Ultra-wideband (UWB) wireless communication is prospering as a powerful partner of the Internet-of-things (IoT). Due to the ongoing development of UWB wireless communications, the demand for high-speed and medium resolution analog-to-digital converters (ADCs) continues to grow. The successive approximation register (SAR) ADCs are the most powerful candidate to meet these demands, attracting both industries and academia. In particular, recent time-interleaved SAR ADCs show that multi-giga sample per second (GS/s) can be achieved by overcoming the challenges of high-speed implementation of existing SAR ADCs. However, there are still critical issues that need to be addressed before the time-interleaved SAR ADCs can be applied in real commercial applications. The most well-known problem is that the time-interleaved SAR ADC architecture requires multiple sub-ADCs, and the mismatches between these sub-ADCs can significantly degrade overall ADC performance. And one of the most difficult mismatches to solve is the sampling timing skew. Recently, research to solve this timing-skew problem has been intensively studied. In this paper, we focus on the cutting-edge timing-skew calibration technique using a window detector. Based on the pros and cons analysis of the existing techniques, we come up with an idea that increases the benefits of the window detector-based timing-skew calibration techniques and minimizes the power and area overheads. Finally, through the continuous development of this idea, we propose a timing-skew calibration technique using a comparator offset-based window detector. To demonstrate the effectiveness of the proposed technique, intensive works were performed, including the design of a 7-bit, 2.5 GS/s 5-channel time-interleaved SAR ADC and various simulations, and the results prove excellent efficacy of signal-to-noise and distortion ratio (SNDR) and spurious-free dynamic range (SFDR) of 40.79 dB and 48.97 dB at Nyquist frequency, respectively, while the proposed window detector occupies only 6.5% of the total active area, and consumes 11% of the total power. The fourth industrial revolution is upon us. Internet-of-things (IoT), big data analytics, and artificial intelligence (AI) are the representative leading-edge technologies that serve as enablers and facilitators of this revolution. In particular, the explosive growth of data produced via IoT has been playing a pivotal role in building big data and creating AI learning data. The proliferation of the IoT is, in turn, attributable to tremendous researches and engineering efforts to develop new methodologies and techniques for low-power designs and wireless communication systems ,2,3,4.Ultra-wideband (UWB) wireless communication is one of the contributors to the prosperity of the IoT and is also one of the representative beneficiaries that is continuing to evolve with the IoT. With the continued development of UWB wireless communications, the demand for multi-GS/s (giga sample per second) high-speed and medium-resolution analog-to-digital converters (ADCs) have been ever-increasing ,7,8,9,10The successive approximation register (SAR) ADCs are well-known power and area-efficient ADCs. In addition, the digital affinity of SAR ADCs enables scalability to various semiconductor technologies, thereby accelerating versatility. However, the SAR ADCs are not as fast as the flash ADCs because of their unique operating characteristic. Even if the SAR ADCs are designed to be relatively high speed, the power efficiency tends to be faded because power-hungry comparators and fast capacitive-digital-to-analog converter (CDAC) settling time are required.To enable high-speed ADC designs while maintaining the power-efficient advantage, researches to apply the time-interleaved architecture to the SAR ADC have been intensively studied ,21,22,23N sub-ADCs. Given that the input in(t)V is applied to the sub-ADCs, as seen in T) gives rise to the voltage error (∆V). The precise relationship between ∆T and ∆V is as follows:M and inf represent the ADC resolution and the input frequency, respectively. From the above equations, it can be seen that the timing skew (∆T) degrades the SNR significantly as inf increases. The sampling error induced by the (sampling) timing skew can be analyzed in inf causes greater SNR degradation. To achieve the SNR above 40 dB, for example, the timing-skew error must be lower than 2.5 ps and 1.2 ps in case inf = 1 GHz and inf = 2 GHz, respectively.The MATLAB simulation results of the 7-bit time-interleaved ADC reported in There have been extensive studies to overcome the timing-skew error problem of the time-interleaved ADCs, and the various timing-skew calibration techniques have been proposed ,28,29,30One of the best-known timing-skew calibration techniques is the statistic-based scheme proposed in several previous literatures ,25,27,29Meanwhile, the derivative-based timing-skew calibration scheme was proposed in ,26. ThisIn addition, the flash-assisted timing-skew calibration scheme was introduced in ,28. ThisV is within a specified window region or not. For example, when the window detector determines that the input is within the window, one of the sub-ADCs samples the input inside the window if there is no timing skew. This case is described in n samples the input within the window. On the other hand, if the timing-skew exists, the corresponding sub-ADCn will sample the input outside the window, which is illustrated in V to enter the window region.More recently, a timing-skew calibration scheme using a window detector was proposed ,22,23. TThen, detecting whether the input is in the specific window region or not is critical in this scheme. To this end, a detection technique using a comparator and its comparison time was presented in ,23. As scompΦ), the clock cycle following the sampling clock (sampleΦ) is used for comparison rather than sampling, as shown in sampleΦ (dummyΦ). However, because of the extra dummy-SAR ADC, which occupies a large area, the presented technique still has critical limitations.To offload the additional calibration logics, a SAR-based window detector has recently been proposed . Figure This paper presents a new window detection scheme and the timing-skew calibration algorithm for the high-speed time-interleaved SAR ADCs. The proposed window detector is more resistant to PVT variations, and it has lower digital complexity than previous works ,23. In aThe block diagram of the proposed time-interleaved SAR ADC is described in The sub-ADCs basically utilized the 2b/cycle architecture presented in ,32,33, wThe window detector SAR ADC has a similar structure to sub-ADCs, except for the input cross-coupled comparators, which are used for window detection. The detailed explanations are mentioned in the following subsections.1-5Φ) and that of the window detector SAR ADC (WDΦ). Then the timing-skew calibration logics control the VDLs to align 1-5Φ with WDΦ.The phase generator generates sampling clock phases of the sub-ADCs  are used in the window detector ADC. All these comparators are sequentially calibrated by single calibration logic and the calibration data are stored in the register in each ADC. 1,2,11M), latch (3-6M), reset switches (7-10M), dummy input transistors (DumM) for kick-back noise reduction, and offset calibration transistors .The proposed window-detector SAR ADC has two differential comparators implemented in the Strong-ARM latch-based dynamic comparators , so as tinp > Vinn, then Ip > In, it leads to OUTp and OUTn to be VDD ("1") and GND ("0"), respectively, due to the regeneration of the latch. . However, if there is an offset, despite Vinp > Vinn, it makes In > Ip. In this case, the comparison error can be corrected by calibration current  by turning on F,CM connected in parallel with input transistor 2M.Because the input difference of comparator makes different currents, if VIf there is no offset, and the input difference is zero, the comparator outputs will be randomly distributed to "1" or "0". However, if there is an offset, the outputs will remain "1" or "0", even though the input difference is zero. Therefore, by applying the input difference to zero and monitoring the comparator outputs, it is always possible to see if there is an offset. And, from this confirmation, the offset calibration can be conducted.cm), the comparator outputs control the up–down counter. If the comparator keeps outputs either "1" or "0", the up–down counter will reach the specific code (OS+ or OS-), and then it turns on or off the calibration transistors .If a small offset remains after a series of the offset corrections, the comparator output may appear slightly alternating between "1" and "0", it can be detected by majority voting scheme . That isWD), respectively. As seen in As aforementioned, we propose to use the comparators which have inevitable offset as the window detector. In this scheme, the smaller window width, the longer calibration convergence time, so it may not be able to keep up with temperature and voltage variations that have a significant effect on timing skew. On the other hand, the larger window width, the lower calibration accuracy. Since the window width of the proposed offset-based window detector is determined by offset, it is necessary to control the offset to set the window width. To force the desired offset, the unwanted offset induced from the process random mismatch must be first compensated.pcal and Incal in p and In in To this end, it is important to know how much offset could be caused by process mismatch. From the Monte-Carlo simulation and post-layout parasitic extraction, the offset is estimated to be ±48 mV. The additional calibration transistors are connected in parallel with the input transistors to compensate the offset. To control the offset 1.5 mV accuracy, the compensation current (IWD) corresponding to the window width. For this, the differential CDACs sample the common-mode voltage (Vcm) and the CWD on the positive input side is switched from VDD to GND which shifts the sampled input difference to “-OS + (-OSWD)”. It is described in WD)”, so if the offset calibration logic compensates it, the input difference will change to zero again. After storing the calibrated offset in the comparator, sampling the Vcm again, if the CWD is not switched, the offset of OSWD is forced as described in WD“ made by CWD switching. Therefore, the only desired offset (OSWD) value remains.In practically, because the comparator has a random offset which is unwanted offset (OS), it is necessary to force only the desired offset (OSWD) ratio and it has a similar structure to sub-ADCs, it is thus advantageous to resist the PVT variations than comparison time-based window detector . If the offset is forced on both comparators, the comparators can be used as window detector with only one conversion cycle. Note that because the window width of the proposed window detector is determined by the switched capacitor  timing-skew calibration  is adoptoutD’s, should be gathered near the zero because the window is set near the zero-crossing as seen in outD’s, E(|outD|), tends to be very small [E(|outD|) may become very large, because outD’s are distributed far from the zero. Therefore, the timing skew can be minimized by adjusting the sampling clock in a direction that can minimize E(|outD|).If there is no timing-skew, the digital outputs of each sub-ADC, ry small . HoweveroutD’s and integrates them for each cycle. After the integration, the timing-skew arbiter compares E(|outD|) with the previous one and investigates whether the timing skew is reduced or increased compared to the previous cycle. Then, if the timing skew is reduced, the arbiter commands the calibrator to keep the adjustment direction of VDL the same as before (keeping the sampling clock lead or lag as it did in the previous cycle). Other if the timing skew increases, the arbiter instructs the calibrator to invert the adjustment direction of VDL in the previous cycle.thn cycle. After all, the outD’s at thn cycle are integrated by the digital integrator, thn mean value of |outD|'s, nE(|outD|) is compared with the previous n-1E(|outD|). If nE(|outD|) ≤ n-1E(|outD|), the arbiter judges that the calibrator is currently working correctly and instructs the calibrator to run the same as the last cycle. In the opposite case, the arbiter instructs the calibrator to operate in reverse to the previous cycle. Then the calibrator controls the VDL to make the sampling clock lead or lag, resulting in timing-skew reduction at th(n+1) cycle. Note that the timing-skew calibration operates in the background to track the voltage–temperature variations.To help readers better understand the above procedure, let us look at an example of the operation of each block in the inf = 1.25 GHz. Plus, to avoid too much load on the VDL, it utilizes a coarse-fine structure, allowing the delay to be linearly controlled.Meanwhile, to cover the estimated timing skew (3σ = 25 ps) acquired from the Monte-Carlo simulation and post-layout extraction, the VDL’s control range is set to ±28 ps, and the accuracy is set to ~1 ps to achieve the SNR above 40 dB at 2, of which the calibration logics and window detector SAR ADC occupied 0.05 mm2 and 0.026 mm2, respectively. The proposed window detector only occupied 6.5% of the total area. The total power consumption of the ADC was 24 mW at 1.2 V supply. The proposed window detector only consumes 11% of the total power. The detailed SAR ADC design process and the various works using it are as follows.To verify the proposed timing-skew calibration technique using the comparator offset-based window detector, we have performed intensive works, including designing a 7-bit, 2.5 GS/s 5-channel time-interleaved SAR ADC in 65 nm CMOS process and post-layout simulations. The top layout of the proposed time-interleaved SAR ADC is presented in In our time-interleaved SAR ADC design, we first focused on minimizing the offset and gain mismatches that cause not only window detection errors but also degrade SNR significantly. To this end, a full-custom metal-oxide-metal (MOM) capacitor was designed for a unit capacitor (~ 4fF) of CDAC to minimize the gain mismatch. Thanks to proper layout and good matching property, the gain mismatch became small enough to ignore the impact on target degradation. In addition, regarding the offset mismatch, assuming that the process random mismatch represents a Gaussian distribution, the offset can be predicted by curve-fitting the probability of the comparator output "1" to the normal cumulative distribution function (CDF). The estimated offset through the Monte-Carlo simulation was ±48 mV (3σ).thn comparator must be calibrated after calibration for th(n-1). Therefore, the calibrated comparators kept its calibration data in the register, while others that have not yet been calibrated maintain its initial data. The 5-bit calibration with ~5 mV accuracy was used for the DDCs, because they did not need coarse-fine calibration, unlike window detecting comparators. It was enough to achieve the SNR above 40 dB. The offset of each comparator was modeled by the Monte-Carlo simulation. In fact, the 15 DDCs were calibrated, but for easy readability, we only show three representative simulation results in the figure.The offset calibration convergence for DDCs is illustrated in In the case of the sub-ADC, Ch.1 and Ch.2 had +23 ps and -20 ps timing skews, respectively, the timing-skew calibration convergence is described in We performed the fast Fourier transform (FFT) analysis of a sinusoidal input signal at Nyquist frequency, and the results are shown in The offset mismatch spurs were suppressed from 2.92 dB to −12.28 dB after offset calibration. However, due to the timing-skew spurs, the SNDR and SFDR were still in 17.84 dB and 23.57 dB, respectively, as shown in The timing-skew spurs were suppressed from 12.4 dB to −23.68 dB after timing-skew calibration. After performing both calibrations, even though the spurs were not completely disappeared, they were suppressed enough to achieve 40 dB SNDR. Eventually, the SNDR and SFDR at Nyquist frequency were 40.79 dB and 48.97 dB, respectively, as seen in Finally, w) of 108-fJ/conversion step at the Nyquist frequency.w among the comparisons.Beginning with the thorough analysis of the advantages and disadvantages of previous time-interleaved SAR ADC designs and their indispensable timing-skew calibration techniques, we have proposed the timing-skew calibration technique using the comparator offset-based window detector. With the proposed calibration algorithm, the design methodology and operation principle of the comparator offset-based window detector are provided in detail. To demonstrate the effectiveness of the proposed technique on the timing-skew calibration, a 7-bit, 2.5 GS/s 5-channel time-interleaved SAR ADC was designed using 65 nm CMOS technology and intensive works were performed. It proves that the proposed calibration scheme well suppressed the mismatch spurs and improves the SNDR and SFDR from 17.59 dB and 23.69 dB to 40.79 dB and 48.97 dB, respectively. The calibration only increased by 6.5% effective area and 11% power consumption, which can be translated to achieving the best FoM


Along with positive SARS-CoV-2 RNA in nasopharyngeal swabs, viral RNA was detectable at high concentration for >3 weeks in fecal samples from 12 mildly symptomatic and asymptomatic children with COVID-19 in Seoul, South Korea. Saliva also tested positive during the early phase of infection. If proven infectious, feces and saliva could serve as transmission sources. In the current pandemic of coronavirus disease (COVID-19), detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in children suspected of having the disease is essential for both infection control and establishing a definite causal relationship in unprecedented cases (http://www.seegene.com). We performed quantitation of the viral RNA with a standard curve constructed using in vitro transcribed RNA. This study was approved by the institutional review board at SMG-SNU Boramae Medical Center; written consent was waived.In South Korea, all confirmed case-patients, regardless of disease severity, must be isolated in hospitals or isolation facilities. For this study, we included all children <18 years of age who were confirmed to have COVID-19 by positive results for SARS-CoV-2 in combined nasopharyngeal and oropharyngeal swab specimens and who were hospitalized in Seoul Metropolitan Government–Seoul National University Boramae Medical Center during March 8–April 28, 2020. We extracted RNA from clinical specimens and detected SARS-CoV-2 by using the Allplex 2019-nCoV Assay kit  (10 copies/mL and remained steadily high (p = 0.148 for trend) for >3 weeks  and week 3 . Except for 1 case, the RNA load in saliva declined rapidly with time (p = 0.003 for trend)  logr trend) , panel Ar trend)  Table 2.>3 weeks , panel Br trend) , panel C10 copies/mL). Only 1 (8%) patient, 27 days of age, had RNA detected in plasma.We collected urine specimens from the 12 patients after a median of 3 (range 0–8) days and plasma specimens at 2 (range 0–8) days from onset. Of these, urine samples of 2 (17%) patients tested positive . We observed no significant differences in feces and in saliva and no correlation between RNA load and age.Symptomatic children had higher initial RNA load in nasopharyngeal swab specimens than asymptomatic children (9.01 vs. 6.32 logIn this study, we detected SARS-CoV-2 RNA in feces of 92% of mildly ill or asymptomatic children with COVID-19. In addition, the RNA load in feces remained steadily high, whereas that in nasopharyngeal swab specimens and saliva declined with time in both symptomatic and asymptomatic children. The detection of SARS-CoV-2 RNA in feces does not necessarily mean that infectious virus is present; thus, lack of virus isolation in our study limits interpretation in the context of infectivity. However, viable virus was isolated in feces in previous studies, and infectivity was dependent on viral RNA load (Our findings also suggest that feces is a promising and reliable source for detecting both current and recent SARS-CoV-2 infection because the viral RNA is present in high loads for a prolonged time. Fecal specimens could aid in seeking the etiologic relationship between COVID-19 and unexpected manifestations in children.We also detected SARS-CoV-2 RNA in saliva during the early phase of the infection for a short period of time. Live virus was isolated in saliva in a previous study, and the possibility of airborne transmission of the virus through normal speaking has been raised (Additional information about the study of viral RNA load in children with COVID-19 in Seoul.


In the present work, structural features of the interaction between peptide nucleic acid (PNA)-based analogs of the tumor-suppressor microRNA-34a with both its binding sites on MYCN mRNA were investigated. In particular, the region from base 1 to 8 (“seed” region) of miR-34a was reproduced in the form of an 8-mer PNA fragment (tiny PNA), and binding to target 3'UTR MYCN mRNA, was studied by a seldom reported and detailed NMR characterization, providing evidence for the formation of anti-parallel duplexes with a well-organized structural core. The formation of PNA-3'UTR duplexes was also confirmed by Circular Dichroism, and their melting curves were measured by UV spectroscopy. Nevertheless, this study offered a valuable comparison between molecular dynamics predictions and experimental evidence, which showed great correlation. Preliminary uptake assays were carried out in Neuroblastoma Kelly cells, using short peptide conjugates as carriers and FITC fluorescent tag for subcellular localization. Moderate internalization was observed without the use of transfecting agents. The reported results corroborate the interest toward the design and development of chimeric PNA/RNA sequences as effective RNA-targeting agents. The majAlong with previously reported information, this study aims principally to deliver further significant structural insights to guide the design of chimeric PNA/RNA-based analogs. To achieve our goal, the portion from nucleobase 1 to 8 of miRNA-34a  as well as to acidic and basic conditions, and high temperatures. Moreover, the peptide-like backbone confers unique properties not found in other classes of nucleic acid analogs; for example, the lack of charges in the PNA backbone results in the loss of electrostatic repulsion between the PNA and RNA strands, thus improving the affinity toward its targets  was selected as a template for the design of PNA-based analogs especially for its crucial role in target recognition  and Tm2 = 60°C (PNA1/RNA-2). The ΔTm = 4°C between the two systems was consistent with the small difference between the two RNA sequences, differing only for one base at 3′ mRNA. Both systems showed high thermal stability and the Tm values were comparable to the ones of full length PNA-RNA (22 unit) complex systems already reported by us , were about 26°C, lower compared to those of PNA1/RNA-1 and PNA1/RNA-2, further proving the benefit of employing PNA based analogs for miRNA targeting despite the presence of mismatches.UV melting experiments of both systems showed a sigmoidal profile, which was indicative of a duplex/single-strand transition . The mel1H] spectrum of the isolated PNA1 strand contains broad low intensity peaks  simulations, performed by using the GROMACS simulation package  which is inherently flexible in both duplexes.in vitro on Human Kelly neuroblastoma cell line, without the use of any transfection agents, and compared to previously reported results from our group , perfectly matching with region 1–8 of miRNA-34a (corresponding to the “seed” region), is able to recognize its target on the 3'UTR of MYCN mRNA. The sequences of the two heteroduplexes PNA1/RNA-1, and PNA1/RNA-2 studied in this work, only differ for a single base at 3' mRNA, which is at terminal position, leading to a fully complementary duplex in PNA1/RNA-1 and a mismatch in PNA1/RNA-2. NMR data indicated the formation of anti-parallel duplexes with a well-organized structural core including the RNA segment from C7 to A2 and the PNA segment PT2-PG7 provided with flexible termini. Further structural investigation by MD simulations evidenced that base pairing and base stacking were maintained in both hetero complexes, thus preserving the overall duplex structure throughout the simulations, in agreement with the organized structural core highlighted by NMR studies. Furthermore, consistently with NMR data, a significant flexibility of the N terminal part (PT1 base) of both duplexes emerged from MD simulations. UV and CD spectroscopic data confirmed the ability of PNA1 to bind both 3′UTR MYCN mRNA binding sites forming stable PNA/RNA complexes. The predicted Tm values of correspondent natural RNA-miRNA-34a complex lied in a much lower range if compared to results obtained in this work for PNA/RNA complexes. Preliminary −1. PNA oligomers were obtained with a purity of >95%; yields were calculated based on the amount of pure PNAs obtained after purification.PNA monomers (Fmoc-A(Bhoc)-OH, Fmoc-T-OH, Fmoc-G(Bhoc)-OH and Fmoc-C(Bhoc)-OH) were purchased from Link Technologies, 2-(1H-7-Azabenzotriazol-1-yl)-1,1,3,3-tetramethyluronoium hexafluorphosphate (HATU) was purchased from IRIS Biotech GMBH, the Fmoc-PAL-PEG-PS resin was purchased from Applied Biosystem. Acetonitrile (ACN) was from Romil, dry N,N-dimethylformamide (DMF), Triisopropylsilane (TIS), 2,6-Lutidine and all other reagents were from Sigma Aldrich (MERCK). LC–MS analysis was performed on an LC–MS Agilent Technologies 6230 ESI-TOF instrument with a Phenomenex Jupiter 3 mm C18 (150_2.0 mm) column at a flow rate of 0.2 mL/min. Purification was carried out on a Phenomenex Jupiter 10 μ Proteo 90 Å (250 × 10 mm) column. Purification was carried out by RP-HPLC with a Shimadzu LC-8A, equipped with a SPD-M10 AV diode array detector using a Kinetex® 5 μm C18 100 Å, AXIA Packed LC Column 50 × 21.2 mm, a column with a flow rate of 20 mL minin vacuo. The PNA oligomer was cleaved from the resin and de-protected by a treatment with a solution of TFA/H2O/TIS (95/2.5/2.5 v/v/v) for 90 min at room temperature. The filtrate was flushed by a stream of nitrogen to remove the most of TFA and the PNA was precipitated by addition of cold diethyl ether, washed three times with diethyl ether and dried in vacuo. Purification was carried out by semi-preparative RP-HPLC applying a linear gradient of acetonitrile (0.1% TFA) from 5 to 50% in 20 min. PNA purity and identity were confirmed by LC-MS system as previously described: a gradient of solvent B (0.05% TFA in CH3CN) from solvent A (0.05% TFA in H2O) of 5% to 50% was applied over 20 min. PNA was identified by electrospray mass analysis. Calculated: 2240.6012; [M+2H]2+: 1121.3006; [M+3H]3+: 747.8670; [M+4H]4+: 561.1503; Found: 2240.9301; [M+2H]2+: 1121.4703; [M+3H]3+: 747.9841; [M+4H]4+: 561.2416. FITC-PNA2 synthesis: The synthesis of FITC- PNA2 sequence was carried out in solid phase see reference : Found 3255.5515 required: 3255.3829 for [M+H]+.PNA1 oligomer was synthesized on a 2 μmol scale using the standard PNA protocol. The synthesis was performed on a Fmoc-PAL-PEG-PS resin (0.16 mmol/g). To improve the coupling efficiency double couplings were carried out on PNA-guanine and adenine monomers. Synthesis was carried out using repetitive cycles of deprotection, coupling and capping at room temperature. After each of these cycles two flow washes (25s) with DMF were performed. Deprotection: 20% piperidine in DMF, 7 min. Coupling: 5 equivalents of PNA monomers were dissolved in DMF to a concentration of 0.22M; a solution of HATU in DMF 0.18M (4eq) and 50 μL of a mixture of DIPEA 0.2 M and 2,6-Lutidine 0.3 M in DMF were added (Pre-activation time: 1 min- coupling time: 20 min). Capping: acetic anhydride/2,6 Lutidine/DMF (5/6/89 v/v/v/), 5 min. At the end of the synthesis the resin was washed with DMF, DCM, diethyl ether and dried UV measurements were carried out on a JASCO V-550 UV/VIS spectrophotometer equipped with a Peltier block ETC-505T temperature controller by using 1 cm quartz cells of both 0.5 and 1 mL internal volume (Hellma). Single strand PNA and complementary RNA were dissolved in ultrapure water and were annealed by warming up at 90°C and slowly cooling down to 4°C in Phosphate buffer 10 mM, 100 mM NaCl, pH = 7.4. The thermal denaturation experiment was carried out using 2.5 μM duplex in Phosphate buffer 5 mM, 50 mM NaCl, pH = 7.4 at a 0.5°C/min scan speed, recording at 260 nm in duplicate. CD spectra were recorded on a Jasco-715 spectrophotometer. CD spectra were recorded at 20°C using a 1 cm quartz cell, a 320–210 nm measurement range, 50 nm/min scanning speed, 1 nm bandwidth, 4 s response time, 2.0 nm data pitch and are the results of 3 scans.NMR experiments were acquired for the following samples: the single strand (ss) PNA at 362 μM concentration, the ss-RNA-1 at 600 μM concentration, the ss-RNA-2 at 357 μM concentration, the PNA/RNA-1 duplex (550 μM PNA/600 μM RNA-1), and the PNA/RNA-2 duplex (335 μM PNA/335 μM RNA-2). The analyzed PNA and RNA sequences are reported in 2O . To assign non-exchangeable protons, the 8-mer duplexes were also lyophilized, dissolved in 98% D2O and additional NMR experiments were conducted. 1D [1H] and 2D  TOCSY  ]. Chemical shifts were referenced to the water peak at 4.75 ppm.All the samples were dissolved in 10 mM sodium phosphate buffer at pH 7.4 with 100 mM NaCl and 10% Daeg-PNA backbone, thus obtaining the starting models of PNA1/RNA-1 and PNA1/RNA-2. The two systems were subjected to molecular dynamics (MD) simulations using the GROMACS simulation package  and cells were treated with 0.5 mL of 0.1 μM solutions of FITC-PNA2 and FITC-PNA3 in Opti-MEM. Wells were gently agitated to provide an even treatment of the cells and incubated at 37°C for 6 h. After incubation, 500 μl of 40% Fetal Bovine Serum (FBS) (Gibco) in RPMI was added to each well. Growth media was removed and wells were incubated at 37°C for 48 h and washed with 1 mL PBS. Passive Lysis Buffer (Promega) (0.5 mL) was added to each well. The plates were wrapped in tinfoil and placed on the rocker for 20 min. The cell lysates were re-suspended and plated in four replicates on a 96 well-plate. The fluorescence of the cell lysate and of the media was read in a dual beam plate reader, at 485/535 nm.Kelly cells were seeded in 6-well plates in duplicates at 0.5 × 104 cells/well density. After 48 h from seeding, the growth media was replaced with serum-free media and cells were treated with 200 μL of 2.5 μM solutions of FITC-PNA2 and FITC-PNA3 in Opti-MEM. Wells were gently agitated to provide an even treatment of the cells and incubated at 37°C for 6 h. After incubation, 100 μl of 40% FBS in RPMI were added to each well in the 8-well coverslip. After 96 h, the cells were gently washed once with PBS, and then treated with 1.5X solution of CellMask™ Plasma Membrane Stains (Thermo Fisher Scientific) in PBS and incubated for 10 min. After this time, the cells were washed twice with PBS, and treated for 10 min with 3.7% EM-grade paraformaldehyde, in PBS, at room temperature. The cells were washed twice with PBS and coverslipped with Vecta shield DAPI mounting medium to stain nuclei. The cells were imaged with a Carl Zeiss, LSM 710 confocal Microscope, with images presented as maximum intensity Z projections, to allow for the 2D display of the data. All images were prepared using the FIJI software (Schindelin et al., Eight well-coverslips were treated with 0.2 mM solution of collagen in DMEM, and incubated at 0–4°C overnight. The wells were washed with PBS before seeding. Kelly cells were plated at 10The original contributions presented in the study are included in the article/MM project conceptualization, experimental design, chemical syntheses and characterization, project funding, and manuscript draft. FM and ML performed NMR studies. EL conducted MD investigation. VP and MA performed synthesis, cellular experiments. MS Project funding and manuscript draft. All authors contributed to the draft of the manuscript and approved the final version. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


C. elegans germ plasm. We find that P granules recruit mRNAs by condensation with the disordered protein MEG-3. MEG-3 traps mRNAs into non-dynamic condensates in vitro and binds to ~500 mRNAs in vivo in a sequence-independent manner that favors embryonic mRNAs with low ribosome coverage. Translational stress causes additional mRNAs to localize to P granules and translational activation correlates with P granule exit for two mRNAs coding for germ cell fate regulators. Localization to P granules is not required for translational repression but is required to enrich mRNAs in the germ lineage for robust germline development. Our observations reveal similarities between P granules and stress granules and identify intrinsically-disordered proteins as drivers of RNA condensation during P granule assembly.RNA granules are protein/RNA condensates. How specific mRNAs are recruited to cytoplasmic RNA granules is not known. Here, we characterize the transcriptome and assembly of P granules, RNA granules in the  RNA granules are RNA/protein condensates that assemble in the absence of limiting membranes. RNA granules form by phase separation, a de-mixing process that drives condensation of RNA and proteins into liquid or gel-like phases . IntrinsC. elegans are a well-studied model for cytoplasmic RNA granules  and used to determine read counts per locus. Read counts obtained in the control GFP iCLIP were used to define a background threshold. We identified 657 transcripts that were reproducibly recovered above the GFP background threshold in two independent MEG-3::GFP iCLIP experiments  experiments  on MEG-3nos-2, pos-1, mex-1 and gld-1, the four transcripts previously reported to localize to P granules  . Extrapolating from this correlation, we predicted that transcripts that ranked higher than the nos-2 cluster in the MEG-3-bound list should all localize to P granules. In total, we examined 18 transcripts among this 492-gene set and found that, as predicted, all localized robustly to P granules . Finally, we examined six genes that were not recovered reproducibly in the iCLIPs and had above average expression in P blastomeres (RPKM = 7). We found none that localized to P granules (T26A5.2), nos-2 cluster in the MEG-3-bound list is a stringent metric for predicting transcripts with robust P granule localization. We designate this 492-gene set as ‘P granule transcripts’ (Among the MEG-3-bound transcripts were granules . To detegranules  to exami = 0.92) . In thisgranules . We alsoscripts’ . This gescripts’ .puf-5 and 34 ± 3% Y51F10.2 molecules localized to P granules in the P2 blastomere. Because P granules occupy only a small portion of the P2 cell volume (5.9 ± 2%), this enrichment corresponds to a ~ 6 fold increase in concentration over the cytoplasm.For all 18 P granule transcripts analyzed by smFISH, localization to P granules was inefficient with many molecules also found diffusely in the cytoplasm . We calcnos-2 mRNA still localized to granules in embryos lacking pgl-1 and pgl-3, but not in embryos lacking meg-3 and meg-4  was sufficient to disassemble polysomes in embryos  McCormi. We analmex-5 mex-6 mutant embryos, which lack embryonic polarity and assemble MEG-3 granules throughout the cytoplasm  that transitioned to a more diffuse cytoplasmic localization in the last P blastomere, the germline founder cell P4  embryos, we detected NOS-2 and Y51F10.2 proteins precociously as early as the 4 cell stage. In contrast, in pos-1(RNAi) embryos, NOS-2 and Y51F10.2 proteins were not expressed  embryos, nos-2 and Y51F10.2 mRNAs did not localize to P granules. In contrast, in pos-1(RNAi) embryos, nos-2 and Y51F10.2 mRNAs remained in P granules through P4 , suggesting that Y51F10.2 functions redundantly with nos-2 in germ cell fate specification . Again, we distinguished aggregates from condensates based on size. In the absence of RNA, MEG-3 formed aggregates under all salt concentrations tested (nos-2 RNA and these aggregates did not recruit nos-2 RNA (MEG-3 has a predicted pI of 9.3 (ExPASy) and thus could potentially interact with the sugar-phosphate backbone of RNA through electrostatic interactions. To explore this hypothesis, we examined MEG-3 condensation behavior in the presence of varying concentrations of salt and RNA  were not as efficient as longer RNAs at stimulating MEG-3 condensation . We prevTo examine whether mRNAs also associate stably with the MEG phase of P granules in vivo, we labeled permeabilized live embryos with the RNA dye SYTO 14. As expected, we observed intense SYTO 14 fluorescence in MEG-3-positive granules . We verimeg-3 and meg-4 and does not require pgl-1 and pgl-3  are non-homologous, but all contain predicted intrinsically-disordered domains and form non-dynamic condensates in vitro. Oskar and Bucky Ball bind Nanos RNA in vitro  additional germ cell fate regulators likely exist among the other P granule mRNAs. It appears unlikely, however, that all P granule-enriched transcripts function in germ cell specification. Unlike nos-2 and Y51F10.2, the other P granule mRNAs we surveyed by in situ hybridization turn over before ever releasing from P granules  strain on meg-2 RNAi, sterility was 95 ± 0.6% at 20°C; meg-1 meg-3 meg-2(RNAi) meg-4(RNAi) maternal effect sterility was 100 ± 0%. To verify the RNAi efficiency of targeting mex-3 and pos-1, embryonic lethality was assayed. Cohorts of 10–20 mothers were allowed to lay eggs for periods ranging from 2 to 4 hr. Embryos were then counted, and adults were scored four days later. The embryonic lethality for both mex-3 and pos-1 were 100 ± 0% and 98 ± 0.2% respectively.To verify the efficiency of RNAi treatments for knocking down CRISPR generated lines were created as in 2O.We prepared freshly-made 100x protease inhibitor mixes for the immunoprecipitation step in the iCLIP protocol. Protease inhibitor mix1(100x): Antipain (3 mg), Leupeptin(5 mg), Benzamidine(10 mg), AEBSF(25 mg) and phosphoramidon (1 mg) were resuspended in 1 mL Phosphate-buffered saline (PBS). Protease inhibitor mix2 (100x): 500 µL of 10 mg/mL Aprotinin, 400 µL of 10 mM Besttatin, 100 µL of 10 mM E64, and 100 µL of 10 mg/mL Trypsin inhibitor were mixed together in HC. elegans embryos collected from ~6.7×107 gravid adults were seeded on 10 cm petri dishes and irradiated 3 times with 400 mJ/cm2 at UV 254 nm by Stratalinker. Crosslinked embryos were collected and resuspended in Immunoprecipitation buffer (IP buffer) with freshly made protease inhibitors as described in this section . Samples were lysed in a Spex 6870 freezer mill followed by centrifugation at 4°C 21,000xg for 30 min to remove embryo debris. Cleared lysates were subjected to immunoprecipitation using anti-GFP antibody (Roche 11814460001) conjugated to protein G magnetic beads (Thermofisher) in the presence of 200unit of RNaseOut per milliliter of lysates. Immunoprecipitated fractions were then washed extensively with IP buffer, low salt buffer  and high salt buffer . Bound fractions were then washed with 1xPBS to remove excess salt followed by RQ1 DNase treatment at 37° C for 10 min [4 units of RQ1 (Promega M6101) and 60 units of SUPERaseIN (ThermoFisher AM2694)]. To perform partial RNA digestion, RQ1 DNase treated bound fractions were washed with 1 mL low salt buffer, 1 mL high salt buffer, 1 mL 1x PNK buffer  and finally resuspend in 500 µL MNase reaction buffer . The MNase reaction was immediately transferred to a thermomixer for 2 min at 37°C. The MNase reaction was stopped with ice-cold 1x PNK buffer with 5 mM EGTA followed by 2 × 1 mL high salt buffer, 2 × 1 mL low salt buffer and 1 × 1 mL PNK buffer.The iCLIP protocol was adapted from 2O] at 37° C for 20 min followed by washes with PNK buffer. Beads were resuspended in in 20 µL ligation mixture  at 16° C for overnight.A dephosphorylation step is necessary to remove 3’ end phosphates that prevent adapter ligation. Beads were resuspended in 20 µL of dephosphorylation reaction  at 37° C for 10 min. Remove unlabeled hot ATP by wash beads with wash buffer . Samples were loaded on a 4–20% TGX protein gel (Bio-Rad 4561093) and transferred to a nitrocellulose membrane.Ligated RNA samples were washed twice with high salt buffer and twice with PNK buffer. Supernatants were removed and samples were resuspended in 80 µL of hot PNK mix for 5’ end labeling  and lysed in a Spex 6870 freezer mill. After clarification lysate by sequential centrifugation at 3000 rpm followed by 17,000xg, 100 µL (5% of lysate) of lysates were saved for mRNAseq. For ribosome profiling, lysates containing 300 μg of total RNA were treated with 100 units of RNaseI (Ambion) for 30 min at 25°C. 40 units of SUPERaseIN (ThermoFisher) were added to prevent further digestion from RNaseI. Monosomes were isolated by sucrose gradients (10–50%) and centrifuged at 40,000 rpm for 3 hr in a SW41 rotor (Beckman Coulter). The extracted RNA was size-selected (15–34 nt) after running on 15% denaturing PAGE gels. An oligonucleotide adapter was ligated to the 3’ end of isolated fragments. After ribosomal RNA depletion using RiboZero (Illumina), the following steps were performed: reverse transcription using SuperScript III reverse transcriptase (Thermo Fisher Scientific), circularization using CirLigase I (Lugicen) and PCR amplification . Trimmed reads were aligned to C. elegans ws235 reference genome using HISAT2 (https://github.com/fishhead1978/iCLIP_2019 (https://github.com/elifesciences-publications/iCLIP_2019). To determine the distribution of mapped read across the genome, an R package RNA centric annotation system (RCAS) was used to generate the plot shown in The 5’ barcodes (NNN- four nt indexes – NN) and 3’ adaptor (AGATCGGAAG) for iCLIP library construction were listed in g HISAT2 , and PCRhttps://usegalaxy.eu/) with options –Minimum cluster Expression Fraction 0.01 --Minimum Block Overlap 0.5 –Minimum Block Expression 0.1 –Mad Multiplier 2.0 –Fold Change Threshold 1.5 – Adjusted p-value Threshold 0.1. Identified peaks with additional 15 nt extensions from both ends were used by MEME suite to search for sequence motif, and no motif reached the E-value cut off <1×10–5. An additional iCount analysis package  with the same options described in the tutorial document (https://icount.readthedocs.io/en/latest/ref_CLI.html) was used to identify significant peaks. 15 nt extensions were added to both sides of peaks and followed by MEME suite motif analysis. No motif with an E-value <1×10-5 were found in either the MEG-3::GFP or GFP iCLIP experiments. Therefore, we conclude that MEG-3 binds RNAs without any sequence bias. The preference for 3’UTR sequences observed in the metagene analysis shown in To identify potential MEG-3 binding motifs, MEG-3::GFP and control GFP iCLIP mapped reads were used in peak caller PEAKachu in galaxy server (http://deeptools.readthedocs.io/en/latest/) were used to compute mapped read coverage. Command lines were listed as below:$ bamCoverage -b < inpit >  o<output.bw> -bs 1 p 8 -ignore chrM --exactScaling -- smoothLength 3$ computeMatrix scale-regions -S < input.bw> -R < MEG-3-bound transcripts.bed> -b 800 -a 1500 m 2000 -bs 1 --skipZeros --sortUsing max -p 8 -o < output.gz>$ plotProfile -m < input.gz> --out<output.pdf> --colors blue green –perGroupTo plot the MEG-3 binding profile , bamCompC. elegans reference genome using HISAT2  were used in cuffdiff analysis:meg-3 meg-4 embryos were trimmed to remove the ligated 3’ linker (CTGTAGGCACCATCAAT) with skewer (NNNNNNCACTCGGGCACCAAGGA) was trimmed, and four random nucleotides included in the RT primer (RNNNAGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGATCTCGGTGGTCGC/iSP18/TTCAGACGTGTGCTCTTCCGATCTGTCCTTGGTGCCCGAGTG) were removed from the 5’ end of reads. Trimmed reads longer than 15 nt were aligned to reference genome ce10 using STAR . To define P granule transcripts, we used the rank order of F35G2.1 (Rank 388), the left most gene in the nos-2 cluster as shown in Read counts obtained in the control GFP iCLIP were used to define background threshold (read count = 60.) We defined MEG-3 bound transcripts by excluding transcripts with MEG-3::GFP iCLIP read counts < 60 as shown in smFISH probes were designed using Biosearch Technologies’s Stellaris Probe Designer. The fluorophores used in this study were Quasar570 and Quasar670. For sample preparation, embryos were extruded from adults on poly-lysine slides (0.01%) and subjected to freeze-crack followed by cold methanol fixation at −20° C. Samples were washed five times in PBS+0.1%Tween20 and fixed in 4% PFA  in PBS for one hour at room temperature. Samples were again washed four times in PBS+0.1%Tween20, twice in 2x SCC, and once in wash buffer  before blocking in hybridization buffer  for 30 min at 37° C. Hybridization was then conducted by incubating samples with 50–100 nM probe solutions diluted in hybridization buffer overnight at 37° C. Following hybridization, samples were washed twice in wash buffer at 37° C, twice in 2x SCC, once in PBS-Tween20 (0.1%), and twice in PBS. Lastly, samples were mounted using VECTASHIELD Antifade Mounting Media with DAPI or Prolong Diamond Antifade Mountant.http://fiji.sc/Fiji).Fluorescence confocal microscopy was performed using a Zeiss Axio Imager with a Yokogawa spinning-disc confocal scanner. Embryo images were taken using Slidebook v6.0 software (Intelligent Imaging Innovations) using a 63x objective. Embryos were staged by DAPI-stained nuclei in optical Z-sections and multiple Z-sections were taken to include germ cells. For In vitro condensation reactions, images are single planes taken using a 40x objective unless otherwise indicated. For fluorescence super-resolution microscopy, images were acquired using ZEISS LSM 880-AiryScan (Carl Zeiss) equipped with a 63X objective. Images were processed using ZEN imaging software (Carl Zeiss). Equally normalized images were exported via either Slidebook v6.0 or ZEN, and contrasts of images were equally adjusted between control and experimental sets. For in vitro fluorescence recovery after photobleaching experiments, images were acquired using Zeiss LSM 800 GaAsp. Images are single confocal planes imaged using a 63x objective every 3 s during a recovery phase of 300 s. All image analyses were conducted using the Fiji image-processing package  was divided by the total intensity of the MEG-3::GFP in the same objects (meg3gI). The intensity ratio of RNA in MEG-3 granules (IsmFISHg/meg3gImeg) before and after heat shock was compared. Each data point represents data from one Z plane acquired from two embryos (eight planes per embryo).MEG-3::GFP granules were identified using the nucleus counter plugin as described above. The minimum threshold was set to the two times the mean intensity of the background signal of the image; and the maximum threshold was calculated by adding six standard deviations of the background intensity. A mask generated from objects identified by the nucleus counter plugin was applied to the raw image to extract RNA or GFP intensity. To remove background signal, the mean intensity of an object across the nucleus was measured, and subtracted from calculated RNA or GFP intensities. To calculate the ratio of RNA signal/MEG-3::GFP granule signal in each selected Z plane, the sum of intensities of RNA in identified objects (ptr-2 RNAi was used to permeabilize the egg shell. A 12.5 mg/mL (20X) Puromycin stock solution  was made with osmolarity calibrated Egg buffer . A 50 mg/mL (200X) Cycloheximide stock solution was made in ethanol. RNAi-treated gravid worms were dissected and permeabilized embryos were released into drug containing egg buffer for 1 hr in a humidity chamber to maintain vapor pressure. Both puromycin and cycloheximide induced cell cycle arrest. After drug treatment, excess buffer was removed and embryos were subjected to image acquisition and quantification using nucleus counter cookbook plugin as described in ‘Quantification of RNA granule size’ section above. Images used for quantification are maximum Z projections acquired using a 63x oil.For drug treatment, smFISH quantification was conducted using Imaris Image Analysis Software visualization in 3D space. The boundary/volume for the germ cell cytosol and germ granules was created by Surface function using MEG-3::GFP signal in Imaris. The sum of intensity of the germ cell cytosol and granules were extracted and the percentage of RNA enrichment in germ granules was calculated.As in sample preparation for smFISH experiments, embryos were extruded from adults and subjected to freeze-crack on poly-lysine slides followed by cold methanol fixation for 15 min and then cold acetone for 10 min. Slides were blocked twice in PBS-Tween20 (0.1%)-BSA (0.1%) for 30 min at room temperature, and incubated with 90 μl primary antibody overnight at 4°C in a humidity chamber. Antibody dilutions (in PBST/BSA): mouse K76 1:10 (DSHB), Rat α-OLLAS 1:80 (Gift from Dr. Jeremy Nathans), mouse α-FLAG M2 1:500 (Sigma F3165). Secondary antibodies (Molecular Probes/Thermo Fisher Sci.) were applied for 1 ~ 2 hr at room temperature.RNA was extracted from embryos or cleared embryo lysates using TRIZOL. The aqueous phase was transferred to Zymo-SpinTM IC Column (Zymo research R1013) for concentration and DNase I treatment as described in manual. RNA quality was assayed by Agilent Bioanalyzer using Agilent RNA 6000 Pico Chip. All RNAs used for library preparation had RIN (RNA integrity number)>9. For mRNA-seq library construction, 0.5 µg of total RNA was treated with Ribo-Zero Gold Epidemiology rRNA Removal Kit. Libraries were then prepared following the TruSeq RNA Library Prep Kit v2 instruction. All sequencing was performed using the Illumina HiSeq2500 at the Johns Hopkins University School of Medicine Genetic Resources Core Facility.MEG-3 full-length (aa1-862) fused to an N-terminal 6XHis tag in pET28a was expressed and purified from inclusion bodies using a protocol modified from MBP-TEV-PGL-3 was expressed and purified as described  with theProteins were labeled with succinimidyl ester reactive fluorophores from Molecular Probes  following manufacturer's instructions. Free fluorophore was eliminated by passage through three Zeba Spin Desalting Columns  into protein storage buffer. The concentration of fluorophore-labeled protein was determined using fluorophore extinction coefficients measured on a Nanodrop ND-1000 spectrophotometer. Labeling reactions resulted in ~0.25–1 label per protein. Aliquots were snap frozen and stored. In condensation experiments, fluorophore-labeled protein was mixed with unlabeled protein for final reaction concentrations of 25–100 nM of fluorophore labeled protein.nos-2 fragments were generated by PCR amplification from the 5’ end of the full length nos-2 template DNA. Free NTPs and protein were removed by lithium chloride precipitation. RNAs were resuspended in water and stored at −20°C. The integrity of RNA products was verified by agarose gel electrophoresis.mRNAs were transcribed using T7 or SP6 mMessageMachine (Thermofisher) using manufacturer’s recommendation. 1 µL of ChromaTide Alexa Fluor 488–5-UTP or 546–14-UTP (Thermofisher) were added to transcription reactions to fluorescently trace label mRNAs. Template DNA for transcription reactions was obtained by PCR amplification from plasmids. 30 nt oligo polyU RNAs were ordered from IDT either unlabeled or with a 3’ FAM modification. Oligos were resuspended in water aliquoted and stored at −80°C. Labeled and unlabeled oligo RNAs were mixed together and used at final concentrations of 20 ng/uL including 25 nM fluorescently labeled oligo.Protein condensation was induced by diluting proteins out of storage buffer into condensation buffer containing 25 mM HEPES (pH 7.4), salt adjusted to a final concentration of 150 mM , and RNA. Unless otherwise indicated, for all co-assembly experiments, we used 500 nM MEG-3 and 20 ng/µL RNA. MEG-3 solutions contained 25 nM fluorescent trace labels with either 488, 555, or 647 (indicated in figure legends). Condensate reactions with the RNA dye contained a final concentration of 100 nM SYTO 14. Condensation reactions were incubated at room temperature for 30 min or as indicated, before spotting onto thin chambered glass slides (ERIE SCIENTIFIC COMPANY 30-2066A) with a coverslip. Images used for quantification are single planes acquired using a 40x oil objective over an area spanning 171 × 171 μm.To quantify the ratio of protein or RNA in condensates, a mask was created by thresholding images, filtering out objects of less than four pixels to minimize noise, applying a watershed filter to improve separation of objects close in proximity, and converting to a binary image by the Otsu method using the nucleus counter cookbook plugin. Minimum thresholds were set to the mean intensity of the background signal of the image plus 1–2 standard deviations. The maximum threshold was calculated by adding 3–4 times the standard deviation of the background. Using generated masks, the integrated intensity within each object was calculated. To remove non-specific background signal the mean intensity of an image field in the absence of the labeled component was subtracted from each pixel yielding the total intensity of each object.Histograms of MEG-3 intensity were generated by taking the log(10) of total intensity for each MEG-3 object, Log(I). Objects in 2–3 experimental replicates of 4 images were identified and quantified as described above the number of objects for each Log(I) value was binned (bin size = 0.2 Log(I) units), and normalized to the total number of objects. The percent of objects in each bin was averaged for each experimental replicate .nos-2 RNA) as illustrated in The percent of MEG-3 in aggregates or condensates was determined by comparing histograms of reactions in which all objects are aggregates (500 mM NaCl or no RNA) or condensates  were added to a chambered coverglass (Grace BioLabs) and imaged using a Zeiss LSM 800 GaAsp. Bleaching was performed using 100% laser power in the 488, 546, or 647 channels. Regions slightly larger than the condensates (radius ≈ 3 µM) were photobleached. A single confocal plane was imaged using a 63x objective every 3 s during a recovery phase of 300 s.I = (bkgI-I)/(i-IbkgiI), where nI is the background corrected and normalized fluorescence intensity, I is the intensity of the FRAPed granule, bkgI is the fluorescence intensity outside of the condensate, iI is the initial intensity before bleaching, and bkgiI is the initial background intensity. Recovery rates were determined by fitting individual traces to a first order equation nI = (Arec·(1-ek-t), where Arec is the fluorescence recovery amplitude and k is the rate of fluorescence recovery. For RNAs where fluorescence recovery was in the linear range for the entire time course, initial recovery rates were calculated by fitting to a linear equation nI = kt, where k is the initial rate of fluorescence recovery  adult gravid hermaphrodites expressing MEG-3::HALO  suspended in egg buffer were added to prevent embryo compression, and placed on slides for imaging. Embryo contents were extruded by puncturing the eggshell near the anterior region of the germline blastomere using a 3i Ablate! laser system at 532 nm pulse setting with a power level of 155 (1 mM SYTO 14 RNA Dye (ThermoFisher) and 1 mM JF-3::HALO  were disl of 155 . All embl of 155 .B) and after (IA) extrusion and used to calculate a fluorescence ratio (IA/IB). Photobleaching was minimal for MEG-3::Halo; however it was significant for SYTO 14. To correct for photobleaching, total fluorescence intensity was corrected for photobleaching using the average photobleaching rate calculated from the cytoplasm of intact embryos in the imaging area. For some embryos, granules left the field of view and could not be counted. The IA/IB, therefore, is a minimal estimate of the fraction MEG-3 and SYTO 14 that remained in the granule phase after extrusion  software.Sequencing datasets and processed results generated in this paper are available at GEO accession GSE139881 for iCLIP (GSE139878), embryonic RNAseq (GSE139879) and ribosome profiling results (GSE139880). In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:C. elegans. Significant findings include the characterization of mRNAs that are bound in P granules and the demonstration that P granule formation is driven by the intrinsically disordered protein MEG-3. Similarities between P granules and stress granules are also revealed by these studies.RNA granules are protein-RNA condensates that are not enclosed by membranes. In this paper, Seydoux and colleagues use a variety of techniques to examine the messenger RNA content of P granules. P granules are present in germline cells in Decision letter after peer review:eLife. Your article has been reviewed by James Manley as the Senior Editor, a Reviewing Editor, and two reviewers. The following individuals involved in review of your submission have agreed to reveal their identity: Roy Parker (Reviewer #1); Dustin L Updike (Reviewer #2).Thank you for submitting your article "Recruitment of mRNAs to P granules by gelation with intrinsically-disordered proteins" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.eLife. Nevertheless, both referees made a number of comments regarding presentation. They also pointed out a number of specific issues that deserve clarification. Finally, they suggest a couple of straightforward experiments that would strengthen the paper. Please address these issues as thoroughly as possible.The reviewers concurred that your manuscript presented significant results and was in principle suitable for Reviewer #1:eLife.This manuscript addresses the mechanisms by which RNAs and proteins condense together to form P-granules, and what the function of P-granules is in terms of regulating mRNA function. The work makes two main points. First, it demonstrates that P-granules are formed from untranslating mRNPs that interact in a sequence independent manner with the Meg proteins. This is a nice demonstration of the composition and assembly mechanisms of P-granules and synergizes well with what is known about the selectivity of RNA recruitment to other RNP granules. Second, the work demonstrates that the function of P-granules in development is to promote the localization of specific mRNAs into the P4 cell. This is a very significant contribution. Taken together, this work is an important manuscript and after addressing the comments below should be published in Essential revisions:1) I think the most important contribution of the manuscript is the demonstration of a clear function for P-granules in the accumulation of mRNAs in the P4 cell. Given this, I suggest:a) Change the title to something like: "P-granules function to drive cell-type specific accumulation of mRNAs".b) Rewrite the abstract to emphasize this point (or at least mention it).c) Add at least one paragraph in the discussion that makes this point, and supports it with the critical observations. Ideally, this would be followed by second paragraph discussing how the formation of a P-granule creates a localization sink by changing the diffusion rate of granules as compared to individual mRNAs.2) Although the authors present convincing data that Meg3/4 are required for P-granule assembly in embryos and can form assemblies in vitro with Meg-3 protein, I would recommend the authors be cautious about their interpretation that "P-granules from by gelation with intrinsically disordered proteins" for a few reasons.a) How do the authors know the assembly is not driven by RNA interactions, and then that RNA assembly recruits Meg-3 to it? At a minimum, the authors should examine the assembly/"gelation" of RNA in their in vitro conditions in the absence of the Meg-3 protein to assure themselves that the RNA-Meg-3 assemblies they study require Meg-3 for assembly.b) Since Meg-3 forms "aggregates" by itself, which are solubilized by RNA, it seems that RNA is altering Meg-3 self-interactions. The manuscript would be improved if the authors could clarify if these Meg-3 aggregates are artifacts of the in vitro system, or do they have biological meaning?c) What is the difference between gelation and assembly in this context? As I see it, the authors show that the RNA and protein assemblies formed in vitro show slow rates of Meg-3 or RNA exchange in a manner affected by RNA length. Why not just call these non-dynamic assemblies since "gels" implies different things to different people. If they are defining an assembly as a gel if it has a slow exchange rate of a component, then they should be explicit about this point. If they are defining a gel as an assembly where every component is interconnected, then referring to these assemblies as gels seems premature.3) The work in this manuscript is consistent with Meg3/4 playing a role in promoting RNP condensation when there is a limited amount of untranslating mRNAs. A prediction of this model is that when cells are heat shocked, the increase in untranslating mRNAs will correspondingly drive RNP granule formation. Thus, one predicts that in a meg3/4 mutant, heat shock would restore P-granules. . Given that this is a simple experiment, and if it worked would reveal a new property of P-granules, it would be nice to try, although it is not required for publication.3b) A related issue is that it would improve the manuscript to clarify if separate stress granules form under heat shock, or those that form, merge with P-granules.4) As I read it, the analysis of mRNAs in Figure 1D that are called as "enriched" in P-granules will also be strongly affected by their abundance. As such, this analysis could miss low abundance but highly enriched mRNAs. I suggest either a) clarify how the analysis was done such that this is not an issue, or b) acknowledge the limitations in the text with how this analysis is performed and the types of RNAs it will miss.Reviewer #2:Seydoux and Fire, (1994) showed the enrichment of polyadenylated transcripts in the germline blastomeres of the early embryo; after, a handful of developmentally regulated mRNAs, but not rRNAs, were shown to be enriched in the P granules of early embryos . The identity of P-granule bound mRNAs is instrumental to understanding P-granule function in the early embryo, but in the intervening years, this small list of P-granule transcripts has not increased despite attempts from multiple labs.In this report, Chih-Yung Lee and colleagues in the Seydoux lab break through this barrier by identifying P-granule transcripts through MEG-3 iCLIP. MEG-3 forms small non-dynamic condensates within P granules, in contrast to PGL protein condensates that are highly dynamic. The authors identify just 18 PGL-1-bound transcripts compared to 657 that bound to MEG-3. 18/18 transcripts from this list localize robustly to P granules, and this localization is MEG-3 dependent.The authors show that MEG-3 transcripts demonstrate no apparent sequence conservation, but correlate with a low-occupancy of ribosomes, suggesting that untranslated transcripts have an affinity for P granules. They then show that translational inhibition recruits new transcripts to P granules. Upon translational activation in the germline precursor cell (P4) of nos-2 and Y51F10.2, these transcripts disperse from P granules to localize throughout the cytoplasm. The timing of nos-2 and Y51F10.2 translation is unaffected in meg-3 meg-4 mutants, suggesting that P-granule localization is a consequence of translational repression and that P granules have some role in delivering transcripts that encode germ cell fate regulators to the nascent germline. Recombinant MEG-3 was shown to interact with RNA through electrostatic interactions in a non-sequence specific, but length-dependent manner and these stable interactions persist in both in vitro and ex vivo conditions.This paper presents several new and significant advances to the RNP phase-separation and germ-granule fields. Two crucial but addressable criticisms are discussed.1) As a control for the MEG-3 iCLIP experiments, the authors perform iCLIP on GFP-expressing embryos. Information for the control (JH1094?) isn't given. The optimal control would express GFP in just the germline blastomeres where MEG-3 and PGL-1 are enriched to avoid identifying the most abundant transcripts in P blastomeres (compared to the whole embryo). Genes like cbd-1, cgh-1, and puf-5 are some of most abundant in the germline. Of the 657 MEG-3-bound transcripts, over half are in the top 1000 germline expressed (11-fold more than expected by chance), and most fall within the top 3000 germline-expressed genes. The statement on line 102 that MEG-3 binds to a specific subset of mRNAs instead of abundant P-blastomere mRNAs will need more supporting data than is currently provided.Correlations provided in Figure 1C and Figure 1—figure supplement 1C may be erroneous and serve as a distraction at the beginning of an otherwise very significant study. Instead, the comparison should be with all ~ 15,000 germline-expressed transcripts. Despite a potential lack of MEG-3 specificity, results are still in line with the author's later and well-supported observations that untranslated transcripts in translationally quiescent P blastomeres have an affinity for MEG-3.An apparent exception to the transcript abundance correlation is that MEG-3-bound transcripts lack those that encode ribosomal proteins. While not necessary to include in this manuscript, it may be interesting to consider why abundant RPL/RPS (RPG) transcripts do not bind MEG-3.2) P blastomeres are translationally quiescent, so shouldn't lower ribosomal coverage of MEG-3 attached transcripts in P blastomeres be expected when the experiment was done on whole embryos? Specificity is not addressed and observations in Figure 2C may be a correlation artifact. While this isn't likely given the later in situ hybridization experiments following translational inhibition, the caveat should be discussed. Reviewer #1:Essential revisions:1) I think the most important contribution of the manuscript is the demonstration of a clear function for P-granules in the accumulation of mRNAs in the P4 cell. Given this, I suggest:a) Change the title to something like: "P-granules function to drive cell-type specific accumulation of mRNAs".b) Rewrite the abstract to emphasize this point (or at least mention it).c) Add at least one paragraph in the discussion that makes this point, and supports it with the critical observations. Ideally, this would be followed by second paragraph discussing how the formation of a P-granule creates a localization sink by changing the diffusion rate of granules as compared to individual mRNAs.4 to maximize the robustness of germ cell fate specification”. Another important point of the paper is the demonstration of a direct role for an intrinsically-disordered protein in recruiting RNAs to RNA granules. To our knowledge this has not yet been shown for other RNA granules, and so we are choosing to maintain the original title.We have modified the abstract to highlight our findings with regard to P granule function and have reworked the Discussion section “P granules enrich maternal mRNAs in the germline founder cell P2) Although the authors present convincing data that Meg3/4 are required for P-granule assembly in embryos and can form assemblies in vitro with Meg-3 protein, I would recommend the authors be cautious about their interpretation that "P-granules from by gelation with intrinsically disordered proteins" for a few reasons.a) How do the authors know the assembly is not driven by RNA interactions, and then that RNA assembly recruits Meg-3 to it? At a minimum, the authors should examine the assembly/"gelation" of RNA in their in vitro conditions in the absence of the Meg-3 protein to assure themselves that the RNA-Meg-3 assemblies they study require Meg-3 for assembly.nos-2 and Y51 RNAs do not accumulate in macroscopic granules in embryos lacking meg-3meg-4. We are confident therefore that MEG proteins promote RNA condensation. We are not excluding the possibility that smaller RNA aggregates form independently of meg-3meg-4 and refer to the possibility of RNA-only aggregation in the Introduction.We include a new figure  which shows that RNA alone does not form condensates under our assay conditions. Similarly, in vivo, b) Since Meg-3 forms "aggregates" by itself, which are solubilized by RNA, it seems that RNA is altering Meg-3 self-interactions. The manuscript would be improved if the authors could clarify if these Meg-3 aggregates are artifacts of the in vitro system, or do they have biological meaning?We estimate that, in embryos, the stochiometric ratio of MEG-3 to mRNA molecules is ~1:5. MEG-3 aggregates form in vitro under much higher MEG-to-RNA stochiometric ratios (e.g. 1:0.05). MEG-3 aggregates, therefore, may not be physiological. However, because we do not know how much RNA is available to MEG-3 in vivo, we prefer not to make any conclusions re: the physiological relevance of MEG-3 aggregates at this time.c) What is the difference between gelation and assembly in this context? As I see it, the authors show that the RNA and protein assemblies formed in vitro show slow rates of Meg-3 or RNA exchange in a manner affected by RNA length. Why not just call these non-dynamic assemblies since "gels" implies different things to different people. If they are defining an assembly as a gel if it has a slow exchange rate of a component, then they should be explicit about this point. If they are defining a gel as an assembly where every component is interconnected, then referring to these assemblies as gels seems premature.We have replaced “gel” with “non-dynamic assemblies” throughout the manuscript.3) The work in this manuscript is consistent with Meg3/4 playing a role in promoting RNP condensation when there is a limited amount of untranslating mRNAs. A prediction of this model is that when cells are heat shocked, the increase in untranslating mRNAs will correspondingly drive RNP granule formation. Thus, one predicts that in a meg3/4 mutant, heat shock would restore P-granules. . Given that this is a simple experiment, and if it worked would reveal a new property of P-granules, it would be nice to try, although it is not required for publication.We have done this experiment and found that Y51F10.2 RNA does NOT accumulate in granules in embryos depleted of MEG proteins even upon heat shock .Similarly, ectopic localization of non-P granule RNAs to P granules upon heat shock also requires MEG proteins .We conclude from these experiments that formation of large (micron-sized) RNA granules requires MEG proteins both in wild-type and under our heat shock conditions. Our experiments, however, do not exclude the possibility that smaller RNA aggregates form in the absence of MEG proteins.3b) A related issue is that it would improve the manuscript to clarify if separate stress granules form under heat shock, or those that form, merge with P-granules.We have monitored the formation of stress granules using a G3BP::GFP fusion and find that G3BP puncta form in all cells under our heat shock conditions. In P blastomeres, some G3BP puncta associate with P granules. We have added these data as a new panel  referred to in Materials and methods section.4) As I read it, the analysis of mRNAs in Figure 1D that are called as "enriched" in P-granules will also be strongly affected by their abundance. As such, this analysis could miss low abundance but highly enriched mRNAs. I suggest either a) clarify how the analysis was done such that this is not an issue, or b) acknowledge the limitations in the text with how this analysis is performed and the types of RNAs it will miss.We have added acknowledgements in Results section and Discussion section that low abundance mRNAs may have been missed.Reviewer #2:[…] This paper presents several new and significant advances to the RNP phase-separation and germ-granule fields. Two crucial but addressable criticisms are discussed.1) As a control for the MEG-3 iCLIP experiments, the authors perform iCLIP on GFP-expressing embryos. Information for the control (JH1094?) isn't given. The optimal control would express GFP in just the germline blastomeres where MEG-3 and PGL-1 are enriched to avoid identifying the most abundant transcripts in P blastomeres (compared to the whole embryo). Genes like cbd-1, cgh-1, and puf-5 are some of most abundant in the germline. Of the 657 MEG-3-bound transcripts, over half are in the top 1000 germline expressed (11-fold more than expected by chance), and most fall within the top 3000 germline-expressed genes. The statement on line 102 that MEG-3 binds to a specific subset of mRNAs instead of abundant P-blastomere mRNAs will need more supporting data than is currently provided.Correlations provided in Figure 1C and Figure 1—figure supplement 1C may be erroneous and serve as a distraction at the beginning of an otherwise very significant study. Instead, the comparison should be with all ~ 15,000 germline-expressed transcripts. Despite a potential lack of MEG-3 specificity, results are still in line with the author's later and well-supported observations that untranslated transcripts in translationally quiescent P blastomeres have an affinity for MEG-3.We now include the requested comparisons showing all transcripts . These comparisons confirm that our iCLIP experiments recovered specific transcripts within a wide range of expression levels. We acknowledge, however, that low abundance transcripts may have been missed, and have added this caveat to the text in the Results section and Discussion section.JH1094 expresses GFP in all blastomeres and therefore is not the optimal control suggested by the reviewer. Nevertheless, when we plot the abundance of all P blastomere-enriched transcripts versus their abundance in the MEG-3 IP, we obtain only a low correlation , confirming that the MEG-3 IP is recovering specific transcripts.An apparent exception to the transcript abundance correlation is that MEG-3-bound transcripts lack those that encode ribosomal proteins. While not necessary to include in this manuscript, it may be interesting to consider why abundant RPL/RPS (RPG) transcripts do not bind MEG-3.mRNAs coding for ribosomal proteins, while abundant, are well translated, and thus were not recovered in the MEG-3 iCLIP, which generally favors mRNAs with low ribosome footprints.2) P blastomeres are translationally quiescent, so shouldn't lower ribosomal coverage of MEG-3 attached transcripts in P blastomeres be expected when the experiment was done on whole embryos? Specificity is not addressed and observations in Figure 2C may be a correlation artifact. While this isn't likely given the later in situ hybridization experiments following translational inhibition, the caveat should be discussed.We have modified Figure 2—figure supplement 2A to show ribosome footprints on all embryonic transcripts, transcripts enriched in P blastomeres, and P granule transcripts – this analysis confirms that P granule transcripts have on average lower ribosome coverage than even P blastomere-enriched transcripts.