# Transcriptomic characterization of postnatal muscle maturation in mice, with a focus on myopathy-associated genes

Alix Simon, Sarah Djeddi, Pauline Bournon, David Reiss, Julie Thompson, Jocelyn Laporte

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Alix Simon, Sarah Djeddi, Pauline Bournon, David Reiss, Julie Thompson, et al. Transcriptomic characterization of postnatal muscle maturation in mice, with a focus on myopathy-associated genes. Disease Models & Mechanisms, 2025, 18 (2), pp.DMM052098. 10.1242/dmm.052098. hal-04939413

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# Transcriptomic characterization of postnatal muscle maturation in mice, with a focus on myopathy-associated genes

Alix Simon¹, Sarah Djeddi¹, Pauline Bournon¹, David Reiss¹, Julie Thompson²,
Jocelyn Laporte¹,*

¹Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), CNRS UMR 7104, INSERM UMRS 1258, Université de Strasbourg, 67404 Illkirch, France

²Complex Systems and Translational Bioinformatics (CSTB), ICube laboratory – CNRS, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Université de Strasbourg, 67000 Strasbourg, France

*Correspondence to Jocelyn Laporte: IGBMC, 1 rue Laurent Fries, 67404 Illkirch, France; Phone +33388653412; Email jocelyn@igbmc.fr

**Keywords:** skeletal muscle maturation; alternative splicing; differential expression; myopathy; Lrp4

## Abstract

Gene differential expression (DE) and alternative splicing (AS) are mechanisms that give rise to a plethora of tissue-specific transcripts. While these mechanisms have been studied in various tissues, their role during muscle maturation is not well understood. Since this stage of development is impaired in multiple muscular diseases, we used RNA-seq to analyze transcriptome remodeling in skeletal muscle from late embryonic stage (E18.5) to adult mouse (7 weeks). Major transcriptomic changes were detected, especially in the first two weeks after birth with a total of 8571 DE genes and 3096 AS genes. Comparison of these two mechanisms showed that they regulate different biological processes essential for the structure and function of skeletal muscle. Investigation of genes mutated in muscle disorders revealed previously unknown transcripts. In particular, we validated a novel exon in *Lrp4*, a gene mutated in congenital myasthenia, in mice and human. Overall, the characterization of the transcriptome in disease-relevant tissues revealed key pathways in the regulation of tissue maturation and function. Importantly, the exhaustive description of AS and resulting transcripts can improve genetic diagnosis.
**Summary statement**

This study utilizes RNA-sequencing to reveal major transcriptome remodeling through differential expression and alternative splicing during postnatal skeletal muscle maturation in mice.

**Introduction**

Skeletal muscle represents about half of the total weight of the human body. It has diverse functions including breathing, mobility, and metabolic activities. Muscle development has been extensively studied and is composed of the following steps: differentiation of progenitors into myoblasts, fusion of myoblasts into multinucleated myotubes which maturate into myofibers, and growth of myofibers first through fusion with myoblasts issued from satellite cells then through cell autonomous hypertrophy (Buckingham *et al.*, 2003; Bentzinger, Wang and Rudnicki, 2012; Chal and Pourquié, 2017). In mice, differentiation and fusion of myoblasts occur in the late embryonic stage, around embryonic day 10.5-12.5 (E10.5-E12.5), formation of myofibers occurs in the fetal stage from E14.5-E17.5 until birth, myofiber hypertrophy through cell fusion from birth to weaning (about 2-3 weeks), and myofiber hypertrophy triggered by growth factors signaling from weaning to adulthood (3 to 7 weeks) (Biressi *et al.*, 2007). Pre- and post-natal muscle development and maturation is affected in a plethora of muscle diseases including the severe congenital myopathies and muscular dystrophies (Jungbluth *et al.*, 2018; Mercuri, Bönnemann and Muntoni, 2019).

Postnatal muscle development and maturation is governed by multiple mechanisms including external cues, cellular pathways and reconfiguration of molecular composition. Among these mechanisms, transcriptome remodeling is key and includes specific regulation of gene expression and alternative splicing (AS). AS is the process by which one gene can lead to different transcripts and subsequently potential protein isoforms. In recent years, next generation sequencing technologies have allowed the characterization of changes in gene expression and/or AS during skeletal muscle development in different experimental systems and animal models, especially concerning muscle cell differentiation (Brinegar *et al.*, 2017; Spletter *et al.*, 2018; Dos Santos *et al.*, 2023; Wang *et al.*, 2023).

Here, we report an extensive characterization of the transcript expression and splicing found in mouse skeletal muscle during postnatal maturation, focusing particularly on genes associated with myopathies. Using bulk RNA sequencing, we studied key points in muscle maturation: the end of the embryonic development at E18.5 just before birth, the maturation of the muscle by fusion of satellite cells at 2 weeks, and the mature adult muscle at 7 weeks. Specific patterns of gene expression and splicing were identified. Additionally, the
transcriptome characterization of myopathy-associated genes revealed distinct features and previously unknown exons associated with these genes.

# Results

## Morphological hallmarks of postnatal skeletal muscle maturation

To understand the morphological changes taking place during postnatal muscle development in mice, we first performed tibialis anterior muscle histology at one day (P1), 2 weeks (2w), and 7 weeks (7w) after birth (n=3 for each age). At P1, hematoxylin and eosin (HE) staining revealed small and rounded myofibers with occasionally internalized nuclei, which are hallmarks of immature myofibers (Fig. 1A, top panel). Over time, the diameter of myofibers increased and they achieved their characteristic polygonal shape at 2w, with further development observed at 7w. From 2w, nuclei were positioned under the sarcolemma, as expected in mature myofibers. Oxidative staining was carried out for nicotinamide adenine dinucleotide (NADH) and succinate dehydrogenase (SDH). These stains were used to assess the internal architecture of myofibers, their metabolic activity and to differentiate between oxidative slow fibers (dark) and glycolytic fast fibers (light). NADH stain revealed homogeneously stained myofibers at P1, whereas the two fiber types were distinguishable at 2w and even more so at 7w (Fig. 1A, middle panel). SDH stain was used to compare the mitochondrial oxidative activity at the different ages. At P1, only a weak oxidative activity was observed, and increased with time at 2w and 7w, also revealing the 2 populations of myofibers (Fig. 1A, bottom panel). Finally, electron microscopy (EM) was used to investigate the ultrastructure of maturating myofibers (Fig. 1B). Z disks, A and I bands were observed at all ages, but were better defined at 2w and 7w, supporting the premise that sarcomeres are already formed at birth. At P1, sarcomeres and Z disks were misaligned, and no triads were observed. Sarcomere alignment and triads are observed from 2w. Overall, these investigations highlight important changes in the intracellular structures, organelle organization and metabolic profile during postnatal muscle maturation.

## Transcriptome remodeling impacts more genes during early postnatal maturation than late postnatal maturation

We hypothesized that the normal postnatal maturation of skeletal muscle is driven by transcriptome remodeling through either gene differential expression (DE) or alternative splicing (AS). We performed 100 bp paired-end bulk RNA sequencing at key timepoints during postnatal muscle maturation in male WT mice: at E18.5 (just before birth) in hindlimb
muscles and at 2w and 7w in the tibialis anterior. For each age, four biological replicates were included. Differential gene expression and splicing analyses were carried out between E18.5 and 2w for early stage postnatal maturation and between 2w and 7w for late stage (Fig. 2A).

Principal component (PC) analysis based on gene expression separated the different timepoints (Fig. 2B). Indeed, PC 1 and 2 reveal three distinct groups of samples corresponding to E18.5, 2w and 7w. In particular, PC1 (75% of variance) separated E18.5 samples from the other two groups. In terms of DE, a total of 8571 genes were differentially expressed during the early stage between E18.5 and 2w, and 1880 genes during the late stage between 2w and 7w with a threshold of absolute log2 fold-change (log2FC) higher than 1 and an adjusted p-value < 0.05 (Fig. 2C, Fig. S1, Tables S1-2). During early maturation, DE genes were evenly divided between upregulation and downregulation, whereas over 70% of late-stage DE genes were downregulated (Fig. S2A). Additionally, 57% (1071 genes) of the late DE genes were also differentially expressed during early maturation (Fig. 2C). Among these genes, 77% exhibited a consistent evolution over time, while the rest showed opposite DE between early and late stage (Fig. S2A-B). Enrichment analysis of Gene Ontology (GO) terms revealed different processes affected at each stage (Fig. 2D, Fig. S3, Tables S3-6). Early maturation was characterized by upregulation of genes related to muscle structure and mitochondrial organization, muscle contraction and energy metabolism, and by downregulation of genes implicated in organ morphogenesis, synapse assembly, cell cycle, and cell adhesion processes. During late maturation, there was mainly downregulation of genes associated with cell cycle and extracellular matrix related processes.

We then investigated AS by identifying AS events with significant differential inclusion between the different timepoints. PC analysis based on percent spliced in (PSI) values of AS events separated the different timepoints, similarly to PC analysis on gene expression (Fig. 2E). In particular, a separation of E18.5 samples from the other ages was observed on PC1 (31% of explained variance). During early postnatal maturation, 3096 genes underwent AS (with a total of 4881 significant AS events) compared to 1094 genes during late postnatal maturation (with a total of 1593 significant AS events) (Fig. 2F, Fig. S4A). In total, 50% of the late AS events were also significantly detected during early maturation (Fig.S4A). Among these events, 66% exhibited a consistent inclusion evolution over time, while the rest showed opposite differential inclusion between early and late stage (Fig. S4A-B). Over 71% of genes undergoing AS during late maturation were also modulated during early maturation, and GO enrichment analysis showed that, at both stages, AS genes were associated with similar processes, including gene expression regulation, RNA processing, protein localization and transport, catalytic complex and sarcomere organization (Fig. 2G, Fig. S5, Tables S7-8). To
investigate the mechanisms regulating splicing, we extracted the list of genes associated to the GO term "RNA splicing" (GO:0008380) and we evaluated whether these genes exhibited significant DE or AS during postnatal muscle maturation (Table S9). Out of 376 genes associated to RNA splicing, 69 underwent DE during early maturation (5 during late maturation). On the other hand, 113 of these genes showed AS during early maturation (50 during late maturation). These findings highlight that a subset of genes associated with RNA splicing undergo significant DE and AS during postnatal muscle maturation, with pronounced activity during the early maturation phase. We then used the SplicingLore database (Polvèche et al., 2023), which correlates splicing factors with alternative exons, to identify targets of the splicing-associated genes exhibiting DE and AS during early and late maturation (Table 1). Out of the 3096 genes undergoing early AS, 33% were targets of early DE splicing-associated genes, and 58% were targets of early AS splicing-associated genes. Similarly, splicing-associated genes undergoing late DE and AS were respectively linked to 23% and 55% of the 1094 late AS genes. Therefore, DE and AS of splicing-associated genes may explain the numerous AS events observed during early and late postnatal muscle maturation. Overall, the transcriptome was highly remodeled during the first two weeks of postnatal maturation, both in terms of expression and in splicing changes.

## Differential gene expression and alternative splicing modulate different genes and pathways

To investigate whether gene DE and AS regulated the same processes during postnatal maturation, we compared the list of genes that were differentially expressed or that underwent an isoform switch during early and late stages. In total, 1319 genes were both differentially expressed and alternatively spliced, which corresponded to 14% of the DE genes and 39% of the AS genes (Fig. 3A). To identify the processes regulated by these two different mechanisms, we performed GO term enrichment analysis on genes specifically associated to DE (8061 genes) (Fig. 3B, Table S10), specific to AS (2085 genes) (Fig. 3C, Table S11), or shared by both (1319 genes) (Fig. 3D, Table S12). DE-specific genes were associated to ion transport, synapse assembly, and cell adhesion, while AS-specific genes were associated to protein transport, mRNA processing and chromatin organization. Genes regulated by both DE and AS mechanisms were mainly linked to muscle organization and contraction, as well as mitochondrial function. Therefore, while key muscle processes were regulated by both alternative splicing and gene differential expression, nervous system processes that may be linked to the establishment of the neuro-muscular junction were specifically regulated by differential expression while alternative splicing regulated transcription-related processes.
Transcriptomic characterization of myopathy-associated genes during muscle maturation

Next, we investigated whether the genes mutated in myopathies have specific expression
patterns during skeletal muscle development. A list of 199 human myopathy genes was
extracted from the Muscle Gene Table (Benarroch et al., 2020). We extracted gene
characteristics such as the number of transcripts, exons and paralogs, the gene and CDS
length from the Ensembl database for all protein coding genes in mouse and human. We
then compared the characteristics of myopathy genes to the remaining protein coding genes
found in the genome. In mouse, the 199 myopathy genes orthologs were compared with the
remaining 21601 protein-coding genes found in the murine genome. Statistical comparison of
the distribution of myopathy genes and all protein coding genes revealed that myopathy
genes display increased number of transcripts, gene length, maximum number of exons,
average CDS length, and expression level in skeletal muscle (Fig. 4A). Similar conclusions
were drawn from the human data, with the addition of a significantly increased number of
paralogs (Fig. S6). A correlation between gene length and number of exons and transcripts is
expected. Conversely, a higher number of paralogs would suggest a partial functional
redundancy and possible compensation. However, paralogs of myopathy genes are often
expressed in different tissues, like *RYR1* and *RYR2* or *CASQ1* and *CASQ2* for skeletal or
cardiac muscles respectively, or *AMPH* and *BIN1* for brain and skeletal muscle according to
the Gene-Tissue Expression (GTEx) portal (Lonsdale *et al.*, 2013).

Based on our RNA-seq data in mice, 105 (53%) myopathy genes were differentially expressed during early maturation, compared to only 11 (6%) myopathy genes in late maturation, suggesting myopathy genes are preferentially implicated in early muscle maturation (Fig. 4B-C). Of note, *Scn4a*, *Mymk*, *Mb*, *Megf10*, *Chrng*, *Phka1*, *Duxbl1* and *Tnnt1* appeared to be modulated during both early and late maturation. In addition, genes coding for proteins implicated in calcium handling, myofilaments and neuromuscular junction were highly upregulated during the early stage corresponding to the final maturation of these functions, while *Mymk* (Myomaker; mediating the fusion of myoblasts to form myocyte syncytia) was highly downregulated at the late stage when muscle cell fusion is finished.

During development, AS plays a crucial role in the generation of protein diversity from a
single gene. We investigated the repartition of the five common types of AS events:
alternative 3' and 5' splice sites (A3SS, A5SS), mutually exclusive exons (MXE), retained
intron (RI), and cassette exons (CE) in myopathy-associated genes and other protein-coding
genes (Table 2). For myopathy-associated genes, CE and MXE events were the most
prevalent with 149 CE events and 118 MXE events during early maturation and 80 CE
events and 40 MXE events during late maturation, similarly to other protein coding genes. In
myopathy-associated genes, many significant AS events were detected in *Neb* (127 early AS events, 59 late AS events) (Table S13). This result is consistent with the size and the complexity of this gene, which encodes transcripts containing up to 165 exons. However, only 14 early AS events and 3 late AS events were detected in *Ttn*, which encodes transcripts containing up to 347 exons. To limit the influence of *Neb* on the comparison of myopathy-associated genes with other protein-coding genes, we then considered the percentage of genes affected by each type of AS event (Fig. 4D). Myopathy-associated genes were more affected by CE (19.1% of genes affected during early maturation, 13.6% during late maturation) and MXE (19.1% of genes during early maturation, 3.5% during late maturation) events compared to other protein-coding genes (percentage of genes affected by early CE: 7%, late CE: 2.8%, early MXE: 5.2%, late MXE: 0.7%). A similar percentage of genes affected by A5SS, A3SS and RI events were found in myopathy genes compared to the other genes. AS events can potentially modulate protein function through changes in mRNA stability, protein stability, and protein domain composition, suggesting that the impacted genes may have different specific functions in skeletal muscle.

## Known and new alternative exons in myopathy genes

To further characterize AS events in myopathy genes in mice, we focused our analysis on alternative exons, using de novo transcript assembly.

The benefit of finding new exons is highlighted by recent data and our present results concerning alternative exons specifically expressed in skeletal muscle and impacting protein functions. For example, the alternative exon 11 of *Bin1* showed an increased inclusion during muscle maturation (ΔPSI (percent spliced in) = 0.107 between E18.5 and 2w, ΔPSI = 0.02 between 2w and 7w) (Fig. S7). Previous studies found it was mainly expressed in skeletal muscle and barely in any other tissues investigated (Butler *et al.*, 1997; Lee *et al.*, 2002; Cowling *et al.*, 2017). It encodes an in-frame sequence of 15 basic amino acids implicated in the regulation of an open-close conformation impacting the interaction with other proteins such as dynamin 2 (Kojima *et al.*, 2004). The alternative exon 12b of *Dnm2* encoding dynamin 2 showed an increased inclusion during muscle maturation (ΔPSI = 0.153 between E18.5 and 2w, ΔPSI = 0.151 between 2w and 7w) and is mainly found in skeletal muscle (Fig. S8) (Gómez-Oca *et al.*, 2022). Exclusion of exon 12b has been shown to exacerbate phenotypes of X-linked centronuclear myopathy in a mouse model (Gómez-Oca *et al.*, 2022). Both *BIN1* and *DNM2* genes are mutated in autosomal centronuclear myopathies.

In addition to already known alternative exons, we also searched for previously unknown exons in myopathy genes. By performing mixed transcript assembly and comparing the de novo transcripts to the reference genome, we identified a total of 280 exons in myopathy
associated genes with at least one new boundary (Fig. 5A). New boundaries refer to
previously unreported exon-intron junctions, altering the boundaries of existing exons or
introducing new exons entirely. We then selected novel exon candidates with an average
coverage greater than 5 reads, and that were expressed at least 10 times more than the
surrounding intronic background. Finally, we removed candidates without canonical splice
sites, and obtained 28 potential novel exons. Each candidate was then assessed manually to
compare its expression to the flanking exons (Fig. 5B). For example, a previously unknown
*Lpr4* exon was confirmed through RT-PCR and Sanger sequencing. *Lrp4* encodes a receptor
for agrin and is critical for the formation and maintenance of the neuromuscular junction. This
exon 37B is located between exons 37 and 38 of *Lrp4* and its expression level is similar to
that of the flanking exons (Fig. 5B). It is expressed at all ages. This exon 37B is composed of
62 nucleotides framed by canonical splice sites, and introduces an early stop codon after 14
amino acids, leading to the loss of charged residues compared to the canonical protein (Fig.
5C, Fig. S9). Using RT-PCR and Sanger sequencing, we confirmed the presence of exon
37B in male and female mice at 8w (Fig. 5D-E). This exon is highly expressed in skeletal
muscles (tibialis anterior, diaphragm, soleus) and in the heart. A lower expression of exon
37B was also detected in lung, and a faint signal was present in thymus and brain. No
expression of exon 37B was detected in liver, spleen, kidney, pancreas, testis and ovary.
These results indicate that exon 37B may be preferentially expressed in muscle. Alignment
of the exon 37B sequence to the human genome revealed a match located between exons
37 and 38 of the human *LRP4* gene (Fig. 5F). The human and murine sequences showed
91% pairwise identity, with 6 mismatches over 66 nucleotides, and were flanked by canonical
splice sites. This exon is also present in a predicted transcript of *LRP4* (XM_017017734.2)
but has never been confirmed. Using RT-PCR, we confirmed the presence of exon 37B in
male and female human muscle samples, but not in LHCNM2 and C25 myoblasts, HeLa
cells or fibroblasts (Fig. 5G). In conclusion, we were able to validate a new exon in *Lrp4* in
mouse, that is highly expressed in muscle tissues, and confirm its presence in human muscle
samples. While this exon had been computationally predicted in human, it had never been
confirmed, which may be due to its muscle-specific expression pattern.

Discussion

Muscle maturation is defective in a plethora of muscle diseases and tightly regulated via transcriptome modulation. In this work, we investigated the mouse transcriptome at three important key points of skeletal muscle maturation, with a particular focus on myopathy-associated genes. We showed that the transcriptome is greatly remodeled during the early stage of development, either by transcription regulation or by alternative splicing. We then
detailed the differences between myopathy-associated genes and other protein-coding
genes. Finally, we were able to detect and validate a novel exon in *Lrp4*, a gene implicated in
congenital myasthenic syndrome in human (Ohkawara *et al.*, 2014).

Transcriptome remodeling during postnatal muscle maturation

To better understand the regulation of postnatal muscle maturation, we compared histological and structural changes with DE genes and AS events. The myofiber intracellular organization is achieved within the first two weeks of age as shown by the histological and electron microscopy analyses. Concomitantly, we found an extensive remodeling of the transcriptome during the first two weeks of postnatal muscle maturation in mice compared to later stages. Our data are consistent with the findings of a previous study in mice (Brinegar et al., 2017), as in both cases DE and AS analyses revealed that the transcriptome is highly remodeled during the first two weeks after birth. Additionally, our study provides enhanced robustness to the findings by including biological replicates, which were not incorporated in the prior work. These observations reflect the changes averaged over many cell types, since the bulk RNA-seq on tibialis anterior (2w and 7w) and hindlimb muscles (E18.5) performed here did not allow observations at the single cell resolution.

Notably, we observed only a partial overlap between genes that are differentially expressed and those that are alternatively spliced. These results suggest that DE and AS control different mechanisms across time. Genes regulated by DE or by AS code for different pathways during early maturation. DE mainly impacts sarcomere and mitochondrial organization, muscle contraction and energy metabolism, and cell division, while AS modulates mRNA processing, protein localization, muscle development and organelle organization (Fig. 2). These findings correlate with the known maturation events, i.e. decreased cell division and increased structural organization of the myofibers with improved muscle contraction relying on an established metabolism. Indeed, our transcriptome analysis correlates with the histological and ultrastructural investigations. The mitochondrial oxidative activity highlighted by SDH staining progressively increases with age and reaches the adult status only after weaning. This staining also highlights that mitochondria organization matures at the early stage, in parallel to the nuclei position from internalized to sub-sarcolemmal depicted by HE staining and EM (Fig. 1). EM investigations also reveal that sarcomeres are fully matured by 2 weeks with aligned Z-disks and organized triads, correlating with enrichment of sarcomere-related pathways (modulated by DE and AS) and ion channel pathways (dependent mainly on DE) respectively (Fig. 3). Indeed, efficient muscle contraction relies on these pathways.
Overall, our results indicate that DE and AS are complementary mechanisms extensively remodeling the transcriptome during postnatal muscle maturation, leading to the final myofiber organization and efficient contraction.

## Differential expression and alternative splicing in myopathy-associated genes

As discussed above, the muscle transcriptome is extensively remodeled in the first two weeks of postnatal maturation. Defects in perinatal muscle maturation cause a plethora of muscle diseases, especially congenital myopathies and muscular dystrophies. Interestingly, myopathy genes are generally longer than other genes, e.g. *TTN* has the longest coding sequence encoding titin, the longest protein in mammals and *DMD* spans the longest genomic sequence with 2.4 Mb. This suggests myopathy genes may be more susceptible to alternative splicing and we indeed found that they generate a higher number of different transcripts (Fig. 4).

To our knowledge, this work represents the first detailed characterization of the AS events associated with a specific disease class in normal conditions during development. The five main AS forms, including A3S, A5S, MXE, AE and IR, have been studied here. Although AS events vary during maturation when considering all the genes, alternative exon (AE) was the most predominant event, in agreement with other studies (Sultan *et al.*, 2008; Brinegar *et al.*, 2017). Unexpectedly, we found myopathy genes displayed an enrichment for cassette mutually exclusive exon events. Most myopathy genes are highly expressed in muscle, and an association between cassette and mutually exclusive exon events and muscle has previously been reported (Hatje *et al.*, 2017). Moreover, in the same study, a high proportion of mutations was found in these exons which are also more specifically expressed in muscle.

Overall, genes and mutually exclusive and alternative exons that are expressed mainly in skeletal muscle and highly modulated during maturation appear to be excellent candidates to elucidate the missing heritability in myopathies, as nearly half of patients are still lacking genetic diagnosis. Identifying pathogenic mutations from genome or exome sequencing is challenging, and transcript usage may be tissue and age specific, meaning that clinicians may overlook relevant transcripts or exons when searching for mutations.

In this regard, the identification of previously unknown alternative exons in myopathy genes is essential. In this study, we identified and validated a novel exon in *Lrp4*. The candidate exon 37B identified in mouse was confirmed in human muscle samples. The resulting novel transcript lacks the sequence encoding the C-terminal charged region which may impact on the structure, stability and/or function of the protein.
In conclusion, the characterization of the transcriptome in disease-relevant tissues reveals novel pathways essential for the regulation of tissue maturation and function, and the exhaustive description of alternative splicing events and resulting transcripts may improve genetic diagnosis.

# Materials and Methods

## Animal and sample collection

In this study, we analyzed WT male mice at different ages (E18.5, 2 and 7 weeks) on a 129Pas genetic background. The mice were bred in the IGBMC animal facility in France according to French and European regulations and approved by institutional ethics committee (#2019101416421345). Four biological replicates were included for each age. Tibialis anterior muscles were dissected at 2 and 7 weeks, and hindlimb leg muscles were dissected at E18.5.

## RNA extraction, library preparation, sequencing

RNA was extracted from muscles with Trizol reagent (Molecular Research Center, Cincinnati, OH, USA). RNA-seq libraries were prepared with the TruSeq stranded mRNA sample preparation kit by poly(A) selection and then sequenced on a HiSeq 4000 as paired-end 100-bp reads.

After sequencing, reads were preprocessed using cutadapt (version 1.10)(Martin, 2011) to remove adaptor, poly(A), and low-quality sequences (Phred quality score below 20). Reads shorter than 40 bases were excluded for downstream analysis. Then, reads were mapped to the mm39 assembly of the Mus musculus genome with STAR (versions 2.5.3) (Dobin *et al.*, 2013). Quantification of gene expression was achieved using the python package htseq-count, in the union mode with Ensembl release 104 annotations.

## Transcriptome analysis

The full code and package versions used to produce the results are provided in a Quarto notebook and associated R and bash scripts as supplementary material in Zenodo: https://doi.org/10.5281/zenodo.14188535.

To analyze gene differential expression (DE), we processed the count table in the open-source RStudio environment for R (version 4.1.1) with Bioconductor packages. DESeq2 was used to normalize, fit, and compare the data between groups (Love, Huber and Anders,
2014). The cutoff value for DE was set to adjusted p-value < 0.05 and absolute value of
log2FC > 1.

Alternative splicing (AS) events were identified and quantified with rMATS-turbo (Shen et al., 2014; Wang et al., 2024). Statistically significant events were determined according to the recommended criteria of rMATS-turbo (Wang et al., 2024). In particular, AS events were defined as true events if the difference between two conditions was significant with adjusted p-value (FDR) < 0.01 and |ΔPSI| > 0.05. Raw rMATS-turbo outputs are provided as supplementary material in Zenodo: https://doi.org/10.5281/zenodo.14188535.

GO term enrichment analysis was performed with ClusterProfiler (Wu et al., 2021), and
enriched GO terms were clustered based on their semantic similarity (Yu, 2020).

To identify new exons, we performed mixed transcript assembly with StringTie (Pertea et al., 2015), and novel exon candidates were identified with gffcompare (Pertea and Pertea, 2020).

Myopathy-associated genes

Myopathy-associated genes were retrieved from the Muscle Gene table website (https://musclegenetable.fr/) (Benarroch et al., 2020). The following muscle disease classes were considered for the analysis: metabolic myopathies, congenital muscular dystrophies, congenital myopathies, distal myopathies, others myopathies, congenital myasthenic syndromes, muscular dystrophies and ion channel muscle diseases. Mouse orthologs of genes causing muscle diseases, as well as characteristics for human and mouse genes (transcript information, gene length, number of paralogs) were retrieved with Biomart from Ensembl (Kinsella et al., 2011). Human gene expression level in skeletal muscle was retrieved from the Gene-Tissue Expression (GTEx) Portal (Lonsdale et al., 2013).

Histology analysis

Samples were frozen in liquid nitrogen-cooled isopentane and stored at -80°C. Transversal cryosections (8 µm) were prepared and stained, and were observed using the Hamamatsu 322 NanoZoomer 2HT slide-scanner.

Electron microscopy

Samples were fixed by immersion in 2.5% glutaraldehyde and 2.5% paraformaldehyde in cacodylate buffer (0.1 M, pH 7.4), and washed in cacodylate buffer for further 30 min. The samples were postfixed in 1% osmium tetroxide in 0.1 M cacodylate buffer for 1 h at 4°C and dehydrated through graded alcohol (50, 70, 90 and 100%) and propylene oxide for 30 min
each. Samples were oriented and embedded in Epon 812. Semithin sections were cut at 2 µm and ultrathin sections were cut at 70 nm (Leica Ultracut UCT) and contrasted with uranyl acetate and lead citrate and examined at 70 kV with a Morgagni 268D electron microscope (FEI Electron Optics) equipped with a Mega View III camera (Soft Imaging System) or with a Philips CM12 electron microscope equipped with a Gatan OneView Camera (Gatan).

### RT-PCR

To validate the results obtained from the RNA-seq, RT-PCR were performed with the primers indicated in Table 3. cDNA was synthesized with Superscript IV transcriptase (Thermo Fisher Scientific, Waltham, MA, USA).

### Cell lines and human samples used for RT-PCR

Myoblasts (LHCN-M2, C25), HeLa cells, and fibroblasts were obtained from the PluriCell East platform and were properly assessed for contamination. Human paravertebral muscle tissue was donated with informed consent by 3 patients (two females, one male) who were undergoing surgical treatment for scoliosis.

### Protein structure visualization

Protein structure visualization was rendered using the PyMOL Molecular Graphics System, Version 3.1 Schrödinger, LLC. The protein structure of LRP4 was downloaded from the AlphaFold Protein Structure Database (accession: AF-Q8VI56-F1-v4) (Jumper et al., 2021; Varadi et al., 2022).

### Acknowledgments

We thank Christine Kretz and Nadia Messaddeq for technical assistance, the MYOBANK-AFM of the Myology Institute, Stéphane Vasseur, Maud Chapart and Yvan de Feraudy for the human samples, the IGBMC histology platform for histology staining, the PluriCell East Platform for cell culture services, and the Genomeast platform for RNA-seq.

### Competing interests

The authors declare no competing interests.
## Funding

The work of the Interdisciplinary Thematic Institute IMCBio, as part of the ITI 2021-2028 program of the University of Strasbourg, CNRS and Inserm, was supported by IdEx Unistra (ANR-10-IDEX-0002), and by SFRI-STRAT'US project (ANR-20-SFRI-0012) and EUR IMCBio (ANR-17-EURE-0023) under the framework of the France 2030 Program. This work was also funded by Association Française contre les Myopathies-Téléthon (23933), the Muscular Dystrophy Association (576154), and the Fondation pour la Recherche Médicale (201903007992). AS is a fellow of Ecole Inserm Pfizer Innovation and recipient of the Société Française de Myologie Master research fund.

## Data availability

The RNA-seq data used in this paper are publicly available on NCBI's GEO:GSE214621. The code used to analyze the data is provided as supplementary material on Zenodo: https://doi.org/10.5281/zenodo.14188535.

## Authors' contributions

JL designed and supervised the study. AS and SD performed bioinformatics analyses with the help of JT. DR performed histology. PB performed RT-PCR. AS, SD and JL wrote the manuscript.

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<figure><img src="image_2.png" /><figcaption>Figures and Tables</figcaption></figure>
**Fig. 1. Morphological hallmarks of postnatal skeletal maturation in mice. (A)**

Representative histology of tibialis anterior muscle at P1, 2w, and 7w with HE stain (top panel), NADH stain (middle panel) and SDH stain (bottom panel). Scale bar 50µm. (B) Representative electron microscopy of skeletal muscle at P1, 2w and 7w. N indicate nuclei, empty arrows indicate Z disks and full arrows indicate triads. Scale bar 5µm for top panels, 500nm for bottom panels, n=3 for each age.
<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

GO enrichment early DE

<figure><img src="image_8.png" /></figure>

<figure><img src="image_9.png" /></figure>

GO enrichment late DE

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

GO enrichment early AS

<figure><img src="image_15.png" /></figure>

GO enrichment late AS

<figure><img src="image_16.png" /></figure>

**Fig. 2.** AS and DE impact more genes in early post-natal muscle maturation than in late maturation. (A) Stages of postnatal muscle maturation. (B) Principal component analysis of the samples based on gene expression. (C) Proportional Venn diagram of differentially expressed (DE) genes during early and late maturation. (D) Main enriched GO terms in DE genes during early and late maturation. Arrows next to the enriched GO terms indicate they are enriched in upregulated genes (red upward-pointing arrow) or downregulated genes (blue downward-pointing arrows). (E) Principal component analysis of the samples based on AS events PSI (percent spliced in) values. (F) Proportional Venn diagram of AS genes (G) Main enriched GO terms in AS genes during early and late maturation. Tibialis anterior muscle was used at 2w and 7w, and hindlimb muscles were used at E18.5, n=4 for each age.
<figure><img src="image_17.png" /><figcaption>**Fig. 3.** Gene differential expression (DE) and alternative splicing (AS) modulate different genes and pathways in mice. (A) Proportional Venn diagram of DE and AS genes. (B) Enrichment analysis of DE-specific genes (C), AS-specific genes, (D) genes affected by both DE and AS. BP: biological process, CC: cellular component, MF: molecular function.</figcaption></figure>
<figure><img src="image_18.png" /><figcaption>**Fig. 4.** Transcriptomic characterization of myopathy-associated genes during muscle maturation. (A) Distribution of the number of transcripts, gene length, maximal number of exons, average CDS length, number of paralogs and expression in skeletal muscle in myopathy-associated genes compared to other protein-coding genes in mouse. (B & C) Volcano plot of myopathy-associated genes during early (B) and late (C) maturation in mice. Genes with an absolute log2FC > 1 and adjusted p-</figcaption></figure>
value < 0.05 are colored in red. (D) Comparison of AS events in myopathy-associated genes and other protein-coding genes in mice. CE: cassette exon, RI: retained intron, MXE: mutually exclusive exons, A5SS: alternative 5' splice site, A3SS: alternative 3' splice site. The percentage of genes affected by each type AS event during early and late maturation is shown.
A

Analysis pipeline

Tool

<figure><img src="image_19.png" /></figure>

HISAT2

Mixed transcript
assembly
(reference & de novo)

StringTie

Detection of novel
exons in de novo
transcripts

gffcompare

Quality control of novel
exons candidates

Bioinformatics
and wet bench
experiments

B

<figure><img src="image_20.png" /></figure>

C

<figure><img src="image_21.png" /></figure>

D

<figure><img src="image_22.png" /></figure>

E

<figure><img src="image_23.png" /></figure>

F

<table><thead><tr><th></th><th>Identities<br>60/66(91%)</th><th>Gaps<br>0/66(0%)</th></tr></thead><tbody><tr><td>Mouse 1</td><td>agCAGCTCTTCCATCCCTCTGATAGCCTTTCAC</td><td>33</td></tr><tr><td>Human 1</td><td>agCAGCTCTTTCACCCCTCTGATAGTCTTTCAC</td><td>33</td></tr><tr><td>Mouse 34</td><td>CCTTTCTCTTCTGATTGCCTCTTGAGTTCAGgt</td><td>66</td></tr><tr><td>Human 34</td><td>CTTTTCTCTTCTGATTTCCTCTTGATTTCAGgt</td><td>66</td></tr></tbody></table>

G

<figure><img src="image_24.png" /><figcaption>**Fig. 5.** Discovery of new exons in myopathy-associated genes. (A) Analysis pipeline. (B) Visualization of the coverage of *Lrp4* exon 37B in the samples at E18.5, 2w and 7w using the Integrative Genomics Viewer (IGV). (C) Schema of exon 37B in *Lrp4*. (D) Detection of *Lrp4* exon 37b by RT-PCR gel electrophoresis in several tissues in male and female WT mice at 8 weeks (n=1 for each tissue/sex combination). (E) Sanger sequencing of the RT-PCR product. (F) Alignment of the murine 37B exon sequence with the human genome. (G) Detection of *LRP4* exon 37B by RT-PCR gel electrophoresis in myoblasts (LHCN-M2, C25), HeLa cells, fibroblasts, and healthy human paravertebral muscle samples (n=3, 2 females, 1 male).</figcaption></figure>
<table><caption>**Table 1.** Analysis of the impact of DE and AS in splicing-associated genes during early and late postnatal muscle maturation.</caption><thead><tr><th></th><th>Early DE</th><th>Late DE</th><th>Early AS</th><th>Late AS</th></tr></thead><tbody><tr><td>Number of affected splicing-associated genes (GO:0008380)</td><td>69</td><td>8</td><td>113</td><td>50</td></tr><tr><td>Number of affected splicing-associated genes found in SplicingLore</td><td>8</td><td>2</td><td>26</td><td>15</td></tr><tr><td>Number of targets retrieved from SplicingLore</td><td>6264</td><td>1782</td><td>26581</td><td>15992</td></tr><tr><td>Number of targets exhibiting AS at the corresponding stage</td><td>1004</td><td>250</td><td>1781</td><td>596</td></tr></tbody></table>

<table><caption>**Table 2.** Number of significant AS events in myopathy-associated genes and other protein coding genes in mice. CE: cassette exon, RI: retained intron, MXE: mutually exclusive exons, A5SS: alternative 5' splice site, A3SS: alternative 3' splice site.</caption><thead><tr><th rowspan="2">Type of AS event</th><th colspan="2">Number of events in myopathy-associated genes</th><th colspan="2">Number of events in other protein-coding genes</th></tr><tr><th>Early</th><th>Late</th><th>Early</th><th>Late</th></tr></thead><tbody><tr><td>CE</td><td>149</td><td>80</td><td>2547</td><td>879</td></tr><tr><td>RI</td><td>3</td><td>6</td><td>693</td><td>270</td></tr><tr><td>MXE</td><td>118</td><td>40</td><td>1845</td><td>256</td></tr><tr><td>A5SS</td><td>3</td><td>0</td><td>204</td><td>53</td></tr><tr><td>A3SS</td><td>6</td><td>3</td><td>285</td><td>82</td></tr></tbody></table>
<table><caption>Table 3. RT-PCR primers</caption><thead><tr><th>Gene</th><th>Primer sequence</th><th>Product size (bp)</th></tr></thead><tbody><tr><td>Lrp4 37B</td><td>F 5' CTCTTCCATCCCTCTGATAGCCTTTCACC<br>3'<br>R 5' CGCGTTGTTATGTGAGCACAAGGATCAG<br>3'</td><td>473</td></tr><tr><td>LRP4 37B</td><td>F 5' AGAAAGAG/CAGCTCTTTCACCCCTCTG 3'<br>R 5' CTCAGACTGCTCTTCCTGTAACAG 3'</td><td>299</td></tr></tbody></table>
A

Early DE

<figure><img src="image_25.png" /></figure>

B

Late DE

<figure><img src="image_26.png" /></figure>

**Fig. S1. MA scatter plots showing log2FC and mean normalized transcript expression during (A) early muscle maturation, (B) late muscle maturation. Genes with an adjusted P-value < 0.05 are shown in blue, red dashed lines indicate |log2FC| = 1, triangles indicate genes with log2FC values exceeding the plotting limits (99th percentile of values)**
A

DE genes specific to
early (light orange) or
late (dark orange) stages

<figure><img src="image_27.png" /></figure>

<figure><img src="image_28.png" /></figure>

B

<figure><img src="image_29.png" /></figure>
Fig. S2. Comparison of differential gene expression between early and late maturation.

(A) UpSet plot showing the intersections between genes that are up- or down-regulated during early and late muscle maturation. Dots indicate that the gene is present in the corresponding set on the left side of the bottom matrix. (B) Heatmap of normalized expression levels for the 1071 genes that are differentially expressed during both early and late muscle maturation
<figure><img src="image_30.png" /></figure>

<figure><img src="image_31.png" /></figure>

<figure><img src="image_32.png" /></figure>

<figure><img src="image_33.png" /><figcaption>**Fig. S3.** Enrichment analysis of genes (A) upregulated during early muscle maturation, (B) downregulated during early muscle maturation, (C) upregulated during late muscle maturation, (D) downregulated during late muscle maturation</figcaption></figure>
AS events specific to
early (light purple) or
late (dark purple) stages

A

<figure><img src="image_34.png" /></figure>

B

<figure><img src="image_35.png" /></figure>
Fig. S4. Comparison of alternative splicing events between early and late maturation.

(A) UpSet plot showing the intersections between significant AS events during early and late muscle maturation. Dots indicate that the event is present in the corresponding set on the left side of the bottom matrix. (B) Heatmap of the 797 AS events that are significant during both early and late muscle maturation. PSI: percent spliced in, which indicates inclusion level.
<figure><img src="image_36.png" /><figcaption>**Fig. S5.** Enrichment analysis of alternatively spliced genes (A) during early muscle maturation, (B) during late muscle maturation.</figcaption></figure>
<figure><img src="image_37.png" /><figcaption>**Fig. S6. Characterization of human myopathy-associated genes.** Distribution of the number of transcripts, gene length, maximal number of exons, average CDS length, number of paralogs and expression in skeletal muscle in myopathy-associated genes compared to other protein-coding genes in human.</figcaption></figure>
<figure><img src="image_38.png" /><figcaption>Fig. S7. Sashimi plots showing increased inclusion of exon 11 in *Bin1* between E18.5 and 7w.</figcaption></figure>
<figure><img src="image_39.png" /><figcaption>Fig. S8. Sashimi plots showing increased inclusion of exon 12b in *Dnm2* between E18.5 and 7w.</figcaption></figure>
A

<figure><img src="image_40.png" /></figure>

B

<figure><img src="image_41.png" /><figcaption>**Fig. S9.** Impact of exon 37b on LRP4. (A) 3D structure of LRP4 without exon 37B, the amino acids that are lost when exon 37B is included are colored in orange. (B) 3D structure of LRP4 with exon 37B.</figcaption></figure>
**Table S1. Differential expression analysis of early muscle maturation**

Available for download at
https://journals.biologists.com/dmm/article-lookup/doi/10.1242/dmm.052098#supplementary-data

**Table S2. Differential expression analysis of late muscle maturation**

Available for download at
https://journals.biologists.com/dmm/article-lookup/doi/10.1242/dmm.052098#supplementary-data

**Table S3. Enrichment analysis of upregulated genes during early muscle maturation**

Available for download at
https://journals.biologists.com/dmm/article-lookup/doi/10.1242/dmm.052098#supplementary-data

**Table S4. Enrichment analysis of downregulated genes during early muscle maturation**

Available for download at
https://journals.biologists.com/dmm/article-lookup/doi/10.1242/dmm.052098#supplementary-data

**Table S5. Enrichment analysis of upregulated genes during late muscle maturation**

Available for download at
https://journals.biologists.com/dmm/article-lookup/doi/10.1242/dmm.052098#supplementary-data

**Table S6. Enrichment analysis of downregulated genes during late muscle maturation**

Available for download at
https://journals.biologists.com/dmm/article-lookup/doi/10.1242/dmm.052098#supplementary-data
**Table S7.** Enrichment analysis of alternatively spliced genes during early muscle maturation

Available for download at
https://journals.biologists.com/dmm/article-lookup/doi/10.1242/dmm.052098#supplementary-data

**Table S8.** Enrichment analysis of alternatively spliced genes during late muscle maturation

Available for download at
https://journals.biologists.com/dmm/article-lookup/doi/10.1242/dmm.052098#supplementary-data

**Table S9.** Evaluation of DE and AS in genes associated to the RNA splicing GO term

Available for download at
https://journals.biologists.com/dmm/article-lookup/doi/10.1242/dmm.052098#supplementary-data

**Table S10.** Enrichment analysis of DE-specific genes

Available for download at
https://journals.biologists.com/dmm/article-lookup/doi/10.1242/dmm.052098#supplementary-data

**Table S11.** Enrichment analysis of AS-specific genes

Available for download at
https://journals.biologists.com/dmm/article-lookup/doi/10.1242/dmm.052098#supplementary-data
**Table S12.** Enrichment analysis of genes affected by DE and AS

Available for download at
https://journals.biologists.com/dmm/article-lookup/doi/10.1242/dmm.052098#supplementary-data

**Table S13.** Number of AS events detected in myopathy-associated genes during early and late skeletal muscle maturation

Available for download at
https://journals.biologists.com/dmm/article-lookup/doi/10.1242/dmm.052098#supplementary-data