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. 2019 Sep 24;6:179. doi: 10.1038/s41597-019-0185-4

Longitudinal RNA-Seq analysis of acute and chronic neurogenic skeletal muscle atrophy

Jeffrey T Ehmsen 1, Riki Kawaguchi 2,3, Ruifa Mi 1, Giovanni Coppola 2,3, Ahmet Höke 1,
PMCID: PMC6760191  PMID: 31551418

Abstract

Skeletal muscle is a highly adaptable tissue capable of changes in size, contractility, and metabolism according to functional demands. Atrophy is a decline in mass and strength caused by pathologic loss of myofibrillar proteins, and can result from disuse, aging, or denervation caused by injury or peripheral nerve disorders. We provide a high-quality longitudinal RNA-Seq dataset of skeletal muscle from a cohort of adult C57BL/6J male mice subjected to tibial nerve denervation for 0 (baseline), 1, 3, 7, 14, 30, or 90 days. Using an unbiased genomics approach to identify gene expression changes across the entire longitudinal course of muscle atrophy affords the opportunity to (1) establish acute responses to denervation, (2) detect pathways that mediate rapid loss of muscle mass within the first week after denervation, and (3) capture the molecular phenotype of chronically atrophied muscle at a stage when it is largely resistant to recovery.

Subject terms: Somatic system, Regeneration and repair in the nervous system


Measurement(s) skeletal muscle atrophy • gene expression
Technology Type(s) RNA sequencing
Factor Type(s) denervation status • denervation duration
Sample Characteristic - Organism Mus musculus

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.9751892

Background & Summary

Skeletal muscle atrophy is the loss of muscle mass and function that occurs in response to diverse stimuli including disuse/immobility, glucocorticoid treatment, cancer, aging, and denervation15. Biologically, atrophy reflects the active loss of skeletal muscle contractile proteins, leading to loss of strength and functional impairment with substantial impact on quality of life and, in some cases, reduced survival68. In addition, chronically denervated, atrophied muscle shows impaired capacity for reinnervation and functional recovery, which significantly limits prospects for recovery in settings of chronic neuromuscular disease, delayed repair, or large nerve lesions912.

Nerve-evoked contraction is the most important factor for maintaining or regaining muscle mass and force13. Neurogenic atrophy refers specifically to skeletal muscle atrophy resulting from denervation, as may occur in traumatic injury or diseases that affect the peripheral nervous system, such as amyotrophic lateral sclerosis (ALS)1417. A number of “atrogenes” are induced as a result of denervation and in response to various triggers of muscle atrophy; among these are specific ubiquitin ligases targeting components of the sarcomere1829. A comprehensive analysis of the global gene pathways that change in response to denervation and during atrophy may offer an optimal chance of identifying means to pharmacologically maintain or increase muscle mass and function in atrophy-associated disease states.

We provide here a comprehensive RNA-Seq dataset30 to identify gene expression changes across the entire longitudinal course of muscle atrophy, affording the opportunity to (1) establish acute responses to denervation within the first day, (2) detect pathways that mediate rapid proteolysis and loss of muscle mass within the first week after denervation, and (3) capture the molecular phenotype of chronically atrophied muscle (weeks to months after denervation) at a stage when it is largely resistant to reinnervation and recovery.

We generated a longitudinal RNA-Seq dataset from a cohort of adult (8-week-old) wild type C57BL/6 J male mice denervated for 0 (baseline), 1, 3, 7, 14, 30, or 90 days (n = 4 for each timepoint)30. We elected to use tibial nerve transection as a model for muscle denervation, as this approach is physiologically meaningful while limiting the morbidity (i.e., pain and immobility) associated with complete sciatic nerve transection31. The tibial nerve is the largest branch of the sciatic nerve that supplies skeletal muscles of the posterior compartment of the lower limb, including the gastrocnemius and soleus. In brief, we identified and separated the tibial nerve from other branches of the sciatic nerve, then ligated, cut distally, and sutured the proximal stump in place to prevent muscle reinnervation during chronic studies. We have established that this model reliably induces significant gastrocnemius atrophy within one week after denervation, with atrophy becoming progressively more severe over time (Fig. 1c,d).

Fig. 1.

Fig. 1

Overview of the experimental procedure. The tibial nerve, the largest branch of the sciatic nerve, supplies the gastrocnemius muscle and other muscles of the lower limb posterior compartment. In our mouse model of denervation atrophy, the sciatic nerve is identified, and its branches separated to isolate the tibial nerve (a; nerve identities are as follows: 1, sural nerve; 2, tibial nerve; 3, common peroneal/fibular nerve; 4, sciatic nerve). We generated a cohort of C57BL/6 J male mice denervated for 0, 1, 3, 7, 14, 30, or 90 days (b,c). Significant atrophy is apparent by 7 days after denervation, with consistent decline in mass during chronic denervation (d); ***P < 0.001 compared to baseline.

The samples collected and described in this manuscript include transcriptional profiles from a total of 28 denervated gastrocnemii and 28 contralateral (paired) intact gastrocnemii, comprising 4 denervated and 4 contralateral (paired) intact gastrocnemii for each of 7 denervation durations [0 (baseline), 1, 3, 7, 14, 30, and 90 days]30. All specimens were generated from a cohort of male C57BL/6 J mice that were 8 weeks of age at the start of the study. These data provide a comprehensive description of baseline gene expression in adult mouse skeletal muscle and a broad assessment of the acute and longitudinal gene expression changes in atrophying muscle associated with denervation.

Methods

Animal husbandry

8-week-old C57BL/6 J male mice (Stock #000664) were obtained from the Jackson Laboratory (Bar Harbor, ME) and randomized into 7 groups of n = 4 mice per group for the following denervation timepoints: 0, 1, 3, 7, 14, 30, and 90 days. Animal subjects were housed in a controlled environment with a 12:12-h light-dark cycle with ad libitum access to water and food (Envigo 2018 SX). All mouse experiments were carried out under protocols approved by the JHU Animal Care and Use Committee.

Tibial nerve denervation surgery

Mice were anesthetized with 1.5% isoflurane/2% oxygen using a VetEquip inhalation system (Livermore, CA). The left hindlimb was shaved and sterilized, and a 1 cm incision was introduced in the skin overlying the dorsal thigh. Myofascial planes were gently separated to reveal the sciatic nerve. The tibial nerve branch was identified at its distal branch point and gently separated from the sciatic and peroneal nerves, then ligated proximally and distally using a 10-0 polyamide monofilament suture. The tibial nerve was then transected, the nerve length between ligatures carefully resected, and the proximal stump sutured to the biceps femoris muscle to prevent distal reinnervation. The incision was then closed using stainless steel wound clips. Mice were monitored for recovery from anesthesia and then returned to their home cages.

Myofiber morphometry

Gastrocnemii were frozen in O.C.T. in liquid nitrogen-cooled isopentane, then sectioned at 10 μm. Mid-belly transverse sections were blocked with M.O.M. in PBS (1:40 dilution, Vector Laboratories, catalogue #MKB-2213) at room temperature for 1 h, then incubated overnight at 4 °C with a mixture of BA-D5 supernatant (1:100, myosin heavy chain type I, SC-71 supernatant (1:100, myosin heavy chain type IIa), BF-F3 concentrate (1:100, myosin heavy chain type IIb) [all from the Developmental Studies Hybridoma Bank (DSHB)], and rat-anti-laminin (1:1000, Sigma, catalogue #L0663) in 1% BSA/PBS. Sections were then washed 3 × 5 min in PBS and incubated with a mixture of the following secondary antibodies (all at 1:500) for 2 h at room temperature: goat-anti-mouse IgG2b-DyLight-405, IgG1-Alexa Fluor-488, IgM-Alexa Fluor-594 (all from Jackson ImmunoResearch, catalogue numbers 115-475-207, 115-545-205, and 115-585-075, respectively), and goat anti-rat-IgG-Alexa Fluor-647 (Thermo Fisher Scientific, catalogue #A-21247), diluted in 1% BSA/PBS. Sections were washed 3 × 5 min in PBS and coverslipped using Prolong Gold antifade (Thermo Fisher Scientific, catalogue #P36930). Transverse sections were imaged in their entirety using a Zeiss AxioObserver. Myofiber minimum Feret diameters were determined using Fiji (NIH)32, with ~100 randomly selected myofibers of each fiber type (type I, II, or IIa) measured from each of 3 biological replicates for each indicated timepoint. Statistical analysis was performed using Stata v. 11.2 (College Station, TX)33.

RNA Isolation

Skeletal muscle was homogenized in TRIzol (Ambion, catalogue #15596018) using RNase-free stainless steel beads (Next Advance, catalogue #SSB02-RNA). Homogenates were centrifuged at 10,000 rpm at 4 °C for 10 min to pellet debris, and RNA was purified from the TRIzol supernatant using a Direct-Zol RNA mini purification kit with on-column DNase digestion (Zymo Research, catalogue #R2072). RNA integrity (RIN) was assayed using an Agilent 2100 Bioanalyzer.

RNA-Seq library preparation, sequencing, and bioinformatics analysis

RNA-sequencing was carried out using TrueSeq RiboZero gold (stranded) kit (Illumina, catalogue #20020597). Libraries were indexed and sequenced over 18 lanes using HiSeq4000 (Illumina) with 69-bp paired end reads. Quality control (QC) was performed on base qualities and nucleotide composition of sequences using FastQC version 0.11.534, to identify problems in library preparation or sequencing. Sequence quality for the dataset described here was sufficient that no reads were trimmed or filtered before input to the alignment stage. Paired-end reads were aligned to the most recent Mus musculus mm10 reference genome (GRCm38.75) using the STAR spliced read aligner (version 2.4.0)35. Average input read counts were 58.0 M per sample (range 39.1 M to 91.0 M) and average percentage of uniquely aligned reads was 81.9% (range 72.3% to 88.6%). Total counts of read-fragments aligned to known gene regions within the mouse (mm10) refSeq (refFlat version 07.24.14) reference annotation were used as the basis for quantification of gene expression. Fragment counts were derived using HTSeq (version 0.6.0) and the mm10 refSeq transcript model36. Low count transcripts were filtered, and count data were normalized using the method of trimmed mean of M-values (TMM)37 followed by removing unwanted variation using Bioconductor package RUVseq38 with k value of 1. Differentially expressed genes (FDR < 0.1) were then identified using the Bioconductor package limma with voom function to estimate mean-variance relationship, followed by empirical Bayes moderation3941. Pairwise comparisons between denervated and contralateral intact muscle at each timepoint were used as the basis for model contrasts. All bioinformatics analyses were conducted using R version 3.5.142.

Data Records

Sequencing data in the fastq format have been deposited in NCBI Sequence Read Archive (SRA)30. A metadata table (Supplementary Table S1) is available with details for each sample.

Technical Validation

Reproducible skeletal muscle atrophy using tibial nerve denervation model

Tibial nerve denervation resulted in a reliable time-dependent loss of skeletal muscle mass, with a significant difference in mass between denervated and contralateral intact gastrocnemii detected by day 7 post-denervation (Fig. 1c,d). All mice used in this study entered the cohort at the same time, with sequential denervation according to the designated timepoints, to remove age as a potential confounding variable. Mouse gastrocnemius contains a mixed population of myofiber types including so-called slow twitch myofibers (type I) and fast twitch myofibers (type IIa and IIb). After muscle denervation, all three of these myofiber populations showed a significant reduction in size as measured by minimum Feret diameter, with the most substantial rate of individual myofiber atrophy occurring within the first two weeks post-denervation (Fig. 2). Type IIb myofibers, the most abundant myofiber type in mouse gastrocnemius, showed the largest magnitude of atrophy (Fig. 2f). Multiple linear regression with myofiber type, myofiber type-time interactions, and time modeled with a spline at t = 14 days was used to model rates of atrophy among type I, IIa, and IIb myofibers; bootstrapping was used to estimate standard errors. Results are presented in Table 1.

Fig. 2.

Fig. 2

Gastrocnemius myofiber morphometry. Atrophy of type I, IIa, and IIb myofibers was analyzed by assessment of minimum Feret diameter at baseline (t = 0 days) and 7, 14, 30, and 72 days post-denervation. All three myofiber types showed significant atrophy within the first week after denervation, with the greatest change in magnitude observed for type IIb myofibers overall. Scale bar, 100 μm.

Table 1.

Myofiber type-dependent atrophy during acute and chronic denervation.

0–14 days denervation Δ minimum Feret diameter (μm/day) standard error (μm/day) 95% CI P (compared to type IIb)
type IIb −3.03 0.07 −3.16, −2.89
  IIa −0.80 0.04 −0.90, −0.71 <0.0001
  I −1.24 0.06 −1.36, −1.13 <0.0001
>14 days denervation
type IIb −0.17 0.01 −0.19, −0.15
  IIa −0.11 0.01 −0.14, −0.09 <0.0001
  I −0.09 0.01 −0.11, −0.06 <0.0001

RNA quality control

RNA integrity was analyzed using an Agilent 2100 Bioanalyzer (Fig. 3). The mean RNA Integrity Number (RIN) for RNA isolated from denervated and contralateral intact gastrocnemii was 7.8 ± 0.3 and 8.3 ± 0.1 (mean ± SEM), respectively, with no significant difference in RIN by denervation status.

Fig. 3.

Fig. 3

RNA integrity of samples. Following denervation for the designated durations, denervated and contralateral intact gastrocnemii were harvested and homogenized directly in TRIzol, and total RNA was column-purified. RNA samples were reverse-transcribed to cDNA and sequenced on an Illumina platform. Representative RIN tracings from one biological replicate of the cohort, showing total RNA isolated from intact gastrocnemii (a) and paired contralateral denervated gastrocnemii (b). RNA isolated from denervated and intact muscle showed similar quality (c).

Read quality and base-calling accuracy

Read quality was high with Phred quality score >70 for the majority of the cycles, and lower quartile base qualities were generally high (Fig. 4). No reads or samples necessitated exclusion based on read quality. The nucleotide composition patterns (proportions of A/C/G/T) of all samples were as expected, with nearly uniform proportions of each nucleotide across sequencing cycles (with the exception of a non-random pattern of nucleotide proportions in the first 13 sequencing cycles as a result of random hexamer priming) (Fig. 5). No read trimming or filtering was required because the quality distribution and variance appeared normal across all reads and samples.

Fig. 4.

Fig. 4

Read quality. Representative distribution of Phred quality scores at each nucleotide, shown for the paired reads of one biological replicate for contralateral intact (a) and denervated (b) muscle. The boxes indicate the mean, median, and lower and upper quartile.

Fig. 5.

Fig. 5

Alignment quality. Representative distribution of A (red), C (yellow), G (green), and T (blue) at each nucleotide, shown for the paired reads of one biological replicate for contralateral intact (a) and denervated (b) muscle.

Alignment quality

A summary of alignment statistics for all samples is provided in Tables 29. Similar sequencing depths and mapping rates were observed for the denervated and contralateral intact skeletal muscle samples.

Table 3.

Day 0 (baseline) alignments.

CTL-0-1 CTL-0-2 CTL-0-3 CTL-0-4 DN-0-1 DN-0-2 DN-0-3 DN-0-4
Number of input reads 55,742,415 55,520,609 55,035,747 63,030,555 61,655,193 46,879,302 68,278,353 90,993,687
Average input read length 138 138 138 138 138 138 138 138
Number of uniquely mapped reads 44,288,330 42,269,606 46,785,173 52,763,039 49,365,745 36,068,973 56,573,593 65,791,821
Uniquely mapped reads (%) 79.45 76.13 85.01 83.71 80.07 76.94 82.86 72.30
Average mapped length 137.29 136.1 137.64 137.57 137.2 137.61 137.61 135.93
Number of splices: Total 13,449,628 11,337,800 17,752,380 19,213,536 13,937,303 15,460,977 23,318,214 22,103,629
Number of splices: Annotated (sjdb) 13,279,964 11,188,952 17,562,687 18,981,111 13,722,595 15,257,243 23,063,152 21,856,608
Number of splices: GT/AG 13,338,075 11,231,532 17,622,780 19,059,810 13,811,905 15,337,675 23,148,268 21,924,998
Number of splices: GC/AG 79,141 70,961 100,965 116,597 83,254 93,607 131,002 128,493
Number of splices: AT/AC 6,613 5,470 7,814 8,779 7,204 7,569 10,127 10,049
Number of splices: Non-canonical 25,799 29,837 20,821 28,350 39,940 22,126 28,817 40,089
Mismatch rate per base (%) 0.32 0.64 0.19 0.21 0.31 0.22 0.19 0.68
Deletion rate per base (%) 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.01
Deletion average length 1.84 2.66 1.55 1.59 1.65 1.46 1.56 2.78
Insertion rate per base (%) 0.01 0.03 0.00 0.00 0.01 0.00 0.00 0.03
Multi-Mapping Reads:
Number of reads mapped to multiple loci 7,297,246 6,213,049 5,623,293 6,892,906 7,920,730 7,915,620 7,813,515 12,905,331
% of reads mapped to multiple loci 13.09 11.19 10.22 10.94 12.85 16.89 11.44 14.18
Number of reads mapped to too many loci 582,753 255,211 341,804 568,680 987,746 539,784 463,089 172,576
Unmapped Reads:
% of reads unmapped: too many mismatches 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
% of reads unmapped: too short 5.63 11.82 3.69 3.95 4.63 4.62 4.66 13.22

Table 4.

Day 1 post-denervation alignments.

CTL-1-1 CTL-1-2 CTL-1-3 CTL-1-4 DN-1-1 DN-1-2 DN-1-3 DN-1-4
Number of input reads 61,636,872 58,072,077 55,973,096 71,794,344 58,034,876 48,989,931 73,886,622 74,271,951
Average input read length 138 138 138 138 138 138 138 138
Number of uniquely mapped reads 45,746,325 47,654,856 48,094,866 58,843,890 48,750,120 39,908,061 62,480,235 56,047,037
Uniquely mapped reads (%) 74.22 82.06 85.92 81.96 84.00 81.46 84.56 75.46
Average mapped length 137.34 137.47 137.57 137.6 137.62 137.59 137.57 136.25
Number of splices: Total 9,070,911 16,321,200 18,716,287 24,549,738 17,994,490 13,613,414 23,080,273 17,817,564
Number of splices: Annotated (sjdb) 8,836,384 16,122,233 18,519,783 24,297,361 17,785,158 13,408,135 22,808,431 17,582,261
Number of splices: GT/AG 8,966,851 16,190,887 18,583,614 24,365,743 17,858,255 13,494,722 22,900,176 17,663,375
Number of splices: GC/AG 50,713 96,907 103,605 141,926 103,877 83,585 134,880 108,178
Number of splices: AT/AC 4,255 7,466 8,267 11,276 8,327 6,878 11,030 8,758
Number of splices: Non-canonical 49,092 25,940 20,801 30,793 24,031 28,179 34,187 37,253
Mismatch rate per base (%) 0.40 0.26 0.23 0.17 0.19 0.25 0.21 0.63
Deletion rate per base 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.01
Deletion average length 1.37 1.63 1.84 1.71 1.49 1.45 1.66 2.4
Insertion rate per base 0.00 0.01 0.00 0.01 0.00 0.00 0.00 0.02
Multi-Mapping Reads:
Number of reads mapped to multiple loci 9,782,705 6,777,446 5,377,772 8,642,605 6,176,521 5,844,014 7,396,719 9,668,787
% of reads mapped to multiple loci 15.87 11.67 9.61 12.04 10.64 11.93 10.01 13.02
Number of reads mapped to too many loci 1,984,894 619,936 341,393 194,108 530,916 812,052 596,417 413,918
Unmapped Reads:
% of reads unmapped: too many mismatches 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
% of reads unmapped: too short 5.12 4.55 3.44 5.55 3.79 4.17 4.13 10.71

Table 5.

Day 3 post-denervation alignments.

CTL-3-1 CTL-3-2 CTL-3-3 CTL-3-4 DN-3-1 DN-3-2 DN-3-3 DN-3-4
Number of input reads 43,601,767 39,051,346 60,982,532 77,529,167 61,614,609 48,980,170 77,233,032 49,001,916
Average input read length 138 138 138 138 138 138 138 138
Number of uniquely mapped reads 32,795,169 31,708,280 51,656,264 58,276,505 48,300,398 40,533,615 67,261,853 40,543,472
Uniquely mapped reads (%) 75.22 81.20 84.71 75.17 78.39 82.76 87.09 82.74
Average mapped length 137.18 137.54 137.63 136.29 137.27 137.61 137.58 137.7
Number of splices: Total 7,641,732 14,023,149 19,917,676 20,730,824 12,188,893 15,689,660 23,843,242 18,125,528
Number of splices: Annotated (sjdb) 7,481,956 13,875,662 19,704,844 20,503,659 11,912,730 15,485,355 23,536,888 17,920,443
Number of splices: GT/AG 7,559,269 13,909,110 19,774,059 20,569,914 12,051,290 15,551,272 23,642,787 17,982,044
Number of splices: GC/AG 44,922 89,610 110,632 117,092 76,969 104,920 151,795 114,053
Number of splices: AT/AC 3,751 6,827 8,919 9,864 8,217 10,333 14,859 11,510
Number of splices: Non-canonical 33,790 17,602 24,066 33,954 52,417 23,135 33,801 17,921
Mismatch rate per base (%) 0.37 0.18 0.18 0.57 0.35 0.20 0.21 0.15
Deletion rate per base 0.00 0.00 0.00 0.01 0.01 0.00 0.00 0.00
Deletion average length 1.45 1.93 1.54 2.64 1.41 1.76 1.74 1.65
Insertion rate per base 0.00 0.01 0.00 0.02 0.00 0.00 0.00 0.00
Multi-Mapping Reads:
Number of reads mapped to multiple loci 5,971,134 4,893,812 6,531,891 10,323,333 8,224,640 5,219,448 6,412,447 6,047,917
% of reads mapped to multiple loci 13.69 12.53 10.71 13.32 13.35 10.66 8.30 12.34
Number of reads mapped to too many loci 1,070,563 150,149 453,705 168,949 1,656,313 391,356 516,587 143,641
Unmapped Reads:
% of reads unmapped: too many mismatches 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
% of reads unmapped: too short 7.35 5.56 3.28 11.17 4.33 5.33 3.35 4.41

Table 6.

Day 7 post-denervation alignments.

CTL-7-1 CTL-7-2 CTL-7-3 CTL-7-4 DN-7-1 DN-7-2 DN-7-3 DN-7-4
Number of input reads 60,590,610 56,143,558 52,019,275 51,496,201 59,955,862 52,135,014 56,347,860 49,238,405
Average input read length 138 138 138 138 138 138 138 138
Number of uniquely mapped reads 44,746,349 45,413,965 43,059,558 41,428,228 48,787,077 44,968,959 48,225,333 41,382,042
Uniquely mapped reads (%) 73.85 80.89 82.78 80.45 81.37 86.25 85.59 84.04
Average mapped length 137.59 137.52 137.55 137.52 137.54 137.62 137.62 137.71
Number of splices: Total 14,703,980 16,917,306 15,994,824 19,253,856 18,108,367 17,195,995 19,296,266 17,537,132
Number of splices: Annotated (sjdb) 14,509,688 16,698,117 15,827,806 19,075,521 17,848,555 16,979,726 19,078,139 17,331,026
Number of splices: GT/AG 14,581,736 16,782,958 15,879,431 19,119,493 17,951,606 17,055,436 19,144,656 17,402,247
Number of splices: GC/AG 87,629 94,175 90,057 109,413 113,654 107,871 121,143 107,129
Number of splices: AT/AC 6,982 7,259 6,713 8,335 11,444 10,331 10,951 10,114
Number of splices: Non-canonical 27,633 32,914 18,623 16,615 31,663 22,357 19,516 17,642
Mismatch rate per base (%) 0.23 0.25 0.24 0.20 0.21 0.19 0.23 0.16
Deletion rate per base 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Deletion average length 1.46 1.6 1.55 1.66 1.5 1.68 1.61 1.58
Insertion rate per base 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00
Multi-Mapping Reads:
Number of reads mapped to multiple loci 9,428,246 6,672,205 5,740,042 6,966,763 7,352,327 4,543,202 5,722,848 5,194,049
% of reads mapped to multiple loci 15.56 11.88 11.03 13.53 12.26 8.71 10.16 10.55
Number of reads mapped to too many loci 819,014 789,365 391,842 166,663 716,324 332,671 233,636 243,367
Unmapped Reads:
% of reads unmapped: too many mismatches 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
% of reads unmapped: too short 8.41 5.23 4.83 5.53 4.51 3.91 3.51 4.58

Table 7.

Day 14 post-denervation alignments.

CTL-14-1 CTL-14-2 CTL-14-3 CTL-14-4 DN-14-1 DN-14-2 DN-14-3 DN-14-4
Number of input reads 49,441,646 69,876,924 57,832,497 47,973,299 55,891,429 44,966,509 59,715,016 54,942,368
Average input read length 138 138 138 138 138 138 138 138
Number of uniquely mapped reads 36,913,926 57,899,595 48,950,623 38,979,826 46,402,585 39,850,074 51,086,876 47,212,433
Uniquely mapped reads (%) 74.66 82.86 84.64 81.25 83.02 88.62 85.55 85.93
Average mapped length 136.42 137.57 137.64 137.71 137.43 137.6 137.26 137.64
Number of splices: Total 5,674,228 21,316,991 17,945,548 18,202,915 14,603,778 13,578,938 17,163,851 19,981,473
Number of splices: Annotated (sjdb) 5,507,058 21,070,682 17,756,782 18,029,158 14,378,276 13,404,598 16,946,761 19,745,905
Number of splices: GT/AG 5,594,717 21,157,480 17,811,041 18,071,861 14,465,582 13,467,591 17,016,218 19,822,262
Number of splices: GC/AG 33,738 117,529 105,892 108,309 97,389 86,275 114,337 126,876
Number of splices: AT/AC 2,460 8,933 7,681 8,376 8,415 7,229 9,540 11,690
Number of splices: Non-canonical 43,313 33,049 20,934 14,369 32,392 17,843 23,756 20,645
Mismatch rate per base (%) 0.66 0.22 0.19 0.15 0.23 0.21 0.30 0.17
Deletion rate per base 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Deletion average length 1.96 1.53 1.49 1.54 1.6 1.73 1.77 1.81
Insertion rate per base 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Multi-Mapping Reads:
Number of reads mapped to multiple loci 6,729,802 8,099,802 6,448,816 6,968,357 5,711,963 3,266,255 5,086,857 5,109,283
% of reads mapped to multiple loci 13.61 11.59 11.15 14.53 10.22 7.26 8.52 9.30
Number of reads mapped to too many loci 1,288,797 704,083 369,246 131,113 711,573 285,356 277,105 152,218
Unmapped Reads:
% of reads unmapped: too many mismatches 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
% of reads unmapped: too short 7.92 3.98 2.99 3.77 4.72 2.93 4.97 4.27

Table 8.

Day 30 post-denervation alignments.

CTL-30-1 CTL-30-2 CTL-30-3 CTL-30-4 DN-30-1 DN-30-2 DN-30-3 DN-30-4
Number of input reads 52,742,878 46,463,403 57,501,219 60,468,553 73,590,727 48,399,322 51,665,579 54,577,655
Average input read length 138 138 138 138 138 138 138 138
Number of uniquely mapped reads 40,308,924 38,146,896 48,521,247 49,438,872 58,520,852 41,879,303 45,337,494 46,751,912
Uniquely mapped reads (%) 76.43 82.10 84.38 81.76 79.52 86.53 87.75 85.66
Average mapped length 137.26 137.46 137.68 137.65 137.6 137.5 137.65 137.55
Number of splices: Total 9,002,164 12,162,162 17,453,824 21,318,005 19,800,202 14,238,822 17,245,138 17,175,362
Number of splices: Annotated (sjdb) 8,779,541 11,999,102 17,264,634 21,090,387 19,528,567 14,056,750 17,044,059 16,948,110
Number of splices: GT/AG 8,902,807 12,063,473 17,319,770 21,157,409 19,623,217 14,122,315 17,105,745 17,027,539
Number of splices: GC/AG 50,013 69,863 105,703 125,956 132,947 88,561 112,478 111,959
Number of splices: AT/AC 4,129 5,439 7,989 9,587 11,133 6,876 8,957 9,017
Number of splices: Non-canonical 45,215 23,387 20,362 25,053 32,905 21,070 17,958 26,847
Mismatch rate per base (%) 0.41 0.34 0.18 0.18 0.21 0.23 0.16 0.22
Deletion rate per base 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Deletion average length 1.35 1.54 1.52 1.54 1.59 2.1 1.61 1.85
Insertion rate per base 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.01
Multi-Mapping Reads:
Number of reads mapped to multiple loci 7,401,284 5,478,248 6,190,600 8,046,293 8,580,950 4,181,432 4,632,180 5,281,885
% of reads mapped to multiple loci 14.03 11.79 10.77 13.31 11.66 8.64 8.97 9.68
Number of reads mapped to too many loci 1,771,867 704,627 353,874 396,886 672,558 312,239 158,758 369,051
Unmapped Reads:
% of reads unmapped: too many mismatches 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
% of reads unmapped: too short 4.84 3.82 3.70 3.98 7.27 3.68 2.63 3.59

Table 2.

Overall summary of alignments.

CTL DN P
(DN vs. CTL)*
Mean (SD),
range
Mean (SD),
range
Number of input reads

5.71 × 107 (8.50 × 106)

3.91 × 107–7.75 × 107

5.90 × 107 (1.15 × 107)

4.15 × 107–9.10 × 107

0.49
Average input read length 138 138
Number of uniquely mapped reads

4.6 × 107 (7.29 × 106)

3.17 × 107–5.88 × 107

4.89 × 107 (8.40 × 106)

3.57 × 107–6.73 × 107

0.17
Uniquely mapped reads (%)

80.47 (3.75)

73.85–85.92

83.29 (3.99)

72.3–88.62

0.009
Average mapped length

137.39 (0.42)

136.10–137.71

137.45 (0.41)

135.93–137.71

0.58
Number of splices: Total

1.62 × 107 (4.93 × 106)

5.67 × 106–2.45 × 107

1.72 × 107 (3.35 × 106)

1.00 × 107–2.38 × 107

0.37
Number of splices: Annotated (sjdb)

1.60 × 107 (4.91 × 106)

5.51 × 106–2.43 × 107

1.70 × 107 (3.33 × 106)

9.86 × 106–2.35 × 107

0.38
Number of splices: GT/AG

1.61 × 107 (4.90 × 106)

5.59 × 106–2.44 × 107

1.71 × 107 (3.33 × 106)

9.92 × 106–2.36 × 107

0.38
Number of splices: GC/AG

9.38 × 104 (2.83 × 104)

3.37 × 104–1.42 × 105

1.09 × 105 (13.37 × 104)

7.05 × 104–1.52 × 105

0.03
Number of splices: AT/AC

7.31 × 103 (2.18 × 103)

2.46 × 103–1.13 × 104

9.38 × 103 (1.95 × 103)

5.41 × 103–1.49 × 104

0.0004
Number of splices: Non-canonical

2.79 × 104 (8.77 × 103)

1.44 × 104–4.91 × 104

2.77 × 104 (8.62 × 103)

1.76 × 104–5.24 × 104

0.92
Mismatch rate per base (%)

0.28 (0.14)

0.15–0.66

0.25 (0.12)

0.15–0.68

0.32
Deletion rate per base (%)

0.002 (0.004)

0–0.01

0.001 (0.004)

0–0.01

0.49
Deletion average length

1.68 (0.32)

1.35–2.66

1.72 (0.29)

1.41–2.78

0.65
Insertion rate per base (%)

0.005 (0.008)

0–0.03

0.003 (0.007)

0–0.03

0.38
Multi-Mapping Reads:
Number of reads mapped to multiple loci

7.09 × 106 (1.34 × 106)

4.89 × 106–1.03 × 107

6.32 × 106 (2.01 × 106)

3.27 × 106–1.29 × 107

0.10
% of reads mapped to multiple loci

12.46 (1.65)

9.61–15.87

10.64 (2.15)

7.26–16.89

0.0008
Number of reads mapped to too many loci

6.16 × 105 (4.96 × 105)

1.31 × 105–1.98 × 106

4.85 × 105 (3.25 × 105)

1.45 × 105–1.66 × 106

0.25
Unmapped Reads:
% of reads unmapped: too many mismatches 0 0
% of reads unmapped: too short

5.32 (2.21)

2.99–11.82

4.71 (2.29)

2.63–13.22

0.32

*Welch’s t-test.

Table 9.

Day 90 post-denervation alignments.

CTL-90-1 CTL-90-2 CTL-90-3 CTL-90-4 DN-90-1 DN-90-2 DN-90-3 DN-90-4
Number of input reads 60,873,629 47,878,309 64,409,589 64,474,030 67,574,028 41,457,417 56,366,231 64,290,975
Average input read length 138 138 138 138 138 138 138 138
Number of uniquely mapped reads 48,591,921 36,558,406 54,742,091 52,310,648 55,842,215 35,688,427 49,296,566 56,228,095
Uniquely mapped reads (%) 79.82 76.36 84.99 81.13 82.64 86.08 87.46 87.46
Average mapped length 137.54 137.33 137.65 137.54 137.46 137.62 137.69 137.56
Number of splices: Total 17,976,086 9,096,031 19,807,129 23,581,453 14,738,624 10,009,836 16,531,735 17,148,016
Number of splices: Annotated (sjdb) 17,769,205 8,892,794 19,598,023 23,349,415 14,498,430 9,862,716 16,325,792 16,910,940
Number of splices: GT/AG 17,834,684 9,003,295 19,661,022 23,405,840 14,592,638 9,915,222 16,382,464 16,990,053
Number of splices: GC/AG 108,126 48,499 114,242 134,946 101,005 70,463 117,425 118,687
Number of splices: AT/AC 8,761 3,781 8,574 10,432 7,968 5,410 9,247 9,501
Number of splices: Non-canonical 24,515 40,456 23,291 30,235 37,013 18,741 22,599 29,775
Mismatch rate per base (%) 0.20 0.41 0.19 0.19 0.25 0.21 0.17 0.22
Deletion rate per base 0.00 0.01 0.00 0.00 0.01 0.00 0.00 0.00
Deletion average length 1.75 1.37 1.52 1.96 1.61 1.55 1.67 1.88
Insertion rate per base 0.01 0.00 0.00 0.01 0.01 0.00 0.00 0.00
Multi-Mapping Reads:
Number of reads mapped to multiple loci 7,924,888 7,093,313 6,681,303 8,439,457 6,752,769 3,853,430 5,037,828 5,238,591
% of reads mapped to multiple loci 13.02 14.82 10.37 13.09 9.99 9.29 8.94 8.15
Number of reads mapped to too many loci 469,250 1,545,968 447,456 176,878 855,527 419,702 172,340 444,439
Unmapped Reads:
% of reads unmapped: too many mismatches 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
% of reads unmapped: too short 5.92 4.16 3.34 5.34 5.23 2.77 2.88 3.10

Counts per gene

The distribution of normalized gene accounts appears similar among all samples in the dataset (Fig. 6).

Fig. 6.

Fig. 6

Summary of read counts. Density plot showing relative read count distributions for all samples.

Unsupervised clustering analysis of longitudinally denervated samples

Multidimensional scaling using expression levels of all genes demonstrated temporal clustering based on denervation status, with replicates within each denervation timepoint clustering closer to each other than to other denervation timepoints (Fig. 7).

Fig. 7.

Fig. 7

Quality of replicates. Multi-dimensional scaling analysis (a) and cluster dendrogram (b) of transcriptional profiles during neurogenic atrophy shows temporal clustering by denervation status.

Time-dependent comparison of denervated and contralateral intact skeletal muscle transcriptomes

Normalized gene counts from denervated and contralateral intact skeletal muscle at each timepoint are compared in scatter plots (Fig. 8).

Fig. 8.

Fig. 8

Gene expression visualization. Scatterplots showing the log2 transform of normalized counts.

Differential expression analysis

MA-plots showing the log-fold change (M-values, the log of the ratio of counts for each gene across the two samples being compared) against the normalized log-average (A-values, the average counts for each gene across the two samples being compared) indicate substantial differences in gene expression in skeletal muscle during acute and chronic neurogenic atrophy (Fig. 9a–g). Volcano plots indicate minimal differences in gene expression at baseline (intact muscle) (Fig. 9h), but demonstrate that thousands of genes are significantly differentially expressed (FDR < 0.1) within the first day after denervation (Fig. 9i) and beyond (Fig. 9j–n). A summary of the number of differentially expressed genes at each timepoint is shown in Fig. 9o.

Fig. 9.

Fig. 9

Differential expression analysis. MA-plots comparing the log2 fold change of gene expression for denervated vs. contralateral intact skeletal muscle at each timepoint plotted against the normalized average of the counts (ag). Volcano plots showing the -log10 FDR for difference in expression between denervated and contralateral intact skeletal muscle for each gene detected, plotted against the log2 fold-change (hn). Genes with FDR < 0.1 are depicted in red. The total number of significantly differentially expressed genes (FDR < 0.1) at each timepoint is summarized in panel (o).

Usage Notes

The RNA-Seq dataset presented in this study provides a detailed view of the acute and chronic gene expression changes that occur in denervated, atrophying skeletal muscle. These data may provide insight into the early events associated with acute loss of neuronal input that trigger rapid atrophy, as well as the gene expression changes in chronically denervated and severely atrophied skeletal muscle associated with impaired capacity for reinnervation. Defining these changes may afford opportunities to limit the rate and severity of skeletal muscle atrophy, and to enhance functional reinnervation.

Supplementary Information

Supplementary Table 1 (108.5KB, pdf)

Acknowledgements

We thank the Next Generation Sequencing Core Facility at JHMI for assistance with Bioanalyzer analysis, the UCLA Neuroscience Genomics Core (UNGC) for preparing and sequencing the libraries, and Norman Barker (JHMI, Department of Pathology) for photographing Figure 1c. This work was supported by the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation (A.H. and G.C.), U.S. Department of Defense (A.H.), Maryland Stem Cell Research Fund (J.T.E.), a Burroughs Wellcome Collaborative Research Travel Grant (J.T.E.), and the National Institute of Arthritis and Musculoskeletal and Skin Diseases (J.T.E., F32AR072477). The Johns Hopkins Multiphoton Imaging Core is supported by the National Institute of Neurological Disorders and Stroke (NS050274). The myosin antibodies developed by the lab of Dr. Stefano Schiaffino were obtained from the Developmental Studies Hybridoma Bank, created by the NICHD of the NIH and maintained at the University of Iowa, Department of Biology. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Author Contributions

J.T.E., R.K., G.C., and A.H. designed the study; J.T.E., R.K., and R.M. conducted experiments; J.T.E., R.K., G.C., and A.H. analyzed data; and J.T.E. wrote the manuscript with contributions from all authors.

Code Availability

Scripts used in the RNA sequencing analyses are available at https://github.com/icnn/RNAseq-PIPELINE.git.

Competing Interests

The authors declare no competing interests.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

is available for this paper at 10.1038/s41597-019-0185-4.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Citations

  1. 2019. NCBI Sequence Read Archive. SRP196460

Supplementary Materials

Supplementary Table 1 (108.5KB, pdf)

Data Availability Statement

Scripts used in the RNA sequencing analyses are available at https://github.com/icnn/RNAseq-PIPELINE.git.


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