High-resolution analysis of differential gene expression during skeletal muscle atrophy and programmed cell death

Junko Tsuji; Travis Thomson; Elizabeth Chan; Christine K Brown; Julia Oppenheimer; Carol Bigelow; Xianjun Dong; William E Theurkauf; Zhiping Weng; Lawrence M Schwartz

doi:10.1152/physiolgenomics.00047.2020

. 2020 Sep 14;52(10):492–511. doi: 10.1152/physiolgenomics.00047.2020

High-resolution analysis of differential gene expression during skeletal muscle atrophy and programmed cell death

Junko Tsuji ¹, Travis Thomson ², Elizabeth Chan ³, Christine K Brown ³, Julia Oppenheimer ⁴, Carol Bigelow ⁵, Xianjun Dong ¹, William E Theurkauf ⁶, Zhiping Weng ^1,^✉, Lawrence M Schwartz ^3,^✉

PMCID: PMC7750511 PMID: 32926651

Abstract

Skeletal muscles can undergo atrophy and/or programmed cell death (PCD) during development or in response to a wide range of insults, including immobility, cachexia, and spinal cord injury. However, the protracted nature of atrophy and the presence of multiple cell types within the tissue complicate molecular analyses. One model that does not suffer from these limitations is the intersegmental muscle (ISM) of the tobacco hawkmoth Manduca sexta. Three days before the adult eclosion (emergence) at the end of metamorphosis, the ISMs initiate a nonpathological program of atrophy that results in a 40% loss of mass. The ISMs then generate the eclosion behavior and initiate a nonapoptotic PCD during the next 30 h. We have performed a comprehensive transcriptomics analysis of all mRNAs and microRNAs throughout ISM development to better understand the molecular mechanisms that mediate atrophy and death. Atrophy involves enhanced protein catabolism and reduced expression of the genes involved in respiration, adhesion, and the contractile apparatus. In contrast, PCD involves the induction of numerous proteases, DNA methylases, membrane transporters, ribosomes, and anaerobic metabolism. These changes in gene expression are largely repressed when insects are injected with the insect steroid hormone 20-hydroxyecdysone, which delays death. The expression of the death-associated proteins may be greatly enhanced by reductions in specific microRNAs that function to repress translation. This study not only provides fundamental new insights into basic developmental processes, it may also represent a powerful resource for identifying potential diagnostic markers and molecular targets for therapeutic intervention.

Keywords: autophagy, Manduca sexta, metamorphosis, proteasome, ubiquitin

INTRODUCTION

Skeletal muscle is the largest tissue in the human body by mass and serves as its primary reservoir of amino acids. It is highly plastic and displays dramatic increases in both mass and strength during development and in response to eccentric exercise or anabolic steroids [reviewed (25, 74)]. Conversely, it can undergo atrophy and lose both mass and strength in response to any of a number of insults that include inactivity, starvation, denervation, weightlessness, cancer cachexia, HIV infection, sepsis, glucocorticoids, or tenotomy.

Atrophy is typically a protracted process that occurs over the course of weeks to years. For example, under extreme conditions it takes 4–6 wk of muscle unloading in humans to observe a 20% loss of mass in the quadriceps femoris muscle (20). Many adults over age 50 yr experience sarcopenia and lose muscle mass at a rate of ∼1% per year. While this may not seem dramatic, it can result in an ∼40% loss of muscle mass by age 80 yr, which has significant impacts on health (23, 60).

While atrophy can be reversible, there are a number of muscle disorders that result in the actual death of the muscle fiber. Acute injury can lead to the rapid necrotic death of muscle fibers and proinflammatory responses, a process known as rhabdomyolysis (13). However, muscles can also die over a more protracted time course. For example, repeated rounds of mechanical damage and regeneration lead to a decrease in the total number of muscle fibers in Duchenne muscular dystrophy via necroptosis (68, 72). Muscle fiber death can also occur nonpathologically during aging. For example, between ages 5 and 91 yr, there is an ∼60% reduction in the number of muscle fibers in the urethral rhabdosphincter, which is highly correlated with age-dependent incontinence (91).

Animal models have been invaluable for understanding some of the molecular mechanisms that mediate skeletal muscle atrophy and death. However, there are a number of limitations inherent in this approach. The first is that skeletal muscle is a complex tissue that typically contains not only multiple muscle fiber types (e.g., fast versus slow), but also different cell types such as satellite cells, endothelial cells, fibroblasts, pericytes, and macrophages (97). Therefore, it is difficult to determine if an observed change in gene expression occurs in the muscle fiber itself or within one of the other resident cell populations. Another issue is that researchers typically employ an acute insult such as denervation to induce skeletal muscle atrophy, which may not reflect the native processes associated with more developmentally regulated processes.

As a complementary approach, we have examined the intersegmental muscles (ISMs) from the tobacco hawkmoth Manduca sexta. During metamorphosis, the ISMs undergo rapid and sequential programs of atrophy and programmed cell death (PCD) as normal components of development [reviewed in (76)]. The ISMs are organized as sheets of individual giant muscle fibers, where each syncytial cell is ∼5 mm long and up to 1 mm in diameter (55) (Supplemental Fig. S1; supplemental material available at: https://doi.org/10.6084/m9.figshare.12240878). The ISMs attach at the segmental boundaries within the abdomen and provide the major motive force for both larval crawling and for adult eclosion (emergence) at the end of metamorphosis. On day 15 of pupal-adult development, the ISMs initiate a program of atrophy that results in an ∼40% loss of muscle mass by the time the adult ecloses 3 days later at the end of day 18 (84) (Supplemental Fig. S1). Atrophy is triggered by a decline in the circulating levels of the insect molting hormone 20-hydroxyecdysone (20E), which acts as a key regulator of developmental timing at the end of metamorphosis (84). ISM atrophy occurs without overt changes in physiological properties of the muscle such as resting membrane potential or tetanic force per cross-sectional area (81). Like atrophy in mammalian models, ISM atrophy involves increased ubiquitin-dependent proteolysis (31, 80).

Late on day 18, the release of the peptide eclosion hormone (EH) acts on the nervous system to generate the eclosion motor program that helps the animal emerge from the overlying pupal cuticle (102). It also acts directly on the ISMs to trigger PCD, which takes place just in advance of lights out (∼5:30 PM in our colony) (55, 85). The muscles then die during the subsequent 30 h and are no longer detectable. ISM death represents a distinct developmental process rather than the continuation of the atrophy program (81, 84).

The timing of developmental changes during metamorphosis in Manduca is tightly controlled by circadian changes in the circulating levels of the insect molting hormone 20E (84). Judicious administration of exogenous 20E on day 15 blocks both atrophy and death, while steroid treatment on day 17 blocks death and prolongs atrophy (84). However, once either of these sequential programs has been initiated, it cannot be reversed or delayed by hormone treatment. ISM death is nonapoptotic and instead occurs via an autophagic cell death program (77, 82).

The goal of this study is to dissect the molecular pathways that regulate skeletal muscle atrophy and death during development. Our hypothesis is that while there is enhanced catabolism during both atrophy and death, the underlying molecular mechanisms that drive each of these programs are fundamentally different. Atrophy results from the coordinated loss of the contractile proteins while death involves the destruction of the contractile apparatus. Earlier studies provided the identity for a few genes that are differentially expressed during ISM development that were invaluable for providing basic insights into the underlying processes [reviewed in (22)]. However, to obtain a more complete understanding of these programs, we have performed a comprehensive and unbiased RNA-Seq analysis across ISM development to examine the expression of 20,795 genes and 418 microRNAs (miRNAs). Atrophy is associated with the repression of a number of genes, including those encoding the extracellular matrix and the contractile apparatus. Death involves the induction of a number of proteolytic pathways and a shift to anaerobic metabolism. This study provides valuable insights into these developmental processes as well as a resource for hypothesis generation of skeletal muscle atrophy and death in humans.

MATERIALS AND METHODS

Animals.

The tobacco hawkmoth M. sexta was reared and staged as described previously (84). The lateral ISMs were dissected free from adjacent tissue under ice-cold saline, flash-frozen on dry ice, and stored in liquid nitrogen until used for RNA isolation. Some animals were injected on day 17 of pupal-adult development with 25 μg of 20E (Sigma) in 10% isopropanol to delay ISM death (83), and then the ISMs removed before the normal time of eclosion on day 18.

RNA isolation, library construction, and sequencing.

The ISMs of three or four animals per stage [eight developmental stages: days 13, 14, 15, 16, 17, 18, and 1 h posteclosion (PE); plus 20E injection on day 17 (20E)] were homogenized with a Polytron (Kinematica, Bohemia, NY) with the mirVana RNA Isolation kit (Life Technologies) and total RNA was isolated. For each stage of development, three independent biological replicates were constructed with total RNA for each stage of development, analyzed with a Bioanalyzer (Agilent Technologies; Santa Clara, CA), and then subjected to 50SE RNA-Seq using an Illumina HiSeq 2000 (San Diego, CA) by Beijing Genomics Institute (Hong Kong).

For small RNA-Seq library construction, 50 μg of total RNA was fractionated via 15% urea polyacrylamide gel electrophoresis, and the 18–30 nt fraction extracted for library construction. 3′- and 5′-Adaptors were ligated to the small RNA, and the cDNA reverse transcribed and PCR amplified. The libraries were purified by polyacrylamide gel electrophoresis (PAGE) and subjected to 50-SE sequencing as above. In some cases, independent sets of libraries were constructed and sequenced by the University of Massachusetts Deep Sequencing Core Facility.

Quantitative PCR quantification.

Total RNA was isolated from the ISMs on 3 days of pupal-adult development (days 13, 16, and 18). In addition, one group of animals was injected with 25 μg of 20E on day 17 and analyzed late on day 18. mRNA from three independent biological replicates was converted to cDNA using the Superscript III First-Strand Synthesis System (Invitrogen, Carlsbad, CA) and quantified via quantitative qPCR using SYBR Select Master Mix (Applied Biosystems by Life Technologies, Carlsbad, CA) with the following primers (Supplemental Table S1).

Relative mRNA levels were compared by the ∆∆Ct method, and Renilla luciferase expression was normalized to firefly luciferase. All experiments were performed with three biological replicates and two to four technical replicates.

Genome sequence and the annotation.

We downloaded the genomic sequence of M. sexta (Msex1.0) and the transcript and the protein sequences (revised-OGS-June2012) from the Manduca Base (https://i5k.nal.usda.gov/data/Arthropoda/mansex-(Manduca_sexta)/Current%20Genome%20Assembly/2.Official%20or%20Primary%20Gene%20Set/OGS2.0/ (39). Since the gene annotation was not available in the database, we identified the genes in M. sexta with homologs in Drosophila melanogaster. We downloaded proteome data sets from UniProt (release 2013_12) (103) and mRNA sequences from FlyBase (FB2013_06) (39) as the D. melanogaster comprehensive annotations. Using the sequences in the Manduca Base as queries, we ran BLASTP, BLASTX, and BLASTN with E-value < 10⁻⁴ (BLAST+ version 2.2.28) (2) against the D. melanogaster proteome and transcriptome databases. The best BLASTP hits in D. melanogaster were assigned as the gene annotations of M. sexta. For the genes with no BLASTP hits, we assigned the best BLASTX and BLASTN hits to the gene annotations. For the genes in M. sexta that do not have any homologs in D. melanogaster, we conducted the same BLAST search with nr (version 2013/12/17) and nt (version 2013/12/16) databases downloaded from the National Center for Biotechnology Information website. The statistics of the annotated genes in M. sexta are shown in Table 1.

Table 1.

	Genes without Isoforms	Genes with Isoforms
Total input	18,841	20,795
Best BLAST hits	15,477 (82.14%)	16,965 (81.58%)
Human homologs	10,887 (57.78%)	11,903 (57.24%)
Mouse homologs	10,773 (57.18%)	11,797 (56.73%)
Fly homologs	11,968 (63.52%)	13,124 (63.11%)

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For miRNA annotation, we downloaded M. sexta miRNA (mse.gff3) annotation from miRBase v20 (41, 110). In addition, we predicted potential miRNAs with mapped small RNAs in all time points with mirDeep2 (24).

Gene expression and differentially expressed gene clusters.

For RNA-Seq libraries, we mapped all reads in the three biological replicates per stage (days 13, 14, 15, 16, 17, 18 and 20E) to the genome with TopHat2 (v2.0.10) (40) allowing two mismatches. Multiply mapped reads were apportioned by the number of times they mapped to the genome and the RPKM values for the genes were calculated.

To identify differentially expressed genes between a pair of time points during ISM development, we ran the DESeq2 (v1.5.5) (56) algorithm implemented in R using mapped read counts as the input. Transcripts with a false discovery rate (FDR) ≤ 0.01 and absolute fold-change (fc) ≥ 2 were considered to be differentially expressed.

To cluster differentially expressed genes according to their RPKM values, we performed K-mean clustering with the fpc package (v2.1-7) implemented in R (33, 34). We used correlation distance as the distance measurement and bootstrapped each parameter setting 100 times. We tested the different number of clusters, k, from 3 to 20 and selected k = 6 based on the cluster stability measurement (i.e., Jaccard index and silhouette coefficient) and biological knowledge (33, 34).

Transcription factor binding site estimation.

We extracted 1 kb upstream sequences from transcription start sites (TSSs) of all genes in M. sexta. We calculated statistically significantly enriched motifs of transcription factor binding sites (TFBSs) with Analysis of Motif Enrichment (AME version 4.9.1) (61, 62) against the extracted upstream sequences. We further analyzed the detected transcription factor (TF) hits that were differentially expressed (i.e., TFs that belong to any gene clusters) during the ISM developmental stages. To estimate the position of TFBSs, we ran Find Individual Motif Occurrences (FIMO version 4.9.1) (27) against the same set of the upstream sequences. An FDR 1 × 10⁻³ threshold was used to select statistically significant hits for the AME and FIMO analysis. For the motif models, we downloaded the motifs from the TRANScription FACtor (TRANSFAC) database release 12.1 (69 manually selected insect models) (62), JASPAR Core Insect (131 models) (61), and Fly Factor Survey (652 models for 326 genes) (111).

To investigate potential protein-protein interactions among the detected TFs, we obtained the experimental, genetic text-mining, and interolog interaction data from the STRING database (95). We searched the interactions among the detected TFs including one interaction away and drew networks with Cytoscape 3.1.1 (88).

miRNA expression and differentially expressed miRNAs.

For small RNA-Seq libraries, we computationally stripped off the 3′-adaptor sequences and mapped reads to the genome using Bowtie (v1.1.0) (45). We used only perfectly matched reads to the genome and apportioned multiply mapped reads. We computed parts per million (ppm) to estimate the abundance of the annotated and the predicted miRNAs. We calculated differentially expressed miRNAs with the same protocol used for the detection of differentially expressed genes. However, we used a different cut-off for miRNAs to define differentially expressed miRNAs (P value ≤ 0.05, fc ≥ ± 2, and ppm ≥ 10).

miRNA target prediction and enrichment analysis.

We first collected 3′-UTR (untranslated region) sequences of mRNAs from the Manduca Base. For the mRNAs that lack their 3′-UTR annotations, we predicted the 3′-UTR sequences using the assembled transcripts with Cufflinks (v2.2.1) (100). Briefly, we assembled mRNAs based on the mapped RNA-Seq reads in all stages with the options implemented in Cufflinks: -u–pre-mrna-fraction 0.2–min-frags-per-transfrag 25 –overlap-radius 50. Taking into account the prediction results, we made the miRNA target sequence list composed of annotated 3′-UTRs and predicted 3′-UTRs whose length are ≥ 10 bp. The annotated and predicted 3′-UTRs used in this study can be found in the supplemental data. Using the miRNA and the 3′-UTR sequences, we calculated miRNA target sites in the 3′-UTRs with TargetScan 6.0 (49).

To remove false-positive miRNA target genes, we calculated the Pearson correlation coefficient between expression levels of a miRNA and the target genes. We extracted the target genes that have a correlation coefficient ≤−0.6. We also computed statistically significantly enriched miRNAs in a specific gene cluster by hypergeometric test (FDR ≤ 0.01).

miRNA regulation of mRNA stability and translatability.

To evaluate the ability of miRNAs to regulate death-associated transcripts, we subcloned the miR-92b target region of the small cytoplasmic leucine rich repeat protein (SCLP, Msex013021) 3′-UTR into the pFila dual luciferase vector (7) using the primers 5′ GAACAATAATTCTAGTCTCTATGGACTAAGCCTGTGA 3′ and 5′ AAGCGGCCGCTCTAGGACACTTAACATAACATCCCAAACC 3′. As a positive siRNA control, we made a construct that contained a 22-nucleotide sequence that was completely complementary to miR-92b using primers 5′ CTAGATAGAATTCTAGTGCAGGCCGGGATTGGTGCAATTGGGCC 3′ and the synthesized antisense strand was 3′ TACTTAAGATCACGTCCGGCCCTAACCACGTTAAC 5′.

COS-1 cells were maintained in high-glucose Dulbecco's modified Eagle's medium (Gibco, Grand Island, NY) with 10% fetal bovine serum (Atlanta Biologicals, Flowery Branch, GA) and 1× penicillin-streptomycin (Gibco, Grand Island, NY). Cells were transfected with pFila plasmid DNA using Lipofectamine 2000 (Thermo Fisher, Waltham, MA) with or without 1 µl of 20 µM miR-92b mimic (QIAGEN, Valencia, CA). All transfections were performed in triplicate. Cells were lysed, and luciferase activity was quantified using the Dual Luciferase Reporter Assay System (Promega, Madison, WI) on a Polarstar plate reader. The fold-change in firefly luciferase was normalized to the levels of the constitutively expressed Renilla luciferase.

Total RNA was isolated, converted to cDNA with Superscript III First-Strand Synthesis System (Invitrogen, Carlsbad, CA) and quantified via qPCR using SYBR Select Master Mix (Applied Biosystems by Life Technologies, Carlsbad, CA) with the following primers: Renilla forward 5′ CATGGGATGAATGGCCTGATA 3′ and reverse primers 5′ CAACATGGTTTCCACGAAGAAG 3′ and firefly forward 5′ CATAGCTTACTGGGACGAAGAC 3′ and reverse 5′ CCACCTGATAGCCTTTGTACTT 3′ primers. Relative mRNA levels were compared by the ∆∆Ct method, and Renilla luciferase expression was normalized to firefly luciferase. All experiments were performed in duplicate with three technical replicates.

RESULTS

Availability of data and material.

All the sequencing libraries are accessible from GSE80830 in Gene Expression Omnibus.

Differential gene expression during ISM development.

To determine which genes are differentially expressed during ISM development, we generated 21 RNA-Seq libraries composed of three biological replicates from the muscles on each day of pupal-adult development ranging from day 13, when the muscles are homeostatic, to day 18, when they are committed to die (Supplemental Fig. S1). We also utilized ISM RNA from day 18 animals that had been injected on day 17 with 20E to delay the normal timing of cell death. Since the Manduca genome was not annotated at the time that we conducted our initial analyses, we performed our own annotation to allow us to identify the Manduca genes, as well as the orthologs from the fruit fly (D. melanogaster), the silk moth (Bombyx mori), and mouse (Mus musculus). We found that 85.8–87.3% reads were uniquely mapped to the Manduca genome (Supplemental Table S2).

Using the read counts obtained from mapping (85.8–87.3% uniquely mapped reads; Supplemental Table S2), we computed differentially expressed genes of the pairs of all possible stages (Supplemental Fig. S2). There were almost no differences in the levels of gene expression between days 13 and 14, a time when the muscles are homeostatic and not undergoing discernible changes in either physiology or development (Fig. 1). Beginning on day 15, when the muscles initiate atrophy, there are a number of significant changes in gene expression, with 125 genes induced and 235 repressed. This trend continued for the next 2 days with gene repression outstripping induction (day 16: 226 induced vs. 591 repressed; day 17: 877 induced vs. 989 repressed). On day 18, more than double the number of genes that were differentially expressed compared with day 17; there were more newly induced genes than repressed (2,578 vs. 2,104).

Fig. 1. — Differentially expressed genes during the intersegmental muscle (ISM) development. Scatter plots of differentially expressed genes between *day 13* and the other time points during the ISM development as well as 20-hydroxyecdysone (20E)-treated animals (20E). Red dots, upregulated genes; blue dots, downregulated genes. The abundance of almost all transcripts was identical between *days 13* and 14 when the muscles are homeostatic. Starting on *day 15*, when atrophy begins, almost twice as many genes were repressed than were induced. In contrast, when the ISMs became committed to die on *day 18*, more than twice as many genes were induced than were repressed. D, day; n = 3 independent libraries were analyzed for each developmental stage.

Twelve of the induced genes displayed more than a 256-fold monotonic increase (log₂ fold-change = 8) relative to their expression on day 13. Two of these genes (Msex004867, Msex004866; FDR < 3.4 × 10⁻¹¹²) were homologs of the D. melanogaster takeout gene (CG11853), which encodes ligand binding proteins that include the juvenile hormone binding protein and is thought to be an output gene of the circadian clock (14). Two additional genes (Msex015696, Msex008658; FDR < 2.5 × 10⁻¹⁰⁷) encode proteins that are homologous to astacin-like matrix metalloendopeptidase in D. melanogaster (CG6763). The remaining eight genes encoded a series of diverse proteins that include homologs of cuticular protein glycine-rich 29 precursor (Msex015422; FDR < 3.8 × 10⁻⁹¹), cysteine-rich secretory protein (Msex006668; FDR ≤ 3.1 × 10⁻²⁰⁴), inorganic phosphate cotransporter-like protein (Msex005594; FDR ≤ 1.1 × 10⁻⁴⁸), lipase 4 (Lip4) (Msex010110; FDR ≤ 1.3 × 10⁻⁵³), ejaculatory bulb protein III (PebIII) (Msex008696; FDR ≤ 9.7 × 10⁻⁴⁷), an uncharacterized protein that has sequence similarity to protease inhibitor 4 from the moth Lonomia obliqua (Msex003322; FDR ≪ 1.0 × 10⁻³⁰⁰), and Acheron/LARP6, a Lupus antigen-related protein (Msex001882; FDR ≤ 1.5 × 10⁻¹⁹⁹). Interestingly, Acheron (Msex001882) and the uncharacterized protein Msex003322 displayed remarkable levels of induction from day 13 to day 18: from 4.8 and 1.1 RPKM to 2339.5 and 1160.3 RPKM, respectively. The expression change of the other 10 induced genes were from 0.02–0.36 RPKM on day 13 to 57.4–531.0 RPKM on day 18. The dramatic upregulation of Acheron has been documented at both the RNA and protein levels via Northern and Western blotting (90, 104).

Published Northern blots confirm a number of the changes in gene expression that we observed, including actin, myosin heavy chain, small cytoplasmic leucine-rich repeat protein (SCLP), Acheron, polyubiquitin, proteasome subunits, and apolipoprotein III (37, 43, 78, 80, 93, 104). In addition, we selected nine differentially expressed genes for qPCR analysis using the constitutively expressed ubiquitin-fusion protein 80 (Ubf80; Msex008476) as a control: Acheron (Msex001882), RING Finger Protein 145 (Msex012524), heat shock protein 70B (Msex015761), vacuolar proton pump (Msex009238), ecdysone-induced protein 75 (Msex001561), nidogen (Msex009360), polyubiquitin (Msex002975), lipase 4 (Msex010110), and TPR repeat protein (Msex009658) (Fig. 2). RNA-Seq and qPCR measures of transcript abundance were comparable at every day of development examined and also in the 20E group. The absolute fold change between qPCR and RNA-Seq was typically within 1 PCR cycle of one another. Consequently, we concluded that the RNA-Seq data are fully informative about the patterns of gene expression in the ISMs.

Fig. 2. — Corroboration of RNA-Seq data with quantitative PCR (qPCR). The expression levels of the nine genes that were shown to be differentially expressed during atrophy and/or death with RNA-Seq (red) were assessed for equivalence with qPCR (blue). For each day of development, three biological replicates (n = 3) were obtained, and the data were analyzed as fold-change in expression relative to *day 13*. RNA-Seq and qPCR measures of transcript abundance were comparable at every day of development and also in the 20-hydroxyecdysone (20E) group; the absolute fold change between qPCR and RNA-Seq were typically within 1 PCR cycle of one another. Data are means ± SE. D, day.

The functional role of differentially expressed genes during ISM development.

We performed a Gene Ontology (GO) analysis on both up- and downregulated genes across development and in response to 20E (Fig. 3). In agreement with the patterns of differential gene expression shown in Fig. 1 and Supplemental Fig S2, there were no significant changes in gene expression during the period of homeostasis (days 14–15). However, with the initiation of atrophy (days 15–17), there was gene induction of transcripts encoding proteins associated with coagulation, histone H3-K4 methylation, acylglycerol transport, autophagy, fatty acid synthase activity, and vitamin binding. Concurrently, there was a repression of genes encoding components of chitin metabolism, adhesion, and ATP-dependent helicase activity. With the commitment to die on day 18, there was the dramatic induction of genes involved in protein catabolism, immune response, the proteasome, membrane transporters, fatty acid synthase, and DNA methylation. At the same stage, there was a reduction in ribosome gene expression, cuticle formation, cell adhesion, and nucleotide kinase activity. Injecting animals on day 17 with 20E delayed the normal eclosion of animals on day 18 (84, 85). While this blunted the anticipated induction of most of these pathways, it proved to be a potent inducer of immune system genes and a repressor of metabolism and energy utilization.

To obtain a more comprehensive understanding of the patterns of differentially expressed genes during atrophy and PCD, we performed K-mean clustering on gene expression quantification results, i.e., RPKM from day 13 to 18 to determine the number of possible gene clusters. Through bootstrapping, we tested the stability of between four and 20 different clusters and observed the best stability with six clusters (Jaccard coefficient: 0.92–0.86) (Fig. 4A). The clustered gene list and the gene expression RPKM values on each day of development are summarized in the Supplemental Table S2.

Fig. 4. — Expression and functional aspects of clustered genes. A: the patterns of differential gene expression across intersegmental muscle (ISM) development can be best explained with six distinct clusters. Black line, the center of the cluster; gray, represent 25% of the best-fitting genes. The y-axis denotes Log2 fold change (RPKM value), while the number of genes that fall within each cluster are denoted with the colored numbers within each panel. *B–D*: pathway enrichment among the six clusters (C1–C6). The columns represent the clusters, while the rows are the GO terms for cellular component (B), biological process (C), and molecular function (D). n = 3 independent libraries were analyzed for each developmental stage. D, day; FDR, false discovery rate.

Each cluster displayed a distinct pattern of gene expression during ISM development. We further performed GO analysis in each cluster to inspect the functional properties of the grouped genes they represent (Fig. 3). Cluster 1 (hereafter, C1) contained 538 genes whose expression continuously declined from day 13 to day 17 and then slightly increased on day 18. The GO terms mainly related to cell periphery and extracellular parts: “cell periphery” (GO:0071944), “extracellular matrix” (GO:0031012), “cuticle development” (GO:0042335), “biological adhesion” (GO:0022610), “structural molecule activity” (GO:0005198). Prominent in this cluster were the majority of the cuticle genes, which were coordinately and dramatically repressed during ISM development.

The 2,583 genes in C2 displayed relatively stable expression during the early phase of atrophy and then initiated a precipitous decline starting on day 16. Many of the genes in this cluster were represented by GO terms related to cuticle and extracellular matrix. In addition, there were the GO terms related to cellular respiration and metabolism: “cellular respiration” (GO:0045333), “respiratory chain” (GO:0070469), “oxidoreductase complex” (GO:1990204). Many of the major contractile protein genes are also represented in this cluster, including troponins T (Msex004726) and C (Msex006421), myosin heavy chain (Msex009968), and tropomyosin (Msex013366). We found that all of the downregulated genes shown in Table 2 belong to C2.

Table 2.

Manduca Base ID	D13	D18	Log2(fold-change)	FDR	Gene Annotation	Organism
Msex013528-RA	14,803.84	880.05	−3.83	4.49E-45	cuticular protein 49Ae (Cpr49Ae)	D. melanogaster
Msex013529-RA	1,324.51	79.89	−3.81	8.69E-46	cuticular protein 67Fb (Cpr67Fb)	D. melanogaster
Msex005195-RA	2,564.95	0.33	−3.46	1.16E-05	cuticle protein LCP65Ad (Lcp65Ad)	D. melanogaster
Msex009968-RA	10,139.21	1,204.35	−2.91	1.63E-40	myosin heavy chain (Mhc)	D. melanogaster
Msex004528-RA	1,527.35	265.01	−2.16	7.02E-06	CG44085	D. melanogaster
Msex004529-RA	2,400.22	418.15	−2.15	1.08E-05	N.A.	N.A.
Msex000706-RA	3,264.96	712.19	−2.06	2.43E-23	myosin alkali light chain 1 (Mic1)	D. melanogaster
Msex001727-RA	2,983.65	722.77	−1.93	3.02E-40	paramyosin (Prrn)	D. melanogaster
Msex011357-RA	1,521.87	463.52	−1.54	6.69E-07	sallimus (sis)	D. melanogaster
Msex008530-RA	27,229.8	8,788.53	−1.49	4.95E-11	actin 578 (Act578)	D. melanogaster
Msex002562-RA	1,185.56	402.85	−1.44	2.62E-17	CG9986	D. melanogaster
Msex015806-RA	2,383.71	811.96	−1.41	5.40E-09	muscle LIM protein at 84B (Mlp84B)	D. melanogaster
Msex013227-RA	1,233.87	418.34	−1.39	6.02E-05	sallimus (sis)	D. melanogaster
Msex017750-RA	1,136.22	417.85	−1.33	1.46E-09	uncharacterized protein LOC100865369	Apis florea
Msex013367-RA	1,066.72	408.14	−1.28	4.55E-21	tropomyosin 1 (Tm1)	D. melanogaster
Msex015807-RA	1,985.6	748.69	−1.27	5.28E-07	CG7484	D. melanogaster
Msex013366-RA	2,346.98	942.97	−1.19	1.57E-07	tropomyosin 2 (Tm2)	D. melanogaster
Msex013228-RA	2,121.73	833.67	−1.15	8.18E-03	N.A.	N.A.
Msex013228-R8	2,771.25	1,147.37	−1.08	9.92E-03	N.A.	N.A.
Msex016926-RA	1,213.93	516.96	−1.05	8.40E-03	N.A.	N.A.
Msex010227-RA	1,425.23	660.61	−1.01	7.50E-24	60S ribosomal protein LP0 (RpLP0)	D. melanogaster
Msex017592-RA	1,249.95	579.2	−1.00	1.78E-08	40S ribosomal protein S2 (RpS2)	D. melanogaster

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D, day; FDR, false discovery rate; N.A., not available.

The 667 genes in C3 displayed enhanced expression up to day 16, leveled off, and then declined dramatically in advance of death on day 18. The GO terms detected in this cluster were also related to respiratory pathways, for example “NADH dehydrogenase activity” (GO:0003954) and “generation of precursor metabolites and energy” (GO:0006091). Interestingly, we observed a dramatic biphasic expression pattern for ribosome biogenesis in C3, with large increases in expression during the early phase of atrophy followed by a dramatic decline in advance of cell death.

The expression of 582 genes in C4 increased continuously from days 13 to 17 and then declined on day 18. GO terms for this cluster include “transcriptionally active chromatin” (GO:0035327) and “positive regulation of histone H3-K4 methylation” (GO:0051571). Those GO terms were distinct terms in C4, although the GO terms related to metabolite transporter activities and catabolic activities were detected in both C4 and C5.

The 2,511 genes in C5 displayed a modest increase in expression during early development and then a dramatic rise on day 18. This cluster contains almost all of the genes involved in ubiquitin-proteasome-dependent protein degradation, such as polyubiquitin (Msex002996) and a large number of proteasome subunits (Table 3). All the upregulated genes shown in Table 1 were clustered into C5 with the exception of the novel gene Msex004609 (homolog of uncharacterized protein with no discernible domains, LOC101746963 in B. mori), which resides in C4.

Table 3.

Manduca Base ID	D13	D18	Log2(fold·change)	FDR	Gene Annotation	Organism
Msex003322-RA	1.09	1,160.33	9. 86	1.00E-300	uncharacterized protein LOC101743112	B. mori
Msex001882·RA	4.75	2,339.50	8. 69	1.48E-199	La-related protein (CG17386)	D. melanogaster
Msex008699-RA	13.50	1,525.58	6. 57	1.18E-93	ejaculatory bulb-specific protein 3 (PebIII)	D. melanogaster
Msex005579-RA	282.34	5,868.86	4.38	2.09E-86	CG34325	D. melanogaster
Msex007599-RA	76.46	1,290.55	4.14	4.66E-240	glutamine synthetase 2 (Gs2)	D. melanogaster
Msex001006-RA	151.28	1,494.01	3.12	5.85E-14	CG45050	D. melanogaster
Msex002996-RA	774.12	7,048.24	3.10	1.55E-19	N.A.	N.A.
Msex002996-RB	1,513.91	13,773.77	3.10	1.91E-19	ubiquitin-5E (Ubi-p5E)	D. melanogaster
Msex002997-RA	2,827.45	25,383.64	3. 07	1.67E-17	ubiquitin-63E (Ubi-p63E)	D. melanogaster
Msex000653-RA	288.48	2,240.48	2. 90	4.42E-20	hypothetical protein KGM_01767	Danaus plexipus
Msex005540-RA	344.60	2,383.63	2.85	1.77E-78	thin (tn)	D. melanogaster
Msex014957-RA	465.83	3,058.80	2.74	1.99E-32	small cyloplasmic leucine rich repeat protein (Sclp)	D. melanogaster
Msex013021-RA	874.32	5,637.41	2. 69	5.57E-24	small cyloplasmic leucine rich repeat protein (Sclp)	D. melanogaster
Msex011306-RA	190.43	1,072.99	2.43	1.89E-12	laminin subunit beta-1 (LanB1)	D. melanogaster
Msex002976-RA	331.63	1,625.77	2.34	8.34E-24	ubiquitin conjugating enzyme 87F (Ubc87F)	D. melanogaster
Msex013343-RA	343.39	1,627.28	2.33	3.56E-87	neurochondrin	D. melanogaster
Msex011554-RA	434.65	2,107.87	2. 30	3.64E-16	heat shock protein 83 (Hsp83)	D. melanogaster
Msex012988-RA	377.72	1,533.41	2.10	1.88E-51	26S proteasome non-ATPase regulatory subunit 1 (Rpn2)	D. melanogaster
Msex017264-RA	469.41	1,922.63	2.07	1.51E-13	muscle-specific protein 20 (Mp20)	D. melanogaster
Msex000788-RA	449.82	1,815.78	2.06	1.17E-17	CG43897	D. melanogaster
Msex009386-RA	368.65	1,370.78	1.98	1.06E-95	26S proteasome regulatory complex subunit p39A (Rpn9)	D. melanogaster
Msex015814-RA	318.08	1,137.06	1.92	1.92E-53	26S protease regulatory subunit 4 (Pros26.4)	D. melanogaster
Msex004605-RA	372.80	1,245.84	1.81	4.42E-19	proteasome subunit beta type-4 (Prosbeta7)	D. melanogaster
Msex007686-RA	411.06	1,317.94	1.77	4.53E-40	26S proteasome regulatory complex subunit p97 (Rpn1)	D. melanogaster
					probable 26S proteasome non-ATPase regulatory subunit
Msex007558-RA	463.23	1,425.76	1.71	2.95E-61	3 (Rpn3)	D. melanogaster
Msex004609-RA	405.89	1,151.27	1.57	2.50E-10	uncharacterized protein LOC101746963	B. mori
Msex005351-RA	425.53	1,166.59	1.52	4.78E-13	proteasome maturation protein (Pomp)	D. melanogaster
Msex014545-RB	419.37	1,131.53	1.52	1.43E-44	uncharacterized protein LOC101746228	B. mori
Msex012266-RA	590.45	1,527.44	1.45	6.76E-19	CG17737	D. melanogaster
Msex010506-RA	463.51	1,092.21	1.32	1.60E-11	DNA repair protein Rad23 (Rad23)	D. melanogaster
Msex000119-RA	2,144.14	4,967.49	1.30	7.11E-37	N.A.	N.A.
Msex000118-RA	1,812.05	4,071.05	1.26	1.30E-36	26S proteasome non-ATPase regulatory subunit 11 (Rpn6)	D. melanogaster
Msex017071-RA	3,311.99	7,317.55	1.22	6.77E-09	ADP,ATP carrier protein (sesB)	D. melanogaster
Msex009904-RA	575.70	1,163.96	1.06	6.14E-04	CG34417	D. melanogaster
Msex012133-RA	549.29	1,079.71	1.04	2.76E-05	ferritin 1 heavy chain homolog (Fer1HCH)	D. melanogaster

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D, day; FDR, false discovery rate; N.A., not available.

The 679 genes in C6 were expressed at relatively low levels throughout atrophy and then increased dramatically on day 18. The GO terms in C6 relate to immune system pathways, e.g., “immune system process” (GO:0002376) and “antibacterial humoral response” (GO:0019731), and hormone receptor pathways, e.g., “receptor activity” (GO:0004872) and “steroid hormone receptor activity” (GO:0003707). The GO terms detected in C6 are very distinct from the GO terms detected in the other clusters; the genes in this cluster represent many of the presumptive death-associated transcripts.

Transcriptional regulation during the ISM development.

We computed statistically significantly enriched TFBSs within the 1 kb region 5′ to the TSSs of the genes that are differentially expressed in the ISMs. The TFBSs of C2 (42), C3 (5), C4 (2), C5 (42), and C6 (1) TFs were considered for further analysis (Supplemental Table S3). We could not identify any TFBSs that were statistically significant in the genes associated with C1. With the hypothesis that TFs that regulate genes in a specific cluster may also display developmental regulation themselves, we also checked differentially expressed TFs in each cluster. While promoters and enhancers can reside at great distances and be located either 3′ or 5′ to the gene of interest, the current annotation of the Manduca genome precludes performing a more detailed survey. Nevertheless, this analysis allows us to begin creating models of developmentally regulated gene expression in the ISMs.

For genes in C6, we found the enrichment of the binding sites for Enhancer of split mgamma protein (HLHmγ; Msex003078), a direct nuclear target of the Notch signaling pathway (1). The TFBSs of Hairy (h; Msex000196) and Stripe (sr; Msex006516) were enriched in the genes in C4. We found the enrichment of five TFBSs, GFI-1B/CG7368 (Msex006263), Cubitus interruptus (ci; Msex002239), Hunchback (hb; Msex004840), Klumpfuss (klu; Msex003545 and Msex009479), and jim (Msex007169 and Msex011615) in the genes in C3. However, the expression levels of all the TFs were almost negligible (0.02–5.98 RPKM) during the ISM development, except for Stripe (14.77–3.65 RPKM).

Using data from the literature, we created maps of putative protein-protein interactions among the detected TFs (Fig. 5). Despite the fact that the expression levels for some of these TFs were low, we nevertheless found that they formed three subnetworks of protein-protein interactions. Interestingly, in the largest subnetwork detected, Polycomb group protein (Pleiohomeotic, Pho; Msex006348) was the hub between the module of the TFs related to hedgehog pathway and the modules composed of the TFs of ecdysone and circadian rhythm pathways (Fig. 5A). Pho binding sites were overrepresented in the genes in C2 (2,388/2,583 genes; FDR = 5.41 × 10⁻⁶) and C5 (2,291/2,511 genes; FDR = 8.26 × 10⁻⁹). Pho itself was clustered into C5 and displayed a gradual increase until day 17 and then a dramatic induction from 4.46 to 22.07 RPKM on day 18.

To further investigate the transcriptional regulation of the genes in C2 and C5, we focused on the TFBSs that are uniquely enriched in those clusters. Out of 42 enriched TFBSs in the two clusters, 12 and 13 of those were uniquely enriched in C2 and C5, respectively. For the TFBSs enriched in the genes of C2, two TF subnetworks were detected: 1) homeobox genes such as Abd-B (Msex000748) and Homothorax (hth; Msex016683, Msex016684, and Msex017338) and 2) ecdysone receptor signaling like Ultraspiracle (usp; Msex014339) (Fig. 5B). The subnetworks of the TFs regulating C5 also contain ecdysone signaling pathway components such as the Ecdysone-induced protein 74EF (Eip74EF; Msex009996) and the Ftz transcription factor 1 (ftz-f; Msex005610) (Fig. 5C). The binding sites of the TFs related to circadian rhythms were also enriched in C5 genes such as Clock (clk; Msex010427) and Cycle (cyc; Msex013484) genes (Fig. 5C). As with the target cluster of clk/cyc, these genes were also clustered in C5 and showed a twofold increase on day 18. Interestingly, the antagonistic factors to the genes such as Timeless (Msex000831) and Period (Msex001717) were clustered in the repressed gene cluster, C2. Furthermore, we found another circadian clock regulator, Cry (Msex007463) was induced during development.

We observed that ecdysone signaling pathway components were highly expressed during ISM development (Fig. 5D). The most upstream component of the pathway is a nuclear receptor complex consisting of ecdysone receptor (EcR; Msex001634) and Usp, followed by the activation of Eip74E, BR-C (Msex007362), Eip93F (Msex015245 and Msex017016) (98). Although the enrichment of the EcR TFBSs was not detected, the expression of EcR was induced from 6.95 RPKM on day 13 to 20.94 RPKM on day 17 (Fig. 6). Eip74FE, BR-C, and Eip97F were all clustered into C5 and also displayed a ∼3-fold increase on day 18 compared with day 13. H3K27me3 demethylase Utx (Msex004649), which regulates key apoptosis and autophagy genes controlled by the ecdysone signaling pathway (16, 87), was also induced on day 17 (26.31–51.95 RPKM). Furthermore, we also observed enhanced expression of ftz-f1 on day 18 (3.60–34.84 RPKM), a TF required for cell death in Drosophila (112). Although the downstream apoptosis initiator reaper (rpr; Msex002141) and caspase gene dronc (Msex014106) were not statistically significantly upregulated (1.19–2.51 RPKM), another caspase gene drice (Msex006408) was induced twofold, from 10.97 RPKM on day 13 to 22.77 RPKM on day 18.

Fig. 6. — Expression of ecdysone receptor signaling components during development. RNA-Seq expression during development is presented in RPKM. n = 3 independent libraries were analyzed for each developmental stage. An additional group of n = 3 animals were injected on *day 17* with 20-hydroxyecdysone (20E) and then analyzed on *day 18*. Onset of atrophy on *day 15* is accompanied by a downward trend in E75 and a transient elevation of 74EF. Commitment to die was accompanied by a further decline in E75 and elevations in both ECR and 74EF. Data are means ± SE. D, day.

Impact of 20E on gene expression and transcriptional regulation.

A decline in the circulating levels of 20E on day 15 serves to trigger atrophy, while a further decline on day 17 commits the ISMs to die following adult eclosion late on day 18 (84). Injecting day 17 animals with 20E delays both adult eclosion and ISM death. Consequently, to identify ecdysteroid-regulated genes we compared the gene expression in day 18 animals to comparably aged animals that had been injected on day 17 with 20E. Out of 20,795 genes, 1,463, and 2,145 were induced and repressed, respectively (Fig. 7).

Fig. 7. — Gene Ontology term enrichment analysis for gene regulation by 20-hydroxyecdysone (20E). Animals were injected on *day 17* with 20E and analyzed on *day 18* for differential gene expression. Induced genes are displayed on the *left* (red), while repressed genes are shown on the *right* (blue).

The genes induced by 20E were associated with GO terms involved in DNA metabolic processes such as “DNA-dependent DNA replication” (GO:0006261), “DNA conformation change” (GO:0071103), “helicase activity” (GO:0004386), “DNA binding” (GO:0003677) and “RNA binding” (GO:0003723) (Fig. 7). Along with the GO terms detected, we observed the upregulation of nucleosome assembly protein 1 (Nap1) (Msex000075) from 98.40 RPKM on day 18 to 381.53 RPKM following treatment with 20E (276.19 RPKM on day 13). In addition, the GO terms related to cell cycle and development were also observed, e.g., “positive regulation of cell cycle process” (GO:0090068), “ribosome biogenesis” (GO:0042254), “regulation of MAPK cascade” (GO:0043408) and “mitogen-activated protein kinase binding” (GO:0051019). In D. melanogaster, it is known that Lk6 kinase promotes cell growth and development by phosphorylating eukaryotic translation initiation factor 4E (eIF4E) (4). We found that the Lk6 kinase homolog in M. sexta (Msex013719) displayed a gradual decrease during the ISM development, from 156.66 to 160.15 RPKM on day 13 to 22.73–23.34 RPKM on day 18. However, the expression level of Lk6 in the 20E-treated ISMs returned to day 13 levels (169.29–175.20 RPKM). We also observed that eIF4E (Msex004105) was also induced, from 30.38 RPKM on day 18 to 139.13 RPKM in response to 20E. Interestingly “response to DNA damage stimulus” was also detected (GO:0006974). In agreement with this GO term, expression of DNA repair protein RAD51 (Msex010633) was induced from 41.68 RPKM on day 18 to 217.74 RPKM following 20E treatment (75.86 RPKM on day 13). Interestingly, we found the homolog of protease inhibitor-like protein in another moth genus, Antheraea mylitta (Msex008966), was induced sevenfold from 45.03 RPKM on day 18 to 330.45 RPKM in response to 20E.

Since we observed a dramatic and coordinate increase in the ubiquitin-proteasome components on day 18 (Table 2), it was not surprising that 20E treatment led to their repression, e.g., “proteasomal ubiquitin-dependent protein catabolic process” (GO:0043161); “proteasome regulatory particle” (GO:0005838), and “proteasome complex” (GO:0000502) (Fig. 7). Other proteases were likewise repressed, like “peptidase activity” (GO:0008233). The same was true for autophagy-related protein 101 (Atg101; Msex002714), which is consistent with the detected GO term “salivary gland cell autophagic cell death” (GO:0035071) enriched in the downregulated genes.

Using the promoter sequences for the induced and repressed genes, we calculated TFBS motif enrichment to investigate the transcriptional regulation by 20E. The 10 and 49 TFBS motifs were enriched in the promoters of the upregulated and downregulated genes by 20E respectively. We found the 10 TFBS motifs in the promoters of the induced genes by 20E overlapped with those of the repressed genes by 20E [Anterior open (aop), bric a brac 1 (bab1), ci, dendritic arbor reduction 1 (dar1), hb, jim, klu, longitudinals lacking (lola), Pho and sr; Supplemental Table S3]. Interestingly the protein-protein interaction among the TFs of enriched TFBSs in the repressed genes were very similar to the ones enriched in C5 (Fig. 5D). The largest TF subnetwork of enriched TFBSs in the 20E repressed genes were composed of ecdysone pathway and circadian rhythm pathway components. Many TFs upregulated during atrophy were repressed by 20E such as Clk, cry and Eip74EF. However, EcR was consistently upregulated by 20E treatment.

miRNA expression during the ISM development.

MiRNAs (miRs) are 22 nucleotide-long small interfering RNAs that can bind to target sequences within mRNAs and inhibit protein expression either via translational repression or transcript degradation (11, 17). One or more miRs can exert control over the expression of entire developmental pathways (3, 44).

To determine if small interfering RNAs might regulate mRNA stability or translatability during atrophy or death, we generated and sequenced small RNA libraries at each stage of development from day 13 to day 18, plus 1 h PE and 20E treated. Of the sequences obtained, between 71.65 and 80.66% reads were successfully mapped to the M. sexta genome (Supplemental Table S4). In the miRBase v20, we found 93 annotated miRNAs in M. sexta. In contrast, there are 487 annotated miRs in the genome of the silk moth B. mori (10). B. mori and M. sexta are in the same order, Lepidoptera, and are closely related phylogenetically (36, 42). Consequently, we hypothesized that there are likely many more miRNAs in the M. sexta genome than previously identified. Using mirDeep2 (24), we predicted putative miRNAs in the M. sexta genome and found an additional 325 novel miRNA candidates, which brings the total number in line with Bombyx: 418 miRNAs for Manduca and 487 for B. mori. [After we had conducted our analyses, two papers appeared that report additional miRNA sequences from Manduca (108, 109).]

We further sought to determine if the length of the reads mapped to the miRNAs in M. sexta distributes within miRNA length range (5, 30). As shown in Fig. 8, we confirmed a peak of the miRNA mapping reads at 22 nt length in all samples. [It should be noted that there is a second size peak at ∼27 nt, which we have determined to be piRNAs, a different class of small interfering RNAs (70)]. A detailed analysis of these data is being submitted elsewhere (Tsuji J, Thomson T, Brown CK, Theurkauf WE, Wang Z, and Schwartz LM, unpublished observations). We used the miRNA annotation in M. sexta for the downstream analysis. The miRNA annotation used in this study is summarized in Supplemental Table S5.

Fig. 8. — Abundance and length distribution of small RNAs during intersegmental muscle development. Authentic microRNAs (miRNAs) that map to the genome are in black, while the gray bars reflect sequences that were not annotated. The majority of the small RNAs are ∼22 nucleotides long and map as miRNAs. The smaller peak at 27 nt may reflect piRNAs, a distinct class of small interfering RNAs. 20E, 20-hydroxyecdysone; D, day; PE, posteclosion.

We calculated miR expression values with miR mapping reads (67.15–87.55% of total mapped reads). There were 111 miRs that were expressed at least 10 ppm at least at one time point. We detected 31 miRs that were differentially expressed between at least two time points in all possible comparisons throughout the ISM developmental stages and 20E, which represents ∼7.5% of all miR sequences (Supplemental Fig. S3).

Compared with the miR expression on day 13, we found 10 that were upregulated and seven that were repressed during the ISM development (Fig. 9A). For upregulated miRs, we found that mse-miR-2a, mse-miR-87, and mse-miR-965 were stably induced during atrophy but repressed with the commitment of the ISMs to die on day 18. mse-miR-190, mse-miR-745, and two predicted miRs (predicted-scaffold00132-1 and predicted-scaffold00018-5) were elevated from days 14 to 17 and then again PE, but not on day 18. In contrast, mse-miR-34 was induced both before and after the initiation of death on day 18. Treatment with 20E failed to repress its expression. For downregulated miRs, the expression of mse-miR-2765 and two predicted miRs (predicted-scaffold00553-1 and predicted-scaffold01801-1) fell precipitously after day 13 including in the 20E-treated individuals.

Posttranscriptional regulation during the ISM development.

Along with analyzing the miRNA expression, we predicted their putative target genes. Out of 20,795 genes in M. sexta, 13,692 genes had annotated 3′-UTRs in the Manduca Base. For the rest of the genes that lack the 3′-UTR the annotation, we predicted the 1,164 putative 3′-UTRs using the assembled transcripts with Cufflinks (100). The median length of the annotated and predicted 3′-UTRs were 838 and 274 bp, respectively (the median length of total 3′-UTRs = 766.5 bp). Using TargetScan (49), we found 14,260 genes (68.57% of all genes) have at least one predicted miRNA target site in the 3′-UTRs, and 10,539 genes (50.68% of all genes) have multiple target sites of one miRNA species within the gene bodies.

For further analysis, we focused only on the 31 differentially expressed miRs (Supplemental Fig. S3) and the target genes that were anticorrelated against the miR expression (Pearson correlation coefficient ≤ −0.6). The differentially expressed miRs repressed 3–664 genes as the posttranscriptional targets (the miRs and the target genes are summarized in Supplemental Table S5). Out of the 31 differentially expressed miRs, the 16 miRs had specific GO terms enriched in the target genes.

The miRs that displayed a gradual decrease from day 13 to day 18 tended to have targets with the transcripts of upregulated genes in ecdysone signaling, the ubiquitin-proteasome pathway, and daytime circadian rhythms pathway (Fig. 9B, Supplemental Table S5). mse-miR-92b targets included Clk, Eip74EF, ftz-f1, and proteasome subunit proteins (Prosbeta7, Prosbeta2, Pros28.1, Rpt3). mse-miR-2767 targets EcR and ftz-f1 in the ecdysone pathway components. These miR target sites were statistically significantly enriched in the 3′-UTRs of the genes clustered into C5 (mse-miR-92b, FDR = 2.90 × 10⁻⁶; mse-miR-2767, FDR = 3.30 × 10⁻⁵). Interestingly the target genes of the miRs include the genes required for the autophagosome formation. We observed the GO term enriched in both targets, “Atg1p signaling complex” (GO:0034273) (Fig. 9C). In addition to Apoptosis-linked gene-2 (ALG-2) and Autophagy-related 13 and 16 genes (Atg13, Atg16), the SCLP mRNA, which is dramatically increased on day 18 also had a mse-miR-92b target site.

The miRNAs that displayed incremental induction during ISM development were predicted to function as suppressors of downregulated genes during development (Fig. 9B). mse-miR-34 and mse-miR-6096 target 238 genes and 577 genes clustered into C2 (the total target genes, 266 and 644 genes, respectively). The target sites of those miRNAs were statistically enriched in the 3′-UTRs of the genes clustered into C2 (mse-miR-34 FDR = 5.24 × 10⁻³, mse-miR-6096, FDR = 8.88 × 10⁻¹¹). Although mse-miR-34 expression was not associated with any enriched GO terms, mse-miR-6096 was associated with enrichment of numerous metabolic GO terms as well as “mitogen-activated protein kinase binding” (GO:0051019) (Fig. 9C).

While the negative correlation between miRs and their potential mRNA targets is intriguing and suggestive of a potential regulatory mechanism for tuning protein expression during ISM development, we wanted to test this hypothesis more formally. We selected miR-92b, which declines continuously during ISM development, and one of its putative target transcripts, SCLP, which is transiently induced with atrophy and then more dramatically upregulated on day 18 (43). A 411nt portion of the SCLP 3′-UTR was cloned downstream from the luciferase gene from the sea pen Renilla within the pFila vector, which also expresses firefly luciferase as an internal normalization control (7). Mammalian COS-1 cells were transiently transfected with the constructs and then treated with different 22-nt double-stranded RNAs before performing dual luciferase assays. As a control, we treated cells with an miR that shared 100% complementarity with a target sequence within the test 3′-UTR, which functionally served as an siRNA. As anticipated, this treatment resulted in a substantial (∼80%) repression of expression (Fig. 10A). We then tested authentic miR-92b for its ability to alter luciferase activity and observed an ∼40% repression.

Fig. 10. — MicroRNA (miR)-92 represses small cytoplasmic leucine rich repeat protein (SCLP) expression but not transcript abundance. A: the normalized relative luciferase activity (Renilla/Firefly) of the SCLP constructs when treated with miR-92b. The relative luciferase activity was compared 24 h after cotransfection of COS-1 cells with the construct [SCLP-3′-untranslated region (UTR) or SCLP-siRNA] and 1 µl of 20 nM miR-92b mimic. The 100% complementarity between miR-92b against the SCLP-3′-UTR repressed luciferase expression and served as a positive control for silencing. The use of miR-92b that targets the SCLP 3′-UTR also repressed expression. B: miR-92b was cotransfected with either SCLP-siRNA, a vector with a 3′-UTR target site completely complementary to miR-92b, or SCLP-3′-UTR, a vector with a 3′-UTR target site amplified from the 3′-UTR of SCLP. After 24 h, the cells were lysed, and *Renilla* luciferase expression was measured via quantitative (q)PCR and compared by the ∆∆Ct- method. Blue = control and red = treated. The use of an siRNA that was 100% complementary to the 3′-UTR led to transcript degradation, while the use of miR-92b against the authentic SCLP 3′-UTR did not alter transcript abundance, suggesting a block in translation. The Student’s t test was used to test statistical significance for the pairwise comparisons.

The ability of miR-92b to repress expression could have occurred either by blocking translation or by facilitating transcript degradation. To determine which of these two processes might be involved, we repeated the transfections described above and performed qPCR analysis using primers directed against luciferase (Fig. 10B). The use of a miR that is 100% complementary to the target sequence in the luciferase mRNA (siRNA) served as a positive control and resulted in a 69.3% decline in mRNA abundance. In contrast, transfection with miR-92B did not alter luciferase mRNA abundance, suggesting that the block in luciferase expression in our experiments reflected transcriptional repression rather than transcript destruction.

DISCUSSION

The ISMs from Manduca afford a unique system for examining the molecular mechanisms that mediate naturally occurring skeletal muscle atrophy and death. In the current study we employed unbiased RNA-Seq-based methodology to examine simultaneously all of the differentially expressed mRNAs and microRNAs across development. We were able to verify the accuracy of our RNA-Seq data sets in several ways, including qPCR (Fig. 2), Northern blots, and Western blots (e.g., 31, 37, 43, 79, 80, 93, 104). In each case, the developmental changes observed via RNA-Seq were confirmed by the other independent methods.

ISM Atrophy.

Prior to day 15 of pupal-adult development, the ISMs are in a homeostatic state and are neither growing nor regressing. This is seen by examining muscle mass (Supplemental Fig. S1), cellular physiology (81), and by comparing the patterns of gene expression between days 13 and 14, where transcript abundance is almost identical (Fig. 1, Supplemental Fig. S2). In contrast, beginning on day 15 there are dramatic changes in muscle mass (Supplemental Fig. S1) and gene expression, with 125 induced and 235 repressed (Fig. 1, Supplemental Fig. S2). One key aspect of atrophy is a general shift toward catabolism. Genes associated with the extracellular matrix and the contractile apparatus, including actin and myosin heavy chain (cluster 2), are constitutively expressed and then decline precipitously (Fig. 4). Teleologically, it makes sense that the cells would not expend the energy required to make contractile proteins at a time when they are undergoing atrophy. It should be also noted that the coordinated loss of contractile protein mRNAs means that the contractile apparatus does not selectively lose specific essential proteins, meaning that the muscle retains its normal physiological properties even as it rapidly loses mass (81).

ISM atrophy is accompanied by enhanced expression of virtually all of the components of the ubiquitin-proteasome system (UPS) (cluster 5). This includes ubiquitin conjugases (E₂s), ubiquitin ligases (E₃s), and the enzyme protein NH₂-terminal asparagine amidohydrolase (NTAN1), which serves as a mediator of ubiquitin-dependent protein degradation via the N-End rule (29). In addition, there is enhanced expression of more than 65 genes required for the assembly of the 26S proteasome (53). The coordinated induction of proteasome genes helps facilitate the stoichiometric assembly of the complex (65).

The expression of the majority ribosomal genes, including those encoding for RNA helicases and snoRNA binding, transiently increases at the beginning of atrophy and then decline precipitously (cluster 2). The helicases facilitate the recruitment and release of the snoRNAs that modify ribosomal RNA during ribosome biogenesis (59). The repression of these genes presumably plays a number of key roles in facilitating the rapid loss of protein that accompanies ISM atrophy.

Intermediary metabolism genes are also induced transiently during atrophy and then plummet (cluster 4). In particular, enzymes involved in glycogen degradation, such as 4-alpha-glucanotransferase and glycogen debrancher enzymes, are induced, which facilitates the production of glucose to support glycolysis. In agreement with this interpretation, several glycolytic enzymes are also induced, including fructose-bisphosphate aldolase and NADH dehydrogenase. Consequently, atrophy is associated with aerobic metabolism to generate the ATP required for protein degradation.

Atrophy is also associated with enhanced histone H3K4 methylation (cluster 4), a process that enhances transcriptional activation (105). Given the rapid and dramatic changes in gene expression that accompany ISM atrophy and death, it would be informative to map changes in histone methylation marks across development. Interestingly, despite the intense investigation of skeletal muscle atrophy, few studies have addressed methylation status (86).

Lastly, ISM atrophy is also associated with the repression of epithelial genes required for cuticle synthesis, including chitin (cluster 1). There are two likely reasons for this. The first is that the muscles attach to the epithelium at the intersegmental boundaries, and some of these cells were recovered when the ISMs were isolated for analysis since we didn’t want to damage the fibers during dissection. However, the main source of cuticle within the tissue is the tracheal system. Unlike mammals, which employ a closed circulatory system and a respiratory pigment to deliver oxygen to tissues, insects utilize a series of hollow cuticular tubes to facilitate gas exchange (6). Since the cuticular lining of the trachea is withdrawn through the old pupal cuticle during eclosion, there may be associated changes in its structure to make it more pliable.

ISM death.

On day 18, when the ISMs become committed to die, there is a dramatic shift in gene expression, with more genes induced than repressed. Unlike the changes that accompany atrophy where the amplitude of these changes is modest, the commitment to die involves some profound examples of gene induction. The expression of more than a dozen genes increases 250-fold or more in 24 h (cluster 6). For example, Acheron (also known as Larp6) mRNA is induced 1,000-fold on day 18 (90, 104). Acheron is a member of the Lupus Antigen family of RNA binding proteins (104) and functions as a survival protein that protects some terminally differentiated cells and cancers from cell death (89, 90). EH triggers ISM death by inducing the expression of cyclic GMP (83), which induces Acheron phosphorylation and degradation. This leads to the mitochondrial release and degradation of cytochrome c and cellular demise (90).

The loss of cytochrome c suggests that mitochondrial respiration collapses in the condemned ISMs. Indeed, there is an upregulation of genes associated with gluconeogenesis, which reflects a likely shift from aerobic to anaerobic metabolism. For example, the transcription factor Klf15, which regulates the hydrolysis of fat in skeletal muscle and drives gluconeogenesis and amino acid catabolism (32), is induced 13-fold during ISM atrophy in Manduca. The availability of ATP is likely critical for the efficient degradation of macromolecules since the ISMs are not phagocytosed when they die (38). In agreement with this, there is an induction of membrane transporters that presumably facilitate recycling of valuable macromolecules.

The two-stage induction of the UPS presumably serves distinct roles for the developing muscles. The transient increase with the onset of atrophy helps shift the cells from an anabolic state to a catabolic one, whereby muscle protein is progressively lost. The subsequent sharp increase on day 18 helps mediate the wholesale loss of muscle protein during death (31, 37). Biochemical studies have demonstrated that the percentage of ubiquitin that is covalently attached to cellular proteins increases from ∼50% before adult eclosion to almost 100% with the initiation of death (31). This dramatic shift reflects the aggressive destruction of cellular protein. In some tissues, the UPS system also plays regulatory roles in the control of cell death by selectively targeting key cell death pathway components like the antiapoptotic protein Death-associated inhibitor of apoptosis 1 (DIAP1) (19).

The two genes that are most dramatically induced with ISM death encode members of the astacin family of matrix metalloproteinases, which are upregulated ∼3,000-fold between days 16 and 18. Originally identified in the digestive gastric juices from crayfish, astacins are also found in the venom of the brown recluse spider Loxosceles and the tentacles of certain jellyfish (52, 101). Astacins have promiscuous substrate specificities that include skeletal muscle myosin heavy chain (96). One intriguing possibility is that these proteases initiate indiscriminate cleavage of ISM proteins, which in turn then generates fragments of misfolded proteins that are good substrates for the UPS.

Lastly, death is associated with the induction of immune system genes. The reason for this is unclear but innate immune system genes are also induced with muscle damage in Drosophila (28), although in Manduca, this change in gene expression precedes the initiation of muscle damage.

MiRNAs and muscle atrophy and death.

In addition to analyzing changes in transcript abundance during ISM development, we also examined the expression of small interfering RNAs. While our primary focus was on miRs, which are ∼22 nt long, we also noted a second peak of small RNAs that were ∼27 nt in length, which may represent PIWI-interacting RNA (piRNAs), a distinct class of small interfering RNAs (Fig. 8; Tsuji J, Thomson T, Brown CK, Theurkauf WE, Wang Z, and Schwartz LM, unpublished observations). piRNAs are largely confined to gonads where they function to repress transposon expression to protect the integrity of the germline genome (99). We found that piRNA expression is repressed when the ISMs become committed to die and that this is correlated with the derepression of certain DNA transposons. This may represent a novel mechanism for insuring genome damage in cells that do not die by apoptosis.

We found that ∼7.5% (31 unique miRs) were differentially expressed between at least two time points during ISM development. Single miRs can repress protein expression by either blocking translation or by facilitating transcript degradation (35). A single miRNA can modulate entire developmental pathways and exert dramatic effects on cellular physiology through the simultaneous regulation of multiple transcripts (44, 48). We functionally tested the hypothesis that miRs could influence atrophy- or death-associated gene expression by demonstrating that miR-92b could block the translation of SCLP mRNA (Fig. 10). Thus, the dramatic increase in SCLP protein and other death-associated proteins is likely a consequence of both an increase in transcription coupled with the derepression of translation (43).

Not surprisingly, each of the miRs investigated in this study has putative target sequences in a large number of mRNAs. However, we were struck by the observation that in most cases, these targets were all members of a single cluster. For example, more than 20% of the genes in cluster 5 (516 of the 2,511 genes) could be targeted by miR-92b. Thus, a change in the abundance of a single miR would likely modulate the expression of major pathways associated with atrophy and/or death. This observation may explain the disparity that we have noted between the abundance of mRNAs and their encoded proteins. For example, the abundance of mRNA for ubiquitin-proteasome pathway components increase transiently during atrophy and then again with the commitment to die, for a total increase of about fivefold (Figs. 2, 4). However, expression of proteasomal proteins increases at least two orders of magnitude on day 18 (37). While this presumably reflects a number of regulatory processes including protein stability, the loss of miRs is certainly well positioned to exert a major influence on the developmental regulation of protein abundance.

A number of the miRs identified in this study have been reported to influence atrophy and cell death in other organisms (63, 107). For example, miR-92 serves a survival role in a variety of different cell types including embryonic stem cells and rod cells within the retina, in part due to its ability to repress the expression of proapoptotic proteins like BIM (71, 94). This observation has clinical relevance to human muscle disorders since miR-92 expression is repressed in two types of human cardiac failure- idiopathic dilated cardiomyopathy and ischemic cardiomyopathy (92).

Control of ISM gene expression.

One surprising result of our analysis was that almost all of these changes in gene expression could be accounted for by only six discrete patterns. The coordinated control of gene expression during development by a common set of cis-acting regulatory sequences has been referred to as a “gene battery” (15). For example, ribosome biogenesis has been studied in detail in a variety of organisms and shown to be coordinately controlled by specific transcriptional machinery (e.g., 51). These data provide an opportunity to generate hypothetical transcriptional regulatory networks that control the expression patterns observed from our cluster analysis (Fig. 5). For example, the Polycomb complex serves as a central node in the control of gene expression in the ISMs. Polycomb regulatory sequences are found in 92.5% of the genes in cluster 5, which are dramatically induced on day 18. While Pho is typically associated with transcriptional repression (50), the closely related protein pleiohomeotic-like (Phol) can facilitate transcriptional activation (75). BLAST searches with both Drosophila Pho and Phol retrieved the same sequence in Manduca, suggesting that a distinct Phol may not exist in Manduca. One possibility is that Pho may serve multiple roles in transcriptional regulation, especially given its ability to recruit a wide range of transcription regulators to promoters (64).

In Manduca, ISM atrophy and death are regulated by the declining ecdysteroid levels (84). We injected day 17 animals with 20E to delay eclosion and examined the resulting patterns of gene expression (Fig. 3, Supplemental Table S4). 20E blocked the anticipated induction or repression of many pathway components and kept transcript abundance at day 17 levels, such as the induction of the UPS system and the anticipated induction of Acheron (Fig. 2). In addition to providing insight into the steroid control of cell death, these data provide a comprehensive list of 20E-regulated genes that may be involved in developmental processes in other tissues (Fig. 7).

Control of PCD in Manduca versus Drosophila.

Drosophila has been a widely used genetic model for cell death, most notably of larval muscles, salivary glands, and midgut cells following pupariation (69). The best studied example of muscle death focused on the dorsal exterior oblique muscle (DEOM) (112). Two transcription factors that are implicated in DEOM death are the orphan nuclear receptors, FTZ-F1 and HR39. These proteins share sequence similarity and bind to the same promoter regions but tend to be expressed reciprocally and to antagonize one another in cells that are programmed to die (112). In contrast to their pattern of expression in the DEOMs, we observed that HR39 and FTZ-F1 are coordinately induced in the ISMs on day 18, suggesting that they may play different roles in this tissue. This may reflect differences in the nature of the ecdysteroid control of development for the ISMs (rising vs. declining titers) or perhaps other regulatory differences in the process of cell death.

Two additional nuclear proteins have been shown to regulate muscle degeneration in Drosophila are Chromator, which drives muscle degeneration, and East, which represses it (106). However, neither East nor Chromator is differentially expressed in the ISMs on day 18, reducing the likelihood that they play significant roles in either the timing or nature of ISM cell death.

Muscle atrophy in Manduca and mammals.

One of the motivations for undertaking this study was to gain insights that might have relevance to skeletal muscle atrophy and cell death in mammals. There is a general model for mammalian muscle that suggests that a wide range of atrophic stimuli, as diverse as denervation and sepsis, leads to a decrease in PI3-kinase/AKT activity, which in turn activates FOXO transcription factors and the subsequent expression of several RING finger ubiquitin ligases, including Atrogen-1, MuRF1, and MUSA1 (9, 26, 67, 73). Knock-down of atrogen-1 and MuRF1 abrogates atrophy both in vitro and in vivo (9, 26). In addition to the UPS, the PI3K/AKT pathway also activates other proteolytic systems including lysosomal and autophagic pathways within the atrophic muscle (58). The effects of FOXO on atrophy are antagonized by the serine/threonine-protein kinase mTOR, which has been shown to be a negative regulator of skeletal muscle atrophy in both insects and mammals (67).

While these same upstream regulatory components are conserved in insects and regulate muscle growth and atrophy in the fruit fly Drosophila (66), they do not appear to be major regulators of ISM atrophy at the end of metamorphosis in Manduca. At the RNA level, there are no changes in the expression of FOXO, mTOR, or mTor pathway components such as Ragulator complex protein LAMTOR5 or the Regulatory-associated protein of mTOR (data not shown). Moreover, despite the fact that the UPS system is induced with ISM atrophy and death, there is no change in the expression of the Manduca Atrogen-1 ortholog during development. (A MuRF1 homolog has yet to be identified in Manduca.) These data suggest that the upstream regulatory pathways for ISM atrophy are distinct from those employed by mammalian muscle. This may not be so surprising since ISM atrophy is so tightly controlled by the titer of 20E rather than environmental stimuli like nutritional status or neuronal activity.

That said, it does appear that many of the downstream effectors of atrophy are conserved between Manduca and mammals. In each system, there are increases in the UPS and autophagic and lysosomal systems (8, 46, 47, 54) and decreases in both ribosome biogenesis (12, 57) and the expression of contractile protein genes (18, 54).

Summary

In summary, the data presented here provide a range of new insights into the molecular pathways that are differentially regulated during skeletal muscle atrophy and death. There was a dramatic reduction in the expression genes associated with the contractile apparatus, respiration, and adhesion and a concurrent induction of ribosome biogenesis and several proteolytic systems. These and other proteases were induced with death, in some cases by more than three orders of magnitude, such as the astacin family of matrix metalloproteinases. In addition to control of the level of transcription, it appears that a decline in the levels of specific miRNAs can greatly exacerbate expression at the protein level. In at least one case, this appears to be via derepression of translation. In addition, these data sets offer a unique resource for hypothesis generation, and perhaps a systems biology analysis to examine gene networks during development that complement other studies of skeletal muscle atrophy in mammals (21).

GRANTS

This work was supported by a Life Sciences Moment Fund grant from the University of Massachusetts Center for Clinical and Translational Science, the Eugene M. and Ronnie Isenberg Professorship Endowment to L. M. Schwartz, and National Institute of Child Health and Human Development Grant P01HD078253 to W. E. Theurkauf and Z. Weng.

DISCLOSURES

No conflicts of interest, financial or otherwise, are declared by the authors.

AUTHOR CONTRIBUTIONS

L.M.S., W.E.T., and Z.W. conceived and designed research; L.M.S., T.T., E.C., C.K.B., and J.O. performed experiments; J.T., L.M.S., T.T., C.B., and X.D. analyzed data; L.M.S., J.T., T.T., C.B., C.K.B., W.E.T., and Z.W. interpreted results of experiments; J.T., C.B., and L.M.S. prepared figures; J.T., and L.M.S. drafted manuscript; J.T., L.M.S., and T.T. edited and revised manuscript; L.M.S., T.T., E.C., C.K.B., J.O., C.B., X.D., W.E.T., and Z.W. approved final version of manuscript.

ACKNOWLEDGMENTS

We thank Dr. Wendy Smith for the Manduca, Yanzhen Bi for providing the pFila vector, and Stephen Richards for help with Manduca Base. We also thank a number of colleagues for helpful discussions, including: Drs. Leonid Pobezinsky, Craig Woodard, Alexander Gerson, and Michele Markstein.

Current addresses: J. Tsuji, Genomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA; J. Oppenheimer and E. Chan, University of Massachusetts Medical School, Worcester, MA; X. Dong, Genomics and Bioinformatics Hub, Brigham and Women’s Hospital, Boston, MA.

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PERMALINK

High-resolution analysis of differential gene expression during skeletal muscle atrophy and programmed cell death

Junko Tsuji

Travis Thomson

Elizabeth Chan

Christine K Brown

Julia Oppenheimer

Carol Bigelow

Xianjun Dong

William E Theurkauf

Zhiping Weng

Lawrence M Schwartz

Abstract

INTRODUCTION

MATERIALS AND METHODS

Animals.

RNA isolation, library construction, and sequencing.

Quantitative PCR quantification.

Genome sequence and the annotation.

Table 1.

Gene expression and differentially expressed gene clusters.

Transcription factor binding site estimation.

miRNA expression and differentially expressed miRNAs.

miRNA target prediction and enrichment analysis.

miRNA regulation of mRNA stability and translatability.

RESULTS

Availability of data and material.

Differential gene expression during ISM development.

Fig. 1.

Fig. 2.

The functional role of differentially expressed genes during ISM development.

Fig. 3.

Fig. 4.

Table 2.

Table 3.

Transcriptional regulation during the ISM development.

Fig. 5.

Fig. 6.

Impact of 20E on gene expression and transcriptional regulation.

Fig. 7.

miRNA expression during the ISM development.

Fig. 8.

Fig. 9.

Posttranscriptional regulation during the ISM development.

Fig. 10.

DISCUSSION

ISM Atrophy.

ISM death.

MiRNAs and muscle atrophy and death.

Control of ISM gene expression.

Control of PCD in Manduca versus Drosophila.

Muscle atrophy in Manduca and mammals.

Summary

GRANTS

DISCLOSURES

AUTHOR CONTRIBUTIONS

ACKNOWLEDGMENTS

REFERENCES

ACTIONS

PERMALINK

RESOURCES

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