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High Resolution Genome Wide Expression Analysis of Single Myofibers Using SMART-Seq

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High Resolution Genome Wide Expression Analysis of Single Myofibers Using SMART-Seq bioRxiv preprint doi: https://doi.org/10.1101/724393; this version posted October 17, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Blackburn et al. 2019 Manuscript High Resolution Genome Wide Expression Analysis of Single Myofibers Using SMART-Seq Darren M. Blackburn1,2,*, Felicia Lazure1,2,*, Aldo H. Corchado1, Theodore J. Perkins3,4, Hamed S. Najafabadi1, Vahab D. Soleimani1,2,5 1Department of Human Genetics, McGill University, 3640 rue University, Montreal, QC, H3A 0C7 Canada 2Molecular and Regenerative Medicine Axis, Lady Davis Institute for Medical ResearcH, JewisH General Hospital, 3755 Chemin de la Cote-Sainte-CatHerine, Montreal, QC, H3T 1E2, Canada 3Sprott Center for Stem Cell Research, Ottawa Hospital Research Institute, 501 Smyth Road, Ottawa, ON, K1H 8L6, Canada 4Department of BiocHemistry, Microbiology and Immunology, University of Ottawa, 451 SmytH Road, Ottawa, ON, K1H 8M5, Canada 5To whom correspondence sHould be addressed: VaHab D. Soleimani: Department of Human Genetics, McGill University, 3640 rue University, Montreal, QC, H3A 0C7, Canada; [email protected]; TelepHone number: +1 514 340 8222 ext. 26136; Fax number: +1 514 340-7502. *These autHors made equal contributions Running title: Single myofiber RNA-Seq Key Words: Single Myofiber, Skeletal Muscle, SMART-Seq, Gene Expression Analysis, Myofiber Heterogeneity, Aging skeletal muscle Word count: 3930 1 bioRxiv preprint doi: https://doi.org/10.1101/724393; this version posted October 17, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Blackburn et al. 2019 Manuscript ABSTRACT Skeletal muscle is a heterogeneous tissue. fibro/adipogenic cells (FAPs), adipocytes, Individual myofibers that make up muscle tissue mesencHymal cells and fibroblasts, among exhibit variation in their metabolic and others(1-4). Further heterogeneity of skeletal contractile properties. AltHougH tHere are muscle is also manifested by the diversity in the biochemical and histological assays to study composition of myofiber types whicH constitute myofiber Heterogeneity, efficient metHods to muscles (5). Skeletal muscle fiber types are often analyze the whole transcriptome of individual categorized based on their contractile properties, myofibers are lacking. We Have developed giving two broad categories: fast twitcH muscles single myofiber RNA-Seq (smfRNA-Seq) to and slow twitch muscles(5,6). These fiber types analyze the whole transcriptome of individual can be further subcategorized based on metabolic myofibers by combining single fiber isolation properties and myosin Heavy cHain (MyHC) witH SwitcHing MecHanisms at 5’ end of RNA isoforms(5,7). Template (SMART) tecHnology. Our metHod MetHods of investigating cHanges in fiber type in provides high-resolution genome wide response to different stimuli rely on staining and expression profiles of single myofibers. Using biochemical analyses of individual fibers, smfRNA-Seq, we have analyzed the differences biochemical analyses of the whole muscle or in the transcriptome of young and old myofibers sequencing of entire muscles(8). Standard bulk to validate the effectiveness of this new method. RNA sequencing is not suited for the analysis of Using smfRNA-Seq, we performed comparative myofibers at HigH resolution, as it captures the gene expression analysis between single entirety of the muscle tissue, resulting in the myofibers from young and old mice. Our data pooling of different fiber types in addition to non- suggests that aging leads to significant cHanges in myogenic cells (8). Consequently, in sucH the expression of metabolic and structural genes studies, the myofiber-specific gene signature in myofibers. Our data suggests that smfRNA- cannot be inferred based on RNA sequencing of Seq is a powerful tool to study developmental, whole muscle tissue. The emergence of single disease and age-related dynamics in the cell technology provides ample opportunity for composition of skeletal muscle. further investigation into the Heterogeneity of single muscle fibers at tHe transcriptome level. Here, we combine single myofiber isolation of INTRODUCTION the Extensor Digitorum Longus (EDL) in Mus Skeletal muscle is composed of a variety of musculus witH Switching MecHanism at tHe 5’ different cell types, including endothelial cells, end of RNA Template (SMART) tecHnology to 2 bioRxiv preprint doi: https://doi.org/10.1101/724393; this version posted October 17, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Blackburn et al. 2019 Manuscript analyze the whole transcriptome of individual addition of trypsin to the collagenase digestion myofibers (Figure 1)(9), in a method called buffer at a final concentration of 0.25%. This Single MyoFiber RNA-Seq (smfRNA-Seq). process does not damage the fiber itself, with a proper EDL isolation yielding over 200 We describe a robust method to extract RNA myofibers per mouse (Figure 2A). However, tHis from a single myofiber followed by generation of buffer effectively strips the myofibers of their sequencing ready libraries and whole satellite cells as shown by the reduction in the transcriptome analysis. Using tHis tecHnique, we number of PAX7+ cells per fiber (Figure 2B-D). first determined the genes that are found in the whole muscle tHat are not produced by tHe Since muscle fibers are very tough and do not myofiber and are instead produced by non- readily breakdown under normal lysing myogenic cell types. To demonstrate tHe conditions, extracting the RNA from a single effectiveness of this technique, we next went on myofiber can prove cHallenging. WitH wHole to analyze the differences in the wHole muscle, a metHod to overcome tHis is by freezing transcriptome between myofibers isolated from the muscle in liquid nitrogen and grinding it into young and old mice. smfRNA-Seq proved to be a a powder witH mortar and pestle(10). However, useful tool in determining gene expression this metHod cannot realistically be done to a changes that occur in myofibers between single fiber while still collecting all of the RNA. different conditions. Therefore, we lysed tHe fiber witH lysis buffer in RNAse free water, utilizing osmotic pressure and gentle pipetting to break down the fiber and RESULTS retrieve the intact RNA. THis method proved Isolation of high quality mRNA from single effective as more than an adequate amount of myofibers RNA was recovered, even from a single myofiber, for use witH SMART-Seq tecHnology One of the intentions of our novel method is to (Table 1). give researchers the ability to sequence RNA from a single myofiber without the confounding From the extracted RNA, we successfully presence of other cell types. A potential source of generated sequencing-ready cDNA libraries unwanted signal in the sequencing of myofiber using the DNA SMART-Seq HT kit (Takara RNA is tHe presence of muscle stem cells, also Biosciences) in combination with the Nextera XT known as satellite cells, that are physically DNA Library Preparation Kit (Illumina). Final associated with the fibers. Using our method, we single myofiber sequencing-ready libraries were have found that satellite cells can be almost of adequate quantity and of ideal size for completely removed from the fibers witH tHe sequencing, with fragments being of comparable 3 bioRxiv preprint doi: https://doi.org/10.1101/724393; this version posted October 17, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Blackburn et al. 2019 Manuscript average size as those generated from traditional variation between technical replicates (Figure whole muscle RNA-Seq libraries (Figure 2E-F). 3A,B). This is most likely due to the excessive This implies tHat our fiber RNA extraction quantity of sample and could be resolved by procedure generated high quality starting scaling up the protocol. material tHat was compatible witH low-input When looking more in deptH at individual genes library preparation tecHnologies. we see many similarities between tHe single Comparative analysis of whole muscle and myofiber and tHe wHole muscle, but also crucial single myofiber RNA-Sequencing differences. Of particular note, we see tHat muscle specific genes Have similar numbers of By evaluating the number of unique reads reads between the single fiber and the wHole obtained from smfRNA-Seq samples, we found muscle samples (Figure 4A-C). The Myh cluster that sequencing depth of single myofiber libraries codes for a variety of myosin Heavy cHain was comparable to whole muscle RNA proteins (MyHC), wHicH are the motor proteins of sequencing (Figure 3A). We obtained an average muscle wHose various isoforms are tHe basis of of 24 million unique reads from single myofiber the different fiber types(7,11). The similar samples when multiplexing 12 samples per lane expression between the single fiber and the whole on a NextSeq500, and an average of 35 million muscle conclusively sHows tHat tHe RNA unique reads when multiplexing 10 samples per sequenced came from a myofiber alone. (Figure lane. THis corresponds to an average overall 4A). For further confirmation, we also display alignment of 82.42%, with an average unique Ckm, the muscle
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