Background Skeletal muscle is an important organ for health and movement, largely driven by specific muscle fibres. However, the comparison of fibre-type-specific DNA methylation and protein abundance from the same sample presents challenges. By combining previous methodological approaches we were able to directly compare the methylome and proteome in Type I and Type II human skeletal muscle fibres in males and females. Methods We assessed the methylome using the EPICv2 Infinium array and the proteome using liquid chromatography tandem mass spectrometry (LC-MS/MS) from Type I and Type II fibre pools from both males (<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="13395_2025_396_Article_IEq1.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="42" /> </InlineMediaObject> <EquationSource Format="TEX">$n=7$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>n</mi> <mo>=</mo> <mn>7</mn> </mrow> </math></EquationSource> </InlineEquation>) and females (<InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="13395_2025_396_Article_IEq2.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="42" /> </InlineMediaObject> <EquationSource Format="TEX">$n=5$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>n</mi> <mo>=</mo> <mn>5</mn> </mrow> </math></EquationSource> </InlineEquation>). Results We identified 5,689 robust differentially methylated regions (Fisher P-value <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="13395_2025_396_Article_IEq3.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="56" /> </InlineMediaObject> <EquationSource Format="TEX">$< 0.001$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo><</mo> <mn>0.001</mn> </mrow> </math></EquationSource> </InlineEquation>) and found strong relationships between methylation and protein abundance in key contractile and metabolic genes. Further, we generated a reference matrix of Type I and Type II fibres and leveraged deconvolution algorithms to accurately estimate fibre-type proportions using whole-muscle DNA methylation data, providing a method to correct for fibre-type in future studies. These results are presented primarily as a resource for others to utilise. Conclusion We provide integrated methylome and proteome profiles of human muscle fibre-types generalisable to both male and females as a freely accessible interactive repository, MyoMETH (<a href="https://myometh.net">https://myometh.net</a>), allowing further investigation into fibre regulation. Data are available via <a href="http://proteomecentral.proteomexchange.org">ProteomeXchange</a> with identifier PXD066393 and the Gene Expression Omnibus at <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE304045">GSE304045</a>.

Integrated fibre-specific methylome and proteome profiling of human skeletal muscle across males and females with fibre-type deconvolution

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2025年10月10日

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Andrew S. Palmer,
Esther García-Domínguez,
Megan F. Taylor,
Andrew Garnham,
Kirsten Seale,
Joel R. Steele,
Han-Chung Lee,
Ralf B. Schittenhelm,
Nir Eynon

摘要

Background

Skeletal muscle is an important organ for health and movement, largely driven by specific muscle fibres. However, the comparison of fibre-type-specific DNA methylation and protein abundance from the same sample presents challenges. By combining previous methodological approaches we were able to directly compare the methylome and proteome in Type I and Type II human skeletal muscle fibres in males and females.

Methods

We assessed the methylome using the EPICv2 Infinium array and the proteome using liquid chromatography tandem mass spectrometry (LC-MS/MS) from Type I and Type II fibre pools from both males ( $n=7$ $n = 7$ ) and females ( $n=5$ $n = 5$ ).

Results

We identified 5,689 robust differentially methylated regions (Fisher P-value $< 0.001$ $< 0.001$ ) and found strong relationships between methylation and protein abundance in key contractile and metabolic genes. Further, we generated a reference matrix of Type I and Type II fibres and leveraged deconvolution algorithms to accurately estimate fibre-type proportions using whole-muscle DNA methylation data, providing a method to correct for fibre-type in future studies. These results are presented primarily as a resource for others to utilise.

Conclusion

We provide integrated methylome and proteome profiles of human muscle fibre-types generalisable to both male and females as a freely accessible interactive repository, MyoMETH (https://myometh.net), allowing further investigation into fibre regulation. Data are available via ProteomeXchange with identifier PXD066393 and the Gene Expression Omnibus at GSE304045.