journal article·2026-07Open access

Multi‐Omics Insights Into the Mechanisms of Early Muscle Fiber Difference and Transformation Between Lean‐Type and Chinese Indigenous Pigs

Shuailong Zheng, Hainan Wu, Min Liu, Kunpeng Wu, Shuntao Huang, Zulfiqar Ahmed, Lenox Pius, Mengjin Zhu, Dequan Xu

Advanced Science· Volume 13· Issue 38

Abstract

ABSTRACT Skeletal muscle fiber composition is a key determinant of meat quality and metabolic traits. The early postnatal period constitutes a primary window for muscle fiber transformation. In this study, distinct muscle fiber composition is analyzed by histological and molecular characterization of longissimus dorsi muscle of 2‐week‐old lean‐type and Chinese indigenous pigs. Multi‐omics analyses reveal divergence in chromatin states, enhancer landscapes, and promoter activity between breeds. Lean‐type pigs show increased chromatin accessibility and enhancer activation at genes involved in oxidative metabolism and myogenesis, whereas Chinese indigenous pigs exhibit enriched regulatory features at glycolytic and biosynthetic loci. Breed‐specific SNPs and indels are enriched in a subset of enhancers and potentially influence transcriptional regulation. Higher‐order genome architecture further contributes to transcriptional divergence through A/B compartment switching and topologically associating domain boundary remodeling. Promoter–enhancer interaction mapping reveals breed‐specific cis‐regulatory networks, and transcriptional output correlates with enhancer density. Functional validation identifies a super‐enhancer upstream of PPP3CB that recruits MEF2C to activate oxidative fiber programs. In vitro and in vivo perturbation assays confirm that the PPP3CB– MEF2C feedback loop governs muscle fiber‐type specification. Collectively, these findings delineate the epigenomic and 3D genomic architecture underlying early muscle fiber characteristics and provide mechanistic insights relevant to improving meat quality.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Genetic Mapping and Diversity in Plants and Animals · Muscle Physiology and Disorders · Genomics and Chromatin Dynamics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Key Laboratory of Swine Genetics and Breeding of the Ministry of Agriculture and Rural Affairs Huazhong Agricultural University Wuhan China

Key Laboratory of Agricultural Animal Genetics Breeding and Reproduction of the Ministry of Education Huazhong Agricultural University Wuhan China

Colleges of Animal Science & Technology Huazhong Agricultural University Wuhan China

Colleges of Veterinary Medicine Huazhong Agricultural University Wuhan China

Funding

National Key Research and Development Program of China

References (97)

Show source-provided references
1. 10.1038/s41467‐025‐56896‐610.1038/s41467‐025‐56896‐6 ↗
2. 10.1002/ame2.1222310.1002/ame2.12223 ↗
3. 10.1016/j.foodchem.2025.14576410.1016/j.foodchem.2025.145764 ↗
4. 10.2527/jas.2010‐298310.2527/jas.2010‐2983 ↗
5. 10.7150/ijbs.10230910.7150/ijbs.102309 ↗
6. 10.1016/j.molimm.2025.01.00610.1016/j.molimm.2025.01.006 ↗
7. 10.1021/acs.jafc.5c0030010.1021/acs.jafc.5c00300 ↗
8. 10.1016/j.tjnut.2025.07.01810.1016/j.tjnut.2025.07.018 ↗
9. 10.1016/j.freeradbiomed.2024.01.03610.1016/j.freeradbiomed.2024.01.036 ↗
10. 10.1002/advs.20241771510.1002/advs.202417715 ↗
11. 10.3389/fgene.2025.156655310.3389/fgene.2025.1566553 ↗
12. 10.1038/s41576‐018‐0089‐810.1038/s41576‐018‐0089‐8 ↗
13. 10.1093/nar/gkaa120310.1093/nar/gkaa1203 ↗
14. 10.1038/s41588‐025‐02489‐410.1038/s41588‐025‐02489‐4 ↗
15. 10.1093/dnares/dsab00310.1093/dnares/dsab003 ↗
16. 10.1038/s41576‐020‐00303‐x10.1038/s41576‐020‐00303‐x ↗
17. 10.1038/s41421‐022‐00416‐z10.1038/s41421‐022‐00416‐z ↗
18. 10.1038/s41467‐021‐27800‐910.1038/s41467‐021‐27800‐9 ↗
19. 10.1038/nature1108210.1038/nature11082 ↗
20. 10.1038/s41467‐025‐60866‐310.1038/s41467‐025‐60866‐3 ↗
21. 10.1111/asj.1264110.1111/asj.12641 ↗
22. 10.1016/0309‐1740(86)90026‐410.1016/0309‐1740(86)90026‐4 ↗
23. 10.3389/fphys.2021.74721410.3389/fphys.2021.747214 ↗
24. 10.1186/s12864‐022‐08737‐910.1186/s12864‐022‐08737‐9 ↗
25. 10.1007/s00018‐022‐04680‐w10.1007/s00018‐022‐04680‐w ↗
26. 10.3390/genes1402036110.3390/genes14020361 ↗
27. 10.1021/pr501035710.1021/pr5010357 ↗
28. 10.1016/j.isci.2023.10859010.1016/j.isci.2023.108590 ↗
29. 10.1152/physiolgenomics.00286.200610.1152/physiolgenomics.00286.2006 ↗
30. 10.5483/BMBRep.2024‐006910.5483/BMBRep.2024‐0069 ↗
31. 10.1038/s41586‐024‐08333‐910.1038/s41586‐024‐08333‐9 ↗
32. 10.1186/s13287‐018‐0792‐610.1186/s13287‐018‐0792‐6 ↗
33. 10.1101/sqb.2011.76.01094210.1101/sqb.2011.76.010942 ↗
34. 10.1172/JCI13615510.1172/JCI136155 ↗
35. 10.3390/ijms23191132710.3390/ijms231911327 ↗
36. 10.1128/MCB.24.14.6253‐6267.200410.1128/MCB.24.14.6253‐6267.2004 ↗
37. 10.1038/s41594‐024‐01375‐710.1038/s41594‐024‐01375‐7 ↗
38. 10.1038/s41467‐024‐53758‐510.1038/s41467‐024‐53758‐5 ↗
39. 10.1152/physiolgenomics.00163.202210.1152/physiolgenomics.00163.2022 ↗
40. 10.1016/j.stem.2019.06.00410.1016/j.stem.2019.06.004 ↗
41. 10.1073/pnas.211140111810.1073/pnas.2111401118 ↗
42. 10.1002/1873‐3468.1399510.1002/1873‐3468.13995 ↗
43. 10.1038/s41467‐023‐39191‐010.1038/s41467‐023‐39191‐0 ↗
44. 10.1016/j.jbc.2023.10475710.1016/j.jbc.2023.104757 ↗
45. 10.1053/j.gastro.2012.02.04310.1053/j.gastro.2012.02.043 ↗
46. 10.1016/j.mce.2016.10.03610.1016/j.mce.2016.10.036 ↗
47. 10.1007/s00223‐014‐9915‐y10.1007/s00223‐014‐9915‐y ↗
48. Punkt K. · 2002
49. 10.1007/s00424010070010.1007/s004240100700 ↗
50. 10.1172/JCI12904910.1172/JCI129049 ↗
51. 10.1080/15384101.2022.212924010.1080/15384101.2022.2129240 ↗
52. 10.1038/s41392‐024‐02030‐910.1038/s41392‐024‐02030‐9 ↗
53. 10.1038/jhg.2013.6610.1038/jhg.2013.66 ↗
54. 10.1172/JCI3196010.1172/JCI31960 ↗
55. 10.1186/2044‐5040‐3‐1110.1186/2044‐5040‐3‐11 ↗
56. 10.3389/fvets.2023.128455110.3389/fvets.2023.1284551 ↗
57. 10.1186/s12915‐022‐01322‐210.1186/s12915‐022‐01322‐2 ↗
58. 10.1007/s00421‐010‐1361‐610.1007/s00421‐010‐1361‐6 ↗
59. 10.1016/j.bbrep.2023.10160310.1016/j.bbrep.2023.101603 ↗
60. 10.1101/gr.278344.12310.1101/gr.278344.123 ↗
61. 10.1111/j.1600‐0706.2009.17726.x10.1111/j.1600‐0706.2009.17726.x ↗
62. 10.1080/00031305.1980.1048303110.1080/00031305.1980.10483031 ↗
63. 10.1093/bioinformatics/bts63510.1093/bioinformatics/bts635 ↗
64. 10.1186/1471‐2105‐12‐32310.1186/1471‐2105‐12‐323 ↗
65. 10.1186/s13059‐014‐0550‐810.1186/s13059‐014‐0550‐8 ↗
66. 10.1186/gb‐2008‐9‐9‐r13710.1186/gb‐2008‐9‐9‐r137 ↗
67. 10.1002/cpz1.58510.1002/cpz1.585 ↗
68. 10.1016/j.cell.2013.03.03510.1016/j.cell.2013.03.035 ↗
69. 10.1016/j.molcel.2010.05.00410.1016/j.molcel.2010.05.004 ↗
70. 10.1093/nar/gkad105910.1093/nar/gkad1059 ↗
71. 10.1038/s41467‐020‐18035‐110.1038/s41467‐020‐18035‐1 ↗
72. 10.1093/bioinformatics/btp32410.1093/bioinformatics/btp324 ↗
73. 10.1093/bioinformatics/btp35210.1093/bioinformatics/btp352 ↗
74. 10.1101/gr.107524.11010.1101/gr.107524.110 ↗
75. 10.1093/bioinformatics/btg41210.1093/bioinformatics/btg412 ↗
76. 10.1016/j.cels.2016.07.00210.1016/j.cels.2016.07.002 ↗
77. 10.1038/nmeth.192310.1038/nmeth.1923 ↗
78. 10.1016/j.cell.2014.11.02110.1016/j.cell.2014.11.021 ↗
79. 10.1093/bib/bbae21710.1093/bib/bbae217 ↗
80. 10.1101/gr.220640.11710.1101/gr.220640.117 ↗
81. 10.1093/bioinformatics/btu26810.1093/bioinformatics/btu268 ↗
82. 10.1038/s41467‐022‐34626‐610.1038/s41467‐022‐34626‐6 ↗
83. 10.1093/nar/gkae97410.1093/nar/gkae974 ↗
84. 10.1093/nar/gkac23810.1093/nar/gkac238 ↗
85. 10.1016/j.cels.2015.07.01210.1016/j.cels.2015.07.012 ↗
86. 10.1093/nar/gkaa22010.1093/nar/gkaa220 ↗
87. 10.1186/s40104‐022‐00679‐210.1186/s40104‐022‐00679‐2 ↗
88. 10.1038/s41467‐017‐02386‐310.1038/s41467‐017‐02386‐3 ↗
89. 10.1093/bioinformatics/btr06410.1093/bioinformatics/btr064 ↗
90. 10.1089/omi.2011.011810.1089/omi.2011.0118 ↗
91. 10.1093/nar/gkad34710.1093/nar/gkad347 ↗
92. 10.1093/nar/gkac85410.1093/nar/gkac854 ↗
93. 10.1002/jcsm.1262310.1002/jcsm.12623 ↗
94. 10.1038/nprot.2007.24310.1038/nprot.2007.243 ↗
95. 10.1093/nar/gks59610.1093/nar/gks596 ↗
96. 10.1038/nprot.2013.13210.1038/nprot.2013.132 ↗
97. 10.1093/nar/gky35410.1093/nar/gky354 ↗