osteogenic differentiation was induced 24 hr after transfection and cells processed for analyses at indicated time points.The hMSCs were reverse transfected with siRNA oligos using Lipofectamin 2000 and Optimem media (Gibco). Briefly, 600 pmol of siRNA (in 500 μl Optimem was mixed with 10 μl Lipofectamin 2000 (Invitrogen) in 500 μl Optimem. After 15 min of incubation at room temperature, 1 × 103, 2% (w/v) SDS; Triton Dilution Buffer-: 100 mM Tris-HCl, (pH 8.6), 100 mM NaCl, 5 mM EDTA, (pH 8.0), 0.2% (w/v) NaN3,5.0% (v/v) Triton X-100) using a Branson Sonifier (4 cycles of 30 s each at 22% of max amplitude). Twenty μg DNA (sonicated chromatin) was used for each ChIP in IP buffer. Antibodies used: Rabbit general IgG (DAKO), rabbit monoclonal anti-H3K27me3 , anti-SUZ12 , RING1B (produced in our lab), H3K4me3 , H3K27ac (Abcam # ab4729), H3K4me1 (Abcam # 8895), , H3K36me3 , PLZF (Santa Cruz # sc-22839), P300 (Santa Cruz # sc-585), RNA POLII (Santa Cruz # sc 9001X), MED1/TRAP220 (BETHYL # A300-793A), MED12 (BETHYL # A300-774A), JMJD3 (produced in our lab)). Samples were first incubated with antibodies overnight at 4°C by end-over-end rotation and subsequently immune-complexes were enriched using incubation with protein A-Sepharose beads for 3 hr. After washing the samples were de-crosslinked overnight at 68°C (shaking) in ChIP Elution Buffer (20 mM Tris-HCl (pH7.5), 5 mM EDTA (pH 8.0), 50 mM NaCl, 1% (w/v) SDS, 50 μg/ml Proteinase K). Finally, enriched DNA was purified using a Qiagen PCR purification kit. The ChIPs were validated at Polycomb target genes by QPCR.Cells were processed for ChIP as previously described with slight modifications . BrieflyChIP DNA from three parallel ChIPs were pooled or individual ChIPs from three biological replicates were used and 10 ng each was used for making ChIP-seq libraries. The libraries were prepared using ‘ChIP seq DNA sample preparation kit’ from Illumina following manufacturer’s instructions. Individual samples were runsequenced in a single lanes on HiSeq2000 (Illumina). H3K27ac samples were or multiplexed (using NEB kit) and run on a Illumina Genome Analyzer IIx, HiSeq2000 (Illumina), or NextSeq500 as single end sequencing.Templates for 4C were prepared as described previously . The enz7 cells per group) were harvested and fixed in 2% (v/v) formaldehyde in PBS, 10% (v/v) FBS, for 10 min with rotation at room temperature. The procedure was continued as described earlier  or naive hMSCs , 98°C (15 s), 58°C (1 min), 72°C (3 min), repeated for 30 cycles and final amplification for 7 min at 72°C using Phusion High Fidelity DNA Polymerase (Thermo Scientific).SAM was measured using the Bridge-It S-Adenosyl Methionine (SAM) Fluorescence Assay Kit from Mediomics according to the manufacturer’s instructions . Osteogenic differentiation of hMSCs was induced and cells were harvested after 2 days together with naïve cells and processed for SAM assay. The procedures was followed as described in the assay kit manual.GAPDH was used for normalization. The sequences of the primers used are listed in the Total RNA representing the indicated time points were purified from hMSCs using RNeasy Plus Mini kit (QIAGEN 74106), and cDNA was generated by RT-PCR using the TaqMan Reverse Transcription Reagents (Applied Biosystems#N808-0234). Quantifications were done using the Fast SYBR Green Master Mix (Applied Biosystems#4385612) and an ABI Step One Plus instrument. For RNA sequencing, samples were processed using a True Seq RNA Sample preparation kit (Illumina # 15025062) following the manufacturer’s instructions. Samples were multiplexed and sequenced in HiSeq2000.ZBTB16 locus) or control element region without a PLZF peak within the ZBTB16 locus (CtE) were PCR amplified from genomic DNA (gDNA) isolated from hMSCs using primers described in the primer Table and cloned into the PCR8 TOPO TA vector (Invitrogen). The relevant fragments were cut out from the TOPO vector using EcoRI sites and subsequently cloned into the pSINMIN vector using EcoRI sites. Positive clones were confirmed by sequencing.The pSINMIN lentiviral ‘enhancer reporter vector’ was kindly provided by Johanna Wysoca’s lab . The enh6 cells per 15 cm dish (Nunc cell culture) using the CaPO4 method. 48 hr following transfection and media change the supernatant containing viral particles were collected and filtered through 0.45 μm filters. Polybrene was added to the supernatant 8 μg/ml and hMSCs were infected with virus overnight. Cells were trypsinised and reseeded 48 hr later and Puromycin (0.5 μg/ml) was added for selection. Two days later, osteogenic differentiation was induced and cells were harvested after 2 days for flowcytometric analyses or gDNA isolation. Genomic DNA was isolated using the DNeasy Blood and tissue kit (QIAGEN: 69504). Quantitative PCR was performed using GFP primers described in the primer Table. QPCR on the HOXD locus was used for normalization. Untransduced hMSCs were used as a control.Lenti-virus were produced by transfecting 20 μg reporter plasmid together with 15 μg PAX8 and 6 μg of VSV in 293FT cells seeded at a density of 5 × 10Western blotting was performed according to standard procedures. The cells were lysed in high salt lysis buffer (50 mM Tris-HCl (pH 7.2), 300 mM NaCl, 0.5% (w/v) Igepal CA-630, 1 μg/ml aprotinin, 1 μg/ml leupeptin, 1 mM PMSF, 1 mM EDTA (pH 8.0), 50 mM NaF, 20 mM β-glycerophosphate) followed by a brief sonication on a Branson Sonifier with a 2 mm probe (10% of max amplitude for 2 s on ice). Samples were left on ice for 30 min, then centrifuged at 22,000 g for 15 min. Ten percent Tris-glycine or 4–12% Bis-Tris SDS-PAGE gels (Invitrogen) were used to separate proteins for analyses. Seablue Plus two prestained marker (Invitrogen) was used as a molecular weight standard. Blotting was performed using the following antibodies: PLZF (Santa Cruz # sc-22839), NNMT (Abcam # ab58743), GAPDH (Abcam # ab8245), cyclinE , pRB2 .Naive or osteogenic induced hMSCs were washed two times with PBS followed by fixation in 96% ethanol for 15 min at room temperature. Alizarin red solution 1%  was added to the fixed cells and incubated for 60 min at room temperature with gentle rotation. Finally, cells were carefully (not to lose precipitates) washed three times with water and dried. Pictures were taken with a Leica camera (DFC295) fitted to a microscope at 20X magnification.http://easeq.netReads were trimmed for low-quality nucleotides and mapped to the hg19 human genome sequence using Bowtie v0.12.7  using thSpecific PLZF peaks were identified using the IgG library data set as negative control. The procedure resembles that of MACS with some modifications . Each dahttp://meme-suite.org   as per their guidelines. Normalized gene expression was calculated using following formula (by the software):NE = c * #reads / (#reads * length) where NE is the normalized expression or enrichment value,#reads: the reads (sum of base pairs) of falling into either the transcript or the cluster region,7.#reads: all mapped reads (in base pairs),length: the transcript or cluster length in base pairsand c a normalization constant set to 10http://www.ColorBrewer.org  experiments are performed indicating an interaction of the latent enhancer within the ZBTB16 locus and the NNMT gene, which is not dependent on PLZF induction. Induction of the expression of NNMT, which catalyzes the conversion of nicotinomide to N1-methyl nicotinomide in a SAM-dependent manner, results in a modest but significant reduction of SAM levels. Knockdown of the NNMT using an siRNA results in a striking block of induction of ZBTB16 and ALPL mRNA during osteogenesis. The authors conclude that PLZF functions in enhancer activation and that the latent enhancer within its locus regulates the expression of NNMT during osteogenic differentiation. The findings are of interest, but there are several concerns with respect to the strength of some of the main conclusions.The manuscript from Singh et al. reports on genomic roles of PLZF during lineage commitment of human mesenchymal stem cells and evidence for a latent enhancer within the Essential revisions:1) The general pattern of PLZF binding is probably sound based on the absence of peaks in PLZF knockdown cells but the ChIP-seq experiments do not meet current standards for reproducibility. ChIPs from three independent experiments were pooled for sequencing. It is not possible from this experimental design to establish biological reproducibility of the peaks. This requires independent sequencing of ChIP products and application of statistical methods such as IDR. In addition, a table of general metrics for sequencing should be provided to help with data interpretation, including number of uniquely mapped reads, ChIP efficiency (fraction of reads in peaks) etc.NNMT. This is important because of the potential for significant off-target effects of siRNAs. The striking effect of the NNMT siRNA on PLZF and ALPL expression during osteogenic differentiation should be clearly established by more than one siRNA.2) Specificity of siRNA knockdown. Although the methods section indicates that three different siRNAs were tested for PLZF, it is not evident that the three siRNAs generated the same result for PLZF or 3) Role of PLZF in enhancer activation. The ChIP-seq data indicates that PLZF primarily binds to a pre-existing enhancer landscape, with a significant faction of these regions showing an increase in H3K27ac. However, the cause-effect relationship between PLZF binding and gain in H3K27ac is not established. Many other factors are induced during osteogenic differentiation and could be the primary drivers of this change. A cause-effect relationship requires performing ChIP-seq for H3K27ac during osteogenic differentiation in cells in which PLZF has been knocked down.Zbtb16 knockout leads to a skeletal defect , it is not necessarily an osteogenic defect. The only experiment evaluating effects of PLZF knockdown on gene expression is the Western blot for NNMT in Figure 6A, which does appear to show a difference at days 2 and 5 (but not day 10). However, there is no quantitative or statistical analysis of this finding and effects on mRNA levels are not provided. At this stage, there is no convincing evidence that PLZF plays an important role in regulating an osteogenic program of gene expression in this model system. This would require transcriptomic profiling in the PLZF knockdown cells.4) Most importantly, there are no transcriptomic studies of the consequences of PLZF loss of function. Although it was shown that NNMT seems weak.5) The role of the enhancer EnP is not sufficiently dissected. While its activation is well supported by chromatin changes and by a retroviral enhancer assay, deletion of this enhancer should be performed, for example by CRISPR/Cas, to establish its physiological relevance. The 4C data in Figure 4 look rather unconvincing and are not statistically analyzed, and the impact of PLZF on 6) There are many instances of figure panels lacking measures of statistical significance between experimental groups e.g., all of Figures 3, 5A, E, F, G, 6C, D, E, F.eLife.Thank you for submitting your work entitled "PLZF targets developmental enhancers for activation during osteogenic lineage commitment of human mesenchymal stem cells" for consideration by eLife. One of the key conclusions from the Abstract of your manuscript was, 'Together, we show, PLZF functions in enhancer activation…' This conclusion was based on an association of PLZF binding with genomic regions that gain histone acetylation during the differentiation process. An essential revision was to perform ChIP-seq experiments in cells lacking PLZF to establish that H3K27ac was PLZF-dependent. The data provided in Figure 3 of the plan for revision indicates no change in the gain of H3K27ac at the enhancer EnP in the PLZF knockdown cells. This experiment argues against the main conclusion that PLZF targets developmental enhancers for activation during osteogenic lineage commitment of human mesenchymal stem cells, as stated in the title. Therefore, while you can address many of the other points raised as essential revisions, the central underlying mechanisms for how PLZF would alter programs of osteogenic differentiation are not established. Unfortunately, we think that the manuscript is no longer an appropriate candidate for eLife.We have considered the response you provided with regard to your plan for a revision and we regret to inform you that your work will not be considered further for publication in Reviewer #1:Zbtb16, is involved in the osteogenic-differentiation of hMSC. PLZF binds to osteogenic enhancers. Furthermore, the upregulation of Zbtb16 correlates with gain in H3K27 acetylation of osteogenic enhancers. Among these enhancers the authors demonstrated that an EnP enhancer occupied by PLZF within the PLZF locus loop to the neighboring gene NNMT and correlate with gain of NNMT expression during lineage commitment. Overall, the analysis of extensive genomic data is carefully done. However, there are several points need to be addressed to consolidate the conclusion that Zbtb16 is a key osteogenic factor in MSC differentiation model.In this article, the authors made a strong case that PLZF, encoded by Zbtb16 by itself block osteogenic differentiation (instead of just correlate with osteogenic differentiation)? Although it was shown that Zbtb16 knockout leads to skeletal defect , it is not necessarily an osteogenic defect (such as it could be chondrogenic defect).1) Would knockout of Zbtb16 obliterate H3K27ac binding signal in the PLZF bound enhancers? Or alternatively, would Zbtb16 gain of function increase the H3K27ac signal across PLZF bound enhancers? What are the changes in transcriptome with PLZF loss/gain of function? What other factors bind to the same sets of enhancers PLZF bind in osteogenesis related context? (This can be done by leveraging published ChIP-seq data in the context of osteogenesis.)2) Similarly, although the evidence that PLZF binds to active enhancers are strong, the evidence that the occupancy of PLZF leads to the active enhancer status is lacking. Would knockout/knockdown of PLZF-NNMT locus is likely co-regulated by a cluster of enhancers , is there any functional data to show the importance of EnP enhancer in this context?3) The EnP enhancer is very interesting, could the author demonstrate that the EnP-GFP+ cells are in a more primed/committed state than GFP- cells? This can be done by FACS-GFP and RNA-seq. Given that the entire 4) In the title it states that PLZF targets developmental enhancers. Is there any direct evidence to suggest that these enhancers are 'developmentally' involved? Such as cross reference with vista enhancer browser enhancers.Reviewer #2:Zbtb16 is induced during differentiation of hMSCs into osteoblasts in vitro. In addition, they focus on an enhancer called EnP within the Zbtb16 locus that is bound by the PLZF protein and loops to the promoter of the neighboring NNMT gene to regulate its expression. There are major gaps in this scenario.Singh et al. report that PLZF encoded by The function of PLZF in human MSC is not established since the authors do not present loss or gain of function studies, only a ChIP-seq analysis that shows binding to some osteoblastic genes among thousands of genes. In addition, they mention that PLZF is similarly induced during adipocyte and chondrocyte differentiation, which casts doubt on its specificity for osteoblasts. In fact, there are no in vivo data or reference to support the contention that PLZF regulates osteoblastic differentiation in human. The mouse literature indicates a role of PLZF in skeletal patterning through regulation of HOX genes, not osteoblastic regulation. Finally, the PLZF ChIP-seq analysis is incomplete: the authors do not assess the presence of a DNA binding motif for PLZF, or compare their data with previous reports in human cells or in mouse NKT cells.NNMT seems weak. Therefore, the author's scenario describing a looping of this enhancer to the neighboring NNMT gene promoter and the suggestion that this may regulate global functions of methylation that impact osteoblastic differentiation remain vague and hypothetical.The role of the enhancer EnP is not sufficiently dissected. While its activation is well supported by chromatin changes and by a retroviral enhancer assay, deletion of this enhancer should be performed, for example by CRISPR/Cas, to establish its physiological relevance. The 4C data in Figure 4 look rather unconvincing and are not statistically analyzed, and the impact of PLZF on Reviewer #3:ZBTB16/PLZF locus that is developmentally induced and regulates expression of the NNMT gene to influence cellular levels of SAM. The studies are of general interest with respect to understanding mechanisms of osteogenic differentiation. The authors demonstrate that PLZF is strongly induced at an early time point during osteogenic differentiation, coinciding with loss of the repressive H3K27me3 mark and gain of H3K27ac. ChIP-seq studies indicate that PLZF primarily binds to intra- and intergenic regions with features of enhancers, many of which exhibit increases in H3K267ac during differentiation and are near genes that are enriched for relevant functional annotations. Chromatin conformation capture (4C) experiments are performed indicating an interaction of the latent enhancer within the ZBTB16 locus and the NNMT gene, which is not dependent on PLZF induction. Induction of the expression of NNMT, which catalyzes the conversion of nicotinomide to N1-methyl nicotinomide in a SAM-dependent manner, results in a modest but significant reduction of SAM levels. Knockdown of the NNMT using an siRNA results in a striking block of induction of ZBTB16 and ALPL mRNA during osteogenesis. The authors conclude that PLZF functions in enhancer activation and that the latent enhancer within its locus regulates the expression of NNMT during osteogenic differentiation. The findings are of interest, but there are several concerns with respect to the strength of some of the main conclusions.The manuscript from Singh et al. reports on genomic roles of PLZF during lineage commitment of human mesenchymal stem cells and evidence for a latent enhancer within the 1) The general pattern of PLZF binding is probably sound based on the absence of peaks in PLZF knockdown cells but the ChIP-seq experiments do not meet current standards for reproducibility. ChIPs from three independent experiments were pooled for sequencing. It is not possible from this experimental design to establish biological reproducibility of the peaks. This requires independent sequencing of ChIP products and application of statistical methods such as IDR. In addition, a table of general metrics for sequencing should be provided to help with data interpretation, including number of uniquely mapped reads, ChIP efficiency (fraction of reads in peaks) etc.2) Specificity of siRNA knockdown. Although the Materials and methods section indicates that three different siRNAs were tested for PLZF, it is not evident that the three siRNAs generated the same result for PLZF or NNMT. This is important because of the potential for significant off-target effects of siRNAs. The striking effect of the NNMT siRNA on PLZF and ALPL expression during osteogenic differentiation should be clearly established by more than one siRNA.3) Role of PLZF in enhancer activation. The ChIP-seq data indicates that PLZF primarily binds to a pre-existing enhancer landscape, with a significant faction of these regions showing an increase in H3K27ac. However, the cause-effect relationship between PLZF binding and gain in H3K27ac is not established. Many other factors are induced during osteogenic differentiation and could be the primary drivers of this change. A cause-effect relationship requires performing ChIP-seq for H3K27ac during osteogenic differentiation in cells in which PLZF has been knocked down.4) The studies provide limited evidence for a role of PLZF in osteogenic differentiation. Most importantly, there are no transcriptomic studies of the consequences of PLZF loss of function. The only experiment evaluating effects of PLZF knockdown on gene expression is the Western blot for NNMT in Figure 6A, which does appear to show a difference at days 2 and 5 (but not day 10). However, there is no quantitative or statistical analysis of this finding and effects on mRNA levels are not provided. At this stage, there is no convincing evidence that PLZF plays an important role in regulating an osteogenic program of gene expression in this model system. This would require transcriptomic profiling in the PLZF knockdown cells.5) There are many instances of figure panels lacking measures of statistical significance between experimental groups i.e., all of Figure 3, 5A, E, F, G, 6C, D, E, F.[Editors’ note: what now follows is the decision letter after the authors submitted for further consideration.]eLife. Your revised article has been favorably evaluated by Jessica Tyler as the Senior Editor, a Reviewing Editor, and 1 reviewer.Thank you for resubmitting your work entitled "PLZF targets developmental enhancers for activation during osteogenic differentiation of human mesenchymal stem cells" for further consideration at The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance. The first relates to the fact that it was not possible to generate replicates for the ChIP-seq analysis of PLZF due to discontinuation of the original antibody. The reviewers concur that motif analysis of the existing data set yielded the correct motif and that locus-specific confirmation of PLZF binding was performed at key genomic locations using the original antibody for biological replicates. However, it is not clear whether the additional antibodies tested included an antibody recently demonstrated to work for PLZF ChIP-seq in human cells. Second, while new transcriptomic analysis of the consequences of loss of function of PLZF during osteogenic differentiation was performed, the analysis is difficult to follow and does not provide a coherent picture at this stage. To address these concerns, the following revisions/clarifications are required.1) A commercial mAb AF2944 (R&D) against human PLZF was recently used for ChIP-seq in human KJ1a cells . Did the authors attempt to use this antibody? If not, experiments to assess whether this antibody can be used to replicate the locus specific ChIP experiments should be performed. These experiments do not need to 'work' for acceptance of the manuscript, but a positive result would be important because they would indicate that a key reagent is available for replication and extension of this work.2) The analysis of the RNA-seq data shown in Figure 3 is superficial and does clearly link loss of function of PLZF to the overall gene expression program illustrated in Figure 1. The analysis of this data set should be performed along the lines of that shown in Figure 1—figure supplement 1 in order to allow a clearer interpretation of the results.References:Mao AP, Constantinides MG, Mathew R, Zuo Z, Chen X, Weirauch MT, Bendelac A. Multiple layers of transcriptional regulation by PLZF in NKT-cell development. 2016. PNAS 113 (27) 7602-7607. DOI: 10.1073/pnas.1601504113 [Editors’ note: what follows is the authors’ plan to address the revisions.]Essential revisions1) The general pattern of PLZF binding is probably sound based on the absence of peaks in PLZF knockdown cells but the ChIP-seq experiments do not meet current standards for reproducibility. ChIPs from three independent experiments were pooled for sequencing. It is not possible from this experimental design to establish biological reproducibility of the peaks. This requires independent sequencing of ChIP products and application of statistical methods such as IDR. In addition, a table of general metrics for sequencing should be provided to help with data interpretation, including number of uniquely mapped reads, ChIP efficiency (fraction of reads in peaks) etc.We agree with the reviewers, that in order to perform statistical analysis to validate the reproducibility of PLZF ChIP-seq experiment, we have to perform the ChIP-seq using three independent biological replicates. We will repeat the experiment to fulfill this requirement and furthermore provide a table with the general metrics as the reviewers asked for.Experimental set up and time-line:Please note that primary human MSCs are slow growing and have a low nucleus to cytoplasmic ratio and big cell size (a confluent 15 cm plate contains app. 1.5x10^6 cells). Therefore, it will take more than one month to obtain sufficient cells to perform this ChIP-seq experiment.Furthermore, for the sequencing of the ChIP-libraries we expect a turn-around time of approx. 3 weeks at our facility at BRIC. This will be followed by analyses that will take approx. 2-3 weeks.2) Specificity of siRNA knockdown. Although the methods section indicates that three different siRNAs were tested for PLZF, it is not evident that the three siRNAs generated the same result for PLZF or NNMT. This is important because of the potential for significant off-target effects of siRNAs. The striking effect of the NNMT siRNA on PLZF and ALPL expression during osteogenic differentiation should be clearly established by more than one siRNA.We do have data for three different siRNA oligos directed towards PLZF  and NNMT  that were analyzed at the same time as the siRNA used in the experiment presented in Figure 5E and Figure 6A in the submitted manuscript. The effect of the other two siRNAs for PLZF knockdown was similar to the siRNA used in Figure 6A in the manuscript .The effect of the other two siRNAs against NNMT on PLZF and ALPL expression was quite similar to the experiment presented in Figure 5E of the submitted manuscript. Please see Figure 6—figure supplement 1.3) Role of PLZF in enhancer activation. The ChIP-seq data indicates that PLZF primarily binds to a pre-existing enhancer landscape, with a significant faction of these regions showing an increase in H3K27ac. However, the cause-effect relationship between PLZF binding and gain in H3K27ac is not established. Many other factors are induced during osteogenic differentiation and could be the primary drivers of this change. A cause-effect relationship requires performing ChIP-seq for H3K27ac during osteogenic differentiation in cells in which PLZF has been knocked down.We agree with reviewer that an increase in H3K27ac could be mediated by other factors than PLZF induced during osteogenic differentiation. This we already discussed in the discussion section of the submitted manuscript. However, in order to identify the cause-effect relationship between PLZF binding and H3K27ac, we have initially performed ChIP-QPCR experiment for H3K27ac before and after PLZF knockdown in hMSC. The data shown in Moreover, as suggested by the reviewers, in order to reveal if there should be a gene specific effect we are going to perform the ChIP-seq for H3K27ac in PLZF knockdown cells during osteogenic differentiation and compare to control siRNA transfected cells. We will choose PLZF siRNA 57 for this experiment. The experiment will be performed in biological triplicates using antibodies for H3K27ac, PLZF, general H3 and IgG.Experimental plan and time-line:We will grow hMSCs in sufficient amount (4-5 weeks), followed by PLZF knockdown using PLZF siRNA-57 and control siRNA (Scrambled) transfected cells. Then osteogenic differentiation will be induced for 2 days and cells will be fixed for ChIP-seq for H3K27ac, PLZF, general H3 and IgG control. The experiment will be performed in biological triplicates in order to meet the standard for reproducibility.Furthermore, for the sequencing of the ChIP-libraries we expect a turn-around time of approx. 3 weeks at our facility at BRIC. This will be followed by analyses that will take approx. 2-3 weeks. We will furthermore add a table of general metrics information regarding the ChIP-seq data.4) Most importantly, there are no transcriptomic studies of the consequences of PLZF loss of function. Although it was shown that Zbtb16 knockout leads to a skeletal defect , it is not necessarily an osteogenic defect. The only experiment evaluating effects of PLZF knockdown on gene expression is the Western blot for NNMT in Figure 6A, which does appear to show a difference at days 2 and 5 (but not day 10). However, there is no quantitative or statistical analysis of this finding and effects on mRNA levels are not provided. At this stage, there is no convincing evidence that PLZF plays an important role in regulating an osteogenic program of gene expression in this model system. This would require transcriptomic profiling in the PLZF knockdown cells.We had similar concern as the reviewers that it is important to understand the PLZF loss of function. Previously, we have done some initial experiments  The role of the enhancer EnP is not sufficiently dissected. While its activation is well supported by chromatin changes and by a retroviral enhancer assay, deletion of this enhancer should be performed, for example by CRISPR/Cas, to establish its physiological relevance. The 4C data in Figure 4 look rather unconvincing and are not statistically analyzed, and the impact of PLZF on NNMT seems weak.We thank reviewers for appreciating the data about enhancer activation. We agree that in order to establish the physiological relevance of EnP, the deletion of this enhancer by CRISPR/Cas9 would have been an excellent addition. However, the human mesenchymal stem cells that we have used throughout these studies can only be passaged until p11, after which they stop growing. Therefore, it will not be feasible to obtain a stable cell line of these hMSCs with a knockout of the EnP enhancer that will allow us to perform experiments to address its function. Furthermore, since EnP is an intragenic enhancer located within the PLZF locus, it is likely that the deletion would interfere with the genomic structure in such a way that it would directly influence on PLZF expression. Therefore, any observed phenotype would be difficult to interpret e.g. if it is due to the EnP deletion as such or due to a disruption of the locus structure that could influence e.g. splicing and exon usage.We actually thought that the 4C-seq data were very convincing. However, we will do our best to find a solution to improve the presentation of the 4C-seq data to convince the reviewers, and furthermore include appropriate statistics.6) There are many instances of figure panels lacking measures of statistical significance between experimental groups e.g., all of Figures 3, 5A, E, F, G, 6C, D, E, F.We apologize for the missing statistical testing in the indicated experiments. This has been calculated and will be added as requested by the reviewers.[Editors’ note: the author responses to the essential revisions after resubmitting their manuscript for consideration now follows.]The manuscript from Singh et al. reports on genomic roles of PLZF during lineage commitment of human mesenchymal stem cells and evidence for a latent enhancer within the ZBTB16/PLZF locus that is developmentally induced and regulates expression of the NNMT gene to influence cellular levels of SAM. The studies are of general interest with respect to understanding mechanisms of osteogenic differentiation. The authors demonstrate that PLZF is strongly induced at an early time point during osteogenic differentiation, coinciding with loss of the repressive H3K27me3 mark and gain of H3K27ac. ChIP-seq studies indicate that PLZF primarily binds to intra and inter genic regions with features of enhancers, many of which exhibit increases in H3K267ac during differentiation and are near genes that are enriched for relevant functional annotations. Chromatin conformation capture (4C) experiments are performed indicating an interaction of the latent enhancer within the ZBTB16 locus and the NNMT gene, which is not dependent on PLZF induction. Induction of the expression of NNMT, which catalyzes the conversion of nicotinomide to N1-methyl nicotinomide in a SAM-dependent manner, results in a modest but significant reduction of SAM levels. Knockdown of the NNMT using an siRNA results in a striking block of induction of ZBTB16 and ALPL mRNA during osteogenesis. The authors conclude that PLZF functions in enhancer activation and that the latent enhancer within its locus regulates the expression of NNMT during osteogenic differentiation. The findings are of interest, but there are several concerns with respect to the strength of some of the main conclusions.eLife. What follows is a response to the essential revisions listed in the request for a revision plan.We highly appreciate that the reviewers and editor found our study of general interest for the understanding of mechanisms acting in the process of osteogenic differentiation of hMSCs. We are furthermore very thankful that we have got a chance to improve the manuscript for consideration for publication in Essential revisions:1) The general pattern of PLZF binding is probably sound based on the absence of peaks in PLZF knockdown cells but the ChIP-seq experiments do not meet current standards for reproducibility. ChIPs from three independent experiments were pooled for sequencing. It is not possible from this experimental design to establish biological reproducibility of the peaks. This requires independent sequencing of ChIP products and application of statistical methods such as IDR. In addition, a table of general metrics for sequencing should be provided to help with data interpretation, including number of uniquely mapped reads, ChIP efficiency (fraction of reads in peaks) etc.Due to the very unfortunate situation that Santa Cruz discontinued the production of PLZF antibody that we used for ChIP (sc-22839) and that we were unsuccessful in obtaining an “old” aliquot by directly contacting the company we have not been able to repeat the PLZF ChIP. We have tested several other antibodies for PLZF in ChIP but without any success. Either they did not enrich chromatin or the antibodies were rather unspecific . Therefore, we have further tested the PLZF peak data set that we included in the first submission of the manuscript to validate their relevance as discussed below.As pointed out by the reviewers the PLZF binding pattern seems sound due to their disappearance in the PLZF KO situation. Based on the previous analyses and new validations, we strongly believe it is well controlled, which is based on the following:1) Three independent ChIPs for PLZF from three independent experiment were pooled for sequencing.2) The PLZF binding was confirmed by QPCR on target regions in completely independent experiments.3) The loss of PLZF binding on several genomic targets was confirmed after PLZF knockdown. These data are included as a new Figure 2—figure supplement 1C-E in the revised manuscript.-81), which is highly similar to the TAC(T/A)GTA PLZF motif previously reported by Ivins et al. (2003), as shown in Figure 2—figure supplement 1A and B.4) Moreover, in order to further check the validity of PLZF peaks, we have performed a de novomotif analysis of PLZF peaks using the MEME suite at http://meme-suite.org and the MEME-ChIP tool set to search for new motifs in the discriminative mode. Discriminative de novomotif analysis of the DNA sequences within the PLZF peaks, compared to sequences from negative control regions, revealed a significant occurrence of a TACAGC motif  Specificity of siRNA knockdown. Although the methods section indicates that three different siRNAs were tested for PLZF, it is not evident that the three siRNAs generated the same result for PLZF or NNMT. This is important because of the potential for significant off-target effects of siRNAs. The striking effect of the NNMT siRNA on PLZF and ALPL expression during osteogenic differentiation should be clearly established by more than one siRNA.We have included the data for three different siRNA oligos directed towards PLZF  presented in Figure 3—figure supplement 1 and the text. The effect of the other two siRNAs  on PLZF expression was similar to the siRNA #57 which is presented in the main Figures 3A and 7A in the revised manuscript.NNMT knockdown three different siRNAs  were tested and the data are presented in Figure 6—figure supplement 1, and the text. The other two siRNAs against NNMT affected PLZF and ALPL expression in a similar manner to the siRNA presented in Figure 6E-G in the revised manuscript. The siRNA labeled #22 was the one used in the main Figure 6E-G of the revised manuscript.For the 3) Role of PLZF in enhancer activation. The ChIP-seq data indicates that PLZF primarily binds to a pre-existing enhancer landscape, with a significant faction of these regions showing an increase in H3K27ac. However, the cause-effect relationship between PLZF binding and gain in H3K27ac is not established. Many other factors are induced during osteogenic differentiation and could be the primary drivers of this change. A cause-effect relationship requires performing ChIP-seq for H3K27ac during osteogenic differentiation in cells in which PLZF has been knocked down.In order to identify the cause-effect relationship between PLZF binding and H3K27ac, we performed siRNA mediated PLZF knockdown in naïve hMSCs followed by induction of osteogenic differentiation followed by H3K27ac ChIP-seq as suggested by the reviewer.The data revealed a highly reproducible increase in H3K27ac in pre-osteoblasts compared to naïve hMSCs (red in left panel), and this increase in H3K27ac seems to be PLZF dependent. The gain in H3K27ac at PLZF bound regions in pre-osteoblasts (red in left panel) were reduced when PLZF expression was down-regulated by siRNA. Examples of regions showing a gain of H3K27ac in a PLZF dependent manner are shown as ChIP-seq tracks in Figure 3C.These data are included in the main Figure 3 and the text to describe these observations is included in subsection “PLZF affects histone H3K27ac at bound enhancers and an osteogenic gene expression signature”. The list of regions that gain H3K27ac in PLZF dependent manner are included as Table 7 in the revised manuscript.It is of course very reasonable to assume that PLZF functions together with other transcription factors, that like PLZF are induced during osteogenic differentiation, and regulates genes important for osteogenic differentiation. This part is discussed in subsection “PLZF is required for the recruitment of Mediator and RNA PolII at the EnP enhancer”.4) Most importantly, there are no transcriptomic studies of the consequences of PLZF loss of function. Although it was shown that Zbtb16 knockout leads to a skeletal defect , it is not necessarily an osteogenic defect. The only experiment evaluating effects of PLZF knockdown on gene expression is the Western blot for NNMT in Figure 6A, which does appear to show a difference at days 2 and 5 (but not day 10). However, there is no quantitative or statistical analysis of this finding and effects on mRNA levels are not provided. At this stage, there is no convincing evidence that PLZF plays an important role in regulating an osteogenic program of gene expression in this model system. This would require transcriptomic profiling in the PLZF knockdown cells.We agree with the reviewers that it is important to understand the PLZF loss of function effect on transcription during osteogenic differentiation of hMSCs. We have now included novel data of the whole transcriptome profiling before and after PLZF knockdown in hMSC followed by osteogenic differentiation. We observed that PLZF knockdown significantly affected the osteogenic specific gene expression signature. The expression of genes that were normally induced in pre-osteoblasts is reduced in PLZF knockdown cells. These data are included in subsection “PLZF affects histone H3K27ac at bound enhancers and an osteogenic gene expression signature” and are shown in the main Figure 3D and E. Gene list is provided in Table 8.5) The role of the enhancer EnP is not sufficiently dissected. While its activation is well supported by chromatin changes and by a retroviral enhancer assay, deletion of this enhancer should be performed, for example by CRISPR/Cas, to establish its physiological relevance. The 4C data in Figure 4 look rather unconvincing and are not statistically analyzed, and the impact of PLZF on NNMT seems weak.We thank reviewers for appreciating the data about enhancer activation. We agree that in order to establish the physiological relevance of EnP, the deletion of this enhancer by CRISPR/Cas9 would have been an excellent addition. However, the human mesenchymal stem cells that we have used throughout these studies can only be passaged until p11, after which they stop growing and tend to differentiate. Therefore, it will not be feasible to obtain a stable cell line of these hMSCs with a knockout of the EnP enhancer that will allow us to perform experiments to address its function. Furthermore, since EnP is an intragenic enhancer located within the PLZF locus, it is likely that the deletion would interfere with the genomic structure in such a way that it would directly influence the expression of PLZF. Therefore, any observed phenotype would be difficult to interpret e.g. if it is due to the EnP deletion as such or due to a disruption of the locus structure that could influence e.g. splicing and exon usage.We actually thought that the 4C-seq data were very convincing. However, we have re-analysed the data with statistical testing and presented it in the new Figure 5 in the revised manuscript.6) There are many instances of figure panels lacking measures of statistical significance between experimental groups e.g., all of Figure 3, 5A, E, F, G, 6C, D, E, F.We apologize for the missing statistical testing in the indicated experiments. This has been calculated by 2-way ANOVA with multiple comparison testings in all the experiments. The significant p values are indicated with asterisks in new figures and the exact values are mentioned in figure legends,  in the revised manuscript.[Editors' note: the author responses to the re-review follow.]The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance. The first relates to the fact that it was not possible to generate replicates for the ChIP-seq analysis of PLZF due to discontinuation of the original antibody. The reviewers concur that motif analysis of the existing data set yielded the correct motif and that locus-specific confirmation of PLZF binding was performed at key genomic locations using the original antibody for biological replicates. However, it is not clear whether the additional antibodies tested included an antibody recently demonstrated to work for PLZF ChIP-seq in human cells. Second, while new transcriptomic analysis of the consequences of loss of function of PLZF during osteogenic differentiation was performed, the analysis is difficult to follow and does not provide a coherent picture at this stage. To address these concerns, the following revisions/clarifications are required.1) A commercial mAb AF2944 (R&D) against human PLZF was recently used for ChIP-seq in human KJ1a cells . Did the authors attempt to use this antibody? If not, experiments to assess whether this antibody can be used to replicate the locus specific ChIP experiments should be performed. These experiments do not need to 'work' for acceptance of the manuscript, but a positive result would be important because they would indicate that a key reagent is available for replication and extension of this work.We have tested the mAb AF2944 from R&D systems in ChIP-QPCR on the same genomic loci as presented in the manuscript, Figure 2—figure supplement 1: the EnP enhancer, Col1A1 proximal, SMAD3A proximal. We observe that PLZF is enriched at these genomic regions after induction of osteogenic differentiation (2 days) as compared to naïve hMSCs, using the AF2944 antibody . Therefore, we are very pleased to conclude, that this antibody can be considered as a replacement for the Santa Cruz PLZF antibody (sc-22839), which very unfortunately was discontinued by the company. This definitely will be helpful to reproduce and even extend our work in the future.2) The analysis of the RNA-seq data shown in Figure 3 is superficial and does clearly link loss of function of PLZF to the overall gene expression program illustrated in Figure 1. The analysis of this data set should be performed along the lines of that shown in Figure 1—figure supplement 1 in order to allow a clearer interpretation of the results.As per reviewer’s suggestion, we have re-analyzed the RNA-seq data from the PLZF knockdown experiment and is now presenting it in a more comprehensive way in revised Figure 3D and E, and Figure 3—figure supplement 1B and C. The heatmaps in Figure 3D, represents the RPKM-values of differentially regulated genes from RNA-seq of PLZF knockdown or control siRNA  in hMSCs. The vertical order of genes is similar to the clustered heatmap in Figure 1—figure supplement 1B. The RNA-seq data clearly indicate: i) a high degree of reproducibility in biological replicates, ii) pronounced impact of PLZF knockdown on gene regulation at an early stage (2 days) of osteogenic differentiation. Furthermore, in Figure 3E, we present the Beeswarm plots comparing the log2 fold differences between PLZF knockdown or negative control siRNA in hMSCs, harvested at day 0 and day 2 of osteogenic differentiation. The plot shows that PLZF knockdown significantly affected the osteogenic transcriptional program (p<0.0001). We also present the overlap by Venn diagram between differentially regulated genes in the absence or presence of PLZF during osteogenic induction and performed the Gene Ontology (GO) analyses of differentially regulated genes from each group (control siRNA or PLZF knockdown). All new analyses are now included in the main Figure 3 (revised) and Figure 3—figure supplement 1 (revised) and described in the main text, figure legends and Materials and methods section.