Genomic loci mispositioning in Tmem120a knockout mice yields latent lipodystrophy.
Rafal CzapiewskiDzmitry G BatrakouJose I de Las HerasRoderick N CarterAishwarya SivakumarMagdalena SliwinskaCharles R DixonShaun WebbGiovanna LattanziNicholas M MortonEric C SchirmerPublished in: Nature communications (2022)
Little is known about how the observed fat-specific pattern of 3D-spatial genome organisation is established. Here we report that adipocyte-specific knockout of the gene encoding nuclear envelope transmembrane protein Tmem120a disrupts fat genome organisation, thus causing a lipodystrophy syndrome. Tmem120a deficiency broadly suppresses lipid metabolism pathway gene expression and induces myogenic gene expression by repositioning genes, enhancers and miRNA-encoding loci between the nuclear periphery and interior. Tmem120a -/- mice, particularly females, exhibit a lipodystrophy syndrome similar to human familial partial lipodystrophy FPLD2, with profound insulin resistance and metabolic defects that manifest upon exposure to an obesogenic diet. Interestingly, similar genome organisation defects occurred in cells from FPLD2 patients that harbour nuclear envelope protein encoding LMNA mutations. Our data indicate TMEM120A genome organisation functions affect many adipose functions and its loss may yield adiposity spectrum disorders, including a miRNA-based mechanism that could explain muscle hypertrophy in human lipodystrophy.
Keyphrases
- genome wide
- insulin resistance
- dna methylation
- gene expression
- adipose tissue
- copy number
- skeletal muscle
- endothelial cells
- high fat diet induced
- end stage renal disease
- fatty acid
- high fat diet
- type diabetes
- metabolic syndrome
- induced pluripotent stem cells
- ejection fraction
- newly diagnosed
- chronic kidney disease
- polycystic ovary syndrome
- pluripotent stem cells
- electronic health record
- peritoneal dialysis
- protein protein
- weight loss
- amino acid
- signaling pathway
- intellectual disability
- early onset
- genome wide identification
- artificial intelligence
- patient reported outcomes
- smoking cessation
- big data
- deep learning
- data analysis