A Joint Promoterome-Proteome Atlas Highlights the Molecular Diversity of Human Skeletal Muscles

This study presents a comprehensive joint promoterome-proteome atlas of 75 human skeletal muscles, revealing extensive molecular diversity driven by tissue-specific transcription factors and allele-specific variants, while providing an interactive resource to advance the understanding of muscle gene regulation and heritable pathologies.

The Gist

Imagine your body is a massive, bustling city made of over 600 different neighborhoods. Each neighborhood is a skeletal muscle. While they all look like muscle tissue from the outside, they are actually very different inside, just like a library, a bakery, and a power plant are all buildings, but they function completely differently.

For a long time, scientists had a very blurry map of this city. They mostly studied the "downtown" muscles (like those in your thigh) because they are easy to reach for a biopsy. They knew very little about the "remote villages" like the tiny muscles in your eyes, your tongue, or your diaphragm.

This paper introduces FANTOMUS, a brand new, high-definition, interactive atlas that finally maps out the molecular "blueprints" of 75 different human muscles. Here is what they found, explained simply:

1. The "Instruction Manual" vs. The "Finished Product"

To understand how a muscle works, scientists looked at two things:

• The Promoterome (The Instruction Manual): This is the "on/off switch" for genes. It tells the cell which genes to read and when. The researchers used a special technology (CAGE-Seq) to read these switches for every muscle.
• The Proteome (The Finished Product): This is the actual machinery built by the cell (proteins). They used mass spectrometry (a super-precise scale) to weigh and count the proteins.

The Big Discovery: They found that 80% of the genes and proteins are different depending on which muscle you look at. A muscle in your eye is not just a "smaller version" of a muscle in your leg; it is a completely different machine with a different instruction manual.

2. The "Special Forces" of the Muscle World

The study found that three specific groups of muscles are the "odd ones out" with the most unique molecular profiles:

• The Eye Muscles (Extraocular Muscles): These are the VIPs. They are incredibly resistant to aging and many types of muscular dystrophy (muscle-wasting diseases). The map shows they run on a different operating system, using specific "cardiac-like" genes that keep them running smoothly even when other muscles fail.
• The Tongue: It has a unique mix of genes related to skin development and immune defense, likely because it's constantly exposed to the outside world and needs to heal quickly.
• The Diaphragm: This breathing muscle is a powerhouse of immune activity and energy production, constantly working 24/7.

3. The "Switches" Make the Difference

Why are these muscles so different? It's not just which genes they have, but how they use them.

• Analogy: Imagine a piano. Every muscle has the same 88 keys (genes). But the eye muscles play a jazz song, the leg muscles play a heavy metal song, and the tongue plays a folk song.
• The researchers found that hundreds of "conductors" (transcription factors) are directing these different songs. They also found that muscles often use alternative switches (promoters) for the same gene to create slightly different versions of a protein, fine-tuning the muscle for its specific job.

4. The "Genetic Lottery" (Your DNA Variations)

Not everyone's muscles are built exactly the same. The study looked at Single Nucleotide Variants (SNVs)—tiny typos in your DNA code.

• They found over 6,000 specific DNA typos that change how much a gene is turned on or off in a muscle.
• The "Volume Knob" Analogy: Some of these typos act like a volume knob. If you have one version of the typo, your muscle volume might be slightly larger; if you have the other, it might be smaller.
• They validated this by showing that these specific DNA changes are linked to real-world traits like hand grip strength and thigh muscle size.

5. Why This Matters

This atlas is like giving doctors a GPS for the human body's muscle system.

• Understanding Disease: It explains why some muscles (like the eyes) survive diseases that destroy others.
• Personalized Medicine: It helps us understand why a genetic mutation might cause a severe problem in one person's leg but not in another's, or why a drug might work on the diaphragm but not the bicep.
• Future Research: They built a free, interactive website (FANTOMUS) where anyone can explore these maps, helping scientists design better treatments for muscular dystrophies and age-related muscle loss.

In a nutshell: This paper took a blurry, low-resolution photo of human muscles and replaced it with a 4K, color-coded, interactive map. It shows us that our muscles are not a monolith; they are a diverse family of specialized tissues, each with its own unique identity, driven by specific genetic switches and influenced by our individual DNA.

Technical Summary

1. Problem Statement

Human skeletal muscles constitute approximately 40% of body mass and exhibit significant heterogeneity in anatomy, morphology, and function. While previous studies have established that muscles differ in fiber type composition (slow vs. fast-twitch) and metabolic activity, a comprehensive, systematic atlas of their molecular phenotypes (gene expression and protein abundance) across the entire body is lacking.

• Limitations of existing data: Previous transcriptomic studies (e.g., GTEx, Human Protein Atlas) are heavily biased toward easily accessible limb muscles (e.g., thigh), often representing only a single muscle type or a few samples.
• Knowledge gaps: There is insufficient understanding of:
  • The diversity of transcribed regulatory elements (TREs) (promoters and enhancers) across different muscles.
  • The correlation between transcript levels and protein abundance in specific muscle contexts.
  • The impact of allele-specific variants (ASVs) on muscle-specific gene regulation and susceptibility to myopathies.
  • Why certain muscles (e.g., extraocular muscles) are resistant to specific dystrophies while others are not.

2. Methodology

The authors developed FANTOMUS (Functional ANnoTation Of human skeletal MUScle genome), a multi-omic atlas integrating transcriptomics and proteomics.

• Sample Collection:
  • CAGE-Seq: 222 autopsy samples from 75 distinct skeletal muscles across 4 individuals (3 males, 1 female; aged 56–67).
  • Mass Spectrometry (MS): 60 samples from 22 muscles (a representative subset) for proteomic profiling.
• Transcriptomics (CAGE-Seq):
  • Used nAnT-iCAGE (non-Amplified non-Tagging Illumina Cap Analysis of Gene Expression) to map transcription start sites (TSS) and quantify promoter/enhancer activity.
  • Bioinformatics Pipeline: High-quality filtering, peak calling (using CAGEfightR), and annotation against MANE v1.1 and GENCODE v44.
  • Allele-Specific Analysis: Identified SNVs directly from CAGE-Seq reads and estimated allelic imbalance using MIXALIME.
• Proteomics (LC-MS/MS):
  • Performed Liquid Chromatography-Tandem Mass Spectrometry on 60 samples.
  • Quantified protein abundance using iBAQ (intensity-Based Absolute Quantification) and identified 1,804 protein groups.
• Computational Analysis:
  • Differential Expression: Used edgeR and limma for TRE, gene, and protein-level comparisons.
  • Motif Activity Response Analysis (MARA): Utilized MARADONER to infer transcription factor (TF) activities based on TRE expression and motif occupancy.
  • Heritability Partitioning: Applied Stratified Linkage Disequilibrium Score Regression (S-LDSC) to link ASVs to GWAS traits (e.g., muscle volume).
  • Validation: Selected regulatory SNVs were validated using luciferase reporter assays in HEK293T cells, including overexpression of specific TFs (ESR1, NRF1).

3. Key Contributions

• Scale: The largest unified atlas of human skeletal muscle expression to date, covering 75 distinct muscles (including hard-to-reach sites like extraocular muscles, tongue, and diaphragm).
• Multi-Modal Integration: Simultaneous profiling of the promoterome (37,000 TREs) and proteome (1,804 protein groups), allowing for cross-modal correlation analysis.
• Regulatory Landscape: Identification of 6,653 allele-specific variants (ASVs) affecting TRE activity, many of which overlap with muscle-related GWAS loci.
• Functional Atlas: A public, interactive web portal (fantomus.autosome.org) providing access to expression profiles, protein abundances, and regulatory motif activities.

4. Key Results

A. Molecular Diversity and Heterogeneity

• Widespread Differential Expression: Approximately 80% of genes and proteins show non-uniform expression across muscles.
• Distinct Molecular Phenotypes:
  • Extraocular Muscles (EOM), Tongue, and Diaphragm exhibit the most unique molecular profiles.
  • EOM: Enriched for neurogenesis, retina homeostasis, and oxidative metabolism. They show downregulation of atrophy-associated genes (e.g., TRIM63, FBXO32) and specific isoforms of myosin (e.g., MYH4, MYH13), explaining their resistance to muscular dystrophies.
  • Tongue: Unique expression of epidermis development and immune response genes.
  • Diaphragm: High expression of immune-related genes and oxidative phosphorylation proteins.
• Principal Component Analysis (PCA):
  • PC1 separates craniofacial/non-somitic muscles (EOM, tongue, diaphragm) from somitic limb muscles, driven by sarcomere organization and embryonic morphogenesis genes (e.g., HOX genes).
  • PC2 distinguishes upper vs. lower limbs (transcriptome) or inflammatory/ROS-related proteins (proteome).

B. Transcriptome-Proteome Correlation

• The overall correlation between RNA (CAGE-Seq) and protein (MS) levels is moderate (Pearson r = 0.32).
• Outliers:
  • Overabundant proteins: Extracellular matrix, immune, and plasma proteins (likely due to blood infiltration).
  • Underabundant proteins: Ribosomal and proteasome components (suggesting strict translational control).
• EOM Exception: EOM showed the highest RNA-protein correlation (Spearman r = 0.34), suggesting weaker post-transcriptional regulation compared to other muscles.

C. Alternative Promoter Usage

• Analysis of 5,070 multi-TRE genes revealed widespread tissue-specific alternative promoter usage.
• Case Studies:
  • TPM3: EOM-specific downregulation of the high-molecular-weight (HMW) isoform (associated with slow fibers), potentially explaining resistance to TPM3-related myopathy.
  • PITX2: EOM-specific upregulation of long isoforms (PITX2A/B) involved in eye development.
  • ALPK2: Diaphragm-specific upregulation of a specific isoform.
  • SEPTIN9 & RILP: Muscle-specific isoform switching affecting cytoskeletal organization and autophagy.

D. Transcription Factor (TF) Activity

• MARA identified 353 motifs with non-uniform activity.
• Key Regulators:
  • MEF2: Active in slow oxidative muscles; linked to satellite cell differentiation.
  • SIX: Active in fast-twitch muscles.
  • HOX9-13: Active in distal limbs.
  • ALX1/ALX4 & ZBTB7A: Highly active in EOM, regulating eye-specific genes (MYH15, ATP1A3).
  • HSF (Heat Shock Factors): Increased activity in hip/back muscles, correlating with age-related atrophy susceptibility.

E. Allele-Specific Variants (ASVs) and GWAS

• Identified 6,653 ASVs with imbalanced transcriptional signals.
• GWAS Enrichment: These ASVs are significantly enriched for total thigh muscle volume and other muscle-related traits (hand grip strength, lean mass).
• Validation: Luciferase assays confirmed that specific SNPs (e.g., in MTOR, RPL32, SYPL2, ZDHHC5) alter promoter activity. For instance, rs2290311 affects ESR1 (Estrogen Receptor) binding, linking estrogen signaling to muscle mass maintenance.

5. Significance and Impact

• Mechanistic Insight into Myopathies: The atlas explains why extraocular muscles are spared in many dystrophies (e.g., DMD, Limb-Girdle) due to unique isoform expression (e.g., UTRN upregulation, DYSF downregulation) and specific TF networks.
• Genetic Architecture of Muscle Traits: Demonstrates that non-coding regulatory variants (ASVs) play a critical role in heritable muscle phenotypes, providing a resource for prioritizing causal variants in GWAS.
• Resource for Future Research: The FANTOMUS portal serves as a foundational tool for:
  • Studying gene regulation logic in normal vs. pathological states.
  • Understanding individual susceptibility to muscle wasting, aging, and exercise response.
  • Developing targeted therapies for specific muscle groups.

Conclusion:
FANTOMUS provides an unprecedented, high-resolution view of the molecular landscape of human skeletal muscles. By integrating promoter activity, protein abundance, and allele-specific regulation, it reveals that muscle diversity is driven by hundreds of transcription factors and specific regulatory variants, offering new avenues for understanding and treating muscle diseases.