Quantitative control of noise in mammalian gene expression by dynamic histone regulation

Article activity feed

1. 

   Version published to 10.7554/elife.65654 on eLife

   Aug 11, 2021
2. 

   eLife

   May 24, 2021

   Author Response:

   Evaluation Summary:

   This paper will be of interest to biologists who study mechanisms of cell-to-cell variability in gene expression and those who wish to have a tool to alter variability in mammalian cells. Key regulators of gene expression variability in mammalian cells are identified and noise modulation in a synthetic system is shown. The data quality is high. A model for the origin of the observed noise is proposed, but will require some additional experimental evidence.

   We thank the reviewers for their thorough reviews, insightful critics, and very constructive suggestions of our manuscript. It genuinely helps us improve our work and manuscript. We have performed all the additional experiments suggested. We believe that our new results and revised manuscript answered these questions raised by the reviewers and …

   Author Response:

   Evaluation Summary:

   This paper will be of interest to biologists who study mechanisms of cell-to-cell variability in gene expression and those who wish to have a tool to alter variability in mammalian cells. Key regulators of gene expression variability in mammalian cells are identified and noise modulation in a synthetic system is shown. The data quality is high. A model for the origin of the observed noise is proposed, but will require some additional experimental evidence.

   We thank the reviewers for their thorough reviews, insightful critics, and very constructive suggestions of our manuscript. It genuinely helps us improve our work and manuscript. We have performed all the additional experiments suggested. We believe that our new results and revised manuscript answered these questions raised by the reviewers and editors.

   Reviewer #1 (Public Review):

   The manuscript aims to identify origins of stochasticity ('noise') in mammalian gene expression focused on the case when a single transcription factor controls the expression of a target gene. It also aims to devise strategies to control mean and variance of gene expression independently.

   The experimental approach uses a light-induced transcriptional activator in two stimulation modes, namely amplitude modulation (AM: time-constant light input) and pulse width modulation (PWM: periodic light inputs in the form of a pulse train). Perturbation experiments target histone-modifying enzymes to influence epigenetic states, with corresponding measurements of single-cell epigenetic states and mRNA dynamics to dissect mechanisms of noise control. Beyond this synthetic setting, the study is complemented by endogenous gene expression noise in human and mouse cells under the same perturbations.

   Major strengths of the study are:

   • The experimental demonstration that, and under which conditions PWM can reduce gene expression noise in mammalian cells; the corresponding data sets could be very valuable for further quantitative analysis.
   • Providing strong evidence via perturbation studies that the extent of gene expression noise is linked to chromatin-modifying activities, specifically opposing HDAC4/5 histone deacetylase activities and CBP/p300 histone acetyltransferase activities.
   • Proposing a positive-feedback model established by these two opposing activities that is consistent with the reported data from perturbation experiments and on chromatin accessibility / modification states.
   • Providing evidence that also in the natural (human and mouse cell) setting, the regulators HDAC4/5 and CBP/p300 contribute to the control of gene expression noise.

   We thank the reviewer for the careful analysis of our manuscript.

   Major weaknesses are:

   • Limited conceptual novelty because noise-reducing effects of PWM have been demonstrated and analyzed previously in synthetic systems in bacteria (with an engineered positive feedback loop; https://www.nature.com/articles/s41467-017-01498-0) and in yeast (with an engineered single transcription factor as in the present study: https://www.nature.com/articles/s41467-018-05882-2#Sec25).

   We appreciate that the reviewer pointed out two studies with E. coli and yeast with similar PWM. We believed that their concepts were different. The concept of “stabilized unstable steady states” was a specifically developed in control chaos in physical by Ott, Grebogi, and Yorke (OGY theory, https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.64.1196 ). Their motivation was to feedback control chaos with small perturbation in the systems. Non-feedback control with small periodic perturbation has also been shown to control chaos by stabilizing unstable steady state. The E. Coli work to stabilize an unstable steady state could be considered as an extension of these concepts in complex biological systems. In addition, the location of unstable steady state in a bistable system would decrease with increasing light intensity, as shown in the black dashed line in Figure 2E, inconsistent with our result that the mean mRuby is monotonically correlated with the mean light intensity (Figure 1C).

   It is correct that the hypothesis proposed by Benzinger and Khammash in their yeast paper, that the cooperative TF-gene expression curve is sufficient to generate bimodal distribution with high variable TF distribution, shown in Figure 1G. But it is not the case in our study. In our experiment, GAVPO and mRuby expression do not exhibit clear cooperativity. In addition, the authors didn’t show bimodality unless a non-isogenic cell population is used (Fig. 3h in Benzinger and Khammash’s paper).

   • Insufficient evidence for the postulated bistability caused by positive feedback on chromatin states in the mammalian system analyzed, which has implications for the mechanistic explanations provided (e.g., if PWM allows rapid cell switching between 'high' and 'low' states as postulated).

   We agree with the reviewer that the current technology limits the possibility to obtain more direct evidence of bistability in chromatin states. Our scATAC-seq data shows that chromatin openness oscillated between light “on” and “off” phase with reduced heterogeneity comparing to the dark control. Our bulk data suggest that H3K27ac has larger differences between “high” and “low” states. A better measurement would be single-cell ChiP-seq for H3K27ac. However, the current single-cell ChiP-seq technologies provide coverages too low (~1% of scATAC-seq reads) to support measurements at specific loci (https://www.nature.com/articles/s41592-021-01060-3, https://www.nature.com/articles/s41587-021-00869-9 ).

   • Limited theoretical support for the proposed (not directly observable) mechanisms that uses a mathematical model illustrating the potential consistency, but the model is not directly linked to the experimental data and hence of limited use for their interpretation.

   Our ODE model wasn’t built to fit to the experimental data. We used it to generate hypotheses with perturbation in HDAC4/5 and CBP/p300. We validate the model prediction of inhibition p300 reducing heterogeneity.

   It was validated in experiments. We have built a stochastic model containing all the processes in our ODE model, considered nine independent promoters, and have written the code for stochastic simulation algorithm similar to the yeast paper, and performed optimization. But we don’t have enough CPU time to fit to the experimental data and finding the “global minimum” using the parallel tempering Monte-Carlo method (https://pubmed.ncbi.nlm.nih.gov/19810318/).

   Overall, the authors achieved their aim of elucidating mechanisms for noise control in mammalian gene expression by identifying specific, opposing regulators of chromatin states, with clear support in the synthetic setting, and evidence in endogenous expression control. Conceptual advances regarding strategies for the external control of gene expression noise appear limited because of prior work, which includes more in-depth theoretical analysis in simpler (bacterial, yeast) systems.

   Hence, the likely impact of the work will be primarily on the more detailed (in terms of histone regulators, etc.) study of noise control in mammalian cells, while the data sets presented in the study could prove valuable for follow-up quantitative (model-based) analyses because they are unique in combining different readouts such as single-cell protein and mRNA abundances as well as histone and chromatin states.

   We appreciate that reviewer finds this manuscript support that the molecular mechanisms regulate mammalian gene expression noise control in both synthetic and endogenous gene regulations.

   Reviewer #2 (Public Review):

   The manuscript describes a tool to independently tune mean protein expression levels and noise. Light induces dimerization and subsequent activation of transcriptional activator GAVPO. By introducing 5xUAS (a target sequence for dimerized GAVPO) upstream a mRuby reporter gene, the effect of light can be measured on mRuby mean and noise.

   By pulsing light at different periods (from 100-400 minutes), the authors reduce the mRuby noise for intermediate average light intensities. Notably, the pulses are all applied at an absolute light intensity of 100 uW/cm2, with the average light intensity being modulated through the light-off time-periods. Therefore, as all periods tend towards 100 uW/cm2 average light intensity, the PWM duty cycles becomes more similar to the 100 uW/cm2 AM case.

   Strengths:

   The proposed method is an elegant way to independently tune protein mean and noise. This would have a broad application in the field and is much needed to be able to study the consequence of protein expression noise, independently of mean. In addition, the authors use multiple powerful single-cell techniques to try and determine the mechanism underpinning the light-induced noise modulation.

   During constant exposure to light, increased light intensity increases the mean expression of mRuby, while decreasing the noise. This high noise is mostly due to observed bimodality in mRuby expression. Through ODEs and by using small molecule inhibitors, the authors show that this bimodality is caused by some cells being stably off, while other cells enter an on state. In this on state a positive feedback can occur where initial binding of dimerized GAVPO induces histone acetylation and chromatin accessibility, and thus stimulates further GAVPO binding. Bistability induced by constant light exposure is disrupted using small molecule inhibitors of CBP/p300 HAT activity, indicating that histone regulation is a cause for this observed bistability. The stable on state is demonstrated to be more active and accessible through ChIP-seq and ATAC-seq respectively.

   We appreciate that reviewer recognize that our method of independent tuning protein mean and noise has a broad application and is much needed, and our adaptation of integrating multiple single cell analyses to determine noise control mechanism. We believe that this method would be proven especially useful in cell fate control studies, in vitro with stem cell differentiation or in vivo with embryo development.

   Weakness:

   The single-cell ATAC-seq data indicate that pulsing light induces switching from an accessible (light on) to inaccessible (light off) chromatin state. The authors argue that the switching back into a chromatin inaccessible state prevents the positive feedback to occur and thus reduces noise. However, there are weaknesses in the description of the mechanism by which the pulses modulate (i.e., reduce) noise. Overall, since these sections in the manuscript are not easy to understand, it is difficult to parse what mechanism the authors attributed to the observed noise reduction and to assess if the data supports the conclusions.

   We apologize for the lack of clarity in this aspect. We have extensively rewritten the descriptions in the related sections. As the PWM light intensities alternate between 100 uW/cm2 and dark, which located at high and low monostable states. We need to show if the fraction of times at each state are sufficient. The scATAC-seq data indicate, one 150-minute of 100 uW/cm2 light pulse is sufficient to elevate the chromatin accessibility while reduce the cell-cell variations, two features of the high monostable state. The 450-minute dark period will reduce the chromatin accessibility. In this dark period, the cells will fall back to the low monostable state without sufficient activated GAVPO. H3K27ac has larger dynamic range between low and high state (Figure 3J), but single-cell ChiP-seq methods don’t provide sufficient coverage to assess H3K27ac heterogeneity at the 5xUAS-mRuby loci. Nevertheless, indirect evidences with perturbation of p300 activation or GAVPO-p300 interactions support this picture.

   The data from the single-mRNA live-cell imaging experiments are somewhat ambiguous and do not necessarily support some of the arguments. The conclusion that transcription, nuclear export, and mRNA degradation flatten the pulsatile chromatin caused by the PWM is not clear from the data. Especially, since most cells do not show any pulsatile behavior both in the single-cell ATAC-seq and the live-cell imaging data.

   We improved the presentation of the data. With the data presented in logarithm scale, it is visible that most cells exhibit pulsatile behavior (new Figure 5C). These can be further visualized with averaging over subpopulation of cells. As shown in Figure 5G in the revised manuscript. there are approximated 57% of cells show oscillations. The mean mRNA shows a damped periodic oscillation. The statement that nuclear export, and mRNA degradation flatten the pulsatile chromatin caused by the PWM are postulated due to the rate constants in the literatures, and removed in the revised manuscript. The half-life of mRuby is about 24 hours, sufficiently longer than the period of PWM. We have added an analysis of single-cell mRuby dynamics with 400 min PWM, which don’t exhibit periodic oscillations (Figure 5-figure supplement 2).

   Reviewer #3 (Public Review):

   The authors use a synthetic light-controlled transcription factor (GAVPO) to test a model of bistable gene expression that is hypothesized to originate from positive feedback via local histone modifications by trans-activator recruitment of CBP/p300 to facilitate open chromatin, which facilitates GAVPO binding, etc… Their proposed model for the origin of bistability is important because it should apply to any trans-activator that recruits CBP/p300 to modify chromatin and active gene expression. The authors show that periodic modulation of light reduces the bimodal distribution at intermediate light-intensity levels to a unimodal distribution. This is an elegant demonstration of how GAVPO and different temporal patterns of light can reduce cell-to-cell variability in gene expression, if needed.

   Strengths:

   The authors generate an impressive amount of single-cell data of gene expression and chromatin state (flow cytometry, single-cell sequencing, live-cell MS2-tagging) at different intensity levels. The periodic modulation of GAVPO activity by light is a practical demonstration of how to sculpt the gene expression output in useful ways. This may be a very useful tool for future biologists.

   We thank the reviewer for the positive comments on the mammalian noise control mechanism we discovery and its broad implications.

   Weakness:

   The proposed model for bistability is not convincingly tested or supported by the existing data. Each reporter should exhibit a bistable response because the positive feedback is localized to the promoter via cis-effects on gene expression by local chromatin state/GAVPO binding. The authors show a bimodal distribution of gene expression in a population of cells, which is consistent with a bistable response in a single reporter gene. However, their strain has 9 independent reporters integrated into the genome. Thus, I would expect to see up to 10 peaks, not 2 peaks. Moreover, the mathematical model used to validate their observations does not model the total expression from 9 independent promoters, which is a critical omission given the cis-nature of the positive feedback loop. The fact that these 9 promoters generate 2 peaks at intermediate light intensity suggests that the GAVPO bistability likely originates from a trans-effect, i.e., either all 9 promoters are OFF or all 9 promoters are ON, not a cis-effect.

   We appreciate the reviewer’s insight. We agree that theoretically there should be potentially 10 peaks. The separation between two adjacent “high” peaks is about 2 folds. The experimentally measure high mRuby peak with the lowest CV is about 0.47 (cells under maximum light with LMK-235 and A485, Figure 3B). This variation could overshadow the 2-fold differences in mean mRuby and prevent the recognition of multiple “high” peaks. On the other hand, the difference between low state and any of the high states is large enough to be recognized as separate peaks. We emulate the case with the 9 sites chose “low” and “high” states stochastically and stochastically (Figure 3-figure supplement 2). The 9 potential high peaks are convoluted into a broader peak, similar to experimental observations.

   We agree that our model is very simple and didn’t model the total expression from independent promoter. We have built a stochastic model containing all the processes in our ODE model, considered nine independent promoters. Unfortunately the fitting to experimental data using the parallel tempering Monte-Carlo method costs too much time.

   We performed additional experiments to mutate p65AD of GAVPO to specifically reduce its interaction with CBP/p300. The disappearance of bimodal distribution validates that the direct interaction between UAS-binding GAVPO and CBP/p300 causes the bistability, not a trans-effect through intermediates. We performed single-cell mRuby dynamics and selected cells with nearly identical GAVPO (Figure 2H). The mRuby-high cells elevated earlier and stay at high state (red lines in Figure 2G), and the mRuby-low cells remain low (blue lines in Figure 2G). There are a few cells seem to make the transitions between the two states. These data are consistent with bistability model with small rates of stochastic transition in between. Prior exposure to 100 uW/cm2 light also tilted the distribution toward the “high” state, validate the hysteresis properties of the bistability (Figure 2I-J).

   Read the original source
3. 

   eLife

   May 24, 2021

   Reviewer #3 (Public Review):

   The authors use a synthetic light-controlled transcription factor (GAVPO) to test a model of bistable gene expression that is hypothesized to originate from positive feedback via local histone modifications by trans-activator recruitment of CBP/p300 to facilitate open chromatin, which facilitates GAVPO binding, etc... Their proposed model for the origin of bistability is important because it should apply to any trans-activator that recruits CBP/p300 to modify chromatin and active gene expression. The authors show that periodic modulation of light reduces the bimodal distribution at intermediate light-intensity levels to a unimodal distribution. This is an elegant demonstration of how GAVPO and different temporal patterns of light can reduce cell-to-cell variability in gene expression, if needed.

   Strengths:

   Th…

   Reviewer #3 (Public Review):

   The authors use a synthetic light-controlled transcription factor (GAVPO) to test a model of bistable gene expression that is hypothesized to originate from positive feedback via local histone modifications by trans-activator recruitment of CBP/p300 to facilitate open chromatin, which facilitates GAVPO binding, etc... Their proposed model for the origin of bistability is important because it should apply to any trans-activator that recruits CBP/p300 to modify chromatin and active gene expression. The authors show that periodic modulation of light reduces the bimodal distribution at intermediate light-intensity levels to a unimodal distribution. This is an elegant demonstration of how GAVPO and different temporal patterns of light can reduce cell-to-cell variability in gene expression, if needed.

   Strengths:

   The authors generate an impressive amount of single-cell data of gene expression and chromatin state (flow cytometry, single-cell sequencing, live-cell MS2-tagging) at different intensity levels. The periodic modulation of GAVPO activity by light is a practical demonstration of how to sculpt the gene expression output in useful ways. This may be a very useful tool for future biologists.

   Weakness:

   The proposed model for bistability is not convincingly tested or supported by the existing data. Each reporter should exhibit a bistable response because the positive feedback is localized to the promoter via cis-effects on gene expression by local chromatin state/GAVPO binding. The authors show a bimodal distribution of gene expression in a population of cells, which is consistent with a bistable response in a single reporter gene. However, their strain has 9 independent reporters integrated into the genome. Thus, I would expect to see up to 10 peaks, not 2 peaks. Moreover, the mathematical model used to validate their observations does not model the total expression from 9 independent promoters, which is a critical omission given the cis-nature of the positive feedback loop. The fact that these 9 promoters generate 2 peaks at intermediate light intensity suggests that the GAVPO bistability likely originates from a trans-effect, i.e., either all 9 promoters are OFF or all 9 promoters are ON, not a cis-effect.

   Read the original source
4. 

   eLife

   May 24, 2021

   Reviewer #2 (Public Review):

   The manuscript describes a tool to independently tune mean protein expression levels and noise. Light induces dimerization and subsequent activation of transcriptional activator GAVPO. By introducing 5xUAS (a target sequence for dimerized GAVPO) upstream a mRuby reporter gene, the effect of light can be measured on mRuby mean and noise.

   By pulsing light at different periods (from 100-400 minutes), the authors reduce the mRuby noise for intermediate average light intensities. Notably, the pulses are all applied at an absolute light intensity of 100 uW/cm2, with the average light intensity being modulated through the light-off time-periods. Therefore, as all periods tend towards 100 uW/cm2 average light intensity, the PWM duty cycles becomes more similar to the 100 uW/cm2 AM case.

   Strengths:

   The proposed …

   Reviewer #2 (Public Review):

   The manuscript describes a tool to independently tune mean protein expression levels and noise. Light induces dimerization and subsequent activation of transcriptional activator GAVPO. By introducing 5xUAS (a target sequence for dimerized GAVPO) upstream a mRuby reporter gene, the effect of light can be measured on mRuby mean and noise.

   By pulsing light at different periods (from 100-400 minutes), the authors reduce the mRuby noise for intermediate average light intensities. Notably, the pulses are all applied at an absolute light intensity of 100 uW/cm2, with the average light intensity being modulated through the light-off time-periods. Therefore, as all periods tend towards 100 uW/cm2 average light intensity, the PWM duty cycles becomes more similar to the 100 uW/cm2 AM case.

   Strengths:

   The proposed method is an elegant way to independently tune protein mean and noise. This would have a broad application in the field and is much needed to be able to study the consequence of protein expression noise, independently of mean. In addition, the authors use multiple powerful single-cell techniques to try and determine the mechanism underpinning the light-induced noise modulation.

   During constant exposure to light, increased light intensity increases the mean expression of mRuby, while decreasing the noise. This high noise is mostly due to observed bimodality in mRuby expression. Through ODEs and by using small molecule inhibitors, the authors show that this bimodality is caused by some cells being stably off, while other cells enter an on state. In this on state a positive feedback can occur where initial binding of dimerized GAVPO induces histone acetylation and chromatin accessibility, and thus stimulates further GAVPO binding. Bistability induced by constant light exposure is disrupted using small molecule inhibitors of CBP/p300 HAT activity, indicating that histone regulation is a cause for this observed bistability. The stable on state is demonstrated to be more active and accessible through ChIP-seq and ATAC-seq respectively.

   Weakness:

   The single-cell ATAC-seq data indicate that pulsing light induces switching from an accessible (light on) to inaccessible (light off) chromatin state. The authors argue that the switching back into a chromatin inaccessible state prevents the positive feedback to occur and thus reduces noise. However, there are weaknesses in the description of the mechanism by which the pulses modulate (i.e., reduce) noise. Overall, since these sections in the manuscript are not easy to understand, it is difficult to parse what mechanism the authors attributed to the observed noise reduction and to assess if the data supports the conclusions.

   The data from the single-mRNA live-cell imaging experiments are somewhat ambiguous and do not necessarily support some of the arguments. The conclusion that transcription, nuclear export, and mRNA degradation flatten the pulsatile chromatin caused by the PWM is not clear from the data. Especially, since most cells do not show any pulsatile behavior both in the single-cell ATAC-seq and the live-cell imaging data.

   Read the original source
5. 

   eLife

   May 24, 2021

   Reviewer #1 (Public Review):

   The manuscript aims to identify origins of stochasticity ('noise') in mammalian gene expression focused on the case when a single transcription factor controls the expression of a target gene. It also aims to devise strategies to control mean and variance of gene expression independently.

   The experimental approach uses a light-induced transcriptional activator in two stimulation modes, namely amplitude modulation (AM: time-constant light input) and pulse width modulation (PWM: periodic light inputs in the form of a pulse train). Perturbation experiments target histone-modifying enzymes to influence epigenetic states, with corresponding measurements of single-cell epigenetic states and mRNA dynamics to dissect mechanisms of noise control. Beyond this synthetic setting, the study is complemented by endogenous …

   Reviewer #1 (Public Review):

   The manuscript aims to identify origins of stochasticity ('noise') in mammalian gene expression focused on the case when a single transcription factor controls the expression of a target gene. It also aims to devise strategies to control mean and variance of gene expression independently.

   The experimental approach uses a light-induced transcriptional activator in two stimulation modes, namely amplitude modulation (AM: time-constant light input) and pulse width modulation (PWM: periodic light inputs in the form of a pulse train). Perturbation experiments target histone-modifying enzymes to influence epigenetic states, with corresponding measurements of single-cell epigenetic states and mRNA dynamics to dissect mechanisms of noise control. Beyond this synthetic setting, the study is complemented by endogenous gene expression noise in human and mouse cells under the same perturbations.

   Major strengths of the study are:

   • The experimental demonstration that, and under which conditions PWM can reduce gene expression noise in mammalian cells; the corresponding data sets could be very valuable for further quantitative analysis.
   • Providing strong evidence via perturbation studies that the extent of gene expression noise is linked to chromatin-modifying activities, specifically opposing HDAC4/5 histone deacetylase activities and CBP/p300 histone acetyltransferase activities.
   • Proposing a positive-feedback model established by these two opposing activities that is consistent with the reported data from perturbation experiments and on chromatin accessibility / modification states.
   • Providing evidence that also in the natural (human and mouse cell) setting, the regulators HDAC4/5 and CBP/p300 contribute to the control of gene expression noise.

   Major weaknesses are:

   • Limited conceptual novelty because noise-reducing effects of PWM have been demonstrated and analyzed previously in synthetic systems in bacteria (with an engineered positive feedback loop; https://www.nature.com/articles/s41467-017-01498-0) and in yeast (with an engineered single transcription factor as in the present study: https://www.nature.com/articles/s41467-018-05882-2#Sec25).
   • Insufficient evidence for the postulated bistability caused by positive feedback on chromatin states in the mammalian system analyzed, which has implications for the mechanistic explanations provided (e.g., if PWM allows rapid cell switching between 'high' and 'low' states as postulated).
   • Limited theoretical support for the proposed (not directly observable) mechanisms that uses a mathematical model illustrating the potential consistency, but the model is not directly linked to the experimental data and hence of limited use for their interpretation.

   Overall, the authors achieved their aim of elucidating mechanisms for noise control in mammalian gene expression by identifying specific, opposing regulators of chromatin states, with clear support in the synthetic setting, and evidence in endogenous expression control. Conceptual advances regarding strategies for the external control of gene expression noise appear limited because of prior work, which includes more in-depth theoretical analysis in simpler (bacterial, yeast) systems.

   Hence, the likely impact of the work will be primarily on the more detailed (in terms of histone regulators, etc.) study of noise control in mammalian cells, while the data sets presented in the study could prove valuable for follow-up quantitative (model-based) analyses because they are unique in combining different readouts such as single-cell protein and mRNA abundances as well as histone and chromatin states.

   Read the original source
6. 

   eLife

   May 24, 2021

   Evaluation Summary:

   This paper will be of interest to biologists who study mechanisms of cell-to-cell variability in gene expression and those who wish to have a tool to alter variability in mammalian cells. Key regulators of gene expression variability in mammalian cells are identified and noise modulation in a synthetic system is shown. The data quality is high. A model for the origin of the observed noise is proposed, but will require some additional experimental evidence.

   (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

   Read the original source
7. 

   Version published to 10.1101/2020.12.20.423693v1 on bioRxiv

   Dec 21, 2020