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  1. Author Response

    Reviewer #1 (Public Review):

    This paper provides a new method, smfATAC-Seq, which can be used to identify epigenetic alterations that occur in myofibers during muscle regeneration or muscle diseases. Through extracting single myofibers from the Extensor Digitorum Longus (EDL) muscle fiber followed by ATAC-Seq, the chromatin accessibility profile of a single myofiber can be obtained for further analysis. Using the smfATAC-Seq, sufficient reads can be obtained from one myofiber containing around 200-300 myonuclei. This method allows for a small input amount and is easy to follow. The authors show that the chromatin accessibility profile of myonuclei is different from that of muscle stem cells (MuSCs) and changes upon injury and disease. Further analysis of the smfATAC-Seq data may allow for the identification of active regulatory elements in muscle fibers.

    Although the approach does have strengths in principle, the design of the experiments and data analyses performed are superficial. Notably, the data size (i.e., the number of myofibers evaluated) is insufficient to conclude to support the claims in the manuscript.

    We thank the reviewer for their careful and insightful comments on our manuscript. The design of the experiments is centered on the validation of ATAC-seq on single EDL myofibers. We have chosen myofibers under different physiological and disease conditions. We have also taken the recommended required numbers of biological replicates suggested by ENCODE into consideration (https://www.encodeproject.org/atac-seq/). We believe, the number of replicates and the extensive validation of the data firmly supports our conclusion that smfATAC-seq is a powerful and reproducible method to interrogate the chromatin accessibility and to identify active cis-regulatory elements in a single muscle fiber under various physiological and disease conditions.

    Major points:

    1. One muscle contains hundreds of myofibers, while the authors only show 2-4 myofiber replicates for each condition. The authors claim that this method can be used to distinguish different fiber types. However, there is no evidence to support such a claim. Instead of using EDL, the approach should be applied to a muscle that contains a ratio of both fast and slow fiber types, indicating the heterogeneity among myofibers in one muscle in different conditions. In addition, the myofibers from the injured or disease muscles are highly heterogeneous in terms of their regeneration status. What is the rationale for choosing the myofibers? Were all the myofibers injured with central nuclei from end to end? Or is it partial? What is the diameter of this muscle fiber? Can the smfATAC-seq be a method to tell us about the maturity of the myofibers? Unfortunately, the design of the experiments did not provide any interesting biological insights.

    We do understand that a muscle contains hundreds of myofibers and that they are heterogeneous. The main aim of this “Tools and Resource” article is to demonstrate that ATACseq can be reproducibly applied to a single EDL muscle fiber to analyze its chromatin accessibility. We believe that this method can be used in future studies to gain detailed biological insights on the chromatin state of myofibers under various conditions.

    Furthermore, we show that our smfATAC-Seq can distinguish between different fiber types such as slow type and fast type. We show in Figure 3 – Figure Supplement 2 the presence of ATACSeq peaks in the promoter regions of genes associated with fast type fibers such as Troponin I2 (Tnni2) and Troponin T3 (Tnnt3). However, we also show the absence of peaks for genes that are associated with slow type fibers such as Troponin T1 (Tnnt1) and Myosin heavy chain 7 (Myh7). In this manuscript we introduce a new method to the field that can be utilized under various physiological and disease conditions. In the future, smfATAC-Seq can be performed on a muscle that contains both fast and slow type fibers if that is desired by other groups in order to compare the chromatin accessibility between slow and fast type myofibers.

    We agree with the reviewer that myofibers under injury are highly heterogenous as we have stated previously in our manuscript. That is precisely why we have optimized the method to add a step to select for the desired myofiber since random selection from an injured muscle could result in a myofiber that is not under regeneration or only partially regenerated at the time of selection. For that reason, in our method, we have included a step where we stain the myonuclei with Hoechst and visualize the centrally located myonuclei, since that is a marker for regeneration. For the injured condition, we have specifically selected myofibers that are composed solely of centrally located myonuclei, indicating an injured or regenerating myofiber. In the comparison between MDX and WT myofibers, both conditions were uninjured and only myofibers that displayed no centrally located nuclei were selected for processing.

    1. The authors claim that their data "revealed a repertoire of active cis-regulatory elements", but no supporting evidence is provided. In the manuscript, only the smfATAC-Seq signal coverage across the genes known to be functional in muscle development was shown. Identifying the active cis-regulatory elements is essentially impossible without combinational analysis with other epigenetic profiles (e.g., H3K27ac ChIP-Seq, Hi-C). The results presented serve as validation but not an exploration of the regulatory elements for MuSCs and myofibers.

    We have now performed comparative analysis between our smfATAC-Seq and ChIPSeq performed on EDL muscle for H3K27ac by Ramachandran, et al. 2019. The figure for this analysis can be found in Figure 2 – Figure Supplement 2K). We now discuss the results of this analysis in the lines 184- 191 which reads as follows:

    “Accessible chromatin regions are associated with various histone marks such as H3K27ac and H3K4me3 (4-6). Thus, we compared the smfATAC-Seq to publicly available datasets on ChIP-Seq on H3K27ac in EDL muscle that was previously performed by Ramachandran, et al. 2019 (GSM3515022, GSM3515023) (7). The comparative analysis has revealed that there were only 97 peaks in the smfATAC-Seq that did not overlap with the H3K27ac peaks, while the majority of the peaks, 6090 peaks, were common to the H3K27ac peaks present in the entire EDL muscle (Figure 2- Figure supplement 2K). This demonstrates that the accessible regions that are assessed by smfATAC-Seq correspond to the regions of the chromatin marked by histones that are associated with open chromatin such as H3K27ac.”

    1. Muscle regeneration is a long-term process that could take a long time to complete depending on the age of the animal and the severity of the injury. The authors examined the chromatin accessibility profile of the myofibers in uninjured and 7 days post-injured muscle. This short time frame does not provide sufficient information to interpret the chromatin accessibility changes of myofibers during the whole regeneration process. It is difficult to understand the result of these experiments (comparing the uninjured fibers to injured fibers or WT fibers to MDX fibers). What does the ATAC-seq data add to our understanding that these myofibers are different? From a molecular point of view, Can this analysis provide a set of biomarkers of the myofiber cell states during regeneration and disease, for example? Again, the design of the experiments is superficial.

    We agree with the reviewer that regeneration is a long-term process and complete understanding of it requires assessment at multiple time points after injury including long term assessments. As mentioned before, smfATAC incorporates a step that can specifically select myofibers based on their regeneration status, which will be very beneficial for researchers in the future. Using smfATAC-Seq to understand the changes in chromatin state of a single myofiber during different time points after injury will advance our understanding of muscle regeneration and can lead to novel discoveries in the future. However, such experiments are beyond the scope of this “Tools and Resource” article.

    Reviewer #2 (Public Review):

    In this paper, Sahinyan and colleagues developed a method for analyzing chromatin accessibility in single murine myofibers. This goal was achieved by adapting the previously published OMNIATAC protocol to the specific properties of the myofiber environment. To demonstrate the validity of this method, they isolated myofibers from uninjured and regenerating murine EDL muscles dissected from wild type animals. In a second experiment, this method was applied to isolate myofibers from mdx mice, a model of Duchenne Muscular Dystrophy. The resulting datasets were further compared to the one generated from purified muscle stem cells.

    Strengths In general, the authors provided robust quality controls for these datasets, which ensures the validity of their observations. Analysis of chromatin accessibility using this protocol enabled the identification of subsets of peaks specific for each experimental group, which were further analyzed to determine enriched biological processes.

    Weaknesses While the experiments are well executed, the resulting data are descriptive and do not provide further insights into the biological processes under investigation. A more comprehensive analysis could significantly increase our knowledge of the molecular pathways controlling skeletal muscle response to acute or pathogenic injuries.

    We thank the reviewer for their comments and suggestions. As mentioned earlier, the purpose of this “Tools and Resource” article is to provide validation of the method without necessarily providing novel biological insights. However, additional comparative analysis of data in this manuscript between different physiological and disease conditions does provide some biological insights on the chromatin accessibility of myofibers.

    Reviewer #3 (Public Review):

    In this study, the authors adapt the OMNI-ATACSeq for single muscle fiber ATACSeq. This technique, dubbed "smfATAC-Seq" is used to demonstrate epigenetic changes in injury and the mdx dystrophic mouse model. Single-cell ATACSeq has been used to characterize cellular epigenetic heterogeneity of other tissues. However, the fused, multinucleated nature of muscle fibers makes skeletal muscle intractable to this method. Thus, epigenetic studies have been restricted to either whole muscle, or single cells within the tissue (eg muscle stem cells, endothelial and immune cells). While the study is primarily descriptive, the smfATAC-Seq method presented is technically thorough, and will be valuable for the muscle field. Furthermore, the data produced is a good resource that can be mined to generate testable hypotheses in the future.

    Strengths The methods are presented clearly, and the most often studied conditions in the muscle field (injury and dystrophy) are appropriately used as examples to demonstrate the utility of smfATACSeq. In addition, the authors show that the data generated is reproducible, and can capture known aspects of myofiber heterogeneity.

    Weaknesses Since the paper is largely focused on a new method, more emphasis should be placed on what kind of questions can be uniquely answered by smfATCSeq. The authors show selected tracks between smfATAC-Seq and DESeq, however, this is a qualitative comparison. Authors should also provide a more systematic comparison of smfATAC seq with other published epigenetic datasets in whole skeletal muscle (DNaseq, ATACSeq, etc) -- for example, compare quality metrics such as sequencing depth or quantify overlap between identified peaks across methods.

    We thank the reviewer for their comments and suggestions. We have now compared the smfATAC-Seq to other published epigenetic data sets such as whole muscle ATAC-Seq and ChIP-Seq of H3K27ac on whole muscle.

    We have now performed comparative analysis between our smfATAC-Seq and ChIP-Seq performed on EDL muscle for H3K27ac by Ramachandran, et al. 2019. The figure for this analysis can be found in Figure 2 – Figure Supplement 2K. We now discuss the results of this analysis in the lines 184- 191 which reads as follows:

    “Accessible chromatin regions are associated with various histone marks such as H3K27ac and H3K4me3 (4-6). Thus, we compared the smfATAC-Seq to publicly available datasets on ChIP-Seq on H3K27ac in EDL muscle that was previously performed by Ramachandran, et al. 2019 (GSM3515022, GSM3515023) (7). The comparative analysis has revealed that there were only 97 peaks in the smfATAC-Seq that did not overlap with the H3K27ac peaks, while the majority of the peaks, 6090 peaks, were common to the H3K27ac peaks present in the entire EDL muscle (Figure 2- Figure supplement 2K ). This demonstrates that the accessible regions that are assessed by smfATAC-Seq correspond to the regions of the chromatin marked by histones that are associated with open chromatin such as H3K27ac .”

    We have also compared our smfATAC-Seq on the uninjured myofiber to the whole EDL muscle ATAC-Seq that was mentioned by the reviewer (Ramachandran, et al.2019). We have determined that 65% of the peaks in the smfATAC-Seq overlap with the whole muscle ATACSeq by at least 1 bp. We have included a detailed table on the overlap between the two datasets (Table 3).

    We discuss the results of this comparison in the lines 179-182: “We also analyzed the overlap between the smfATAC-Seq on single EDL myofibers with the ATAC-Seq performed on the whole EDL muscle by Ramachandran, et al. 2019 (GSM3981673) (7). This analysis revealed that 65% of the smfATAC-Seq peaks in the uninjured myofiber overlap with the whole EDL muscle ATAC-Seq (Table 3).”

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  2. Evaluation Summary:

    In this paper, Sahinyan and colleagues developed a method for analyzing chromatin accessibility in single murine myofibers. This goal was achieved by adapting the previously published OMNI-ATAC protocol to the specific properties of the myofiber environment. To demonstrate the validity of this method, they isolated myofibers from uninjured and regenerating murine EDL muscles dissected from wild type animals. In a second experiment, this method was applied to isolate myofibers from mdx mice, a model of Duchenne Muscular Dystrophy. The resulting datasets were further compared to the one generated from purified muscle stem cells.

    (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. Reviewer #3 agreed to share their name with the authors.)

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  3. Reviewer #1 (Public Review):

    This paper provides a new method, smfATAC-Seq, which can be used to identify epigenetic alterations that occur in myofibers during muscle regeneration or muscle diseases. Through extracting single myofibers from the Extensor Digitorum Longus (EDL) muscle fiber followed by ATAC-Seq, the chromatin accessibility profile of a single myofiber can be obtained for further analysis. Using the smfATAC-Seq, sufficient reads can be obtained from one myofiber containing around 200-300 myonuclei. This method allows for a small input amount and is easy to follow. The authors show that the chromatin accessibility profile of myonuclei is different from that of muscle stem cells (MuSCs) and changes upon injury and disease. Further analysis of the smfATAC-Seq data may allow for the identification of active regulatory elements in muscle fibers.

    Although the approach does have strengths in principle, the design of the experiments and data analyses performed are superficial. Notably, the data size (i.e., the number of myofibers evaluated) is insufficient to conclude to support the claims in the manuscript.

    Major points:

    1. One muscle contains hundreds of myofibers, while the authors only show 2-4 myofiber replicates for each condition. The authors claim that this method can be used to distinguish different fiber types. However, there is no evidence to support such a claim. Instead of using EDL, the approach should be applied to a muscle that contains a ratio of both fast and slow fiber types, indicating the heterogeneity among myofibers in one muscle in different conditions. In addition, the myofibers from the injured or disease muscles are highly heterogeneous in terms of their regeneration status. What is the rationale for choosing the myofibers? Were all the myofibers injured with central nuclei from end to end? Or is it partial? What is the diameter of this muscle fiber? Can the smfATAC-seq be a method to tell us about the maturity of the myofibers? Unfortunately, the design of the experiments did not provide any interesting biological insights.

    2. The authors claim that their data "revealed a repertoire of active cis-regulatory elements", but no supporting evidence is provided. In the manuscript, only the smfATAC-Seq signal coverage across the genes known to be functional in muscle development was shown. Identifying the active cis-regulatory elements is essentially impossible without combinational analysis with other epigenetic profiles (e.g., H3K27ac ChIP-Seq, Hi-C). The results presented serve as validation but not an exploration of the regulatory elements for MuSCs and myofibers.

    3. Muscle regeneration is a long-term process that could take a long time to complete depending on the age of the animal and the severity of the injury. The authors examined the chromatin accessibility profile of the myofibers in uninjured and 7 days post-injured muscle. This short time frame does not provide sufficient information to interpret the chromatin accessibility changes of myofibers during the whole regeneration process. It is difficult to understand the result of these experiments (comparing the uninjured fibers to injured fibers or WT fibers to MDX fibers). What does the ATAC-seq data add to our understanding that these myofibers are different? From a molecular point of view, Can this analysis provide a set of biomarkers of the myofiber cell states during regeneration and disease, for example? Again, the design of the experiments is superficial.

    Was this evaluation helpful?
  4. Reviewer #2 (Public Review):

    In this paper, Sahinyan and colleagues developed a method for analyzing chromatin accessibility in single murine myofibers. This goal was achieved by adapting the previously published OMNI-ATAC protocol to the specific properties of the myofiber environment. To demonstrate the validity of this method, they isolated myofibers from uninjured and regenerating murine EDL muscles dissected from wild type animals. In a second experiment, this method was applied to isolate myofibers from mdx mice, a model of Duchenne Muscular Dystrophy. The resulting datasets were further compared to the one generated from purified muscle stem cells.

    Strengths
    In general, the authors provided robust quality controls for these datasets, which ensures the validity of their observations. Analysis of chromatin accessibility using this protocol enabled the identification of subsets of peaks specific for each experimental group, which were further analyzed to determine enriched biological processes.

    Weaknesses
    While the experiments are well executed, the resulting data are descriptive and do not provide further insights into the biological processes under investigation. A more comprehensive analysis could significantly increase our knowledge of the molecular pathways controlling skeletal muscle response to acute or pathogenic injuries.

    Was this evaluation helpful?
  5. Reviewer #3 (Public Review):

    In this study, the authors adapt the OMNI-ATACSeq for single muscle fiber ATACSeq. This technique, dubbed "smfATAC-Seq" is used to demonstrate epigenetic changes in injury and the mdx dystrophic mouse model. Single-cell ATACSeq has been used to characterize cellular epigenetic heterogeneity of other tissues. However, the fused, multinucleated nature of muscle fibers makes skeletal muscle intractable to this method. Thus epigenetic studies have been restricted to either whole muscle, or single cells within the tissue (eg muscle stem cells, endothelial and immune cells). While the study is primarily descriptive, the smfATAC-Seq method presented is technically thorough, and will be valuable for the muscle field. Furthermore, the data produced is a good resource that can be mined to generate testable hypotheses in the future.

    Strengths
    The methods are presented clearly, and the most often studied conditions in the muscle field (injury and dystrophy) are appropriately used as examples to demonstrate the utility of smfATACSeq. In addition, the authors show that the data generated is reproducible, and can capture known aspects of myofiber heterogeneity.

    Weaknesses
    Since the paper is largely focused on a new method, more emphasis should be placed on what kind of questions can be uniquely answered by smfATCSeq. The authors show selected tracks between smfATAC-Seq and DESeq, however, this is a qualitative comparison. Authors should also provide a more systematic comparison of smfATAC seq with other published epigenetic datasets in whole skeletal muscle (DNaseq, ATACSeq, etc) -- for example, compare quality metrics such as sequencing depth or quantify overlap between identified peaks across methods.

    Was this evaluation helpful?