We develop a detailed theoretical framework for various types of transcription factor gene oscillators. We further demonstrate that one can build genetic-oscillators which are tunable and robust against perturbations in the critical control parameters by coupling two or more independent Goodwin-Griffith oscillators through either -OR- or -AND- type logic. Most of the coupled oscillators constructed in the literature so far seem to be of -OR- type. When there are transient perturbations in one of the -OR- type coupled-oscillators, then the overall period of the system remains constant (period-buffering) whereas in case of -AND- type coupling the overall period of the system moves towards the perturbed oscillator. Though there is a period-buffering, the amplitudes of oscillators coupled through -OR- type logic are more sensitive to perturbations in the parameters associated with the promoter state dynamics than -AND- type. Further analysis shows that the period of -AND- type coupled dual-feedback oscillators can be tuned without conceding on the amplitudes. Using these results we derive the basic design principles governing the robust and tunable synthetic gene oscillators without compromising on their amplitudes. Transcription factors (TFs) regulate the quantitative levels of several proteins inside a living cell n numbers of this end-product bind with the cis-regulatory modules (CRMs) of the associated promoter that in turn results in down-regulation. Here n is the Hill coefficient associated with the cooperative type binding. Detailed studies on this minimalist model showed n>8 is necessary to generate self-sustained oscillations in the levels of mRNA and protein. This result was obtained with the assumptions that the rate constants associated with the synthesis and decay of the protein and end-product are equal and the binding-unbinding of the end-product with the promoter is much faster than the rate of change in the synthesis and degradation of mRNA, protein and end-product. Further it was assumed that the decay of mRNA and protein product follows a first order type reaction.The minimalist TF network model that can generate self-sustained oscillations is the well-known Goodwin-Griffith oscillator which has a single gene that codes for a TF protein that negatively auto-regulates its own transcription n>8 is unlikely in vivo conditions since the formation of such large multimeric protein complexes via pure three dimensional diffusion (3D) limited collisions (n. Most of these modifications were mainly associated with the insertion of (a) a temporal delay in the negative auto-regulatory loop either explicitly as a time-delay in between the synthesis and binding of end-product at the promoter n = 1. The genetic oscillator module with three TF genes connected in a cyclic negative feedback loop is named as repressilator in vivo experimental conditions. It was argued that it could be partially due to the noisy nature of intracellular environment in vivo conditions. In this context it is essential to investigate how the oscillatory dynamics of these motifs reacts to perturbations in the system parameter values.It was realized later that the inequality condition llisions Figure 1cV ( =  volume of nucleus in case of eukaryotes) is comparable with that of the prokaryotes E. coli (cV ∼10−18 m3) and the influence of the promoter state fluctuations on the overall dynamics of feedforward/feedback loops seems to significantly increase as the nuclear volumes increases as in eukaryotic cells across yeast to human. Further, the Michaelis-Menten type degradation kinetics associated with mRNA and protein is a valid assumption only when the concentrations of these species are much higher than the concentration of the corresponding nucleases and proteases. Nevertheless in most of the in vivo conditions, the intracellular levels of mRNA and protein of a particular TF gene will be much lesser than the corresponding levels of the non-specific nucleases and proteases. When the latter is true then the enzyme mediated decay of mRNA and protein will eventually follow a first order type kinetics. In this article, using a combination of theoretical and simulation tools (a) we develop a generalized theoretical framework of various types of genetic oscillators by explicitly incorporating the promoter state dynamics and other chemical reaction balances in detail. Using our detailed model (b) we identify and classify various critical control parameters and compute their physiological ranges which are required to generate self-sustained oscillations in the intracellular levels of mRNAs and transcription factor proteins and (c) explore various possibilities of coupling independent gene oscillators and fine-tuning the period of such coupled system. We further (d) demonstrate that by coupling two or more independent Goodwin-Griffith oscillators one can design oscillatory network architectures which are tunable and also robust against perturbations in system parameters.Most of the earlier studies on GG and other oscillator models assumed a quasi-equilibrium condition for the binding-unbinding dynamics of the negatively autoregulated TF proteins at their own promoters. This is mainly to reduce the four or higher dimensional Jacobian matrix associated with the non-linear system of differential rate equations into a three dimensional one to ease further analysis since there is an additional rate equation corresponding to the promoter state dynamics apart from the rate equations associated with mRNA, protein and end-product. However this assumption is valid am, protein as ap, the transformed end-product as az and the complex of promoter with the end-product as ax. Here the total cellular concentration of promoter is zad and the overall promoter state occupancy by the end-product will be aX = ax/zad where aXaX to describe promoter state occupancy mainly to account for its partially occupied status mak (Ms−1) and pak (s−1) respectively. The first order decay rate constants corresponding to mRNA and TF protein are maγ (s−1) and paγ (s−1) respectively. The first order on- and off-rates associated with the transformation of protein into the matured end-product are denoted as afλ (s−1) and arλ (s−1) and the corresponding dimensionless dissociation constant is an numbers of end-product molecules with the respective cis-regulatory modules (CRMs) of the promoter of TF gene A are afk (ark (s−1) and the corresponding dissociation constant is defined as The Goodwin-Griffith oscillator consists of a negatively self-regulated gene (we denote it as TF gene A) which codes for a transcription factor protein  In these equations We further transform the parameter associated with the multimerization of end-product and subsequent binding events as follows.Eqs (1–3) one can write the deterministic rate equations corresponding to the temporal evolution of dimensionless concentration variables  over dimensionless time variable τ as follows.Using the scaling transformations given by av = 0, −1) is the first order decay rate constant associated with the protein end-product aZ. Since az (we denote the dimer a-zaz as ay) as in case of Lac repressor system that has been constructed and studied in reference lacI gene) then the first and last equations of Eqs (4) will be modified as follows.The initial conditions are Here various parameters associated with the dimerization of end-product of TF protein A and subsequent assembly of this end-product at the own promoter are defined as follows.−1 s−1) is the forward rate constant associated with the dimerization reaction and −1) is the corresponding reverse rate constant. One should note that for a fully functional Lac repressor system the Hill coefficient will be an = 4 since an octamer of Lac repressor protein (which is a dimer) is involved in the overall looping of DNA that results in strong repression of lacI. The system of Eqs (4) is completely characterized by the following set of dimensionless parameters.Here we have defined an that can be simplified by assuming an in vivo protein level as aσ, aχ, aκ) those are ordinary type perturbation parameters. In Group II, aχ controls the coupled dynamics of changes in the concentrations of end-product and it's binding with the promoter sequence. The lifetime of end-product is controlled by aκ. One should note that almost all the earlier studies assumed that  = 0. Group III consists of the equilibrium and promoter affinity parameters . In this aλ controls the equilibrium associated with the formation of end-product and aμ controls the equilibrium associated with the binding of an molecules of end-product with CRMs of the promoter of TF gene A.Here one should note that the parameters afk) for the assembly of an numbers of TFs at the respective CRMs of promoter and the time required for subsequent looping of DNA and subsequent distal action of TFs on RNAPII-promoter complex. The time component associated with the looping and distal action along with the time required for elongation and termination steps are included in the definition of transcription rate .The kinetics of interaction of an molecules of end-product with the sequentially located CRMs can occur in two different possible ways namely binding of the full-fledged complex of an molecules of end-product (pathway II) or sequential assembly of the monomers of end-product at the corresponding cis-regulatory DNA-binding sites similar to that of a combinatorial binding of TFs with CRMs (pathway I) as in eukaryotic systems (an+1)th order reaction it is still an operable one since the length scale of the genomic DNA is much higher than the combinatorial binding TF proteins. Binding of an numbers of transcription factors in a sequential manner or an-mer of end-product leads to looping of the DNA segment that is present in between promoter and CRMs of TF gene A that results in the spatial or distal communication between the end-product present at CRMs and the already formed RNAPII-promoter complex which in turn activates (positive) or deactivates (negative) the initiation of transcription depending on the type of self-regulation lac-repressor gene. Here binding of lac-repressor at the Operator sequence directly destabilizes RNAP-promoter complex that in turn lead to the down regulation of transcription an-mer via 3D diffusion-controlled collisions and subsequent binding with the cis-regulatory sites can be calculated as follows.The total time required to initiate transcription consists of at least two different components viz. the time required  is the 3D diffusion coefficient associated with the dynamics of monomers of end-product in aqueous medium where T is the absolute temperature (K), R. Since the overall maximum radius of the m-mer will be ∼mR, we find that an-mer in a sequential manner via 3D diffusion will be given by the sum an-mer complex and also we have not considered the possibility of formation of the final an-mer through non-sequential and random pathways and the steric factor associated with the multimerization reaction. The total search-time that is required by the monomer of end-product to find its cognate site on DNA is defined as N/L numbers of cycles of 3D diffusion mediated association that is followed by 1D scanning and dissociation where N is the size of the genomic DNA  and L (bps) is the average 1D sliding-length between non-specific 3D association and dissociation. Here L bps of the genomic DNA via 1D diffusion along the DNA chain, 2s−1) is the 1D diffusion coefficient associated with the sliding of monomers on DNA  and an monomers of end-product search for their binding sites on DNA in a parallel manner, then the total time an monomers to assemble at the sequentially located cis-acting elements can be derived from the theory of combinatorial binding of transcription factors In this equation an in a power law manner as Eqs (6) and (7) one can compute the following ratio.From this equation we find that the 1D scanning time increases with the number of monomers an = 1 an. Eqs (7) and (8) suggest the pathway I is more efficient than pathway II. This means that though the diffusion limited multimerization of the monomers of the end-product is not a reasonable assumption for large values of an, direct assembly of the monomers of the end-products of TFs on the sequentially located cis-regulatory DNA binding sites via a combination of 1D and 3D diffusion controlled routes can be still a reasonable assumption even for higher values of an. In this context we can replace the combinatorial binding of an numbers of TFs with CRMs of template DNA with a single step (an+1)th order reaction as given by the first equation in Eqs (4). One should note that unlike the prokaryotic systems, most of the eukaryotic promoters are activated through a combinatorial binding of several TFs at the corresponding CRMs From the theory of site-specific DNA-protein interactions we find that Eqs (4) has a fixed point an+1).The system of aZ, aM and aX) can be calculated using the fixed point The steady state values of other concentration variables (Eqs (4) near this equilibrium point can be written as follows.Using the Jacobian matrix evaluated around the equilibrium point Here we have defined various matrix elements as follows. PI) of the Jacobian matrix defined in Eqs (10) can be written as follows.The coefficients associated with the characteristic polynomial From the Routh-Hurwitz criterion for a biquadratic polynomial s<0 or s>0. When the third inequality in Eqs (11) is not true then the biquadratic polynomial can have a complex root such that aw, av, aε) which are in turn linearly depend on an presents only in the coefficient terms s, t and u, the third inequality in Eqs (11) can be reversed by increasing the value of an for any set of Group I, II and III parameters. This means that the parameter space that is required to generate oscillations can be expanded by increasing the value of an. Inequality conditions given by Eqs (11) for a stable motion of the dynamical system of Eqs (4) can be directly derived from the following Routh table (GGRT) PI).Here the first inequality condition Eqs (10–11) we find that the system will be inconsistent near the fixed point both at very large as well as small values of Group I type parameters as PI) which means that the period of oscillations will increase proportionately with respect to an increase in these parameters since we find Eqs (11) at various values of an. When the dynamics of promoter state occupancy is much faster than the rate of change in the concentrations of other variables then one can set Eqs (4) reduces to the following form. When Eqs (13) as the base model however with the conditions such that Most of the earlier studies on GG oscillator consider PII) where the coefficients are defined as follows.Here we have defined Eqs (13–14) to generate limit-cycle oscillations will be an, the expression for the critical value of an that is required to generate limit cycle oscillations can be obtained as follows.The Routh-Hurwitz an and aμ and the following limiting conditions exist.Here one should note that the term Eqs (15–17) suggest that strong binding of the end-product (Eqs (4) and (5) then the resulting characteristic polynomial of the Jacobian matrix will be of fifth order as PIII) and the Routh criterion that is required to generate oscillations can be written as follows.The physiological ranges of various parameters associated with Goodwin-Griffith oscillators are listed in 1) and repressilator models (1). In case of one-to-one negative feedback oscillator an number of end-product molecules of TF gene A bind with the cis-regulatory elements associated with the promoter of TF gene B and subsequently down-regulates whereas bn number of end-product molecules of TF gene B down-regulate the promoter of TF protein A upon binding with the corresponding cis-regulatory elements (1). The set of differential rate equations associated with the two TFs one-to-one feedback system can be written in the dimensionless form as follows.One can extend these scaling ideas for one-to-one negative feedback oscillator or toggle switches  denote the TF genes A and B respectively. One should note that the Hill coefficients associated with the binding of the end-product of TF A at the promoter of TF B and end-product of TF gene B at the promoter of TF gene A are an and bn respectively and in general In these equations the subscripts will be such that when h = a, b one needs to set q = b, a. The steady state solutions Eqs (18) corresponding to this two TFs system with respect to the scaled protein levels can be given as follows.In these definitions for The steady state values of other dynamical variables can be calculated using the steady state values of the protein products y in Eqs (19) is the real root of Here Eqs (18) have three possible steady state solutions viz.Eqs (18) (Methods section) near the steady state values 2) or A-AND-B (3) type logics. One can consider various types of regulatory combinations associated with these network architectures. The combinations in A-OR-B type coupling can be denoted as ‘AsAc-BsBc’ where ‘As’ and ‘Bs’ are the types of self-regulation of TF genes A and B respectively whereas ‘Ac’ and ‘Bc’ are the types of their cross-regulation on each other. Each type of regulation can be either ‘P’ or ‘N’ where ‘P’ denotes positive type and ‘N’ denotes the negative type regulation. Using these notations one can denote the configuration given in 2 as NN-NN type, 4 as NN-PP type and 5 as NP-NP type. The configurations given in 4 and 2B5 are the well-studied robust dual-feedback oscillators 3 is an N-N type. When the coupling is via A-OR-B type logic then both the promoters of TF genes A and B will be independently down-regulated upon binding of protein end-products of both the TF genes A and B at the respective cis-regulatory elements associated with each promoter and the first and last equations in Eqs (18) will be modified as follows.h’ the subscript ‘q’ will take a, b and there are totally four equations associated with the overall promoter state dynamics. Various modified parameters in Eqs (21) are defined as follows.In these equations for each value of subscript ‘The steady state solutions corresponding to the modified equations can be obtained by numerically solving the following set of coupled polynomial equations.hsZ is defined as in Eqs (20). When Eqs (22) as y is the real root of dy) of both end-products (az-bz) will be the key regulating molecule that binds at the cis-acting elements associated with the promoters of both TF genes A and B however with different Hill coefficients (hn) and subsequently down-regulate them. The respective modified differential rate equations corresponding to the dimerization and binding of dimer at the promoters of TF genes A and B can be written as follows.Here Eqs (23) are defined as follows.The modified and new parameters and variables in hχ for h = a, b one needs to substitute q = b, a. Here −1s−1) and −1) are the forward and reverse rate constants associated with the diffusion limited dimerization reaction between the protein end-products of TF gene A and B. The corresponding steady state solutions to Eqs (24) can be written as follows.In the definition of Here q = b for h = a and for h = b we need to set q = a. The parameters associated with dual feedback oscillators are summarized in In this set of equations we need to set Eqs (18) one can write the set of differential rate equations associated with the three TFs repressilator model as follows (1). Similar to a, b, c) denotes respectively TF gene A, B and C in a cyclic  manner and the variables as well as various control parameters are defined as in case of Eqs (18) and generally Eqs (19) one can derive the steady state solutions with respect to the scaled protein levels for three TFs system as follows.Here the subscripts will be such that y is the real root of In this equations Eqs (20) as follows.Using these steady state values of protein products 2 and 2C3 one can also construct the repressilator type model by cyclically coupling three independent GG oscillators A/B/C through -AND- or -OR- type logical gates as we have constructed in 2-3. When the type of interaction is through -AND- type logic, then the a-zbz dimer down-regulates TF gene B, b-zcz dimer down-regulates TF gene C and the c-zaz dimer down-regulates TF gene A. The set of modified differential equations corresponding to the configuration that is given in 3 can be written as follows. Under identical values of all the control parameters such as  where the indices will be extended for three TF genes A/B/C. One can also consider a fully interconnected network of TF genes A/B/C. In these configurations the self-regulated promoters of each TF gene A/B/C will be negatively regulated by the end-products of the remaining two other TF genes. Here the mode of overall combinatorial interactions among these regulating end-products and the corresponding promoters can be either through -AND- or -OR- type logics as represented by the dashed lines in 2-3. In case of -OR- type logical gate, the negatively self-regulated promoter of TF gene A will also have cis-regulatory binding sites for the end-products of both TF genes B and C and so on. One can write the modified set of differential equations associated with such fully interconnected configuration (2) as follows.When the type of interaction is through -OR- type logic as depicted in Eqs (31), there will be three equations for each promoter and there are totally nine equations associated with the overall promoter state dynamics. In the second set of three equations as well as in the associated parameters for each value the subscript ‘h’ from the set , the subscripts q and k will take the remaining values. This means that when h = a then q = b and k = c and so on. Various modified parameters in Eqs (31) are defined as follows.In the first one of Eqs (31) needs to be obtained by numerically solving the following set of equations.The steady state solution to 3 (with dashed lines), the complex a-zb-zcz will be the key regulating molecule that binds with the promoters of all the three TF genes A/B/C and down-regulate them. Similar to Eqs (23) one can write the modified set of differential equations corresponding to repressilator configuration that is fully interconnected through -AND- type logic as follows.In case of fully interconnected configuration through -AND- type logic that is depicted in Here we have defined Here various modified and new parameters are defined as follows.Eqs (31) for each value the subscript ‘h’ from the set , the subscripts q and k will take the remaining values. This means that when h = a then q = b and k = c and so on for other values.In these equations similar to 1-3 and 1-4 and Eqs (4–5) corresponding to the negative-feedback-only (NFO) model considered in reference Lac I oscillatory system the effective Hill coefficient is lac I end-products involved in the overall negative feedback. Numerical analysis of this NFO model system using the physiological range of parameters as given in 1.Sample trajectories and phase portraits of GG oscillator for 4 shows the strong influence of 1-3. These results also demonstrate how the oscillator responds to temporal perturbations is Group I parameters. As we have shown in the theory section, the period of oscillations increases with increase in the Group I parameters whereas the amplitude seems to decrease as the value of Group I parameters increase. One should note that square of period of oscillation is inversely proportional to the total energy of an oscillator whereas the total energy is directly proportional to the square of amplitude. This means that the total energy of a GG oscillator can be fine-tuned by perturbing the Group I parameters. The Goodwin-Griffith oscillator seems to abruptly enter into the modified limit-cycle orbit upon introducing the perturbation and relax back much faster upon removal of perturbation in the parameter 2-3 the relaxation of oscillator to the original orbit upon removal of perturbation seems to be through slow asymptotic spirals. 1 suggest that the period of oscillations increases monotonically with respect to increase in the value of Group I parameters as we have predicted in the theory section. When 2 shows that when 1-3) is an adaptable one that can act as a toggle switch as well as an oscillator depending on the type of configuration. As we have shown in the theory section, the configuration depicted in 1 requires identical values of all the control parameters as well as initial conditions to generate coupled as well as synchronized oscillations. Particularly this configuration can efficiently act as a toggle switch since the fixed point 2-3 can act as coupled oscillators. Sample trajectories and phase portraits of one-to-one coupled oscillators corresponding to the configuration given in 1 are shown in 1-6. The minimum achievable value of the critical Hill coefficient that is required to generate self-sustained oscillations around the unstable fixed point (Cnh = 5 that is closer (Cnh = 6) to the critical value corresponding to GG oscillator. Variations of critical Hill coefficient with respect to changes in combination of different groups of control parameters are shown in 1-8. Results suggest that the minimum value of critical Hill coefficient that is required to generate self-sustained oscillations can be achieved only when 1 also suggests that the inequality condition 2 we find that Cnh is also independent on the changes in the ordinary perturbation parameter hχ. However it is strongly dependent on hσ and the condition Cnh. Results suggested that when there are identical perturbations in the given control parameter, then the one-to-one coupled oscillator (1) behaves similar to that of GG oscillator. That is to say the period of oscillations increases and amplitude decreases with an increase in Group I parameters. Here the identical perturbations are such that for the parameter hw we have The dual feedback motif (delτ) and subsequently reaches one of the stable steady-states via asymptotic spirals. Here the target steady state is dependent on the type of disproportion in the parameter values among TF genes A and B. For example when the perturbation is from k’ denotes the control parameter under consideration such as hμ) as well as duration of the perturbation (hμ and duration of perturbation pulseτ) at which the perturbation in the control parameter is introduced into the system.Upon receiving a transient pulse of perturbation or imbalance in the control parameters the dual feedback oscillator exits from the limit-cycle orbit with a time-delay  whereas Cnh = 2 for the coupled oscillators with A-AND-B type logic (3). Results suggest that the limit cycle orbit of coupled oscillators with A-AND-B and A-OR-B type logics are stable one. When there are temporal perturbations in Group I parameters associated with one of the Goodwin oscillators (TF gene A/B) then the other unperturbed oscillator responds to the changes in the behavior of the perturbed oscillator depending on the type of logical coupling between them. As shown in 1-2, B1-2 and C1-2 in case of A-OR-B coupling an increase in the magnitude of Group I parameters associated with one of the oscillators A/B does not change the period of the entire system of oscillators (period-buffering) though there is a decrease in the amplitude of the oscillator that is perturbed in 1-4 suggest that an increase in the parameter -1-2 and B1-2. Whereas perturbation in -1-2. Here one should note that in case of A-OR-B type coupling the parameter Eqs (21). Above results corresponding to A-OR-B type logical coupling with respect to changes in the parameter Eqs (21). When there are perturbations in only one of these two split parameters  the configurations given in 2-3 do not require any asymmetry in the values of control parameters or initial conditions to trigger the stable oscillations. When the mode of coupling of TF genes A/B/C of GG oscillators is through -OR- type logic then in the presence of identical values of all the sets of control parameters the TF genes A/B/C oscillate in a synchronized manner with respect to period and amplitude. When there is a perturbation in set of the control parameters Figures S2B1-2 in File S1 the system tries to resist the perturbation by keeping the synchronized limit-cycle orbit intact whereas in the second phase the system becomes unstable and chaotic whose magnitude depends on the extent of perturbation. Upon removal of perturbation, in the third phase the system enters into new asynchronous limit-cycle orbit with stable phase differences among the TF gene oscillators. When there is a perturbation in one of the split parameters Figure S2B1 in File S1 the second phase will have several repeating elements of resistance and instability. Perturbation in the control parameters Figures S2B3-4 in File S1. Contrasting from these results, the oscillator depicted in 3 seems to be more robust against changes in the Group I control parameters and also they return back to the initial coherent type limit-cycle orbit upon removal of perturbations as shown in Figures S2C1-2 in File S1. Sample trajectories of fully interconnected configurations given in 2-3 (with dashed lines) are shown in Figures S3A1-3 andSB1-3 in File S1. These results suggests that the fully interconnected three TF genetic oscillator will be more stable against perturbations in the critical control parameters when the mode of coupling is through -AND- type logic than the -OR- type logic.Sample trajectories and phase plane portraits associated with the configuration given in 3) and A-OR-B (2) type coupled dual feedback oscillators are demonstrated in Figures S4A-D and S4A-D inFile S1. These results show that A-AND-B type coupled oscillators can be tuned by changing the promoter state binding parameter hμ efficiently without conceding on the amplitude of oscillations. Increase in hμ monotonically decreases the amplitude (and increases the period) of A-OR-B type coupled oscillators. Whereas A-AND-B type oscillator shows two distinct regions of responses with respect to changes in hμ namely a responsive region and nonresponsive region. For the settings in Figure S4B in File S1, the A-AND-B system responds to the perturbations in hμ when hμ<10−5. When hμ>10−5 then changes in hμ will not affect the period of oscillations much. On the other hand the amplitude (measured in terms of hP/hsP) of A-AND-B oscillator is ≥1 in a wide range of hμ as well as hw values. Further A-OR-B type coupled oscillators behaves similar to that of single GG oscillator with respect to changes in the perturbation of Group I parameter hw. In case of both types of coupled oscillators the amplitude seems to be inversely proportional to the critical Cnh rather than the period of oscillations as it is apparent from Figures S4C and D in File S1 and there exists an optimum value of Group I parameter hw at which the amplitude of oscillations is a maximum. Figures S5A-D in File S1 shows that increase in Group I parameter hv increases the period of oscillations and decreases the critical Cnh in both -AND- and -OR- type coupled oscillators. However the period of -AND- type oscillator seems to be more robust against changes in hv than -OR- type coupled dual feedback oscillator. Contrasting from these there exist a cutoff value of hε∼2  beyond which the amplitude of oscillations is practically zero in both types of coupled oscillators that is apparent from Figures S5C andD in File S1. The discontinuities in plots depicted in Figures S4 and S5 in File S1 mainly originate from the fact that each data point belongs to different values of critical Hill coefficients. For example upon iterating the perturbation parameter, we first find out the critical Hill value for the perturbed values and then obtain its amplitude and period of the perturbed system with newly calculated hill coefficient. This means that each data point in those plots comes from altogether different dynamical systems since the Hill coefficients are different. Therefore we may not expect continuous type plots either.Tuning capabilities of A-AND-B (mhγ) for eukaryotic mRNAs than the prokaryotic ones which results in the general observation that the values of an = 1) such as the one in E. coli. Whereas in case of eukaryotic systems such as yeast and human its value will be scaled up respectively to 1 times higher than E. coli cell whereas human cell nucleus is ∼102 times higher than E. coli cell. The parameter aμ  is the only parameter that can be externally modified in a working model and all the others are fixed system parameters which can be modified only at the time of designing the oscillatory module. In case of Lac based oscillators aμ can be modified through changing the concentration of IPTG lacI gene.Transcription factor gene oscillators play critical roles in driving cell-cycle to circadian rhythms. Here we have identified the critical control parameters associated with self-sustained oscillations of such oscillators and classified them into Groups I, II and III depending on their functionality. Group I parameters control the intracellular dynamics of synthesis and degradation of various molecules associated with regulated TF gene Figure 1et.al in reference 4-5 can be further increased by the explicit delay owing to the oligomerization steps associated with the end-products of TF genes A/B (here gene A can be lacI and gene B can be araC). Further studies by Tsai et.al in reference 4-5) can increase the robustness and tunable nature of the original oscillator without compromising on the overall amplitude. Here the positively auto regulated TF gene acts as a booster for the overall protein level of the negatively self-regulated oscillatory TF protein. In this context one can also consider a positive coupling of a positively auto-regulated TF protein K (booster) with N-N or NN-NN type dual feedback oscillators as depicted in 6. Upon analyzing various classes of oscillators depicted in Figures S4 and S5 in File S1 we find that the A-AND-B coupled dual feedback oscillator can be externally tuned by modifying the promoter state binding hμ without conceding on the amplitude of oscillations. The inherent chaotic response of the -OR- type coupled oscillators could be one of the reasons why the oscillations of most of the synthetic oscillators disappeared after certain period of time in vivo conditions. Nevertheless the overall period of network of oscillators coupled through -OR- type logic are more resistant (period-buffering) to perturbations in the control parameters than the oscillators coupled through -AND- type logic. One should note that the temporal perturbations in the system parameters ultimately result in perturbations in the intra cellular concentrations of protein end-products of coupled TF genes that in turn are looped back into the system. In this context the -OR- type coupled genes respond to perturbations in an additive way whereas those genes coupled through -AND- type logic respond in a multiplicative way. This could be the reason why the period of oscillations of -OR- type coupled oscillators are more resistant to perturbations than -AND- type coupled oscillators. This means that the period of network of oscillators coupled through -AND- type logic can be more easily tuned by perturbing any one of the coupled oscillators. Depending on the circuit functionality one can also chose a combination of both the types of coupling. So far we have assumed a copy number of TF genes as one (hzd = 1). This may not be true in the bacterial based synthetic circuits constructed on plasmids since the plasmid copy number will be more than one in most of the times which can lead to further complexity. For example, a plasmid copy number of two for a NFO model that was constructed in reference 2 and 2B3 with TF gene A  =  B since it can mimic both -AND- as well as -OR- type coupled GG oscillators. This could be one of the possible reasons for observing stable and robust oscillations with such constructs Understanding the design principles associated with the genetic oscillator is one of the central topics in synthetic and systems biology. An efficient synthetic oscillator should be robust against transient perturbations in the control parameters and fluctuations in the promoter state occupancies. The period of oscillators should be easily tunable without compromising the amplitude. Stricker In summary, in this paper we have considered various types of transcription factor oscillators by explicitly incorporating the promoter state dynamics and other chemical reaction balances in detail. Using our detailed model we have identified and classified various critical control parameters and numerically obtained their physiological and optimum ranges to generate self-sustained oscillations in the intracellular levels of mRNAs and transcription factor proteins. We further derived the basic design principles associated with robust and tunable gene oscillators. We have further demonstrated that by coupling two or more independent Goodwin-Griffith oscillators via -OR- or -AND- type logics one can construct genetic-oscillators which are fine-tunable and also robust against perturbations in the system parameters. When there is a perturbation in one of the -OR- type coupled oscillators, then the overall period of the system remains constant whereas in case of -AND- type of coupling the overall period of the system moves towards the perturbed oscillator. Though there is a period-buffering, the oscillators coupled through -OR- type logic seems to be more sensitive to perturbations in the parameters associated with the promoter state dynamics than -AND- type.Eqs (4) which describe the Goodwin-Griffith model, the numerical integration scheme can be written as follows. We use Euler type numerical scheme Eqs (34)). We divide the total scaled simulation time T into N equal intervals such that Δτ = T/N. For simulation purpose we set Δτ  = 10−5 and the corresponding Δt = 0.03 s for a lifetime 1/paγ∼60 mins. We use Newton's method Eqs (9) particularly for Initial and boundary conditions are Eqs (18) as follows.In this numerical scheme we set the initial guess value of the fixed point solution as a, b) denotes the TF genes A and B respectively. Various matrix elements are defined as follows.Here subscripts  one need to first solve the steady state equations. Upon substituting the steady state protein values into to the corresponding Jacobian matrix one can construct the characteristic polynomial and the Routh table. The corresponding inequality conditions for oscillations will be derived from this table. This procedure need to be carried out at various values of an from an = 1 in an iterative way. We set the default initial value of promoter state variable as E. coli bacterial cell (volume ∼10−18 m3) hsm∼102 molecules and hsp∼104 molecules h = a, b and c respectively denotes TF genes A, B and C. Concentration of a single TF molecule inside a bacterial cell will be ∼2 nM E. coli that gives a decay rate of aw = 0.1 and we measure the time in terms of number of protein lifetimes. Since the dynamics of binding-unbinding of a single transcription factor protein (an = 1) with its cis-regulatory site on DNA is a typical diffusion-controlled site-specific DNA-protein interaction, under in vivo conditions of a bacterial cell we find that −1 (pγ) that will be scaled down to the interaction of hn number of TF molecules with sequentially located combinatorial binding sites as in vivo 3D diffusion controlled collision rate ∼104 M−1s−1. In case of nucleus of yeast cell −1 γp−1 and in case of nucleus of human cell we find −1 γp−1. Since av∼10−4 for a typical bacterial promoter an. Using these values one can estimate the physiological ranges of various groups of control parameters as given in lacI (an = 4) system (Eqs. (4–5)) the values of parameters will be h = nhqn, In these definitions for File S1This file contains Figure S1-Figure S5. Figure S1. Three gene repressilator model. A1-4. Phase portraits and trajectories of TF genes A, B and C of a repressilator. Simulation settings are Cna = 2. Total simulation time is 200 (number of lifetimes of the protein product of TF gene A) and integration step is Figure S2. Dynamics of three independent Goodwin-Griffith oscillators cyclically coupled. A1-3. Phase portraits of TF genes A/B/C which are three independent GG oscillators cyclically coupled through -OR- type logic as given in Cna = 5 (we have set this to 6 for clarity of results). Total simulation time is 500 (number of lifetimes of the protein product of TF gene A) and integration step is Cna = 2. Total simulation time is 500 and integration step is C1) affects only TF gene A whereas the orbit of other TF genes B/C seems to be stable and upon removal of the perturbation the system returns back to initial limit-cycle orbit. In C2 the parameter Figure S3. Dynamics of three Goodwin-Griffith oscillators which are fully interconnected. A1-3. Phase portraits of TF genes A/B/C which are three independent GG oscillators which are fully interconnected with -OR- type logic as given in Cna = 6. Total simulation time is 500 (number of lifetimes of the protein product of TF gene A) and integration step is Cna = 2. Total simulation time is 500 (number of lifetimes of the protein product of TF gene A) and integration step is Figure S4. Tuning dynamics of A-OR-B and A-AND-B types of coupled oscillators with respect to perturbations in μ and w. A, C. Tuning capability of GG oscillators coupled through A-OR-B type logic as given in Cnh and amplitude with respect to changes in −7 to 10−3 with hw = 1) whereas plots C and D show the variation of these quantities with respect to changes in hw (iterated from 0.1 to 10 with aγ) and amplitude is measured in terms of number of hP/hsP. Figure S5. Tuning dynamics of A-OR-B and A-AND-B types of coupled oscillators with respect to perturbations in v and ε. A, C. Tuning capability of GG oscillators coupled through A-OR-B type logic as given in Cnh and amplitude with respect to changes in −7 to 10−4 with hε = 1) whereas plots C and D show the variation of these quantities with respect to changes in hε (iterated from 0.7 to 8 with aγ) and amplitude is measured in terms of number of hP/hsP.(ZIP)Click here for additional data file.


Site-directed mutagenesis of the putative C/EBPα binding sites decreased FTO promoter activity. Overexpression and RNAi studies also indicated that C/EBPα was required for the expression of FTO. Chromatin immunoprecipitation (ChIP) experiment was carried out and the result shows direct binding of C/EBPα to the putative binding regions in the FTO promoter. Collectively, our data suggest that C/EBPα may act as a positive regulator binding to FTO promoter and consequently, activates the gene transcription.Several susceptibility loci have been reported associated with obesity and T2DM in GWAS. Fat mass and obesity associated gene (FTO) is the first gene associated with body mass index (BMI) and risk for diabetes in diverse patient populations. FTO is highly expressed in the brain and pancreas, and is involved in regulating dietary intake and energy expenditure. While much is known about the epigenetic mutations contributing to obesity and T2DM, less is certain with the expression regulation of FTO gene. In this study, a highly conserved canonical C/EBP The research of crystal structure confirmed FTO gene encodes a 2-oxoglutarate (2-OG) Fe tissues . The funα to C/EBPζ. They promote the expression of certain genes through interaction with promoter region. Once bound to DNA, C/EBPs can open up chromatin structure or recruit basal transcription factors to regulate gene expression of many housekeeping and tissue-specific genes. C/EBPα is required for both adipogenesis and normal adipocyte function [α is not only necessary but also sufficient to initiate the 3T3-L1 adipocyte differentiation program [α. Mice lacking C/EBPα show abnormal adipose tissue formation [α in various fibroblast cell lines promotes adipogenesis.CCAAT/enhancer-binding proteins (or C/EBPs) are a family of transcription factors, composed of six members called C/EBPfunction . For exa program . In mousormation . Moreoveα binding sequence at positions −45~−54 relative to the transcriptional initiation site in the FTO promoter. siRNA and cotransfection studies indicated that C/EBPα upregulates its transcription. C/EBPα associates with the binding sites of the FTO gene promoter, as demonstrated in ChIP assays in vivo. Thus, our study established a molecular basis for further understanding the mechanisms governing FTO gene expression, by which FTO may act as a regulator to enhance adipogenesis.More recently, we have reported that transcription factor Foxa2 negatively regulates human FTO gene promoter, but the positive transcription factor has not been revealed. In the present study, the human FTO gene promoter structure and its transcriptional control elements have been identified. Mutational and functional analysis of the promoter revealed a functional C/EBPThe human embryonic kidney 293 (HEK 293) and human cervical carcinoma (HeLa) cells were cell lines obtained from Shanghai Cell Biology Medical Research Institute, Chinese Academy of Sciences. These cells were maintained in DMEM (Invitrogen) containing 10% heat-inactivated fetal bovine serum and 1% antibiotic-antimycotic agents.http://mbs.cbrc.jp/research/db/TFSEARCH.html) and AliBaba 2.1 (http://www.gene-regulation.com).To identify transcriptional regulatory sequences and potential transcription factor binding sites on the putative promoter regions, the sequences of human, mouse, and rat were obtained from GenBank and aligned by Clustal X program. We analyzed the 5′-flanking regions at the transcription start site with TFsearch (The cloning of the human FTO gene promoter region and the constructing of promoter luciferase report plasmids were performed as described previously . For assα and pcDNA3.1 empty vector were purified and cotransfected by using Lipofectamine 2000 (Invitrogen). Total RNA was isolated 24 hours later and analyzed by RT-PCR. For western blotting experiments, lysates were obtained from cells cultured for 48 hours in 6-well plates.In overexpression experiments, the expression plasmids pcDNA3.1-C/EBPμL Lipofectamine (Invitrogen) in serum-free medium. After 4 h incubation, complete medium without antibiotics was added and cells were incubated for 24 h. siRNAs specifically targeting C/EBPα  were custom designed [In the RNA interference experiments, HEK293 cells were seeded in 6-well plates 24 h before transfection. Cells grown to 50% confluency were washed once with serum and antibiotic-free medium and transfected with 100 nM C/EBP siRNA using 2 designed . Scramblα sites at −45/−54 of human FTO promoter was performed using MutanBEST site-directed mutagenesis kit (Takara) with the pGL3-100 plasmid as the template. The mutagenesis primers designed for the mutations were as follows (the mutated sequences are underlined): mu- C/EBPα-Forward: 5′-CCTCCTGAACAATGTAGTTCTC-3′, Reverse: 5′-CTACGGGAGCCTGCCATGTTTC-3′; mu-Sp1-Forward: 5′-GGGGTAATAGACTACGCTCTT-3′, Reverse: 5′-CCGCCGACGACCGGGAACCTAC-3′. The mu-C/EBPα-Sp1 plasmid was created using mu-Sp1 as template. In the mutant expression clones, the sequences of the entire region mutated were amplified by PCR and the expected mutations were verified by DNA sequencing.Mutation of the putative C/EBPμg of total RNA using M-MLV reverse transcriptase (Promega). Real-time PCR was performed with ABI system (ABI 7500). The Qiagen 2x SYBR Green master mix was used for PCR reaction. Negative control reactions contained sterilized double-distilled water instead of cDNA and were included in each run to ensure absence of contamination. Thermal denaturation  was used to confirm the specificity of desired PCR products. Quantitated mRNA levels of analyzed genes were normalized to GAPDH mRNA to generate a relative expression ratio. Primers utilized were as follows: FTO, forward 5′-ACTTGGCTCCCTTATCTGACC-3′ and reverse 5′-TGTGCAGTGTGAGAAAGGCTT-3′; GAPDH, forward 5′-AGGACTCATGTCCATGCCAT-3′ and reverse 5′-ACCCTGTTGCTGTAGCCAAA-3′.The indicated plasmids or siRNAs were transfected into cells as described above. Total RNA was isolated according to the standard TRIZOL (Invitrogen) method. First-strand cDNA was synthesized from 1 μL of lysis buffer containing a protease inhibitor cocktail . Protein concentrations were determined by the colorimetric BioRad Protein Assay (BioRad). Protein samples were prepared with 5x SDS sample buffer and loaded at 20 μg of protein per lane for SDS-PAGE. Western blot was performed with FTO (Abgent) and C/EBPα (Santa Cruz) antibodies, followed by goat anti-mouse IgG conjugated with HRP. GAPDH was detected as loading control. Chemoluminescence signals from three independent western analyses were quantified using an ECL imager and analyzed using Quantity One software (BioRad).After transfection and treatment, cells growing on 6-well cell-culture plates were washed in ice-cold PBS and lysed with 200 μg of normal rabbit IgG, anti-C/EBPα antibody (Santa Cruz) and the DNA was purified using gel exclusion columns. The purified ChIP DNA fragment was subjected to semiquantitative PCR analysis . Specific forward (5′-CATTGCTATAGCGCCGACAGCG-3′) and reverse (5′-GAGAATTTCCCAGGTCCGACAG-3′) primers were designed to amplify the FTO promoter region between −133 and +36 bp relative to the transcription start site, which contains C/EBPα binding sites. The sample from total chromatin before immunoprecipitation (at 1:10 dilution) was used as positive control. The PCR products were analyzed on a 2% agarose gel and quantified by densitometry using Fluor's fluorimeter and Quantity One software (Bio-rad).ChIP assays were performed according to the protocols provided by the manufacturer . Chromatin DNA was fragmented by sonication to an average length of 0.5 kb. Formaldehyde-fixed DNA/protein complex was immunoprecipitated with 5 t-test using SPSS software. P-value less than 0.05 was considered significant.Data are expressed as means ± SEM. Comparisons between means were performed by unpaired two-tailed Student's α binding site (TGGGAAAT at −45/−54 bp) and an Sp1 binding site (GTAGCGGA at −1/−8 bp) were predicted within the FTO core promoter region by TFSEARCH and Alibaba 2.1 program  was used as template. The luciferase activity of mutant constructs was measured and compared with that of the wild-type promoter (pGL3-100) using HEK 293 cell line.To investigate further the function of the C/EBPα site mutant (pGL3-mu-C/EBPα) decreased by 57.1% (Hela cell) or 55.6% (HEK 293 cell) compared with that of pGL3-100. In contrast, the change of luciferase activity is virtually absent in the reporter construct pGL3-mu-Sp1 containing the mutant Sp1 binding site. Furthermore, the two separate site-specific mutagenesis pGL3-mu-C/EBPα/Sp1 behaved similarly to the pGL3-mu-C/EBPα; luciferase activity was suppressed to 39.3% (Hela cell) or 41.7% (HEK 293 cell) (The results showed the relative luciferase activities (RLU) of the C/EBP93 cell) .α transfactor binding sites have been identified to play a role in regulating the activity of human FTO promoter. In the following experiments, we further examined the ability of C/EBPα to modulate the expression of FTO. C/EBPα expression vector pcDNA3.1-C/EBPα or C/EBPα siRNA was transfected into HEK 293 cells. FTO mRNA and protein levels were detected by RT-PCR or Western blotting, respectively. As illustrated in α increased the FTO transcript level 2.1-fold (α significantly inhibited the FTO expression at both the mRNA level (66.3%) and protein level (56.2%).The C/EBP2.1-fold  and FTO 2.1-fold . Conversα binds to the FTO promoter. Nuclear lysates prepared from HEK 293 were subjected to sonication to shear DNA to lengths between 200 and 1000 bp on ice followed by phenol/chloroform extraction to recover protein/DNA complexes. C/EBPα antibody was used to pull down the complexes as instructed. The resultant precipitates were then used as templates for PCR amplification of FTO promoter sequence containing the C/EBPα binding motif. As shown in α antibody yielded a corresponding band as that of amplification with input (1 : 10), an aliquot of chromatin that was not incubated with an antibody, while no band was showed in the negative control (IgG). These results clearly demonstrate an in vivo recruitment of C/EBPα binding element on the human FTO promoter. Taken together, our results suggest that C/EBPα specifically binds to the predicted motifs to regulate FTO transcription and expression directly.ChIP analysis was performed to test if C/EBPThe association of the genetic variants of FTO gene with obesity and diabetes was recently identified by several independent GWA studies. Subsequent studies have revealed the influence of FTO variants on measures of appetite, food intake, or energy expenditure. FTO is highly expressed in the brain  and pancreas. The putative influence of FTO in hypothalamic-pituitary-thyroid axis has been determined , 11. A nα binding sequence was identified in the core promoter region of the FTO gene, suggesting that the binding sites may play important roles in regulating the expression of FTO gene. Promoter-reporter gene constructs that contain the proximal C/EBP binding site showed that C/EBPα strongly activates reporter gene expression. Moreover, mutation of the C/EBPα binding site within the promoter completely blocked transactivation by C/EBPα. We then performed gene transfection-mediated overexpression and RNA interference- (RNAi-) mediated gene silencing of C/EBPα on HEK 293 cells and the results suggested that C/EBPα promoted the expression of FTO. Consistent with this, ChIP experiments showed that C/EBPα binds to the predicted binding element in the FTO promoter. Taken together, these findings provide compelling evidence that C/EBPα to be a positive transcriptional factor contributes to the transcription and expression regulation of human FTO gene.The human FTO gene transcription has been studied previously by our group. We had reported that the region (−100/+34) seems to be crucial because deletion of this fragment would not remain as the basal promoter activity. Transfactor Foxa2 was defined to regulate the transcription and expression of FTO gene negatively. There are no data about transcription factors positively involved in FTO gene expression. Here, we improved the regulatory mechanism of human FTO gene expression. A conserved C/EBPα, β, δ, γ, ε, and ζ), containing conserved DNA binding domain at C-terminus and an activation domain at their N-terminus. Data presented that different C/EBP number occurs at different point-in-time in adipogenesis, indicative of their own distinct roles during the progress [α is expressed in liver, adipose tissue, and muscle and is required for both adipogenesis and normal adipocyte function. Ectopic expression of C/EBPα in various fibroblast cell lines promotes adipogenesis. Moreover, it was reported that C/EBPα promotes adipogenesis by inducing the expression of peroxisome proliferator activated receptor γ (PPARγ). It was reported that PPARγ was able to promote adipogenesis even in the absence of C/EBPα, whereas C/EBPα could not promote adipogenesis in the absence of PPARγ [γ expression and adipocyte differentiation [α mediates different signaling pathways involved in adipogenesis. While some researchers have found that FTO expression was not modulated during differentiation of preadipocytes into mature adipocytes, some have even demonstrated that FTO expression is decreased during differentiation of primary preadipocytes isolated from human subcutaneous adipose tissue or preadipocytes derived from Simpson-Golabi-Behmel syndrome (SGBS) [The C/EBP transcription factors consist of six members  , 18. TheκB and C/EBP family can be activated by inflammatory cytokines such as interleukin-1 (IL-1) and IL-6, respectively, whereas IL-6 suppresses the transcription of adiponectin [FTO has also shown a positive association with the expression of adiponectin, an anti-inflammatory adipokine in adipose tissues. NF-ponectin –21. Muchα and Foxa2, respectively, positively and negatively regulated the expression of human FTO gene. Given the complex interacting network of transcription factors involved in time-space characteristics of gene expression, it can often be difficult to determine which factor plays a crucial role in the transcriptional regulation process. Data derived from further experiments would unravel the details of FTO functions and regulatory networks.In summary, we have confirmed so far that C/EBP


Early steps of gene expression are a composite of promoter recognition, promoter activation, RNA synthesis and RNA processing, and it is known that SUMOylation, a post-translational modification, is involved in transcription regulation. We previously found that SUMO-1 marks chromatin at the proximal promoter regions of some of the most active housekeeping genes during interphase in human cells, but the SUMOylated targets on the chromatin remained unclear. In this study, we found that SUMO-1 marks the promoters of ribosomal protein genes via modification of the Scaffold Associated Factor B (SAFB) protein, and the SUMOylated SAFB stimulated both the binding of RNA polymerase to promoters and pre-mRNA splicing. Depletion of SAFB decreased RNA polymerase II binding to promoters and nuclear processing of the mRNA, though mRNA stability was not affected. This study reveals an unexpected role of SUMO-1 and SAFB in the stimulatory coupling of promoter binding, transcription initiation and RNA processing. Small Ubiquitin-related Modifier (SUMO) proteins are highly conserved among eukaryotes, and protein SUMOylation has a critical role in a variety of cellular signaling pathways including control of cell cycle progression, DNA repair, gene expression and nuclear architecture . Among vIn this study, we first sought to identify the SUMOylated protein bound to the chromatin at active promoters, and we found that Scaffold Associated Factor-B (SAFB), a DNA and RNA binding protein, is one of the SUMO-1 targets. Two homologs (SAFB1 and SAFB2) have been found with 74% similarity at the amino acid level, and up to 98% similarity in some functional domains and display redundant activity . SAFB1 iHere, we provide evidence that both SAFB1 is a SUMO-1 substrate bound to the chromatin during interphase in a region centering on 100 bp upstream of the transcription start site. Like SUMO-1, depletion of SAFB diminished RNAPII binding to promoters and decreased RNA expression of these ribosomal protein genes, revealing an unexpected role of SAFB linking transcription initiation to RNA processing of the highly active ribosomal protein (RP) genes.8 HeLa-SUMO1 cells were lysed in lysis buffer I (50 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid–potassium hydroxide (HEPES–KOH), pH 7.5, 140 mM NaCl, 1 mM Ethylenediaminetetraacetic acid (EDTA), 10% glycerol, 0.5% NP-40, 0.25% Triton-X-100), and the cell pellet was resuspended in lysis buffer II ), and, following centrifugation (1400 x g), the chromatin was recovered from the pellet and resuspended in lysis buffer III . The isolated chromatin was sheared to 200–300 bp by sonication, incubated with 375 μl of Ni-NTA beads (Qiagen) for 16 h at 4°C. After washing in wash buffer I , chromatin fragments were eluted in 6 ml elution buffer (washing buffer I with 300 mM imidazole). The nickel eluate was incubated with 375 μl of streptavidin beads (Invitrogen) for 6 h at 4°C. After three stringent washes, wash buffer II , and three times of 10 mM Tris buffer, pH 8. The chromatin was then trypsinized (ratio 1:120 w/w) in solution for 2 h at 37°C. Following lyophilization, the digested solution was dissolved in 50 μl high performance liquid chromatography (HPLC) grade water and subjected to LC–MS/MS; protein identification was analyzed using Massmatrix 2.4.2  and loaded onto 200 μl of cushion buffer . The samples were centrifuged for 10 min at 800 × g. The cytoplasmic supernatant was treated with proteinase K, extracted with phenol–chloroform and precipitated with ethanol. The nuclear pellet was resuspended in 100 μl of DNAse I buffer  and treated 20 U of DNase I (Invitrogen) for 60 min at 37°C. The samples were then extracted with phenol–chloroform and precipitated with ethanol. The mRNA levels were determined by reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) using the iScript reverse transcription and iQSYBR Green supermix (Bio-Rad). The results were normalized to 18S rRNA.Nuclear and cytoplasmic RNAs were purified by lysis of HeLa-SUMO1 cells in 200 μl of lysis buffer  or HeLa-SUMO1 cells (if ChAP) were fixed with 1% formaldehyde, lysed in lysis buffer, sonicated to size ranging from 200 to 1000 bp, chromatin was diluted 4-fold, after removal of a control aliquot, incubated at 4°C overnight with antibody against 8WG16 (1:100), 5 μg Ser-5p antibodies, or 5 μg IgG antibody was used as a negative control. Immunocomplex was precipitated with 50 μl protein A sepharose beads , washed with Radioimmunoprecipitation assay buffer, 10 mM Tris pH 7.5, 300 mM NaCl, 1% NP-40, 1% deoxylcholate, 0.1% SDS (RIPA) buffer followed by crosslink reversal. The immunoprecipitated DNA was purified by PCR purification kit (Qiagen). All the experiments included at least three independent replicates. The primer sequences are available in Supplementary Table S2.Immunoprecipitation was performed following established procedures . ChromatWe have previously shown that SUMO-1 is enriched on the chromatin proteins bound to promoter regions of some of the most active genes during interphase, such as ribosomal protein (RP) encoding genes , which aSince SUMOylated chromatin-associated proteins and transcription factors are low in abundance, and SUMOylated targets are highly dynamic and rapidly reversed by SUMO proteases, a cell line called HeLa-SUMO1 that stably expresses SUMO-1 fused with a hexahistidine and biotinylated (HB) tag was used for isolation of SUMO-1-labeled chromatin proteins. SUMO-1 modified chromatin associated proteins were shown to be present during interphase and absent during mitosis . To iden6-biotin (HB) tag, and followed by ChIP-qPCR analysis. Transfection into control cells of a HB-tag only plasmid was used to control for nonspecific binding. SAFB-1 was found to associate with all eight of the RP promoters tested (Figure The top 20 proteins identified by mass spectrometry are listed in order of highest score in Table d Figure .To determine if SAFB was responsible for the recruitment of SUMO-1 binding on the specific promoters, we tested whether depletion of SAFB affected the recruitment of SUMO-1 to promoters that we had previously characterized to be SUMO-1 bound . Since tWe have shown previously that SUMO-1 marks the chromatin just upstream of the transcription start site of constitutive housekeeping genes and that the SUMO-1 mark stimulated transcription. In addition, the SUMO-1 mark was also found enriched on exons in the human genome, suggesting a potential role for facilitating splicing . Given tTo further investigate the effect of SAFB on RNA metabolism, we asked whether depletion of SAFB affected mRNA stability. Actinomycin D was included in media to block new mRNA transcription, and we harvested RNA species at different time points. We found that there is no change of mature mRNA, suggesting the RP RNA is fairly stable for at least 2 h, independent of SUMOylation or of SAFB Figure . The preSince ribosomal protein expression is highly sensitive to cell proliferation rates, we tested whether depletion of SAFB or SUMO-1 affected cell proliferation. We depleted SAFB and SUMO-1 from HeLa cells as usual Figure , and seeIn this study, we discovered that SUMO-1 binds to the chromatin at promoters of ribosomal protein genes via the scaffold attachment factor, SAFB. We found that SAFB is SUMOylated, and depletion of SAFB caused a decrease of SUMO-1 association with the promoters on the chromatin. These promoters, encoding RP genes and translation factors, are among the most active RNAPII promoters in the cell, and SUMO-1-tagged SAFB stimulates both the recruitment of RNAPII and the splicing of the product RNAs. In addition, a number of RNA processing factors were found to be SUMO-1 targets, suggesting that SUMO-1 marks on the promoter during the transcription cycle can be important for determining the efficiency of pre-mRNA splicing. The SUMO-1-SAFB axis revealed in this study, defines a fast track for gene expression; blocking this pathway via RNAi mediated depletion did not cause a total inhibition of transcription and processing but rather a decrease toward the expression levels of most protein-encoding genes .The SAFB1 protein has been reported to be covalently modified by SUMO-1 as well as SUMO-2/3, and this modification is associated with transcriptional repression activity . The lysSUMOylation of multiple proteins in a single pathway that stimulate the DNA repair process has been described , and we in vivo (Nuclear function depends on organizing platforms for establishing structural and functional domains in the nucleus. In this study, we found that SUMOylation facilitates RNAPII recruitment on the constitutive promoters, which is consistent with the observation in yeast . In addiin vivo , and it in vivo . TherefoTaken together, the results of this study suggest a novel function for SAFB in regulation of gene expression by coordinating transcriptional initiation and RNA processing. It is possible that SUMOylated SAFB associates with the CTD of the initiating RNAPII and travels with RNAPII as it synthesizes nascent pre-mRNA, and subsequently facilitates the assembly of splicing complexes and splicing on the first intron to emerge, and further coordinates transcription and pre-mRNA processing levels.Supplementary Data are available at NAR Online.


Since decades it has been known that non-protein-coding RNAs have important cellular functions. Deep sequencing recently facilitated the discovery of thousands of novel transcripts, now classified as long noncoding RNAs (lncRNAs), in many vertebrate and invertebrate species. LncRNAs are involved in a wide range of cellular mechanisms, from almost all aspects of gene expression to protein translation and stability. Recent findings implicate lncRNAs as key players of cellular differentiation, cell lineage choice, organogenesis and tissue homeostasis. Moreover, lncRNAs are involved in pathological conditions such as cancer and cardiovascular disease, and therefore provide novel biomarkers and pharmaceutical targets. Here we discuss examples illustrating the versatility of lncRNAs in gene control, development and differentiation, as well as in human disease. It has long been known that several classes of non-protein-coding RNA molecules exert important cellular functions. For instance, ribosomal RNAs (rRNAs) are essential elements of the translation machinery and small nuclear RNAs (snRNAs) are required for splicing of nascent RNA transcripts. Also, various classes of small (around 20–30 nucleotides) noncoding RNAs such as micro (mi)RNAs, small inhibitory (si)RNAs or PIWI interacting (pi)RNAs are well known as gene silencers. With the recent advent of massive parallel sequencing techniques, however, it has been observed that a tremendously high portion, approximately 70 %, of the genome is transcribed in various contexts and cell types , 2. A laA plethora of biological tissues, organs, pathological samples and cultured cells have been analyzed for noncoding RNA expression, and it is clear that these molecules are omnipresent. Apparently, defining noncoding RNA function has proven more challenging than detecting them, as the number of reports showing comprehensive functional data is far smaller than those describing their identification in various contexts. The flexibility of RNA transcripts and their ability to fold into complex 3D-conformations enables them to form specific interactions with proteins. They can interact with RNA or DNA molecules via base pairing, even with double-stranded DNA, and form networks with DNA, protein complexes and RNA molecules, illustrating their large potential as an important player with many biological functions. In this review, we will discuss mechanisms of lncRNA functions with a focus on their role in development and disease Table . Table 1Like mRNAs, lncRNAs are transcribed by Polymerase II, mostly 5′-capped, polyadenylated and spliced, though on average they contain a lower number of exons than mRNAs and their expression level assessed across different tissues is lower , 4. TherDeep-sequencing experiments revealed many examples of genes producing both protein-coding and noncoding transcripts by alternative splicing. However, so far, only very few reports demonstrate a functional role for both the noncoding RNA(s) and the protein(s) encoded by transcripts derived from the same gene , 16. It RNA molecules have the potential to form highly structured macromolecules by folding into double-stranded stems, single-stranded loops and bulges, which again can fold further into three-dimensional structures, allowing for the potential formation of complex shapes. So far, the structure of only a few RNAs has been experimentally determined using a combination of chemical assays, and by determining the accessibility of base-paired or single-stranded RNA by various RNases , 18. HowThe similarity between mRNA-encoding and lncRNA genes is furthermore reflected by the chromatin signatures at the genomic regions from where they are transcribed. Their transcriptional start site is, in most cases, marked by the H3K4me3 histone modification and the transcribed region by the H3K36me3 mark, no matter if the lncRNA originates from its own promoter or from an enhancer. However, these histone marks are less prominent than observed at mRNA coding genes, whereas H3K4me1, a characteristic mark of enhancers, tends to be more prominent at genomic regions encoding lncRNAs , 21–23. So far, the most commonly used categorization of the highly heterogeneous class of lncRNAs is their position in the genome relative to protein-coding genes Fig. . LncRNAscis.Genome-wide sequencing of RNA species isolated from cytosolic or nuclear fractions of cells has shown that the majority of lncRNAs tend to be localized in the nucleus or are associated with chromatin, while a considerable fraction localizes to the cytoplasm , 28, 29.The genomic sequences of lncRNAs are, in general, less conserved than exons, but more than introns of protein-coding genes, pointing towards a rapid evolution with moderate constraints , 30. In A different explanation for low conservation of lncRNAs is the increasing number of such transcripts in increasingly complex species. This finding, in combination with the observed highly tissue-specific expression of many lncRNAs, suggests that lncRNAs might be key molecules promoting species-specific features and organ complexity –38. ThusThe best-described function for lncRNAs in the nucleus is their role in regulating gene and genome activity on various levels Fig. a–e. ManyXist), a lncRNA that is highly expressed from the inactive X-chromosomes in females (Xi) and recruits PRC2 to the Xi to silence gene expression [Prominent examples of histone-modifying complexes interacting with lncRNAs are the two polycomb repressive complexes, PRC1 and, in particular PRC2, which mediates methylation of lysine 27 on histone 3 (H3K27me), a histone mark associated with repressed or poised genetic loci. The first report of an interaction of PRC2 with a noncoding RNA came from studies on X-chromosome inactivation in mammals, which involves X-inactive specific transcript , which removes a histone mark of active chromatin and thus reinforces the establishment of a repressive chromatin environment on target loci [Hotair in mice leads to de-repression of imprinted genes and of HoxD genes, which lose H3K27-methylation and gain H3K4-methylation marks, as expected from loss of the enzymatic activity of PRC2 and LSD1 at these loci. Furthermore, Hotair knockout mice show skeletal homeotic transformation phenotypes, which are typical for mutations affecting Polycomb mediated repression [HoxC cluster including Hotair do not display these phenotypes, suggesting a complex interplay of multiple genomic regions in regulating HoxC cluster gene expression [Another prominent example is get loci   is a lncRNA that is activated during early cardiac differentiation and acts upstream of MESP1, a basic Helix-loop-helix transcription factor involved in early heart development. Bvht also exerts its function via an interaction with PRC2 [Fendrr; or Foxf1 adjacent noncoding developmental regulatory RNA) is likewise involved in cardiac development and heart function and interacts with PRC2. Fendrr also interacts with WDR5, which is well known for its presence in the MLL complexes that mediate H3K4 methylation, a mark that is thought to oppose H3K27me. Fendrr might play a role at poised genes, or is involved in tuning the balance of active and repressive marks at its target gene promoters, thus adjusting the correct expression level of its targets [ith PRC2 . The lnc targets , 47. The targets –52.An intriguing mechanism as to how lncRNAs might recruit their protein interaction partners to specific genomic loci is DNA-RNA triplex formation , which hFAL1). The interaction of FAL1 with BMI1, an essential subunit of PRC1, regulates its protein stability [FAL1 in an ovarian cancer cell line led to gene expression changes, slower cell cycle progression and induction of senescence, similar to the effects of the BMI1 knockdown. This latter phenotype could be partially rescued by knockdown of the senescence-promoting factor CDKN1A (p21). Additional ChIP data suggested that BMI1 binds to the promoter of CDKN1A and, together with FAL1, suppresses the expression of this target and of many other genes.An example of a lncRNA interacting with the PRC1 complex is Focally amplified lncRNA on Chromosome 1  via a POLII-dependent mechanism to its locus in order to repress the neighboring INK4B-ARF-INK4A genes, antagonize cellular senescence and indirectly promote cell cycle activity [Whereas igenesis . ANRIL ractivity , 59.HOTTIP and NeST have been described to recruit WDR5 to their neighboring genes and thus enhance their transcription [The repressive H3K27-methylation, catalyzed by EZH2 in the PRC2 complex, is opposed by MLL complexes, which mediate methylation of H3K4me2/3, a mark associated with loci that are actively transcribed or primed for activation. WDR5 is an integral part of all MLL complexes, but also interacts with several other protein complexes . WDR5 hacription , 63.ecCEBPA), a transcript starting upstream of the CEBPA gene, leads to down-regulation of CEBPA and increased DNA methylation of the locus. A subsequent global analysis of all lncRNAs bound to DNMT1 [IL17b, the pancRNA knockdown resulted in cell death of the developing blastocyst. Supplementing the embryos with IL17b protein rescued the phenotype.Whereas many lncRNAs associating with Polycomb complexes act by promoting PRC occupancy at genomic target sites, lncRNAs described in the context of DNA methylation have mostly been found to oppose this epigenetic mark. Frequently, transcription of noncoding RNAs, which interact with DNMTs, keeps a locus free of DNA methylation , 64–66 a. InitiaTcf21 antisense RNA reducing DNA methylation (TARID), keeping the protein-coding gene (Tcf21) on the opposite DNA strand free of DNA methylation required GADD45A and the TET proteins [In the case of proteins  pointingSChLAP1 have opposing roles. SChlAP1 interacts with the SNF5 subunit of the chromatin remodeling complex SWI/SNF, and globally inhibits binding of SWI/SNF to chromatin, subsequently leading to genome-wide de-repression of gene activity [Myheart (Mhrt), a lncRNA transcribed divergently to Myh6 and overlapping with Myh7 in antisense direction, binds to BRG1, the ATPase subunit of the SWI/SNF complex, and excludes it from the Myh6/7 locus, thus preventing chromatin remodeling [Mhrt. Cardiac stress leads to upregulation of BRG1 to a level allowing it to overcome the repulsion of the SWI/SNF complex from chromatin by Mhrt and to bind to the Myh6 locus.In addition to interaction with enzymatic complexes, which covalently modify chromatin, lncRNAs have also been shown to control chromatin remodeling complexes that can alter the nucleosome spacing in an energy dependent manner. In human prostate cancer, gene expression analyses showed that SWI/SNF and the lncRNA activity . Similarmodeling . BRG1, iEvf2 lncRNA, transcribed from the genomic region between Dlx5 and Dlx6, promotes SWI/SNF binding to the enhancers of these genes. However, Evf2 inhibits the remodeling activity of SWI/SNF and thus interferes with upregulation of Dlx5/Dlx6. Accordingly, in Evf2 mutant mice, Dlx6 and, to a lesser extent, Dlx5 are upregulated [Evf2 to BRG1 can be out-competed by other RNAs of similar length and results in reduced remodeling activity, suggesting that the binding of lncRNAs to the SWI/SNF complex is promiscuous. Xist, on the other hand, binds to components of the SWI/SNF complex, but excludes the complex from the Xi, rather than recruiting it [lncTCF7 or WNT signaling pathway activating non-coding RNA (WSPAR), transcribed 200 kb upstream of TCF7, can recruit SWI/SNF to the TCF7 promoter and thus activate TCF7 expression and WNT signaling [The egulated , 70. In iting it . The SWIignaling .The specificity of lncRNA interactions with chromatin-modifying complexes has been questioned. For instance, a large number of lncRNAs have been shown to co-purify with PRC2, possibly suggesting non-specific binding , 52, 73.definitiveendoderm-associated lncRNA1 (DEANR1) , for instance, is transcribed downstream of FOXA2 and is highly induced during differentiation of ESCs towards definitive endoderm [DEANR1 inhibits endodermal differentiation due to the reduction of FOXA2 expression. This interpretation is strongly supported by the fact that endoderm differentiation is rescued in DEANR1 knockdown cells upon forced FOXA2 expression. Mechanistically, DEANR1 was proposed to interact with SMAD2/3 and to recruit it to the FOXA2 promoter.Besides chromatin modifiers, transcription factors have also been found to interact with lncRNAs. The lncRNA endoderm , 77. Knorhabdomyosarcoma associated transcript (RMST) is required for neuronal differentiation by mediating binding of the transcription factor SOX2 to approximately half of its binding sites [Lethe (after the ‘river of forgetfulness’ in Greek mythology) interacts with RelA and prevents it from binding to DNA [p50-associated cyclooxygenase-2 (COX-2) extragenic RNA (PACER), on the other hand, sequesters p50, which forms homodimers and is repressive at high concentration, thereby lowering its concentration and allowing it to form activating heterodimers with p65 [lnc dendritic cells (lnc-DC) binds to the transcription factor STAT3 in the cytoplasm and prevents its dephosphorylation by SHP1, thereby activating STAT3 and thus dendritic cell differentiation [The lncRNA ng sites . Certaing to DNA . p50-asswith p65 . Anotherntiation .BCAR4). This lncRNA binds to the SMAD nuclear interacting protein 1 (SNIP1) and a phosphatase (PNUTS) involved in RNA polymerase II regulation. In response to cytokine stimulation, BCAR4 lifts the inhibitory effect of SNIP1 on p300, a histone acetyl transferase and transcriptional activator. Acetylated histones are necessary for BCAR4 mediated recruitment of PNUTS, which in turn leads to active polymerase II at GLI2 controlled genes [An elaborate mechanism linking transcription factor binding and chromatin modifications has been found for breast cancer anti-estrogen resistance 4  [Previously, transcripts found at enhancers had been interpreted as byproducts of transcription from promoters contacted by enhancers. Now, it is well established that RNA transcripts produced at active enhancers are functionally important –87. An e cluster , 89. To  cluster   . WhetherIn general, eRNAs are co-regulated with their neighboring gene(s)  and presHaunt , for instance, has been shown to lead to upregulation of several genes of the neighboring HoxA gene cluster. However, larger deletions in the Haunt locus impair HoxA expression [Haunt was furthermore observed at the single cell level confirming that the expression of HoxA1 and Haunt are anti-correlated [LncRNAs transcribed from enhancer regions can also have inhibitory effects on their target gene. The promoter deletion of the lncRNA pression , demonstrrelated .Playrr (D030025E07Rik), a lncRNA encoded upstream of the homeodomain transcription factor Pitx2 [Pitx2 expression is constrained to the left side of the gut dorsal mesentery, whereas expression of Playrr is detected on the right, but spreads to both sides in Pitx2 deletion mutants. A CRISPR/Cas9 generated mutation resulting in Playrr RNA decay caused upregulation of Pitx2 expression [Pitx2 and Playrr. An enhancer involved in Pitx2 regulation in the gut overlaps the TSS of Playrr. In the cells on the left-hand side, where Pitx2 is expressed, the Pitx2 locus was found to be in closer proximity to the Playrr locus than in cells on the right side and to cause down-regulation of Playrr by an unknown mechanism. In cells on the right, on the other hand, Playrr RNA is thought to cause a separation of the Pitx2 locus from the enhancer at the Playrr locus suggesting that Playrr expression interferes with the looping of the Pitx2 promoter to its enhancer at the Playrr locus and thus with Pitx2 gene activation , which escapes X-chromosome inactivation was suggested to stabilize the perinucleolar location of the Xi [Firre was proposed to mediate focal trans-chromosomal contacts [Firre and a role in the control of factors involved in RNA processing [Furthermore, the lncRNAs er cells . Other l from Xi . Deletiof the Xi . Additiocontacts . This fiocessing . These ePnky (divergent to Pou3f1) binds to the splicing factor PTBP1 and thereby regulates the splicing patterns of a subset of genes involved in neurogenesis [TUNA (megamind), which interacts with PTBP1 as well, functions via the same mechanism remains to be investigated [MIAT) has been found to influence splicing in different systems. In embryonic neurogenesis, MIAT is involved in controlling the splicing pattern of Wnt7b [MIAT binds to splicing factors, and in post-mortem brains of schizophrenia patients, it was found to be down-regulated, suggesting that it might contribute to this pathological phenotype [MALAT1, a highly expressed lncRNA enriched in nuclear speckles, has been suggested to be a general component of the splicing machinery [MALAT1 knockout did not show disintegration of splicing speckles [NORAD) [NORAD sequesters PUMILIO proteins and thereby promotes genomic stability  . NORAD sity Fig. f. AblatiCDR1as was shown to act as a sponge for the miRNA let-7 [CDR1as in zebrafish caused impaired midbrain development, similarly to the effect of a let-7 inhibitor. It was also shown that small polypeptides can be derived from some circRNAs, extending the functional repertoire of these stable RNA molecules [The most recently described class of lncRNAs that came into focus are the circRNAs. Due to their circular structure, they are resistant to degradation by exonucleases and are therefore thought to be highly stable within a cell. The brain specific circRNA NA let-7 , 27  [H19 deletion on the maternally inherited chromosome led to an increase in Igf2 expression and thus to increased bodyweight. This phenotype could be rescued by deletion of one Igf2 allele. H19 knockout mice are viable and fertile [H19 transcript [Igf2r gene is silenced by the lncRNA Airn, which is transcribed from the opposite strand, overlapping the 5-prime region of Igf2r. Here, silencing is not achieved by the lncRNA transcripts as such, but by transcription through the Igf2r promoter, which interferes with RNA PolII recruitment [The mechanisms first found to be linked to lncRNAs were imprinting and X-chromosome inactivation. Accordingly, the first lncRNA that was genetically targeted and deleted was ears ago . H19 is 2 (Igf2) –116. An anscript . The impruitment . Severalruitment .Xist was obtained two decades ago when Xist knockout mice were generated and analyzed [Xist are unaffected, whereas females die during the first half of gestation. Interestingly, knockout females with a single X-chromosome (XO) lacking Xist are healthy, strongly suggesting that it is not the lack of Xist, but the failure to adjust the X-chromosome gene dosage that causes embryonic lethality.Insight into the developmental function of analyzed , 121. MaGtl2 , showed clear cis-acting effects on neighboring genes resulting in perinatal lethality [In a more recent example, the deletion of another imprinted lncRNA gene in the mouse, ethality .NEAT1 resulted in viable and fertile mice, however, knockout females showed about 50 % reduced fertility due to reduced progesterone production and corpus luteum formation [Many other mouse models in which lncRNAs have been removed by deletion of genomic fragments did not show overt phenotypes, but after detailed analyses, some specific defects have been observed , 123–126ormation . Ovary tFendrr is one of few rare examples of lncRNAs demonstrated to play an essential role in organ development and embryo survival. Fendrr, which is divergently transcribed from the Foxf1 promoter, was analyzed by two different strategies [Fendrr leaving most of the genomic context undisturbed resulted in impaired heart function, omphalocele , and embryonic death [Fendrr interacts with chromatin-modifying complexes and with DNA, possibly through triplex formation, and thereby changes the chromatin landscape of specific target promoters in trans, in particular those of mesodermal transcription factors [Fendrr rescued the developmental defects caused by the loss of Fendrr, strongly suggesting that the observed phenotype is caused by lack of Fendrr RNA, and not by disruption of genomic sites or promoter elements of the adjacent Foxf1 gene. This conclusion was supported by a different knockout strategy, in which the first exon was left intact and which resulted in perinatal death [Fendrr is only transiently expressed in nascent lateral mesoderm [rategies , 123. Inic death . Fendrr  factors . A BAC-tmesoderm . Howevermesoderm .DEANR1  is expressed downstream of the endoderm master regulator FOXA2 [DEANR1 depletion results in reduced expression of FOXA2 and accordingly to reduced differentiation of hESCs towards definitive endoderm. Interestingly, this defect can be rescued by restoring normal levels of FOXA2 expression, suggesting that DEANR1 functions mainly in cis. Another study described the same lncRNA, here called ALIEN, in cardiovascular progenitor cells in mouse and zebrafish. Depletion of ALIEN interfered with cardiac development, although the functional mechanism remains to be investigated further. DEANR1 was described to be localized in the nucleus, whereas ALIEN was seen in the perinuclear space and in the cytoplasm, even though both were analyzed in differentiating human stem cells. The discrepancy between the two studies might be a consequence of modifications in the differentiation method [More lncRNAs involved in mesoderm and endoderm development have been reported. For instance or FOXA2 , 77. DEAn method , 77.Pitx2, which is essential for the development of many different organs, especially during the establishment of left–right asymmetry, is regulated by a lncRNA in the embryonic gut [Playrr is transcribed from a distant known enhancer region. The expression patterns of Pitx2 and Playrr are negatively correlated due to interference of Playrr with Pitx2 activation (for details see above).Also, the transcription factor onic gut . In thisPouIII genes Pou3f3 and Pou3f2 (Brn1 and Brn2) encoding important neuronal transcription factors, were also found to play roles in neuronal development [Dali  (DNMT1-Associated Long Intergenic RNA) is transcribed 50 kb downstream of Pou3f3. The depletion of Dali leads to a reduction of Pou3f3 expression and to impaired neuronal differentiation [Dali. Furthermore, Dali physically interacts not only with various chromatin modifiers, but also with POU3F3 itself suggesting a multilayered association between Dali and POU3F3. The replacement of Pantr1 , which is divergently transcribed to Pou3f3, by insertion of the lacZ gene did not influence Pou3f3 transcription itself, but modulated other Pou3f transcription factors in trans [Pantr2 (or Linc-Brn1b), expressed convergent with Pou3f3, did not have this effect on Pou3f factors, and upon deletion led to fewer intermediate progenitors in the developing cortex. Thus, each of these three different lncRNAs, which are all transcribed near the Pou3f3 locus, affect neuronal development yet through distinct mechanisms.LncRNAs expressed during neuronal and brain development have attracted particular attention. As described earlier, many lncRNAs are highly specifically expressed in distinct cell types, as illustratively shown in a targeted LacZ reporter screen  and in eelopment , 131. Thin trans . Pantr2 Evf2 in the Dlx5/6 locus [Evf2 was targeted by inserting a polyadenylation signal close to the promoter without deleting genomic DNA. Evf2−/− embryos have less GABAergic neurons than wild type controls. This mutant effect could be rescued by in utero electroporation of Evf2 RNA, confirming that the phenotype is indeed dependent on this lncRNA.Furthermore, another lncRNA located in a region important for neural development is /6 locus . Evf2 waRMST, also termed non-coding rhabdomyosarcoma (NCRMS) in humans, is a noncoding transcript expressed in rhabdomyosarcomas [RMST is induced during neuronal differentiation of hESCs, and its depletion interferes with neuronal differentiation via its binding partner SOX2 (see above) [RMST was found associated with obesity in a GWAS study, possibly pointing to a role of RMST in a neuronal regulatory network influencing energy balance [sarcomas  and in dsarcomas . RMST ise above) , 129. In balance .retinal noncoding RNA2 and 4 (RNCR2 and RNCR4). They were first found to be expressed in the developing retina and later also assigned a functional role in this process [RNCR4 is part of a network including the RNA helicase DDX3X and the miR-183/96/182 that is essential for retinal architecture [RNCR2, also known as MIAT or Gomafu, interferes with retinal cell differentiation when overexpressed or depleted [MIAT is expressed earlier in the developing brain, where it localizes to the nuclear matrix [MIAT is highly abundant in differentiating progenitors, where it is involved in corticogenesis by regulating the splicing pattern of Wnt7b [Two more lncRNAs involved in nervous system development are the  process . RNCR4 iitecture . RNCR2, depleted , 137. Fur matrix . Purifyiof Wnt7b   is essential for maintaining the proliferating progenitor pool by repressing differentiation factors, amongst them the transcription factors MAF and MAFB, probably in a PRC2 linked manner [ANCR leads to differentiation and loss of progenitor cells. Its differentiation promoting counterpart is a cytosolic lncRNA, terminal differentiation induced ncNRA (TINCR) that interacts with STAU1 and as a protein-RNA complex stabilizes mRNAs of pro-differentiation genes including MAF and MAFB [TINCR depleted cells restored the expression of the differentiation gene signature showing that TINCR is crucial for ensuring appropriate protein levels in particular of MAF and MAFB.Another ectodermal derivative, the developing epidermis, has also been shown to be regulated by lncRNAs. During epidermal differentiation and maintenance, the nuclear lncRNA d manner –141. Depand MAFB  , and its expression level and copy number significantly correlated with patient survival [FAL1 depletion [MALAT1 after tumor induction reduced metastasis formation in a xenograft lung cancer model and in a metastasizing breast cancer model [MALAT1 knockout mice do not show overt phenotypes [MALAT1 in humans might also not be harmful for normal human cells, which makes it an attractive target for systemic application in patients.In addition, somatic copy number alterations (SCNA) found in cancer tissue often include lncRNA loci , 147. Fosurvival . Furthersurvival , 148–150survival , 151–154epletion . In a dier model , 155. MAenotypes , 157 sugBRAFP1, which has been shown to be either mutated or aberrantly expressed in cancers, like its coding homologue BRAF. A mouse model revealed that induced overexpression of Braf-rs1 (the murine homologue of BRAFP1) leads to DLBCL (diffuse large B cell lymphomas)-like tumors. However, when the transgene was first induced to form tumors and then shut down again, the tumors regressed demonstrating the functional significance of the pseudo gene [Braf-rs1 was shown to cause upregulation of Braf by acting as a ceRNA (competing endogenous RNA) and by “sponging” miRNAs that would otherwise target Braf transcripts.A special case is the noncoding pseudo gene udo gene . Braf-rsINK4B-ARF-INK4A locus, which plays a major role in OIS, is silenced in proliferating cells by Polycomb group proteins. This mechanism is dependent on the lncRNA ANRIL, which is transcribed from within the locus and acts in cis [MIR31HG gene located 400 kb upstream of the INK4B-ARF-INK4A locus, also encodes a lncRNA involved in the regulation of INK4A [UCA1, stabilizes mRNAs of protein-coding genes involved in the senescence pathway, probably by sequestering hnRNPKA1 [linc-p21, which in turn regulates gene expression in concert with p53 and p21 [One mechanism that cells can employ to prevent tumor formation is oncogene-induced senescence (OIS) . The INKs in cis , 59, 160of INK4A . A thirdhnRNPKA1 . Also, t and p21 –166.MIAT and ANRIL [ANRIL locus led to increased mortality in mice, particularly in combination with a high fat diet [LncRNAs have also been linked to cardiovascular diseases (CVD), which are a major cause of death in western societies, and have been studied both in patient data, as well as in mouse models. It was observed that several genomic regions significantly associated with myocardial infarction encode lncRNAs, for example nd ANRIL , 168. Defat diet .myosin heavy chain 7 (Myh7) locus, an important structural protein required for heart contractions, revealed that one, the lncRNA Mhrt, was down-regulated after induced myocardial infarction. Ectopic expression of Mhrt in mice, which had been subjected to this operation reduced the severity of symptoms observed in control mice during recovery [LIPCAR) was found to significantly correlate with mortality caused by CVD and could thus be considered as a biomarker [In other studies, massive parallel RNA sequencing revealed numerous lncRNAs displaying altered expression following surgically-induced myocardial infarction in mice , 171. Inrecovery . When lniomarker . WhetherLncRNAs have been widely suggested as biomarkers and therapeutic targets in certain pathological settings. One reason for this is the extremely specific expression of many lncRNAs, opening the potential of targeting cellular subgroups rather than affecting patients systemically as in conventional treatments. Even if a lncRNA itself is not the disease driver, it can serve as drug target in cases where it acts as co-factor for a driver gene, which is more broadly expressed. Also, since lncRNAs often play quantitative roles rather than acting as switches in genetic programs, side effects of therapeutic treatments might be easier to control.In recent years, the analysis of lncRNAs has highlighted the large diversity of cellular functions involving RNA molecules and has greatly expanded the catalog of functions previously attributed to noncoding RNAs. By now, we can conclude that noncoding RNAs play roles at all levels of gene control, including epigenetic mechanisms and nuclear organization, as well as in RNA processing, stability and translation. The recent discoveries of lncRNA functions provide good reasons for the notion that further investigation of lncRNAs bears high chances for the discovery of novel gene regulatory mechanisms in the future.cis or trans, but can also be side products of transcription affecting the expression of overlapping genes or accommodate regulatory DNA elements in their genomic loci, the analysis of their exact mode of action and functional roles in development and disease processes is more complex and difficult than that of protein-coding genes. It is now up to the responsibility of journal editors and reviewers to enforce the high standards of investigation this new and exciting field of research deserves.So far, only few lncRNAs playing an essential role in embryonic development, organogenesis or tissue homeostasis have been reported. Studies based on in vitro differentiation systems can provide important insights into the molecular modes of lncRNA function in local gene control or in regulatory networks. However, with regard to the roles of lncRNAs, for example in lineage decisions and cellular differentiation many findings are hampered by the lack of definitive proof in vivo. In particular, data derived from in vitro differentiated stem cells, whose genomic integrity and quality is hard to control, have to be interpreted cautiously. Also, the type of genetic change introduced into a lncRNA gene/locus for functional analysis  needs to be considered carefully in order to draw the right conclusions –176. Sin